SCIENCE'S LAST FRONTIERS: Consciousness, Life and Meaning
Thinking About Thought Paradigm shifts in modern science and the new science of mind Towards a Unified Theory of Life, Mind and Matter Piero Scaruffi
Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Title | Index | Preface | Author | Annotated Bibliography Mind | Brain | Cognition | Common Sense | Connectionism Consciousness | Consciousness: History of | Consciousness: Physics of | The Self and Free Will Memory | Dreams | Emotions | Machine Intelligence | Language | Metaphor | Pragmatics | Meaning Ecological Realism | Evolution | Life Self-organization | Quantum & Relativity Theory TM, ®, Copyright © 1998 Piero Scaruffi All rights reserved.
I continuously update the chapters as new scientific data and theories come available. You are welcome to download and distribute what is available now on this website, but please do not assume it will never change. It does change almost weekly. Register to my mailing list if you want to receive monthly updates.
Ancient Greeks thought that there exists a consciousness substance and named it Thymos.
"The only incomprehensible thing about the universe is that it is comprehensible" (Albert Einstein) "The more the universe seems comprehensible, the more it seems pointless" (Steven Weinberg) "The more familiar I get with the universe, the less familiar I feel with myself" (piero scaruffi). http://www.thymos.com/tat/title.html (1 of 2)25/07/2003 14:18:50
SCIENCE'S LAST FRONTIERS: Consciousness, Life and Meaning
"O you proud Christians, wretched souls and small, Who by the dim lights of your twisted minds Believe you prosper even as you fall, Can you not see that we are worms, each one Born to become the angelic butterfly That flies defenseless to the Judgement Throne?" (Dante, Canto 10, "Purgatorio")
"To do is to be - Descartes To be is to do - Voltaire Do be do be do - Frank Sinatra" (Anonymous - Men's Restrooms, Greasewood Flats, Scottsdale)
"We are born naked, wet and hungry. Then things get worse." (Anonymous - Signature found on the Internet)
Last of all, he will be able to see the sun, and not mere reflections of it in the water, but he will see it in its own proper place, and not in another; and it will contemplate it as it is. (Plato, "Republic")
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SCIENCE'S LAST FRONTIERS: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi
Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind
Title ● Index ● Preface ● Mind and Matter ● Machine Intelligence ● Common Sense: Engineering the Mind ● Connectionism and Neural Machines ● Cognition: A General Property of Matter ● Memory and Beyond (Conscious and Unconscious) ● Dreams ● Emotions ● Ecological Realism: The Embodied Mind ● Evolution: Of Designers and Design ● The Physics Of Life ● Inside the Brain ●
Language: What We Speak ● Metaphor: How We Speak ● Pragmatics: Why We Speak ● Meaning: Journey to the Center of the Mind ● Self-organization and the Science of Emergence ● The New Physics: The Ubiquitous Asymmetry ● A History of Consciousness ● Consciousness: the Factory of Illusions ● A Physics Of Consciousness ● The Self and Free Will: do we think or are we thought ● Finale ●
I continuously update the chapters as new scientific data and theories come available. You are welcome to download and distribute what is available now on this website, but please do not assume it will never change. It does change almost weekly. Register to my mailing list if you want to receive monthly updates.
Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Permission is granted to download/print out/redistribute this file provided it is unaltered, including credits.
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Preface By the time you finish reading this book you will be a different person. Not because this book will change the way you think and act, but simply because the cells in your body, including the neurons of your brain and the genes inside your cells, are continuously changing. By the time you finish reading this book you will "literally" be a different body, a different mind. By the time you finish reading this book only a tiny part of your body and of your brain will still be the same that it is now. Every word that you read is having an effect on the connections between your neurons. And every breath you take is pacing the metabolism of your cells. And, as you read, your cells keep copying mutated variants of your original DNA to the new cells. This book is about what just happened to you. Who is this book for? ❍
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Casual readers, who are looking for interesting scientific topics to enlighten themselves or their friends Educated intellectuals aiming at completing/ broadening their knowledge of modern scientific disciplines Professional philosophers and psychologists who are interested in the debate on consciousness and cognition Students and researchers who are looking for an easy-to-use summary of theories of consciousness and cognition
As with any book worth reading, the objective of this book is to fill a gap. In my case, the gap is a lack of books that provide an interdisciplinary account of the studies on the mind being conducted around the world. While many books carry that label, most of them focus on the one or two disciplines that the author is familiar with. First and foremost, my book aims at providing an accessible, illuminating and stimulating introduction to
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Thinking About Thought: Consciousness, Life and Meaning
those studies across a number of disciplines: Philosophy, Psychology, Computer Science, Mathematics, Biology, Neurophysiology and Physics. Second, this book also attempts to define a common background among disciplines that approach the subject from different perspectives, as a preliminary step to building a unified science of the mind. Third, this book highlights the paradigm shifts that are occurring in Science. There are a number of new ideas that could revolutionize our understanding of the world. Fourth, this book also offers a humble personal opinion on what the solution to the mystery of mind may be. We may have already found the solution, even if we don't have conclusive evidence. Fifth, this book raises a lot of questions and answers very few of them, leaving room for the reader to engage in her own philosophizing. Interest on the subjects of mind, consciousness and life is growing exponentially and is affecting a growing number of disciplines. What used to be the exclusive domain of philosophical speculation is now part of scientific research conducted by neurophysiologists, biologists, physicists, mathematicians, computer scientists and cognitive psychologists. All of a sudden new fascinating horizons have been opened for science. A variety of new disciplines have established themselves: Artificial Intelligence, Artificial Life, Cognitive Science, Systems Theory, Self-organizing Systems, etc. Even more important, a new vision of the world we inhabit has begun to materialize, one in which order is spontaneous, one in which the properties of life and intelligence "emerge" from matter, from energy and from a few fundamental laws. For the first time ever, it seems possible to reconcile mind and matter, to unify in one powerful theory both Physics and Psychology. My book is a humble attempt at providing an overview for ordinary humans of one of the most exciting fields of study of our days. I start with a survey of the philosophical debate on the relationship between mind and matter, then I delve into neurophysiological models of the brain and computational theories of cognition. Along the way, I explore memory, reasoning, learning, emotions, common sense, language, metaphor, mental imagery and even dreams from different perspectives. I survey the work and the ideas of the protagonists of each field. I introduce the mathematical disciplines of Connectionism and Cybernetics. I deal with the meaning of meaning. I discuss the importance of pragmatics in human communication and of the environment in animal behavior. I briefly summarize the salient features of modern Physics (Quantum Theory and Relativity Theory). Finally, I tackle life and consciousness, the ultimate subjects of the human quest for truth. It is a fascinating journey around the world of the scientific ideas that are likely to shape the intellectual scenario of the third millennium. I pay attention to phenomena of our mind that have been traditionally neglected, notwithstanding the fact that they occur every day in our minds: jokes, dreams, emotions, metaphors, tools, games. There is little of exceptional value in being able to remember. as memory may well be a ubiquitous property of all living and even non-living matter; but joking…have you ever seen a stone make a joke or laugh? Physics has explained everything we have found in the universe. We know how the universe started and http://www.thymos.com/tat/preface.html (2 of 8)25/07/2003 14:20:00
Thinking About Thought: Consciousness, Life and Meaning
how it will end. We know what drives it. We know what makes it. Our knowledge of fundamental forces and elementary particles is increasing daily. Two things remain to be explained: how am I alive and how do I think. What does it take for something to be alive and to think? Can we "build" a machine that thinks and is alive? What is thought (consciousness)? And what is life? Physics has no answer. It never tried to give an answer. Life and thought were "obviously" beyond the reach of formulas. Well, maybe the formulas are wrong. Or maybe religious convictions kept scientists from viewing living and thinking as physical phenomena to be studied the same way we study galaxies and electricity. The most important revolution of our century may be the idea that thinking and living can (and must) be explained by Science, just like any other phenomena in the universe. Science may never be the same again, literally. Any scientific theory that does not provide a credible account for consciousness and life is faulted from the beginning, as it ignores the two phenomena its own existence depends upon. We are alive and we are conscious. The final step of the scientific program that started thousands of years ago, when humans first started asking themselves questions about the universe, will then be to find out the meaning of all this: why are we conscious and why are we alive? why is the universe the way it is and why are we in it? Meaning has become the ultimate goal of science. As much as we think we know, we still don't know much: we don't even know why we know what we know. A new view of nature is emerging, which encompasses both galaxies and neurons, gravitation and life, molecules and emotions. As a culmination of centuries of studying nature, mankind has been approaching the thorniest subject of all: ourselves. We are part of nature, but science leaves us in the background, limiting our role to the one of observers. For a long time we have enjoyed this privileged status. But we seem no longer capable of eluding the fundamental issue: that what we have been studying for all these centuries is but us, albeit disguised under theories of the universe and theories of elementary particles. And now it is about time that we focus on the real subject. The mind appears to us as the ultimate and most refined product of life. And life appears to us as the ultimate and most refined product of matter. Life and mind must follow from a logical inference on the essence of the universe. If we had the right theory of the universe, we would need no effort in explaining why life happened and what the mind is. The fact that we do not have yet a good theory of the mind means that probably we do not have a good theory of the universe. Therefore, in a sense, the new science of the mind is doing more than just studying the mind: it is indirectly reformulating the program of Science in general. New insight in mind, cognition and consciousness may come from a revision of science. At every point in the history of science, a paradigm shift allows to explain previously unexplained phenomena. Modern science has introduced and is introducing a number of "paradigm shifts" that are changing our perception of the universe and of who we are. Namely: ❍
Henry Simon's symbolic processing paradigm
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Jerry Fodor's computational functionalism
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Thinking About Thought: Consciousness, Life and Meaning
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Kenneth Craik's representational paradigm
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Charles Darwin's theory of evolution
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Albert Einstein's theory of relativity
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Ilya Prigogine's thermodynamics of non-equilibrium systems
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Gerard Edelman's theory of neural selection
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Fredrick Bartlett's reconstructive memory
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William James' connectionism
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Noam Chomsky's generative grammar
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Stuart Kaufman's self-organization
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Humberto Maturana's autopoiesis
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George Lakoff's cognitive metaphor
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Roger Penrose's quantum theory of consciousness
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Lotfi Zadeh's fuzzy logic
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Rodolfo Llina's brain model
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Allan Hobson's theory of dreaming
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Richard Dawkins' memes
My book indulges in these and other paradigm shifts because they may allow us to achieve a better understanding of what "thought" is, how it related to the matter of the brain and matter in general, and why we think at all. This book is also, and mainly, a history of the ideas that Science neglected in the past. Therefore, besides "informing" the reader on what is going on, this book emphasizes these recurring themes: ❍
The mystery of life can be explained by science and it is being explained as a property of
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matter, no less than electricity or evaporation ❍
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Mind in the sense of "cognition" could be explained by science but science has been trapped in vague and unscientific definitions of "mind", "intelligence", "thought" Once "mind" is restricted to "cognition" (memory, learning, reasoning, etc.), it will be reduced to another property of matter, actually ubiquitous in nature Consciousness is the real mystery, still unexplained, and the cause may very well lie in a fundamental inadequacy of our science, a fundamental limit in our Physics to explain natural phenomena
Signs of a new science, which could accommodate a theory of consciousness, are visible. Thanks to progress in all fields, from Mathematics to Neurobiology, our knowledge has been immensely enriched by a wealth of empirical data and by a wealth of theoretical tools. While differing on the specifics, many scientists and philosophers feel that mankind is now ready for a momentous synthesis. The main theme of such a synthesis may be that of the spontaneous "emergence" in our universe of such unlikely properties as life and consciousness. If we can explain how it developed, we can explain what it is and how it works. And what it means. And what we are. Ultimately, this book is about the gap between "I" and "me". Piero Scaruffi Redwood City, November 1997 Post Scriptum I don't make a big deal of my own ideas. I hope that this book is going to be useful, first and foremost, as a survey of what is going on, so that many more people can be informed. My own ideas, as exposed mostly at the end of each chapter, can be summarized as follows. I believe in the existence of a common underlying principle that governs inanimate matter (the one studied by Physics), living matter and consciousness. And I believe that principle to be a form of Darwinian evolution. The second underlying principle is "ex nihilo nihil fit": nothing comes from nothing. Life does not arise by magic: it must come from properties of matter. Ditto for cognition. Ditto for consciousness. Many schemes have been proposed to explain how life or consciousness may be "created" from inanimate and unconscious matter, how a completely new property can arise from other properties. I don't believe this is
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Thinking About Thought: Consciousness, Life and Meaning
the case. Both life and consciousness are ultimately natural phenomena that originate from other natural phenomena, just like television programs and the motion of stars. The term "mind" has been abused so much that I have become hostile to it. The terms that I accept are "brain" and "consciousness". The brain is made of neural assemblies and consciousness is made of what we call (for lack of a better term) "thoughts". Neural assemblies are interconnected neurons and thoughts are made of interconnected emotions. The dynamics of both systems is controlled by a law of selection: neural assemblies and thoughts are continuously generated and experience determines which ones get stronger and which ones get weaker. The substance of the brain and the substance of consciousness are the same. Brain processes and thoughts arise from different properties of the same matter, just like a piece of matter exhibits both gravitational and electric features. The feature that gives rise to consciousness is therefore present in every particle of the universe, just like the features that give rise to electricity and gravity. What we call "mind" is actually two things, which must be carefully kept separate: "cognition" (i.e., the faculties of remembering, learning, reasoning, etc.) and consciousness. Cognitive faculties do not require consciousness. Cognition and consciousness are related only because we have not explained them yet. Cognition is a feature of all matter, whether living or not: degrees of remembering, learning, etc. are ubiquitous in all natural systems. They can be explained without revolutionizing Science. The "emotions" associated with them belong instead to consciousness, just like the emotions of tasting or pleasure. The explanation of consciousness does require a conceptual revolution in Science, specifically the introduction of a new feature of matter, which must be present even in the most fundamental building blocks of the universe. Biology and Physics offer us completely different theories of Nature. Physics' view is "reductionist": the universe is made of galaxies, which are made of stars which are made of particles. By studying the forces that operate on particles, one can understand the universe. Biology's view is Darwinist: systems evolve. Consciousness, like all living phenomena, can be more easily explained in the framework of Biology than in the framework of Physics. Reconciling the two views is the great scientific challenge of the next century. We know that the world of living beings is a Darwinian system: competition, survival of the fittest, evolution and all that stuff. We know that the immune system is a Darwinian system. We are learning that the brain is also a Darwinian system, where the principles of natural selection apply to neural connections. It is intuitive that memory is a Darwinian system: we remember the things that we use frequently, we forget things we never use. I claim that the mind is a Darwinian system as well: competition, survival of the fittest and evolution work among thoughts as well. The Darwinian system recurs at different levels of organization, and one of them happens to be our thought system, i.e. our mind. The main addition to the Darwinian paradigm that I advocate is a crucial role for endosymbiosis: I believe that new organisms can be created by "merging" two existing organisms. If each organism is made of smaller organisms, then it is not surprising that a Darwinian law governs each level of organization: each http://www.thymos.com/tat/preface.html (6 of 8)25/07/2003 14:20:00
Thinking About Thought: Consciousness, Life and Meaning
component organism "was" a living organism, and, like all living things, was designed to live and die and evolve according to the rules of natural selection. The organism that eventually arose through the progressive accretion of simpler organisms is a complex interplay of Darwinian systems. It is not surprising that muscles, memory, the immune system and the brain itself all exhibit Darwinian behavior (get stronger when used, weaker when not used, etc.). I also believe that the solution to the mystery of consciousness lies in a fundamental flaw of Physics. The two great theories of the universe that we have today, Quantum Physics and Relativity Theory, are incompatible. They both have an impressive record of achievements, but they are incompatible. One or both must go. I believe that once we replace them with a theory that is equally successful in explaining the universe, consciousness will be revealed to be a trivial consequence of the nature of the world. My explanation of where our mind comes from goes like this. If consciousness is ubiquitous in nature, then it is not difficult to accept the idea that it was there, in some primitive form, since the very beginnings of life, and that it evolved with life. It became more and more complex as organisms became more and more complex. Early hominids were conscious and their consciousness, while much more sophisticated than the consciousness of bacteria, was still rather basic, probably limited to fear, pain, pleasure, etc. In mammals and birds consciousness was related to sounds (i.e., fear to screaming). Early hominids had a way to express through sounds their emotions of fear and pain and pleasure. Conscousness was a factor, a skill, that helped in natural selection. Minds were always busy thinking in very basic terms about survival, about how to avoid danger and how to create opportunities for food. What set hominids apart from other mammals was the ability to manufacture tools. We can walk and we can use our hands in ways that no other animal can. The use of tools (weapons, clothes, houses, fire) relieved us from a lot of the daily processing that animals use their minds for. Our minds could afford to be "lazy". Instead of constantly monitoring the environment for preys and predators, our minds could afford to become "lazy". Out of that laziness modern consciousness was born. As mind had fewer and fewer practical chores, it could afford to do its own "gymnastics", rehearsing emotions and constructing more and more complex ones. As more complex emotions helped cope with life, individuals who could generate and deal with them were rewarded by natural selection. Emotions underwent a Darwinian evolution of their own. That process is still occurring today. Most animals cannot afford to spend much time philosophizing: their minds are constantly working to help them survive in their environment. Since tools were doing most of the job for us, our minds could afford the luxury of philosophizing, which is really mental gymnastics (to keep the mind in good shape).
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Thinking About Thought: Consciousness, Life and Meaning
In turn, this led to more and more efficient tools, to more and more mental gymnastics. As emotions grew more complex, sounds to express them grew more complex. It is not true that other animals cannot produce complex sounds. They cannot produce "our" set of complex sounds, but they could potentially develop sound systems based on their sounds. They don't need sound systems because they don't produce complex emotions. They have the sounds that express the emotions they feel. Human language developed to express more and more complex emotions. The quantity and quality of sounds kept increasing. Language trailed consciousness. Ideas, or "memes", also underwent Darwinian evolution, spreading like viruses from mind to mind and continuously changing to adapt to new degrees of consciousness. The history of consciousness is the history of the parallel and interacting evolution of: tools, language, memes, emotions and the brain itself. Each evolved and fostered the evolution of the others. The co-evolution of these factors led to our current mental life. This process continues today, and will continue for as long as tools allow more time for our minds to think. The software engineer son of a miner is "more" conscious than her father. And his father was more conscious than his ancestor who was a medieval slave. Consciousness is a product of having nothing better to do with our brain.
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Studies on Consciousness, Mind and Life
THYMOS Studies on Consciousness, Mind and Life What does Thymos mean | My personal website | My e-mail Versione italiana | Version francaise | Version espanola | Deutsche Version | Japanese Version Research Interests: ● ● ● ● ●
Cognitive Science, Philosophy of Mind, Artificial Intelligence, Neurobiology, Theoretical Physics
Annotated Bibliography on the Mind (with links to publishers, libraries, bibliographies, etc.) (TM, ®, Copyright © 1998 Piero Scaruffi All rights reserved.) Thinking about Thought (my book on formal theories of Cognition, Mind, Consciousness) (TM, ®, Copyright © 1998 Piero Scaruffi All rights reserved.) Seminar on Formal Theories of Consciousness (TM, ®, Copyright © 1998 Piero Scaruffi All rights reserved.)
Essays
Independent Workshops
A History of Philosophy
Seminar on History of Knowledge (TM, ®, Copyright © 2002 Piero Scaruffi All rights reserved.) Register to my mailing list. Every two months or so, I send out news and updates on cognitive science and the likes, reviews of books, announcement of conferences, and the status of my book. News from the scientific world
A simple theory of consciousness Statement of work (2000) Research statement (1995) Abstract Papers Academic Biography Publications
Recent reviews:
Recent essays:
SEEING REASON MEMORY FROM A TO Z LOOKING FOR SPINOZA FROM COMPLEXITY TO LIFE CONSCIOUSNESS AND THE WORLD
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Education Academic Resume Industrial Resume Theses Supervised Lectures http://www.thymos.com/index.html (1 of 6)25/07/2003 14:20:14
Language as a neural process ● Consciousness as multi-track evolution ● A reductionist explanation of the self ● The experimental study of consciousness ● Free Will and Identity ● Truth ● Emotions ● Quantum Consciousness ● Dreaming ● Endosymbiosis ● Artificial Creativity ● The multi-track evolution of Mind
Studies on Consciousness, Mind and Life
The History of Art: a biological and cognitive perspective ●
Conferences | Publishers | Webliography on the Mind | U.S.A. Libraries
Search this website Search the Internet
Personal Research Statement: ●
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The very fundamental idea of my research is that the mental cannot be reduced to the physical and that somehow the property that, under special circumstances, enables a particular configuration of matter (e.g., the brain) to exhibit "consciousness" must be present in all matter, starting from the most fundamental constituents. I think that cognition is a property of all living organisms that comes in (continous) degrees. Memory and learning can be said to be ubiquitous in nature, as long as we assume that they come in degrees. There are striking similarities between the behavior of cognitive (living) matter and the behavior of noncognitive (dead) matter (a piece of paper that is repeatedly bent will tend to "remember" of having been bent by "staying" bent). The "degrees of cognition" that we find ubiquitous in nature can be expressed in the formalism of Fuzzy Logic, but modern physics is built on Quantum Mechanics, which is built on the Theory of Probabilities. A possible
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Education/Other Relevant Experience: Piero received a degree in Mathematics (summa cum laude) in 1982 from University of Turin, where he did work in General Theory of Relativity (mainly applied to black holes) and Theoretical Physics (a unification model for quantum chromodynamics). For a number of years he was the head of the Artificial Intelligence Center at Olivetti, based in Cupertino, CA. He has written a number of books (all of them in his native Italy) and has published hundreds of articles on publications both in Italy and the U.S. He has been a visiting scholar in Artificial Intelligence at Harvard University in 1984 and at the Knowledge System Laboratory of Stanford University in 1995/1996. He has lectured at several Universities around the world, and recently taught classes on Formal Theories of the Mind at U.C. Berkeley and at the California Institute for Integral Studies.
Studies on Consciousness, Mind and Life
starting point for reconciling biological and physical sciences, i.e. for unifying Cognitive Science and Physics, would thus be to replace probabilities with Fuzzy Logic in Quantum Mechanics.
Year 2000 statement of work Inquire about New Media internships in Cognitive Science
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Main technical papers: Butera, Scaruffi: "Computer-aided tuning in an expert system for software configuration" (Vienna, Third SPIE Symposium, 1986) Logiudice, Scaruffi: "Knowledge Modules: a structure for representing the granularity of real-world knowledge" (Montreal, Sixth Canadian Conference on Artificial Intelligence, 1986) Donalisio, Petrone, Scaruffi: "A framework to build expert systems for decision support" (Boston, Second Conference on Applications of A.I., 1987) Scaruffi: "Expert Systems for Management" (Osaka, Japanese Conference on Artificial Intelligence, 1987) Butera, Iacono, Scaruffi: "A model-based heuristic approach to board troubleshooting" (Detroit, Expert Systems in Manufacturing, 1988) Scaruffi, Steccanella, Barbetti: (Madrid, Knowledge Engineering Workshop, 1988) "A model of knowledge communication for building intelligent tutoring systems" Ronchi, Butera, Frascari, Scaruffi: "A dual-blackboard architecture for tele-diagnosis" (Artificial Intelligence in Design and Manufacturing [vol.1/2, Academic Press], 1988) Scaruffi: "The new wave of personal distributed intelligence" (ACM Computational Intelligence, 1988) Scaruffi, Barbetti: "A domain-independent framework for tutoring systems" (ACM/AIE IEA, 1989) Chiantore, Perotto, Resta, Scaruffi "An expert system for product configuration" (World Congress on Expert Systems, 1991) http://www.thymos.com/index.html (3 of 6)25/07/2003 14:20:14
Studies on Consciousness, Mind and Life
Qian, Russi, Scaruffi: "Generation of production rules from neural networks" (Intl Symposium on Methodologies for Intelligent Systems, 1991) Scaruffi: "Towards unification of cognitive and physical sciences: cognition as a property of matter" (Cognitive Society Conference:, 1996) Scaruffi: "The Factory of Illusions: artificial and natural creativity" (Berliner Festspiele 2000, 1999) Scaruffi: Consciousness as multi-track evolution (Conference on Consciousness, 2001) Scaruffi: A reductionist explanation of the self (Conference on Consciousness, 2001) Scaruffi: The experimental study of consciousness (Conference on Consciousness, 2001)
List of main lectures and seminars on Artificial Intelligence, Cognitive Science and Theories of the Mind: October 1999: U.C. Berkeley, Extensions, USA September 1998: U.C. Berkeley, Extensions, USA April 1998: California Institute for Integral Studies, USA April 1997: U.C. Berkeley, Extensions, USA ●
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Talk #1 - Practical Applications of A.I. This talk will provide a survey of real-world applications of A. I.: so called "expert systems", neural networks, natural language processing systems. It will also bridge the history of artificial intelligence with the history of its applications, the history of A.I. in the academia with the history of A.I. in the industry. It will identify the areas of our society that have been affected and will be affected by artificial intelligence technique, briefly dealing with the economic and social impacts. Talk #2 - Theories of the Mind. This talk will provide an interdisciplinary survey of theories of the mind, consciousness and life that are emerging from a broad range of fields: neurophysiology, cognitive psychology, philosophy of the mind, non-standard logic, biology, artificial life and nonlinear dynamics. The student will gain a basic understanding of the various research programs that deal with the mind, consciousness and life: how the brain works, how its structure relates to the mind, how conscious phenomena relate to the mind, how mind relates to life, how science can explain all of this. Included in this talk will be topics such as self-organizing systems (Kauffman), memes (Dawkins), the multimind (Ornstein), concepts (Rosch), mental models (Johnson-Laird), situated cognition (Gibson, Neisser, Barwise), autopoietics (Maturana), neural darwinism (Edelman), emotions
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Studies on Consciousness, Mind and Life
(Aggleton), convergence zones (Damasio), time binding (Llinas), language (Chomsky, Austin, Searle, Grice), etc. October 1990: Universidad Nacional de Colombia, Department of Systems, Colombia May 1989: University of Cagliari, Department of Philosophy, Italy August 1988: Monterey Institute for International Studies, USA May 1987: University of Bari, Department of Mathematics, Italy
List of theses supervised: Supervised about 20 graduate theses jointly with faculty members of Italian Universities: 1982) Turin: "A keyed file system for optimized relational access" 1982) Turin: "A syntax-driven editor for a data management system" 1984) Turin: "A semantic network based architecture for document retrieval" 1985) Pisa: "Partitioning a knowledge base into knowledge modules" 1985) Pisa: "An expert system for quality assurance" 1986) Pisa: "An integrated parser for text understanding" 1987) Pisa: "An expert system for board troubleshooting" 1987) Pisa: "A dual-frame architecture for text understanding" 1987) Pisa: "A framework for building intelligent decision support systems" 1988-90) etc etc
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Studies on Consciousness, Mind and Life
Greek thought evolved an intriguing division of mental life into two souls, the Thymos (pron: "theemos") and the Psyche. ●
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The Thymos pertains to the active soul, what we today refer to thought, consciousness, awareness, etc. It was associated with breath, heart and liver. Breath was identified with soul, as in most ancient systems of philosophy (the Hindu "atman" comes from the word for "breathing") and with language (breath is what you need to utter sounds). Liver was reputed to be the origin of emotions (there must have been painful liver diseases at the time :-). The heart was considered the seat of desires and intentions. The Psyche is the immanent soul, independent from the body, a precursor of the eternal soul of Christianity that survives the body in the other world.
It appears that this was a very ancient belief, predating civilizations, as the same distinction can be found in most ancient cultures: in Egypt there were the ba and ka, in China the p'o and hun, in Judaism the nephesh and the ruach, in Buddhism the kama-manas and the buddhi-manas, in Zoroastrianism the daena and the urvan. Countless esoteric beliefs, all derived from ancient theosophies, distinguish between an active entity (alaya-vijnana, karana-sarira) and a passive entity (manas, suksma-sarira). Interestingly, the concept was abolished by Christianity but resurfaced in Islam (the ruh and the nafs). In ancient Greece the Thymos became the active, rational and mortal part of the person (the part that has control over the body), while the Psyche became the quiescent and immortal part of the person. The Thymos became a core concept of Socrates' philosophy. In Socrates' theology the doctrine of Thymos is a meditation on the history of philosophy from Homer to Socrates himself, by which Socrates hails the passage from unconscious philosophizing to rational self-consciousness. Interestingly, Socrates warned against the dangers of self-awareness. He warned that consciousness would cost us greatly, both in terms of desire to live and in terms of our harmony with nature. In Plato's late dialogues this contradiction has a happy ending, as Socrates finds in conscious thought the meaning of life itself. Platonic philosophy elevated the Thymos above the Psyche. The Psyche is viewed as a sort of lower mind that can connect with either a higher mind (nous), that a Christian may perhaps interpret as God, or with the Thymos, that a Christian cannot interpret because it has no correspondent. Thymos is the cause of anger and passion. In a sense, it is opposite of meditation. Inquire about New Media internships in Cognitive Science
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ANNOTATED BIBLIOGRAPHY OF MIND-RELATED TOPICS
Annotated Bibliography of Mind-related Topics Compiled by Piero Scaruffi This month's reviews | E-mail suggestions to:
[email protected] Select the first letter of the last name of the author: A|B|C|D|E|F|G|H|I|J|K|L|M|N|O|P|Q|R|S|T|U|V|W|Y|Z Introduction | Index by Topic | Milestone books My seminar on Theories of Mind | My book on Mind & Consciousness | My workshops Conferences | Publishers | Webliography on the Mind | U.S.A. Libraries Thanks to Bob Engelmore for inviting me at Stanford University, where this bibliography was first drafted. TM, ®, Copyright © 1998 Piero Scaruffi All rights reserved.
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Mind and Matter (Popper, Eccles, Searle, Rucker, Penrose, Broad, Kim, Chalmers, Feigl, Davidson, Russell, Brentano, Meinong, Fodor, Stich, Block, Lycan, Putnam, Tye, Armstrong, Lewis, Ryle, Wittgenstein, Churchland, Dennett, Bateson, Dretske, Strawson, Heidegger)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Takeover of the Mind No doubt most people feel that their mind is more important than their body. People may be afraid of losing a limb in an accident, but would still prefer that to losing consciousness. A person who is lying in an irreversible coma is considered "technically dead" even if her body is still alive. We don't mind the transplant of an organ, even of the heart; but we would oppose a transplant of the brain: most people would interpret a heart transplant on them as "somebody is giving me her heart"; but they would interpret a brain transplant on them as "I am giving my body to someone else". The mind seems to be so much more important than the body. We can envision a future in which minds will exist without bodies, but not a future in which we would be happy to be bodies without minds. Ultimately, we are our minds, not our bodies. It is likely that this was not always the case. There was probably a time when survival of the body was more important than survival of the mind. The preeminence of the mind is a recent phenomenon. The main goal of our ancestors was probably to protect their bodies from predators and from natural catastrophes. If the body dies, the individual (whatever an individual is made of) simply dies. Nature grants the body an obvious preeminence over the mind, a preeminence that we have forgotten but that was probably there for a long time during the evolution of the human species. For a long time, the mind may have been simply a means to achieve the goal of protecting the body. Nothing more than an evolutionary advantage over other species in protecting the body. Just like some animals have a fur to protect them from cold weather. Then, somehow, that evolutionary advantage became the predominant part of the individual. To the point that we declare "dead" somebody whose body is alive but whose mind is not. There has been steady progress towards turning the tables: the mind has slowly taken over the body, and now we think of an individual as her mind (whereas we still think of a dog as its body, regardless of whether it has a mind or not). http://www.thymos.com/tat/mind.html (1 of 9)25/07/2003 14:21:09
Thinking About Thought: Consciousness, Life and Meaning
Historically, ancient civilizations don't seem to have appreciated how awesome the human mind is and don't seem to have realized how "low" non-human things are. For example, ancient Greeks believed that the rivers were children of a god. Today, it may sound strange to think of a river as a "living being", because we know that most of its water changes all the time and we know that its water comes from melting snow and rain, and so forth. But isn't that true of humans too? Don't we change cells all the time? Don't we take in energy and matter from outside (as food)? Doesn't a river have a personality? Other than the fact that rivers live far longer than us, it is not so obvious that having a mind makes humans all that different from rivers, as we today believe. The first part of the mystery we face is why this happened and how. The second part is, in a sense, proof that the mind is a recent accident: we ask what is the mind. When we ask what is the mind, we implicitly assume that the body is a given. The body is a given and we wonder what the mind is. We don’t take the mind for granted and wonder what the body is and why we have bodies. We are bodies that wonder about our minds, not minds that wonder about our bodies. At some point, minds happened to bodies. And now bodies use their minds to wonder "how did that happen" and "what is my mind". The quest for a rational explanation of the human mind has always started with the task of defining the relationship between mind and matter: is our mind made of matter? (Note that we don’t ask: is our body made of spirit?) Is it made of a different substance? What differentiates the mental from the non-mental? How do our mind and body relate? Is our mind inside our body? Is our mind born with the body? Will it die with the body? Does it grow with the body? These days, having learned quite a bit about the brain and being reassured by countless psychological experiments that our brain is the main entity responsible for our thinking, we are mostly interested in the specific relationship between brain and mind: what is the relationship between the neural and the mental? How does the mental originate from the neural? And, finally, what is in the mind? Dualism and the mind-body debate Historically, two main schools of thought have antagonized each other: "dualism" and "monism". According to dualism, mind and body are made of two different substances. The first and most famous of dualists was the French philosopher Rene` Descartes (17th century), who is credited as starting the whole "mind-body debate". He observed that reality is divided into matter and spirit. These are two different worlds, made of two different substances. He defined what matter is and what mind is: matter is whatever exhibits the property of "extension" (geometric properties such as "size", "shape", etc.) and mind is… "cogito", i.e. thought (a more scientific definition of mind will came later from Brentano). "Res extensa" (things that have an extension) and "res cogitans" (things that think) belong to two separate realms, and cannot be studied with the same tools. This dualism had an enormous influence on future generations. Newton's Physics, for example, is a direct consequence of that approach: Physics studies the realm of matter, and only deals with matter. And such it will remain until the end of the 20th century. Descartes' dualism was a departure from Aristotle's dualism that had rules for centuries. Aristotle divided http://www.thymos.com/tat/mind.html (2 of 9)25/07/2003 14:21:09
Thinking About Thought: Consciousness, Life and Meaning
things into living and nonliving. Living beings behaved differently and therefore required a different treatment. Descartes realized that living and nonliving matter are, ultimately, the same matter, that obeys the same physical laws. There is "one" physical world for everything. Living matter appears to "behave" because it is more complex. In reality, animals are mechanical automata. The real distinction is at the level of thought. Some beings (and, for Descartes, it was only humans) can think. The difference is not between living and nonliving matter, which are ultimately the same substance, but between matter and mind, which are two different substances. In a sense, Aristotle's philosophy was centered on life, whereas Descartes' philosophy was centered on man. (It will take three centuries to resurrect the idea that animals, too, may have a mind, and therefore return to Aristotle). Descartes also clearly understood that the brain was the seat of the body-mind interaction, although he couldn't explain it. Dualists The 18th century British philosopher David Hume was also a dualist, but he pointed out that "mind" is really a set of "perceptions" (that probably include "sensations"). The self is an illusion. The mind is simply a theater where perceptions play their part in rapid succession, often intersect and combine. The self is like a republic, whose members have an independent life but are united by a common constitution: the republic is one, even if the members (and maybe even their individual constitutions) are continuously changing. The identity of the republic is provided not by its contents, that are continuously fluctuating, but by the causal relationship that holds its members together. Epiphenomenalism The mystery remained of how mind and body interact, since they are different substances with different properties. The Swiss biologist Charles Bonnet attempted to solve the dilemma by introducing "Epiphenomenalism", the idea that the mind cannot influence the body (an idea later borrowed by the British philosopher Thomas Huxley). Bonnet expanded on Descartes' intuition that mind-body interaction must occur in the brain. He then analyzed the brain and realized that mental activity reflects brain actitivy. Bonnet also expanded on Descartes' intuition that a body is a mechanical device. He simply added that the automaton is controlled by the brain. Different animals have different functioning (an idea that Huxley married to Darwin's theory) but ultimately they are all bodies run by brains in an optimal way to survive and reproduce. Humans, and possibly other animals as well, are also conscious, but consciousness has no role in directing the automaton. Mind cannot influence the body. The mind merely observes the behavior of the body, although it believes that it actually causes it. "Epiphenomenalism" therefore accepts that mind and body are made of different substances, but mind has no influence on body. The brain causes the mind, but the mind has no saying on the brain's work. Mental events have no material effects, whereas material events may have mental effects. Mental events are simply by-products of material events (like smoke is a by-product of a fire but has no impact on the fire). The world of ideas The problem with dualism is how mind and brain influence each other while being made of two different substances. There is no doubt that the mind and the brain communicate somehow both ways. How can that http://www.thymos.com/tat/mind.html (3 of 9)25/07/2003 14:21:09
Thinking About Thought: Consciousness, Life and Meaning
happen if they are made of different stuff? One way out of this problem is to assume the existence of an intermediary between the two. For example, the influential Austrian philosopher Karl Popper and the Bristih neurophysiologist John Eccles, a Nobel-prize winner, posit the existence of a first world (the world of physical bodies), a second world (the world of mental states) and a third world (the world of products of the mind). The second world communicates with both the others. Abstract objects of mathematics, scientific theories and art products are examples of activities that belong to neither the mental world nor the physical world. Mind plays the role of intermediary between the imaginary world (World 3) and the real world (World 1). "Downward causation" operates from World 3 to World 1. The mind is basically an operator that relates abstract objects and physical ones. Interesting things happen in this third world. First of all, objective knowledge belongs to it: the third world evolves through the growth of objective knowledge. Objective knowledge confers a degree of autonomy to the third world. For example, numbers are created by the mind, but then mathematical laws determine what happens to them, regardless of what our minds think and feel. The growth and evolution of objective knowledge obey the same law that drives biological phenomena of survival and evolution (basically, trial and error). Eccles argues that the interaction between the mind and the brain of an individual is analogous to a probability field of Quantum Mechanics. Mental "energy" can cause neural events by a process analogous to the way a probability field causes action. He calls "psychon" the mental unit that transmit mental intentions to the neural units. The British physicist Roger Penrose, one of the leaders in General Relavitiy, also subscribes to the notion that there exists a separate world of conscious states and that the mind can access that world. But Penrose's "world of ideas" is still a physicist's world: "protoconscious" information is encoded in space-time geometry at the fundamental Planck scale, and our mind has access to them (i.e., is conscious) when a particular quantum process occurs in our brain. The American philosopher John Searle does not go that far, but he too rejects the idea that the universe can be partitioned into physical and mental properties: things such as "ungrammatical sentences, my ability to ski, the government and points scored in football games" cannot be easily categorized as mental or physical. The traditional "mental versus physical" dichotomy appears to be pointless. A more humble formulation is due to the American mathematician Rudy Rucker, who believes in the existence of a separate "mindscape". Rucker asks: "Is what you thought yesterday still part of your mind?" The question is not easy to answer if you assume that ideas are part of minds. Rucker's conclusion is that there exists a world of ideas separate from the mental and the physical. Our minds can travel the mindscape that contains all possible thoughts just like our bodies can travel the physical space that contains all possible locations. Minds share the same mindscape the way bodies share the same physical space. We all share the same mindscape, just like we all share the same universe. In particular, the mindscape contains all mathematical objects and mathematicians explore mindscape the same way astronauts explore physical space. Ditto for natural laws and physicists. Mathematical formula and laws of nature have an independent
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Thinking About Thought: Consciousness, Life and Meaning
existence of their own. This is, of course, but a new spin on Plato's old world of ideas. ..................................... Mind or Matter It used to be a simple question: what is the soul? "Mind" complicated the question because it related the soul to a specific place, the brain, without being as specific. Is mind the soul? Is mind more than the soul? Is mind less than the soul? The author of this book thinks that the problem is simply formulated in a nonscientific way. "Mind" is a generic term that refers to the set of cognitive faculties we humans have and sometimes it also encompasses consciousness. It would be more appropriate to focus on cognition itself. While some may be reluctant to credit animals with a mind, most will have no problem crediting them with some degree of cognitive faculties, such as memory, learning and even reasoning. Cognition can safely be assumed as a property of at least all living organisms, but a property that comes in (continuous) degrees: humans have more of it than, say, snails. Furthermore, there are striking similarities between the behavior of cognitive (living) matter and the behavior of non-cognitive (dead) matter. Even a piece of paper exhibits a form of memory that resembles the way our memory works: if you bend it many times in the same direction, it will progressively "learn" to bend in that direction; if you stop bending it, it will slowly resume its flat position. Any piece of matter "remembers" what has happened to it in its shape, and sometimes in its chemical composition (that laboratory scientists can sometimes trace back in time). Far from being unique to the mind, cognitive faculties appear to be ubiquitous in nature. Memory and learning can therefore be said to be ubiquitous in nature, as long as we assume that they come in degrees. Cognition may not necessarily be an exclusive property of living matter. Cognition may be a general property of matter, that the human brain simply amplifies to perform very interesting actions. At least that part of the mind, the one that has to do with cognitive faculties, may be "reduced" to material processes after all. The other part, consciousness, is a vastly more difficult topic. The Darwinian Mind "Thought" is an entirely different game. "Mind" defined as the totality of thoughts is a far more elusive mystery. But it is my belief that this mind, just like the brain, obeys laws that are Darwinian in nature. Both the mind (the system of thoughts) and the brain (the system of neural connections) obey the same laws of selection and evolution that apply to species and to antibodies. Both neural structures and thoughts are selected by the environment and vary in a fundamentally random way. The same process that accounts for the origin of species is probably responsible for the origin of thoughts. Just like species spawn more species and generate a branch of the tree of life, so thoughts generate threads of thoughts. Threads of http://www.thymos.com/tat/mind.html (5 of 9)25/07/2003 14:21:09
Thinking About Thought: Consciousness, Life and Meaning
thoughts may get weaker and weaker until they disappear, or they may get stronger and stronger. It all depends on experience. But at any time, the mind is full of competing threads. In this respect, "personality" may just be the result of natural selection of thought threads. Whatever threads are reinforced by the experience of an individual constitute the personality of the individual. The Factory of Illusions The mind is a factory of illusions. It creates an inner reality, as opposed to the outer reality of the world. We see colors and shapes, smell odors and perfumes, hear voices and sounds. We perceive the flowing of time. But the universe is made of particles and waves. The mind translates the world into sensations. Then it elaborates sensations to produce thoughts, memories, concepts, ideas. None of this is real. It is all one gigantic illusion. We will never even be sure whether anything exists at all. Then the mind creates consciousness, i.e. the awareness of feeling those sensations and, among them, the subjective sensation of existing. May consciousness be the direct consequence of the existence of those illusions? Is any being endowed with sensory perception also endowed with consciousness? Science needs crisp, reliable definitions, especially definitions of the objects it studies. Unfortunately, the mind is one of those things that we intuitively, "obviously" know, but, when we try to formalize, we realize we don’t know at all. The most common way to define what the mind is, is to list cognitive faculties: the mind is something that is capable of learning, remembering, reasoning, etc. The truth is that, by doing so, we have only shifted level: we now have to define learning, remembering, reasoning, etc. The more scientific we try to be, the more we end up with definitions that are broader than we would want them to be. As we saw, many things (and certainly many biological systems) can be said to be capable of some form of learning, remembering, reasoning, etc. Crystals exhibit powerful processes of self-organization. What is so special about the mind? It is not the cognitive faculties. It is the inner life. The mind is a factory of illusions, that translates this world of particles and waves into a world of colors, sounds and smells. And it is the illusion of all illusions: consciousness. Therein lies the secret of the mind.
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Armstrong David Malet: A MATERIALIST THEORY OF THE MIND (Humanities Press, 1968) Armstrong David Malet: THE NATURE OF MIND (Cornell Univ Press, 1981) Armstrong, David Malet: THE MIND-BODY PROBLEM (Westview, 1999)
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Thinking About Thought: Consciousness, Life and Meaning
Bechtel William: PHILOSOPHY OF MIND (Lawrence Erlbaum, 1988) Block Ned: READINGS IN PHILOSOPHY OF PSYCHOLOGY (Harvard Univ Press, 1980) Bonnet, Charles: ESSAI DE PSYCHOLOGIE (1754) Brentano Franz: PSYCHOLOGY FROM AN EMPIRICAL STANDPOINT (1874) Broad Charlie Dunbar: MIND AND ITS PLACE IN NATURE (1929) Chalmers David: THE CONSCIOUS MIND (Oxford University Press, 1996) Chomsky Noam: LANGUAGE AND THOUGHT (Moyer Bell, 1991) Churchland Paul: MATTER AND CONSCIOUSNESS (MIT Press, 1984) Crane, Tim: THE MECHANICAL MIND (Penguin, 1995) Davidson Donald: INQUIRIES INTO TRUTH AND INTERPRETATION (Clarendon Press, 1984) Dennett Daniel: CONTENT AND CONSCIOUSNESS (Routledge, 1969) Dennett Daniel: KINDS OF MINDS (Basic, 1998) Descartes Rene`: PRINCIPIA PHILOSOPHIAE (1644) Dretske Fred: KNOWLEDGE AND THE FLOW OF INFORMATION (MIT Press, 1981) Dretske Fred: EXPLAINING BEHAVIOR (MIT Press, 1988) Eccles John: EVOLUTION OF THE BRAIN (Routledge, 1991) Eccles John: THE SELF AND ITS BRAIN (Springer, 1994) Feigl Herbert: THE MENTAL AND THE PHYSICAL (Univ of Minnesota Press, 1967) Fodor Jerry: LANGUAGE OF THOUGHT (Crowell, 1975) Fodor Jerry: REPRESENTATIONS (MIT Press, 1981) Fodor Jerry: MODULARITY OF THE MIND (MIT Press, 1983)
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Thinking About Thought: Consciousness, Life and Meaning
Fodor Jerry: THE ELM AND THE EXPERT (MIT Press, 1994) Gardner Howard: MIND'S NEW SCIENCE (Basic, 1985) Gregory Richard: OXFORD COMPANION TO THE MIND (Oxford, 1987) Heidegger Martin: BEING AND TIME (1962) Hume, David: A TREATISE OF HUMAN NATURE (1739) Husserl Edmund: LOGICAL INVESTIGATIONS (1900) Kim Jaegwon: SUPERVENIENCE AND MIND (Cambridge University Press, 1993) Kim Jaegwon: MIND IN A PHYSICAL WORLD (MIT Press, 1998) Leibniz: THE MONADOLOGY (1714) Lewis David K.: PHILOSOPHICAL PAPERS (Oxford Press, 1983) Lewis David K.: ON THE PLURALITY OF WORLDS (Basil Blackwell, 1986) Lycan William: CONSCIOUSNESS (MIT Press, 1987) Lycan William: MIND AND COGNITION (MIT Press, 1990) McGinn Colin: CHARACTER OF MIND (Oxford Univ Press, 1997) Popper Karl & Eccles John: THE SELF AND ITS BRAIN (Springer-Verlag, 1977) Popper Karl: KNOWLEDGE AND THE BODY-MIND PROBLEM (Routledge, 1994) Priest, Stephen: THEORIES OF THE MIND (Houghton Mifflin, 1991) Putnam Hilary: MIND, LANGUAGE AND REALITY (Cambridge Univ Press, 1975) Rosenthal David: NATURE OF MIND (Oxford University Press, 1991) Rucker Rudy: INFINITY AND THE MIND (Birkhauser, 1982) Russell Bertrand: ANALYSIS OF MIND (1921) Russell Bertrand: ANALYSIS OF MATTER (Allen and Unwin, 1927)
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Thinking About Thought: Consciousness, Life and Meaning
Russell Bertrand: AN INQUIRY INTO MEANING AND TRUTH (Penguin, 1962) Ryle Gilbert: THE CONCEPT OF MIND (Hutchinson, 1949) Searle John: THE REDISCOVERY OF THE MIND (MIT Press, 1992) Sterelny, Kim: THE REPRESENTATIONAL THEORY OF MIND (Blackwell, 1990) Stich Stephen: FROM FOLK PSYCHOLOGY TO COGNITIVE SCIENCE (MIT Press, 1983) Stich Stephen: DECONSTRUCTING THE MIND (Oxford Univ Press, 1996) Tye Michael: TEN PROBLEMS OF CONSCIOUSNESS (MIT Press, 1995) Whitehead Alfred: THE CONCEPT OF NATURE (Cambridge Univ Press, 1920) Wittgenstein Ludwig: PHILOSOPHICAL INVESTIGATIONS (Macmillan, 1953)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Inside the Brain (James, Thorndike, Pavlov, Skinner, Koehler, Lashley, Hebb, Jerne, Young, Edelman, Changeux, Purves, Damasio, Harth, Freeman, Gazzaniga, MacLean, Brown, Mora, Muller, Goertzel, Zeki, Valiant, Thelen)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Understanding how the brain works is not a minor task. The structure of our mental organs (the brain) determines what we are capable of thinking, just like the structure of our arms or legs determines which movements we are capable of. Connectionism Human memory may be deficient in many ways (it forgets, it does not remember "photographically"), but somehow it is extremely good at recognizing. I recognize a friend even if he grew a beard, even if he's wearing different clothes every day, even if I see him sideways, and at any possible angle. How can I recognize all those images as the same image if they are all different? It is almost impossible to take the identical shot of a person twice: some details will always be different: how can I recognize that it is the same person, if the image is always different? I can show you two pictures of a street, taken at different times: you will recognize them as pictures of the same street. But there are probably countless differences: cars that were parked moved away and new cars took their places, pedestrians that were walking are gone, dogs and birds have changed positions, smoke has blown away, all the leaves of all the trees have moved because of the breeze, etc. How do you recognize that it is the same street, if the image of that street is never the same? The key to understanding the mind may lie in the peculiar structure of our brain. Unlike most of our artifacts, which are designed to be modular, hierarchical and linear, a brain is an amazingly complicated piece of work. Several theories were proposed over the centuries to make sense of its structure, until finally
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Thinking About Thought: Consciousness, Life and Meaning
"Connectionism" came around. Connectionism is one of the most important ideas of our century. Its implications extend beyond the field of neurophysiology, where it received its main impulse. Connectionist models have surfaced well beyond the borders of brain anatomy, notably in Cybernetics. At the turn of the century, the influential American philosopher and psychologist William James had a number of powerful intuitions: that the brain is built to ensure survival in the world; that cognitive faculties cannot be abstracted from the environment that they deal with; that the brain is organized as an associative network; that associations are governed by a rule of reinforcement. The latter two laid the foundations for Connectionism; the former two laid the foundations for a cognition grounded in a Darwinian scenario of survival of the fittest, and, in a sense, provided a justification for the preeminence of Connectionism. Selective behavior Other psychologists contributed, directly or indirectly, to the connectionist model of the brain. The scientists that subscribed to the school of Behaviorism, such as the Russian physiologist Ivan Pavlov and the American psychologist Burrhus Skinner, were influential in emphasizing the simple but pervasive law of learning through conditioning: if an unconditioned stimulus (e.g., a bowl of meat) that normally causes an unconditioned response (e.g., the dog salivates) is repeatedly associated with a conditioned stimulus (e. g., a bell), the conditioned stimulus (the bell) will eventually cause the unconditioned response (the dog salivates) without any need for the unconditioned stimulus (the bowl of meet). Behaviorists came to believe that all forms of learning could be reduced to conditioning phenomena. To Skinner, all learned behavior is the result of selective reinforcement of random responses. Mental states (what goes on in our minds) have no effect on our actions. Skinner did not deny the existence of mental states, he simply denied that they explain behavior. A person does what she does because she has been "reinforced" for doing that, not because her mind decided so. Skinner noticed a similarity between reinforcement and natural selection: random mutations are "selected" by the environment, random behavior is also selected by the environment. A random action can bring reward (from the environment) that will cause a reinforcement and therefore will increase the chances that the action is repeated in the future. An action that does not bring reward will not be repeated. The environment determines which behavior is learned, just like the environment determines which species are evolved. Cognition Fiercely opposed to Behaviorism was the school of Gestalt, which strongly believed in higher cognitive processes and opposed the idea that the individual stimulus could cause an individual response. For example, the German psychologist Max Wertheimer claimed in 1938 that perception ought to be more than the sum of the things perceived, that the whole is more than the sum of the parts. He showed, for example, how one can alter the parts of a melody but the listener would still recognize the melody. Perception of the whole does not depend on perception of all of its parts; we recognize the shape of a landscape way before http://www.thymos.com/tat/brain.html (2 of 8)25/07/2003 14:21:34
Thinking About Thought: Consciousness, Life and Meaning
we recognize each tree and rock in the landscape, and we recognize that a tree is a tree before we recognize what kind of tree it is, because regnognizing the species requires an analysis of its parts. Already in the 1920s, the German psychologist Wolfgang Koehler had claimed that most problem-solving is not due to a decomposition of the problem but to sudden insight. One may not recognize a familiar face for a few seconds, and then suddenly recognize it. This is not due to a myriad calculations, but to a sudden insight that cannot be broken down into atomic processes. It is just a sudden insight. The German neurologist Kurt Goldstein's classical work still stands as a fundamental challenge to the dogmas of neurology and psycholody. Kurt Goldstein viewed of the organism as a system that has to struggle to cope with the challenges of the environment and of its own body. The organism cannot be divided into "organs" and far less into "mind" and "body", because it is the whole that reacts to the environment. Nothing is independent within the organism. The organism is a whole. "Disease" is a manifestation of a change of state between the organism and its environment. Healing does not come through "repair" but through adaptation. The organism cannot simply return to the state preceding the event that changed it, but has to adapt to the conditions that caused the new state. In particular, a local sympton is not meaningful to understand a "disease", and the organism's behavior during a disease is hardly explained as a response to that specific symptom. A patient's body will often undergo mass-scale adjustments. Goldstein emphasizes the ability of organisms to adjust to catastrophic breakdowns of their most vital (mental or physical) functions. The organism's reaction is often a redistribution of its (mental or physical) faculties. Coherently, gestalt psychologists claimed that form is the elementary unit of perception. We do not construct a perception by analyzing a myriad data. We perceive the form as a whole. Around 1950 experiments by the American neurologist Karl Lashley confirmed that intuition: a lesion in the brain does not necessarily cause a change in the response. Lashley concluded that functions are not localized but distributed around the brain, that there are no specialized areas, that all cortical areas are equally potent in carrying out mental functions (this was his "principle of equipontentiality"). Lashley realized that this architecture yields a tremendous advantage: the brain as a whole is "fault tolerant", because no single part is essential to the functioning of the whole. While today we know that regions of the brain are specialized, the structure of each region does comply with Lashley's principle. Lashley also enunciated a principle which can be viewed as dual, the principle of "mass action": every brain region partakes (to some extent) in all brain processes. Lashley even imagined that memory behaved like an electromagnetic field and that a specific memory was a wave within that field. While he never came to appreciate the importance of the "connections" (over mass), Lashley's ideas were sort of complementary to the ideas of connectionism. Today, we know that functions are indeed localized in the brain, but Lashley was right that the processing of information inside the brain involves "mass action". The function is analyzing data from the retina is localized in a specific region of the brain, but the function of "seeing" is not localized, because it requires processes that are spread around the brain. http://www.thymos.com/tat/brain.html (3 of 8)25/07/2003 14:21:34
Thinking About Thought: Consciousness, Life and Meaning
There are maps of the retina in the brain (even more than one), and there are maps of the entire body in the brain, and they are orderly maps. The brain keeps a map of what is going on in every part of the body. The primacy of the connections Another behaviorist, the American psychologist Edward Thorndike, a student of William James, is the man credited with outlining the essence of the connectionist model of the mind. In a sense, he explained how Skinner's reinforcement occurs. Thorndike had been the first psychologist to propose that animals learn based on the outcome of their actions (the "law of effect") and Skinner had simply generalized his ideas. Thorndike modeled the mind as a network of connections among its components. Learning occurs when elements are connected. Behavior is due to the association of stimuli with responses that is generated through those connections. Thorndike went also very close to formulating Hebb’s law when he discovered the law of effect: the probability that a stimulus will cause a given response is proportional to the satisfaction that the response has produced in the past. This principle sort of reconciled natural selection and Behaviorism. At the same time, Connectionism also reconciled Behaviorism and Gestalt, because it could account for Lashley’s findings: in a network of connections, the relative importance of a connection could be negligible. Connectionism can be viewed at various levels of the organization of the mind. At the lowest level, it deals with the neural structure of the brain. The brain is reduced to a network of interacting neurons. Each neuron is a fairly simple structure, whose main function is simply to transmit impulses to other neurons. When anything happens to a neuron, it is likely to affect thousands of other neurons because its effects can propagate very quickly from one neuron to the other. From the outside, the only thing that matters is the response of the brain to a certain stimulus. But that response is the result of thousands of messages transmitted from neuron to neuron according to the available connections. A given response to a given stimulus occurs because the connections propagate that stimulus from the first layer of neurons to the rest of the connected neurons until eventually the response is generated by the last layers of neurons. As long as the connections are stable, a given stimulus will always generate the same response. When a connection changes, a different response may be produced. Connections change, in particular, when the brain "learns" something new. The brain "learns" what response is more appropriate to a given stimulus by adjusting the connections so that next time the stimulus will produce the desired response. As a matter of fact, the functioning of the brain can be summarized as a continuous refining of the connections between neurons. Each connection can be strengthened or weakened by the messages that travel through it. In 1949 the Canadian physiologist Donald Hebb had a very simple, but very powerful, intuition: that strengthening and weakening of connections depend on how often they are used. If a connection is never used, it is likely to decay, just like any muscle that is not exercised. If it is used very often, it is likely to get reinforced. One more time, a Darwinian concept came to play a key role: competitive behavior. Connections "compete" to survive. At a higher level, a connectionist organization can be found in the way our mind organizes concepts. http://www.thymos.com/tat/brain.html (4 of 8)25/07/2003 14:21:34
Thinking About Thought: Consciousness, Life and Meaning
Concepts are not independent of each other: a concept is very much defined by the other concepts it relates to. The best definition of a concept is probably in terms of other concepts and the way it relates to them. Concepts also rely on an associative network. Therefore, the four maxims by James also apply to concepts. The Neural Structure of the Brain The human brain is probably the single most complex structure that we have found in the universe. Even the human genome is simpler. First of all, the brain is really just the upper extremity of the spinal cord. Nerves departing from the spinal cord communicate with the rest of the body. The spinal cord contains the same grey matter of the brain. Most of the human brain is made of two hemispheres, linked by the "corpus callosum", and covered by the cortex. Under the corpus callosum is located one of the main areas of control of behavior, containing the "thalamus", the "hypothalamus" and the "amygdala". The thalamus is a mini-mirror of the cortex: it seems to replicate the same information, but on a smaller scale. The two amygdalas are widely believed to be in charge of emotions: affection, fear and attention originate or are amplified here. The function of the two thalami seems to be to convey signals from the senses to the cortex and from the cortex to the muscles. The amygdala has the power to take over this strategic highway. The hypothalamus, located below the thalamus, is involved in many functions, but in particular seems to be responsible for controlling body temperature (pretty much like a thermostat). Behind the hemispheres is the "cerebellum", one of the main areas of integration of stimuli and coordination of action. The cerebellum contains areas like the "pons" that communicate with the rest of the body. The cerebellum is a bit like a miniature brain: it is divided into hemispheres and has a cortex that surrounds these hemispheres. The cortex is one of the main areas of sensory-motor control. The cortex is by far the largest structure in the brain: in humans, it accounts for about two thirds of the total brain mass. The terms "cortex" and "neocortex" are often used interchangeably because the neocortex constitutes most of the cerebral cortex in humans, but this is not true in general. The Portoguese neurologist Antonio Damasio Damasio has hypothesized that regions of the cortex form "convergence zones" for associative memories. Here different aspects of an experience are united. Located at the base of each hemisphere are the hippocampi. The hippocampus is one of the main areas of recalling long-term memory. It takes about three years to consolidate short term memory into long term memory. For three years the hippocampus is directly responsible for retrieving a memory. After that period, the memory slows into long term memory. Lesions to the hippocampus result in forgetting everything that happened over the last three years and http://www.thymos.com/tat/brain.html (5 of 8)25/07/2003 14:21:34
Thinking About Thought: Consciousness, Life and Meaning
not being able to remember anything ever again for longer than a few seconds. Alternatively, one can view a brain hemisphere as two concentric spheres: the inner one is the limbic system, comprising amygdala, thalamus, hypothalamus and hippocampus; the outer one is the neocortex. The neocortex processes sensory information and channels it to the hippocampus, which then communicates with the other organs of the limbic system. The limbic system appears to be a central processing unit that mediates between sensory input and motor output, between bodily sensations and body movements. In other words, the limbic system appears to be the main connection between mind and body. The limbic system is (evolutionarily speaking) the oldest part of the brain, the part that humans share with all mammals and that is well developed also in other vertebrates. Finally, the brainstem is the general term for the area of the brain between the thalamus and spinal cord. This is at the bottom of the brain, next to the cerebellum, and represents the brain's connection with the "autonomic" nervous system, the part of the nervous system that regulates functions such as heartbeat, breathing, etc. These are mechanic functions, but no less vital. Dominance Since Roger Sperry’s "split-brain" studies of the 1960’s, it has been held that the two hemispheres control different aspects of mental life: the left hemisphere is dominant for language and speech, the right brain excels at visual and motor tasks and may also be the prevalent source of emotions. This is due to the fact that two hemispheres are not identical. For example, the speech area of the cortex is much larger in the left hemisphere. The roles of two hemispheres are not so rigid, though: a child whose left hemisphere is damaged will still learn to speak and will simply use the right hemisphere for language functions. Just like it dominates in language, the left hemisphere also dominates in movement. Both hemispheres organize movement of limbs (each hemisphere takes care of the limbs at the opposite side of the body), but the left hemisphere is the one that directs the movement and that stores the feedback (the one that learns skills). If the two hemispheres are separated, the right limbs keep working normally, but the left limbs become clumsy and are often unable to carry out even simple learned skills like grabbing a glass. Brain asymmetry is not uncommon in other species, but handedness (that individuals always prefer one hand over the other) is uniquely human, and handedness appears to depend on the asymmetry of the hemispheres. The main "bridge" between the two hemispheres is the corpus callosum, but a number of other "commissures" (communication channels) exist, and their
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Thinking About Thought: Consciousness, Life and Meaning
purpose is not known.
The life of neurons
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Brown Jason: THE LIFE OF THE MIND (Lawrence Erlbaum, 1988) Changeux JeanPierre: NEURONAL MAN (Pantheon, 1985) Changeux JeanPierre: ORIGINS OF THE HUMAN BRAIN (Oxford University Press, 1995) Churchland Paul: ENGINE OF REASON (MIT Press, 1995) Damasio Antonio: DESCARTES' ERROR (G.P. Putnam's Sons, 1995) Edelman Gerald: NEURAL DARWINISM (Basic, 1987) Festinger Leon: THEORY OF COGNITIVE DISSONANCE (1957) Freeman Walter: SOCIETIES OF BRAINS (Erlbaum, 1995) Gazzaniga Michael & LeDoux Joseph: INTEGRATED MIND (Plenum Press, 1978) Gisolfi Carl & Mora Francisco: THE HOT BRAIN (MIT Press, 2000) Goertzel Ben: THE EVOLVING MIND (Gordon & Breach, 1993) Goldstein Kurt: THE ORGANISM: A HOLISTIC APPROACH TO BIOLOGY (American Book, 1939) Hebb Donald: ESSAY ON MIND (Lawrence Erlbaum, 1980) Ivry, Richard & Robertson, Lynn: THE TWO SIDES OF PERCEPTION (MIT Press, 1998)
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Thinking About Thought: Consciousness, Life and Meaning
Hebb Donald: THE ORGANIZATION OF BEHAVIOR (John Wiley, 1949) Hull Clark: PRINCIPLES OF BEHAVIOR (Appleton-Century-Crofts, 1943) James William: THE PRINCIPLES OF PSYCHOLOGY (1890) Koehler Wolfgang: INTELLIGENSPRUEFUNGEN AM MENSCHENAFFEN (1925) Lashley Karl Spencer: BRAIN MECHANISMS AND INTELLIGENCE (Dover, 1963) Lavine Robert: NEUROPHYSIOLOGY (Collamore, 1983) MacLean Paul: THE TRIUNE BRAIN IN EVOLUTION (Plenum Press, 1990) Purves Dale: NEURAL ACTIVITY AND THE GROWTH OF THE BRAIN (Cambridge Univ Press, 1994) Skinner Burrhus: BEHAVIOR OF ORGANISMS (1938) Thelen Esther & Smith Linda: A DYNAMIC SYSTEMS APPROACH TO THE DEVELOPMENT OF COGNITION AND ACTION (MIT Press, 1994) Thorndike Edward: ANIMAL INTELLIGENCE (1898) Underwood Geoffrey: OXFORD GUIDE TO THE MIND (Oxford Univ Press, 2000) Valiant Leslie: CIRCUITS OF THE MIND (Oxford University Press, 1994) Young John: A MODEL OF BRAIN (Clarendon Press, 1964) Zeki Semir: A VISION OF THE BRAIN (Blackwell, 1993)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Cognition: A General Property of Matter (Helmholtz, Craik, Simon, Newell, Johnson-Laird, Fauconnier, Lakoff, Marr, Paivio, Kosslyn, Pylyshyn, Finke, Tye, Selz, Minsky, Schank, Arbib, Leyton, Sowa)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Cognition Cognition is the set of faculties that allow the mind to process inputs from the external world and to determine action in the external world. They comprise perception, learning, memory, reasoning and so forth. Basically, we perceive something, we store it in memory, we retrieve related information, we process the whole, we learn something, we store it in memory, we use it to decide what to do next. All of these are part of cognition. Is all of cognition conscious? Is there something that we remember, learn or process without being aware of it? Probably. At least, the level of awareness may vary wildly. Sometimes we study a poem until we can remember all the words in the exact order: that requires a lot of awareness. Sometimes we simply store an accident without paying too much attention to it. Consciousness is like another dimension. One can be engaged in this or that cognitive task (first dimension) and then it can be aware of it with different levels of intensity (second dimension). It is, therefore, likely that cognitive faculties and consciousness are independent processes. Since it processes inputs and yields outputs, cognition has the invaluable advantage that it lends itself to modeling and testing endeavours, in a more scientific fashion than studies on consciousness. Language too is a cognitive process. Its function and nature require a separate treatment, but it is likely that language's fundamental mechanisms are closely related to the mechanisms that support the other faculties. Mediation
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Thinking About Thought: Consciousness, Life and Meaning
Over the last few decades, psychologists have been deeply influenced by the architecture of the computer. When it appeared, it was immediately apparent that the computer was capable of performing sophisticated tasks that went beyond mere arithmetics, although they were performed by a complex layering of arithmetic sub-tasks. The fact that the computer architecture was able to achieve so much with so little led to the belief that the human mind could also be reduced to a rational architecture of interacting modules and sequential processes of computation. In the second half of the 19th century, the German physiologist and physicist Hermann Helmholtz anticipated modern thinking about cognition when he advanced his theory that perception and action were mediated by a (relatively slow) process in the brain. The "reaction time" of a human being is high because neural conduction is slow. His studies emphasized that the stimulus must first be delivered to the brain and the idea of action must first be delivered to the limbs before anything can occur. Helmholtz thought that humans have no innate knowledge, that all our knowledge comes from experience. Perceptions are derived from unconscious inference on sense data: our senses send signals to the brain, which are interpreted by the brain and then turned by the brain into knowledge. Perceptions are mere hypotheses on the world, which may well be wrong (as proven by optical illusions). Perceptions are hypotheses based on our knowledge. Knowledge is acquired from perceptions. This paradigm would become the "classical" paradigm of cognition. Representation The British psychologist Kenneth Craik speculated in 1943 that the human mind may be a particular type of machine which is capable of building internal models of the world and process them to produce action. Craik's improvement over Descartes' automaton (limited to mechanical reactions to external stimuli) was considerable because it involved the ideas of an "internal representation" and a "symbolic processing" of such representation. Descartes' automaton had no need for knowledge and inference. Craik's automaton needs knowledge and inference. It is the inferential processing of knowledge that yields intelligence. Symbol Processing Craik's ideas predated the theory of knowledge-based systems, which were born after the economist and Nobel-prize winner Herbert Simon and the psychologist Alan Newell developed their theory of physical symbol systems. Both the computer and the mind belong to the category of physical symbol systems, systems that process symbols to achieve a goal. A physical symbol system is quite simple: the complexity of its behavior is due to the complexity of the environment it has to cope with. It was Simon's belief that no complex system can survive unless it is organized as a hierarchy of subsystems. The entire universe must be hierarchical, otherwise it would not exist. Production Soon, the most abused model of cognitive psychology became one in which a memory containing knowledge is operated upon by an inference engine; the results are added to the knowledge base and the cycle resumes indefinitely. For example, I may infer from my knowledge that it is going to rain and http://www.thymos.com/tat/cognitio.html (2 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
therefore add to my knowledge that I need an umbrella. In this fashion, knowledge is continuously created, and pieces of it represent solutions to problems. Every new piece of knowledge, whether acquired from the external world or inferred from the existing knowledge, may trigger any number of inferential processes, which can proceed in parallel. John Anderson's ACT, as developed in 1976, was a cognitive architecture capable of dealing with both declarative knowledge (represented by propositional networks) and procedural knowledge (represented by production rules). Declarative knowledge ("knowing that") can be consulted, procedural knowledge ("knowing how") must be enacted to be used. The relationship between the two types of knowledge is twofold. On one hand, the production system acts as the interpreter of the propositional network to determine action. On the other hand, knowledge is continuously compiled into more and more complex procedural chunks through an incremental process of transformation of declarative knowledge into procedural knowledge. Complex cognitive skills can develop from a simple architecture, as new production rules are continuously learned. Anderson, therefore, thought of a cognitive system as having two short-term memories: a declarative memory (that remembers experience) and a procedural memory (that remembers rules learned from experience). Anderson also developed a probabilistic method to explain how categories are built and how prototypes are chosen. Anderson's model maximizes the inferential potential of categories (i.e., their "usefulness"): the more a category helps predict the features of an object, the more the existence of that category makes sense. For each new object, Anderson's model computes the probability that the object belongs to one of the known categories and the probability that it belongs to a new category: if the latter is greater than the former, a new category is created. Later editions of the architecture organize knowledge in three levels: a knowledge level (information acquired from the environment plus innate principles of inference), an algorithmic level (internal deductions, inductions and compilations) and an implementation level (setting parameters for the encoding of specific pieces of information). Newell, with the help of John Laird and Paul Rosenbloom, proposed a similar architecture, SOAR, based on two powerful concepts. The "universal weak method" is an organizational framework whereby knowledge determines the inferential methods employed to solve the problem, i.e. knowledge controls the behavior of the rational agent. "Universal sub-goaling" is a schema whereby goals can be created automatically to deal with the difficulties that the rational agent encounters during problem solving. A model of practice is developed based on the concept of "chunking", which is meant to produce the "power law of practice" that characterizes the improvements in human performance during practice at a given skill: the more you practice, the better you get at it. Within SOAR, each task has a goal hierarchy. When a goal is successfully completed, a chunk that represents the results of the task is created. In the next instance of the goal, the system will not need to fully process it as the chunk already contains the solution. http://www.thymos.com/tat/cognitio.html (3 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
The process of chunking proceeds bottom-up in the goal hierarchy. The process will eventually lead to a chunk for the top-level goal for every situation that it can encounter. These are two of the most sophisticated architectures advanced by the proponents of the symbolic processing approach in order to explain how the mind goes about acting, solving problems and learning how to solve new problems. Mental Modules The British psychologist David Marr, whose 1982 study of vision is a landmark in psychology, built one of the most influential cognitive architectures. Marr concluded that our vision system must employ innate information to decipher the ambiguous signals that it perceives from the world. Processing of perceptual data must be performed by "modules", each specialized in some function, which are controlled by a central module. In a fashion similar to Chomsky and Fodor, Marr assumes that the brain must contain semantic representations (in particular, a grammar) which are innate and universal (i.e., of biological nature) in the form of modules that are automatically activated. The processing of such representations is purely syntactical. Marr, Chomsky and Fodor advanced the same theory of the mind, albeit from three different perspectives: they all believe that the mind can be decomposed in modules, they all believe that syntactical processing can account for what the mind does. Specifically, Marr explained the cognitive faculty of vision as a process in several steps. First, the physical signal sent to the world is received (in the form of physical energy) by transducers, that transform it into a symbol (in the form of a neural code) and pass it on to the input modules. Then these modules extract information and send it to the central module in charge of higher cognitive tasks. Each module corresponds to neural subsystems in the brain. The central module exhibits the property of being "isotropic" (able to build hypotheses based on any available knowledge) and "Quinian" (the degree of confirmation assigned to a hypothesis is conditioned by the entire system of beliefs). The visual system is thus decomposed in a number of independent subsystems. They provide a representation of the visual scene at three different levels of abstraction: the "primal sketch", which is a symbolic representation from the meaningful features of the image (anything causing sudden discontinuities in light intensity, such as boundaries, contours, shading, textures); a two-and-a-half dimensional sketch, which is a representation centered on the visual system of the observer (e.g., describes the surrounding surfaces and their properties, mainly distances and orientation) and computed by a set of modules specialized in parameters of motion, shape, color, etc.; and finally the tri-dimensional representation, which is centered on the object and is computed according to some rules (Shimon Ullman's correspondence rules). This final representation is what is used for memory purposes. Not what the retina picked up, but what the brain computed. Production vs computation http://www.thymos.com/tat/cognitio.html (4 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
The obvious criticism against production systems is that they don't "look like" our brain. David Marr claimed that a scientist can choose either of three levels of analysis: the computational level (which mathematical function the system must compute, i.e. an account of human competence), the algorithmic level (which algorithm must be used, i.e. an account of human performance) or the physical level (which mechanism must implement the algorithm). Different sciences correspond to different levels (cognitive science studies the mind at the computational level, a neurologist studies the mind at the physical level, an eye doctor studies the mind at the computational level). Newell refined that vision by dividing cognition into several levels. The program level represents and manipulates the world in the form of symbols. The knowledge level is built on top of the symbolic level and is the level of rational agents: an agent is defined by a body of knowledge, some goals to achieve and some actions that it can perform. An agent's behavior is determined by the "principle of rationality": the agent performs those actions that, on the basis of the knowledge it has, will bring it closer to the goals. General intelligent behavior requires symbol-level systems and knowledge-level systems. Newell then broadened his division of cognitive levels by including physical and biological states. The whole band can be divided into four bands: neural, cognitive, rational and social. The cognitive band can be divided based on the response times: at the memory level the response time (the time required to retrieve the referent of a symbol) is about 10 milliseconds; at the decision level the response time is 100 milliseconds (the time required to manipulate knowledge), at the compositional level it is one second (time required to build actions), at the execution level it is 10 seconds (time required to perform the action). In the rational band the system appears as a goal-driven organism, capable of processing knowledge and of exhibiting adaptive behavior. Mental Models While the view based on production systems has long remained predominant among cognitive scientists, numerous alternatives have been offered. The British psychologist Philip Johnson-Laird has questioned both the plausibility and the adequacy of a cognitive model based on production rules. A mind that only used production rules , i.e. logic, would behave in a fundamentally different way from ours. People often make mistakes with deductive inference because it is not a natural way of thinking. The natural way is to construct mental models of the premises: a model of discourse has a structure that corresponds directly to the structure of the state of affairs that the discourse describes. For the same reason children are able to acquire inferential capabilities before they have any inferential notions: children solve problems by building mental models that are more and more complex.
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Thinking About Thought: Consciousness, Life and Meaning
In his view, the mind represents and processes models of the world. The mind solves problems without any need to use logical reasoning. A sentence is a procedure to build, modify, extend a mental model. The mental model created by a discourse exhibits a structure that corresponds directly to the structure of the world described by the discourse. To perform an inference on a problem the mind needs to build the situation described by its premises. Such mental model simplifies reality and allows the mind to find an "adequate" solution. Johnson-Laird's theory admits three types of representation: "propositions" (which represent the world through sequences of symbols), "mental models" (which are structurally analogous to the world) and "images" (which are perceptive correlates of models). Images are ways to approach models. They represent the perceivable features of the corresponding objects in the real world. Models, images and propositions are functionally and structurally different. Linguistic expressions are first transformed into propositional representations. The semantics of the mental language then creates correspondences between propositional representations and mental models, i.e. propositional representations are interpreted in mental models. But they key to understanding how the mind works is in the mental models. The French linguist Gilles Fauconnier advocates a similar vision in his theory of "mental spaces". Mental spaces proliferate as we think or talk. The mappings that link mental spaces, in particular analogical mappings, play a central role in building our mental life. In particular, "conceptual blending" is a cognitive process which can be detected in many different cognitive, cultural and social activities. By merging different inputs, it creates a blended mental space that lends itself to what we call "creative" thinking. Therefore, Fauconnier finds that the same principles that operate at the level of meaning construction operate also at the level of scientific and artistic action. The American linguist George Lakoff has given mental spaces an internal structure with his theory of "cognitive models Mental Imagery "Mental imagery" is seeing something in the absence of any sensory signal, such as the perception of a memory. The mystery is what is seen when in the brain there is no such image. Scientists have found no pictures or images in the brain, no internal eye to view pictures stored in memory and no means to manipulate them. Nevertheless, there is an obvious correspondence between a mental image of an object and the object. Ronald Finke, for example, has identified five principles of equivalence between a mental image and the perceived object: the principle of implicit encoding (information about the properties of an object can be retrieved from its mental image), the principle of spatial equivalence (parts of a mental image are arranged in a way that corresponds to the way that the parts of the physical object are arranged), the principle of perceptual equivalence (similar processes are activated in the brain when the objects are imagined as when http://www.thymos.com/tat/cognitio.html (6 of 13)25/07/2003 14:23:02
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they are perceived), the principle of transformational equivalence (imagined transformations and physical transformations are governed by the same laws of motion), the principle of structural equivalence (the mental imagery exhibits structural features corresponding to those of the perceived object such that the relations between the object's parts can be both preserved and interpreted). During the 1980s, the debate has become polarized around two main schools of thought: either (Kosslyn) the brain has mental pictures that somehow represent the real-world images, or (Pylyshyn) the brain represents images through a non-imaginistic system, namely language, i.e. all mental representations are descriptional. Stephen Kosslyn put forth a representational theory of the mind of a "depictive" type, as opposed to Fodor's propositional theory and related to Philip Johnson-Laird's models. Kosslyn thinks that the mind can build visual representations, which are coded in parts of the brain, and which reflect what they represent. Mental imagery involves scanning an internal picture-like entity. Mental images can be inspected and classified using pretty much the same processes used to inspect and classify visual perceptions. For example, they can be transformed (rotated, enlarged, reduced). There exist two levels of visual representation: a "geometric" level, which allows one to mentally manipulate images, and an "algebraic" one, which allows one to "talk" about those images. Kosslyn thinks that mental imagery achieves two goals: retrieve properties of objects and predict what would happen if the body or the objects should move in a given way. Reasoning on shapes and dimensions is far faster when we employ mental images than concepts. Kosslyn's is a theory of high-level vision in which perception and representation are inextricably linked. Visual perception (visual object identification) and visual mental imagery share common mechanisms. Opposed to Kosslyn's "pictorialism" is Pylyshyn's "descriptionalism". Pylyshyn believes in a variant of Fodor's language of thought: to him images are simply the product of the manipulations of knowledge encoded in the form of propositions. Allan Paivio's theory mediates these positions because it argues that the mind may use two different types of representation, a verbal one and a visual one, corresponding to the brain's two main perceptive systems. They both "encode" memories, but they do so in different ways (codes). Recently, Michael Tye has proposed a unified theory of mental imagery that embraces both the visual stance and the linguistic stance, i.e. that tries to bridge Kosslyn's pictorialism and Pylyshyn's descriptionalism. The Frame In the 1920s, the German psychologist Otto Selz had one of the fundamental ideas of cognitive psychology, bound to influence Cognitive Science half a century later: to solve a problem entails to recognize that the situation represented by the problem is described by a known schema and fill the gaps in http://www.thymos.com/tat/cognitio.html (7 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
the schema. Given a problem, the cognitive system searches the long-term memory for a schema that can represent it. Given the right schema, information in excess contains the solution. A schema is a network of concepts that organize past experience. Representation of present experience is a partially complete schema. By comparing the two representations (the complete schema with the partial schema) one can infer (or, better, "anticipate") something relative to the present situation. Thanks to the schema's anticipatory nature, to solve a problem is equivalent to comprehend it, and comprehending ultimately means reducing the current situation to a past situation. An influential figure in the development of cognitive science who rediscovered Selz’s ideas in the 1960s is Marvin Minsky, whose "frame" is but a variation on the schema. A "frame" is a packet of information that helps recognize and understand a scene. It represents stereotypical situations and finds shortcuts to ordinary problems. A frame is the description of a category by means of a prototypical member (i.e., its properties) and a list of actions that can be performed on any member of the category. A prototype is described simply by a set of default properties. Default values, in practice, express a lack of information, which can be remedied by new information. Any other member of the category can be described by a similar frame that customizes some properties of the prototype. A frame can provide multiple representations of an object: taxonomic (conjunctions of classification rules), descriptive (conjunction of propositions of the default values) and functional (a proposition on the admissible predicates). Memory is a network of frames, one for each known concept. Each perception selects a frame (i.e., classifies the current situation in a category) which then must be adapted to that perception; and this is equivalent to interpreting the situation and deciding which action must be performed. Reasoning is adapting a frame to a situation. Knowledge imposes coherence on experience. Because it does not separate cognitive phenomena such as perception, recognition, reasoning, understanding and memory which seem to occur always at the same time, the frame is more biologically plausible than other forms of knowledge representation. Plus, it offers computational advantages, because it focuses reasoning on the information that is relevant to the situation at hand. Minsky has later generalized the idea of the frame in a more ambitious model of how memory works. When a perception, or a problem-solving task, takes place, a data structure called "K-Line" (Knowledge Line) records the current activity (all the agents active at that time). The memory of that event or problem is a process of rebuilding what was active (the agents that were active) in the mind at that time. Agents are not all attached the same way to K-lines. Strong connections are made at a certain level of detail, the "levelband", weaker connections are made at higher and lower levels. Weakly activated features correspond to assumptions by default, which stay active only as long as there are no conflicts. K-lines connect to K-lines and eventually form societies of their own. The Script http://www.thymos.com/tat/cognitio.html (8 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
In the 1970s, Roger Schank employed similar ideas in his model of "conceptual dependency" and in his theory of "case-based reasoning". Case-based reasoning is a form of analogical reasoning in which the elementary unit is the "case", or situation. A type of memory called "episodic" archives generalizations of all known cases. Whenever a new case occurs, similar cases are retrieved from episodic memory. Then two things happen. First, the new case is interpreted based on any similar cases that were found in the episodic memory. Second, the new case is used, in turn, to further refine the generalizations, which are then stored again in episodic memory. The crucial features of this model are similar to the ones that characterize frames. Interpretation of the new case is expectation-driven, based on what happened in previous cases. Episodic memory contains examples of solutions, rather than solutions or rules to find solutions. Because the episodic memory is continuously refined, Schank refers to it more generally as "dynamic" memory: it can grow of its own, based on experience. The script is an extension of the idea of the case. A scene is a general description of a setting and a goal in that setting. A script is a particular instantiation of a scene (many scripts can be attached to one scene). A script is a social variant of Minsky's frame. A script represents stereotypical knowledge of situations as a sequence of actions and a set of roles. Once the situation is recognized, the script prescribes the actions that are sensible and the roles that are likely to be played. The script helps understand the situation and predicts what will happen. A script therefore performs anticipatory reasoning. A script is a generalization of a class of situations. If a situation falls into the context of a script, then an expectation is created by the script, based on what happened in all previous situations. If the expectation fails to materialize, then a new memory must be created. Such new memory is structured according to an "explanation" of the failure. Generalizations are created from two identical expectation failures. Memories are driven by expectation failures, by the attempt to explain each failure and learning from that experience. New experiences are stored only if they fail to conform to the expectations. Here, again, remembering is closely related to understanding and learning. Memory has the passive function of remembering and the active function of predicting. The comprehension of the world and its categorization proceed together. More and more complex structures have been added by Schank and his associates to the basic model of scripts. A "memory organization packet" (MOP) is a structure that keeps information about how memories are linked in frequently occurring combinations. A MOP is both a storing structure and a processing structure. A MOP is basically an ordered set of scenes directed towards a goal. A MOP is more general than a script in that it can contain information about many settings (including many scripts). A "thematic organization packet" is an even higher-level structure that stores information independent of any setting. Ultimately, knowledge (and intelligence itself) is stories. Cognitive skills emerge from discourse-related
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functions: conversation is reminding and storytelling is understanding (and in particular generalizing). The stories that are told differ from the stories that are in memory: in the process of being told, a story undergoes changes to reflect the intentions of the speaker. The mechanism is similar to script-driven reasoning: understanding a story entails finding a story in memory that matches the new story and enhancing the old story with details from the new one. Underlying the mechanism is a process of "indexing" based on identifying five factors: theme, goal, plan, result and lesson. Memory actually contains only "gists" of stories, that can be turned into stories by a number of operations (distillation, combination, elaboration, creation, captioning, adaptation). Knowledge is embodied in stories and cognition is carried out in terms of stories that are already known. The Self-organizing Schema Schemas resurface also in Michael Arbib's work. Just like with Minsky’s frames and Schank’s scripts, Arbib argues that the mind constructs reality through a network of schemas. And, again, a schema is both a mental representation of the world and a process that determines action in the world. Arbib's theory of schemas is based on two notions, one developed by an American mathematician of the last century, Charles Peirce, and one due to the great Swiss psychologist Jean Piaget. The first one is the notion of a "habit", a set of operational rules that, by exhibiting both stability and adaptability, lends itself to an evolutionary process. The second one is the notion of a "schema", the generalizable characteristics of an action that allow the application of the same action to a different context (yet another variation on Selz). Both assume that schemas are compounded as they are built to yield successive levels of a cognitive hierarchy. Arbib argues that categories are not innate, they are constructed through the individual's experience. What is innate is the process that underlies the construction of categories. Therefore, Arbib’s view of the rules of categories is similar to Norman Chomsky's view of the rules of language. What sets Arbib’s theory apart from Minsky’s and Schank’s is that Arbib’s is shown to cohexist with a model of the brain as an evolving self-organizing system of interconnected units, e.g. with neural networks. Conceptual Graphs Both frames and scripts are ultimately ways of representing concepts. A broader abstraction with a similar purpose has been proposed by John Sowa in his mathematical theory of "conceptual graphs", which is based both on Selz’s schemas and on Peirce's existential graphs (a graph notation for logic). A "conceptual graph" represents a memory structure generated by the process of perception. In practice, a conceptual graph describes the way percepts are assembled together. Conceptual relations describe the role that each percept plays. Conceptual graphs are finite, connected, bipartite graphs (bipartite because they contain both concepts and conceptual relations, represented by boxes and circles). Some concepts (concrete concepts) are associated with percepts for experiencing the world and with motor mechanisms for acting upon it. Some concepts are http://www.thymos.com/tat/cognitio.html (10 of 13)25/07/2003 14:23:02
Thinking About Thought: Consciousness, Life and Meaning
associated with the items of language. A concept has both a type and a referent. A hierarchy of concept types defines the relationships between concepts at different levels of generality. Formation rules ("copy", "restrict", "join" and "simplify") constitute a generative grammar for conceptual structures just like production rules constitute a generative grammar for syntactic structures. All deductions on conceptual graphs involve a combination of them. The Unity of Cognition Perception, memory, learning, reasoning, understanding and action are simply different aspects of the same process. This is the opinion implicitly stated by all modern models of the mind. All mental faculties are simply different descriptions of the same process, different ways of talking about the same thing. One, whole process of cognition. There is never perception without memory, never memory without learning, never learning without reasoning, never reasoning without understanding, and so forth. One happens because all happen at the same time. The mind contains this powerful algorithm that operates on cognitive structures. That algorithm has been refined by natural selection to be capable of responding in optimal time. This can be partly because that algorithm operates on structures that already reflect the nature of our experience. Our experience occurs in situations, each situation being a complex aggregate of factors. The actions we performed in a given situation are rather stereotyped. The main processing of the algorithm goes into recognizing the situation. Once the situation is recognized, somehow it is reduced to past experience and that helps figure out quite rapidly the appropriate action. Needless to say, various levels of cognition can be identified in other animals, and even in plants. Even in crystals and rocks. Everything in nature can be said to remember and to learn, everything can be said to be about something else. Cognition is not "all" there is in the mind: this is the utalitarian, pragmatic, mechanic part of the mind. The mind also has awareness. But consciousness does not seem to contribute to the algorithm, does not seem to affect the structure of past experience, does not seem to have much to do with our ability to deal with situations. A being with no consciousness, but with the same cognitive algorithm and the same cognitive structures (i.e., with the same cognitive architecture), would probably behave pretty much like us in pretty much all of our daily actions, without the emotions. Cognition does not seem to require consciousness. Ultimately, it is simply a material process of selforganization. It seems possible to simulate this process by an algorithm, which means that it is not exclusive to conscious beings. It may well be possible to build machines that are cognitive systems. Cognition may actually turn out to be a general property of matter, of all matter, living and nonliving. Further Reading Anderson John Robert: THE ARCHITECTURE OF COGNITION (Harvard Univ Press, 1983)
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Anderson John Robert: THE ADAPTIVE CHARACTER OF THOUGHT (Lawrence Erlbaum, 1990) Anderson John Robert: RULES OF THE MIND (Lawrence Erlbaum, 1993) Arbib Michael: CONSTRUCTION OF REALITY (Cambridge University Press, 1986) Ballard Dana: COMPUTER VISION (Prentice Hall, 1982) Block Ned: IMAGERY (MIT Press, 1981) Craik Kenneth: THE NATURE OF EXPLANATION (Cambridge Univ Press, 1943) Fauconnier Gilles: MENTAL SPACES (MIT Press, 1994) Finke Ronald: PRINCIPLES OF MENTAL IMAGERY (MIT Press, 1989) Finke Ronald: CREATIVE COGNITION (MIT Press, 1992) Franklin Stan: ARTIFICIAL MINDS (MIT Press, 1995) Green David: COGNITIVE SCIENCE (Blackwell, 1996) Hampson Peter & Morris Peter: UNDERSTANDING COGNITION (Blackwell, 1995) Johnson-Laird Philip: MENTAL MODELS (Harvard Univ Press, 1983) Johnson-Laird Philip: THE COMPUTER AND THE MIND (Harvard Univ Press, 1988) Johnson-Laird Philip & Byrne Ruth: DEDUCTION (Lawrence Erlbaum, 1991) Kosslyn Stephen: IMAGE AND MIND (Harvard University Press, 1980) Kosslyn Stephen: GHOSTS IN THE MIND'S MACHINE (W. Norton, 1983) Kosslyn Stephen & Koenig Olivier: WET MIND (Free Press, 1992) Kosslyn Stephen: IMAGE AND BRAIN (MIT Press, 1994) Laird John, Rosenbloom Paul & Newell Alan: UNIVERSAL SUBGOALING AND CHUNKING (Kluwer Academics, 1986) Leyton Michael: SYMMETRY, CAUSALITY, MIND (MIT Press, 1992)
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Luger George: COGNITIVE SCIENCE (Academic Press, 1993) Marr David: VISION (MIT Press, 1982) Minsky Marvin: SEMANTIC INFORMATION PROCESSING (MIT Press, 1968) Minsky Marvin: THE SOCIETY OF MIND (Simon & Schuster, 1985) Newell Allen: UNIFIED THEORIES OF COGNITION (Harvard Univ Press, 1990) Paivio Allan: IMAGERY AND VERBAL PROCESSES (Holt, Rinehart and Winston, 1971) Posner Michael: FOUNDATIONS OF COGNITIVE SCIENCE (MIT Press, 1989) Pylyshyn Zenon: COMPUTATION AND COGNITION (MIT Press, 1984) Schank Roger: SCRIPTS, PLANS, GOALS, AND UNDERSTANDING (Lawrence Erlbaum, 1977) Schank Roger: DYNAMIC MEMORY (Cambridge Univ Press, 1982) Sowa John: CONCEPTUAL STRUCTURES (Addison-Wesley, 1984) Stillings Neil: COGNITIVE SCIENCE (MIT Press, 1995) Tye Michael: THE IMAGERY DEBATE (MIT Press, 1991) Ullman Shimon: THE INTERPRETATION OF VISUAL MOTION (MIT Press, 1979)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Common Sense: Engineering the Mind (Brouwer, Heyting, Martin-Lof, Gupta, Davis, McCarthy, Ginsberg, Reiter, McDermott, Moore, Zadeh, Kosko, Hayes, Allen, Kuipers, DeKleer, Forbus, Lenat)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Sense of the Mind In our quest for the ultimate nature of the mind, we are confounded by the very way the mind works. The more we study it, the less it resembles a mathematical genius. On the contrary, it appears that the logic employed by the mind when it is to solve a real problem in a real situation is a very primitive logic, one that we refer to as "common sense", very different from the austere formulas of Mathematics but quite effective for the purposes of surviving in this world. If the mind was shaped by the world, then the way the mind reasons about the world is a clue to where it came from and how it works. In emergency situations, our conscious throught is often powerless. Common sense determines what we do, regardless of what we think. The puzzling aspect of common sense is that it is sometimes wrong. There are plenty of examples in the history of science of "paradoxes" about common sense reasoning. Using common sense reasoning, Zeno proved that Achilles could never overtake a turtle. Using common sense reasoning, one can easily prove that General Relativity is absurd (a twin that gets younger just by traveling very far is certainly a paradox for common sense). Common sense told us that the Earth is flat and at the center of the world. Physics was grounded on Mathematics and not on common sense precisely because common sense is so often wrong. There are many situations in which we teach ourselves to stay "calm", to avoid reacting impulsively, to use our brain. These are all situations in which we know our common sense would lead us to courses of actions that we would probably regret. Why don’t our brains simply use mathematical logic in all their decisions? Why does our common sense tell us things that are wrong? Why can't we often resist the power of that falsehood? Where does common sense come from, and where does its power come from? http://www.thymos.com/tat/common.html (1 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
The Demise of Deduction Logic is based on deduction, a method of exact inference. Its main advantage is that its conclusions are exact. That is the reason why we use it to build bridges or plane wings. But deduction is not the only type of inference we know. We are very familiar with "induction", which infers generalizations from a set of events, and with "abduction", which infers plausible causes of an effect. Induction has been used by any scientist who has developed a scientific theory from her experiments. Abduction is used by any doctor when she examines a patient. They are both far from being exact, so much so that many scientific theories have been proved wrong over the centuries and so much so that doctors make frequent and sometimes fatal mistakes. The power of deduction is that no mistake is possible (if you follow the rules correctly). The power of induction and abduction is that they are useful: no scientific theory can be deducted, and no disease can be deducted. If we only employed deduction, we would have no scientific disciplines and no cures. Alas, deduction works only in very favorable situations: when all relevant information is available, when there are no contradictions and no ambiguities. Information must be complete, precise and consistent. In practice, this is seldom the case. The information a doctor can count on, for example, is mostly incomplete and vague. The reason we can survive in a world that is mostly made of incomplete, inexact and inconsistent information is that our brain does not employ deduction. Illogical Reasoning Common sense is a key factor for acting in the real world. We rarely employ Logic to determine how to act in a new situation. More often, the new situation "calls" for some obvious reaction, which stems purely from common sense. If we used Logic, and only Logic, in our daily lives, we would probably be able to take only a few actions a day. Logic is too cumbersome, and allows us to reach a conclusion only when a problem is "well" formulated. In more than one way, common sense helps us deal with the complexity of the real world. Common sense provides a shortcut to making critical decisions very quickly. Common sense encompasses both reasoning methods and knowledge that are obvious to humans but that are quite distinct from the tools of classical Logic. When scientists try to formalize common sense, or when they research how to endow a Logic-based machine (such as the computer) with common sense, they are faced with the limitations of Logic. It is extremely difficult, if not utterly impossible, to build a mathematical model for some of the simplest decisions we make. Common sense knows how to draw conclusions even in the face of incomplete or unreliable information. Common sense knows how to deal with imprecise quantities, such as "many", "red", "almost". Common sense knows how to deal with a problem that is so complex it cannot even be specified (even cooking a meal theoretically involves an infinite number of choices). Common sense knows how to revise beliefs based on facts that all of a sudden are proved false. Logic was not built for any of these scenarios. Furthermore, common sense does not have to deal with logical paradoxes. Paradoxes arising from selfreferentiality (such as the liar’s paradox) have plagued Logic since the beginning. http://www.thymos.com/tat/common.html (2 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
A program to ground common sense in predicate logic is apparently contradictory, or at least a historical paradox. Science was born out of the need to remove the erroneous beliefs of common sense: e.g., the Earth is not the center of the universe. Science checks our senses and provides us with mathematical tools to figure out the correct behavior of the world notwithstanding our sense’s misleading perceptions. Science was born out of the need to get rid of common sense. What was neglected is that common sense makes evolutionary sense. Its purpose is not to provide exact knowledge: its purpose is to help an individual survive. Intuitionism The limits and inadequacies of Logic have been known for decades and numerous alternatives or improvements have been proposed. In retrospect, we can recognize two main approaches: one criticizes the very concept of "truth", while the other simply extends Logic by considering more than two truth values. As an example of the first kind, "Intuitionism" (a school of thought started in 1925 by the Dutch mathematician Luitzen Brouwer) prescribes that all proofs of theorems must be constructive. Unlike classical Logic, in which the proof of a theorem is only based on rules of inference, in intuitionistic logic only "constructable" objects are legitimate. Classical Logic exhibits properties that are at least bizarre. For example, the logical OR operation yields "true" if at least one of the two terms is true; but this means that the proposition "my name is Piero Scaruffi or 1=2" is to be considered true, even if intuitively there is something false in it. Because of this rule, the logical implication between two terms can yield even more bizarre outcomes. A logical implication can be reduced to an OR operation between the negation of the first terms and the second term. The sentence "if x is a bird than x flies" is logically equivalent to "NOT (x is a bird) OR (x flies)". The two sentences yield the same truth values (they are both true or false at the same time). The problem is that the sentence "if the week has eight days then today is Tuesday" is to be considered true because the first term ("the week has eight days") is false, therefore its negation is true, therefore its OR with the second term is true. By the same token, the sentence "Every unicorn is an eagle" is to be considered true (because unicorns do not exist). On the contrary, intuitionists accept formulas only as assertions that can be built mentally. For example, the negation of a true fact is not admissible. Since classical Logic often proves theorems by proving that the opposite of the theorem is false (an operation which is highly illegal in Intuitionistic Logic), some theorems of classical Logic are not theorems anymore. Intuitionists argue that the meaning of a statement resides not in its truth conditions but in the means of proof or verification. Per Martin-Lof’s theory of types (which dates from the 1970s) is an indirect consequence of this approach to demonstration. A "type" is the set of all propositions which are demonstrations of a theorem. Any element of a type can be interpreted as a computer program that can solve the problem represented (or "specified") by the type. This formalizes the obvious connection between intuitionist logic and computer programs, whose task is precisely to "build" proofs.
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Alan Gupta's "revisionist theory of truth" also highlights how difficult it is to pin down what "true" really means. Truth is actually impossible to define: in order to determine all the sentences of a language that are true when that language includes a truth predicate (a predicate that refers to truth), one needs to determine whether that predicate is true, which in turn requires one to know what the extension of true is, while such extension is precisely the goal. The solution is to assume an initial extension of "true" and then gradually refine it. Truth can only be refined step by step. An indirect, but not negligible, advantage of Gupta’s approach is that truth becomes a circular concept: therefore all paradoxes that arise from circular reasoning in classical Logic fall into normality. Frederick and Barbara Hayes-Roth’s form of opportunistic reasoning (the "blackboard model") follows the same principles, albeit in a computational scenario. Reasoning is viewed as a cooperative process carried out by a community of agents, each specialized in processing a type of knowledge. Each agent communicates the outcome of its inferential process to the other agents and all agents can use that information to continue their inferential process. Each agent contributes a little bit of truth, that other agents can build on. Truth is built in an incremental and opportunistic manner. Searching for truth is reduced to matching actions: the set of actions the community wants to perform (necessary actions) and the set of actions the community can perform (possible actions). An agent adds a necessary action whenever it runs out of knowledge and has to stop. An agent adds a possible action whenever new knowledge enables it. When an action is made possible that is also in the list of the necessary actions, all the agents that were waiting for it resume their processing. The search for a solution is efficient and more natural, because the only actions undertaken are those that are both possible and necessary. Furthermore, opportunistic reasoning can deal with an evolving situation, unlike classical Logic that considers the world as static. Plausible Reasoning In our daily lives, we are rarely faced with the task of finding the perfect solution to a problem. If we are running out of gasoline in the middle of the night, we are happy with finding a gas station along our route, even if its gasoline may not be the best or the cheapest. We almost never pause to figure out the best option among the ones that are available. We pick one that leads to a desired outcome. What our mind is looking for all the time is "plausible" solutions to problems, as opposed to "exact" ones. Mathematics demands exact solutions, but in our daily lives we content ourselves with plausible ones. The reason is that sometimes a plausible solution enables us to survive, whereas looking for an exact one would jeopardize our lives. A gazelle who paused to work out the best escape route while a lion is closing in on her would stand no chances. Often, finding the perfect solution is simply pointless, because by the time we would find it the problem would have escalated. Classical Logic is very powerful, but lacks this basic attribute: quick, efficient response to problems when an exact solution is not necessary (and sometimes counterproductive). Over the years, several techniques have been proposed for augmenting Logic with "plausible" reasoning: degrees of belief, default rules, inference in the face of absence of information, inference about vague quantities, analogical reasoning, induction, etc. The Impossibility of Reasoning http://www.thymos.com/tat/common.html (4 of 16)25/07/2003 14:23:24
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A very powerful argument in favor of common sense is that logical reasoning alone would be utterly impossible. Classical Logic deducts all that is possible from all that is available, but in the real world the amount of information that is available is infinite: the domain must be somehow artificially closed to be able to do any reasoning at all. And this can be achieved in a number of ways: the "closed-world assumption" (all relations relevant to the problem are mentioned in the problem statement), "circumscription" (which extends the closed-world assumption to non-ground formulas as well, i.e. assumes that as few objects as possible have a given property), "default" theory (all members of a class have all the properties characteristic of the class if it is not otherwise specified). For example, a form of default theory allows us to make use of notions such as "birds fly" in our daily lives. It is obviously not true that all birds fly (think of penguins), but that statement is still very useful for practical purposes. And, in a sense, it is true, even if, in an absolute sense, it is not true. It is "plausible" to claim that birds fly (unless they are penguins). At the same time, common sense reasoning introduces new problems in the realm of Logic. For example, John McCarthy's "frame problem" notes that it is not possible to represent what does "not" change in the universe as a result of an action, because there is always an infinite set of things that do not change: what is really important to know about the new state of the universe, after an action has been performed? Most likely, the position of the stars has not changed, my name has not changed, the color of my socks has not changed, Italy’s borders have not changed, etc. Nevertheless, any reasoning system, including our mind, must know what has been changed before it can calculate the next move. A reasoning system must continuously update its model of the world, but McCarthy (one of the father founders of Artificial Intelligence) suggests that this is an impossible task: how does our mind manage? Complementary paradoxes are the "ramification problem" (infinite things change, because one can go into greater and greater detail of description) and the "qualification problem" (the number of preconditions to the execution of any action is also infinite, as the number of things that can go wrong is infinite). Somehow we are only interested in things that change and that can affect future actions (not just all things that change) and in things that are likely to go wrong (not just all things that can go wrong). "Circumscription" (McCarthy’s solution to the frame problem) deals with default inference by minimizing abnormality: an axiom that states what is abnormal is added to the theory of what is known (this is called "predicate circumscription"). This reads as: the objects that can be shown to have a certain property, from what is known of the world, are all the objects that satisfy that property (or, the only individuals for which that property holds are those individuals for which it must hold). This definition involves a second-order quantifier. Technically, this is analogous to Frege's method of forming the second-order definition of a set of axioms: such a definition allows both the derivation of the original recursive axioms and an induction scheme stating that nothing else satisfies those axioms. For similar reasons Raymond Reiter introduced the "closed-world axiom" (what is not true is false), or "negation as failure to derive": if a formula cannot be proved using the premises, then assume the formula's negation. In other words, everything that cannot be proved to be true must be assumed to be false. His "Default Logic" employs the following inference rule: "if A is true and it is consistent that B is true, then assume that B is also true" (or "if a premise if true, then the consequence is also true unless a condition http://www.thymos.com/tat/common.html (5 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
contradicts what is known"). Ultimately, these are all tricks to account for how the mind can do any reasoning at all in the face of the gigantic complexity that surrounds it. Second Thoughts There is at least one more requirement for "plausible" reasoning. Classical logic is monotonic: assertions cannot be retracted without compromising the entire system of beliefs. Once something has been proven to be true, it will be forever. Classical logic was not designed to deal with "news". But our daily lives are full of events that force us to reexamine our beliefs all the time: our system of logic is non-monotonic. Therefore, a crucial tool for plausible reasoning is non-monotonic logic, which allows inferences to be made provisionally and, if necessary, withdrawn at any time. A handful of such logics became popular during the 1980s. Drew McDermott's formulation of Modal Logic is based on a coherence operator: "P is coherent with what is known" if P cannot be proven false by what is known. Robert Moore's "Autoepistemic Logic" is based on the notion of belief (related to McDermott's coherence) and models the beliefs of an agent reflecting upon his own beliefs. And so forth. Matthew Ginsberg classified formal approaches to nonmonotonic inference into: proof-based approaches (Reiter's logic), modal approaches (McDermott's logic, Moore's logic) and minimization approaches (circumscription). Ginsberg argued that a variety of approaches to nonmonotonic reasoning can be unified by resorting to multi-valued logics (logics that deal with more than just true and false statements). Uncertainty Another aspect of common sense reasoning that cannot be removed from our behavior without endangering our species is the capability (and even preference) for dealing with uncertainties. Pick any sentence that you utter at work, with friends or at home and it is likely that you will find some kind of "uncertainty" in the quantities you were dealing with. Sometimes uncertainty is explicit, as in "maybe I will go shopping" or "I almost won the game" or "I think that Italy will win the next World Cup". Sometimes it is hidden in the nature of things, as in "it is raining" (can a light shower be considered as "rain"?), or as in "this cherry is red" (how "red"?), or as in "I am a tall person" (how tall is a "tall" person?). The classic tool for representing uncertainties is Probability Theory, as formulated by Thomas Bayes in the late 18th century. Probabilities translate uncertainty into the lingo of statistics. One can translate "I think that Italy will win the next World Cup" into a probability by examining how often Italy wins the World Cup, or how many competitions its teams have won over the last four years, or whatever. One can express a personal feeling in probabilities, as all bookmakers do. Bayes’ theorem and other formulas allow one to draw conclusions from a number of probable events. http://www.thymos.com/tat/common.html (6 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
Technically, a probability simply measures "how often" an event occurs. The probability of getting tails is 50% because if you toss a coin you will get tails half of the times. But that is not the way we normally use probabilities: we use them to express a belief. The foremost proponent of probabilities as a measure of somebody's preferences was Leonard Savage who, in the 1960s, thought of the probability of an event as not merely the frequency with which that event occurs, but also as a measure of the degree to which someone believes it "will" happen. The problems with probabilities are computational. Bayes' theorem, the main tool to propagate probabilities from one event to a related event, does not yield intuitive conclusions. For example, the accumulation of evidence tends to lower the probability, not to increase it. Also, the sum of the probabilities of all possible events must be one, and that is also not very intuitive. Our beliefs are not consistent: try assigning probabilities to a complete set of beliefs (e.g., probabilities of winning the world cup for each of the countries of the world) and see if they add up to 100%. In order to satisfy the postulates of probability theory, one has to change her belief and make them consistent, i.e. tweak them so that the sum is 100%. Bayes rule ("the probability of a hypothesis being true is proportional to the initial belief in it, multiplied by the conditional probability of an observational data, given that prior probability") would be very useful to build generalizations (or induction), but, unfortunately, it requires one to know the initial belief, or the "prior" probability, which, in the case of induction, is precisely what we are trying to assess. In 1968 mathematicians Glenn Shafer and Stuart Dempster devised a theory of evidence aimed at making Probability Theory more plausible. They introduced a "belief function" which operates on all subsets of events (not just the single events). In the throwing of a die, the possible events are only six, but the number of all subsets is 64 (all the combination of two sides, three sides, four sides and five sides). The sum of the probabilities of all subsets is one, the sum of the probabilities of all the single events is less than one. And this holds in general. Dempster-Shafer's theory allows one to assign a probability to a group of events, even if the probability of each single event is not known. Indirectly, Dempster-Shafer's theory also allows one to represent "ignorance", as the state in which the belief of an event is not known (while the belief of a set it belongs to is known). In other words, Dempster-Shafer's theory does not require a complete probabilistic model of the domain. An advantage (and a more plausible behavior) of evidence over probabilities is its ability to narrow the hypothesis set with the accumulation of evidence. Fuzzy Logic One of the major breakthroughs in inexact reasoning came in 1965 from California, when the mathematician Lotfi Zadeh invented "Fuzzy Logic". Zadeh applied Lukasiewicz's multi-valued logic to sets. In a multi-valued logic, propositions are not only true or false but can also be partly true and partly false. A set is made of elements. Elements can belong to more than one set (e.g., I belong both to the set of authors and to the set of Italians) but each element either belongs or does not belong to a given set (I am either Italian or not). Zadeh's sets are "fuzzy" because they violate this rule. An element can belong to a
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Thinking About Thought: Consciousness, Life and Meaning
fuzzy set "to some degree", just like Lukasiewicz's propositions can be true to some degree (and not necessarily completely true). The main idea behind Fuzzy Logic is that things can belong to more than one category, and they can even belong to opposite categories, and that they can belong to a category only partially. For example, I belong both to the category of good writers and to the category of bad writers: I am a good writer to some extent and a bad writer to some other extent. In more precise words, I belong to the category of good writers with a given degree of membership and to the category of bad writers with another degree of membership. I am not fully into one or the other. I am both, to some extent. Fuzzy Logic goes beyond Lukasiewicz's multi-valued logic because it allows for an infinite number of truth values: the degree of "membership" can assume any value between zero and one. Zadeh's theory of fuzzy quantities implicitly assumes that things are not necessarily true or false, but things have degrees of truth. The degree of truth is, indirectly, a measure of the coherence between a proposition about the world and the state of the world. A proposition can be true, false, or… vague with a degree of vagueness. Fuzzy Logic can explain paradoxes such as the one about removing a grain of sand from a pile of sand (when does the pile of sand stop being a pile of sand?). In Fuzzy Logic each application of the inference rule erodes the truth of the resulting proposition. Fuzzy Logic is also consistent with the principle of incompatibility stated at the beginning of the century by a father of modern Thermodynamics, Pierre Duhem: the certainty that a proposition is true decreases with any increase of its precision. The power of a vague assertion rests in its being vague: the moment we try to make it more precise, it loses some of its power. A very precise assertion is almost never certain. For example, "today is a hot day" is certainly true, but its truth rests on the fact that I used the very vague word "hot". If now I restate it as "today the temperature is 36 degrees", the assertion is not certain anymore. Duhem’s principle is the analogous of Heisenberg’s principle of uncertainty: precision and uncertainty are inversely proportional. Fuzzy Logic models vagueness and reflects this principle. While mostly equivalent to Probability Theory (as proven by Bart Kosko, one of Fuzzy Logic’s most cunning scholars), Fuzzy Logic yields different interpretations. Probability measures the likelihood of something happening (whether it is going to rain tomorrow). Fuzziness measures the degree to which it is happening (how heavily it is raining today). And, unlike probabilities, Fuzzy Logic deals with single individuals, not populations. Probability theory tells you what are the chances of finding a communist in a crowd, whereas fuzzy logic tells you to what degree that person is a communist. Technically, a fuzzy set is a set of elements that belong to a set only to some extent. Each element is characterized by a degree of membership. An object can belong (partially) to more than one set, even if they are mutually exclusive, in direct contrast with one of the pillars of classical logic: the "law of the excluded middle". Each set can be subset of another set with a degree of membership. A set can even belong (partially) to one of its parts. Degrees of membership also imply that Fuzzy Logic admits a continuum of truth values from zero to one, unlike classical Logic that admits only true or false (one or http://www.thymos.com/tat/common.html (8 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
zero). In Kosko's formalization, a fuzzy set is a point in a unitary hypercube (a multi-dimensional cube whose faces are all one). A non-fuzzy set (a traditional set) is one of the vertexes of such a cube. The paradoxes of classical Logic occur in the middle points of the hypercube. In other words, paradoxes such as the liar's or Russell's can be interpreted as "half truths" in the context of Fuzzy Logic. A fuzzy set's entropy (which could be thought of as its "ambiguity") is defined by the number of violations of the law of non-contradiction compared with the number of violations of the excluded middle. Entropy is zero when both laws hold, is maximum in the center of the hypercube. Alternatively, a fuzzy set's entropy can be defined as a measure of how a set is a subset of itself. Possibility Theory Possibility theory (formulated by Zadeh in 1977, and later expanded by French mathematicians Didier Dubois and Henri Prade) developed as a branch of the theory of fuzzy sets to deal with the lexical elasticity of ordinary language (i.e., the fuzziness of words such as "small" and "many"), and other forms of uncertainty which are not probabilistic in nature. The subject of possibility theory is the possible (not probable) values of a variable. Possibility theory is both a theory of imprecision (represented by fuzzy sets) and a theory of uncertainty. The uncertainty of an event is described by a pair of degrees: the degree of possibility of the event and the degree of possibility of the contrary event. The definition can be dually stated in terms of necessity, necessity being the complement to one of possibility. Its basic axioms are that: 1. the grade of possibility is one for a proposition that is true in any interpretation and is zero for a proposition that is false in any interpretation; 2. the grade of possibility of a disjunction of propositions is the maximum grade of the two. When the grade of necessity of a proposition is one, the proposition is true. When the grade of possibility of a proposition is zero, the proposition is false. When the grade of necessity is zero, or the grade of possibility is one, nothing is known about the truth of the proposition. Possibility Logic has a graded notion of possibility and necessity. A Fuzzy Physics? Unlike Probability theory, Fuzzy Logic represents the real world without any need to assume the existence of randomness. For example, relative frequency is a measure of how a set is a subset of another set. Many of Physics' laws are not reversible because otherwise causality would be violated (after a transition of state probability turns into certainty and cannot be rebuilt working backwards). If they were expressed as "ambiguity", rather than probability, they would be reversible, as the ambiguity of an event remains the same before and after the event occurred.
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Thinking About Thought: Consciousness, Life and Meaning
Fuzziness is pervasive in nature ("everything is a matter of degree"), even if science does not admit fuzziness. Even probability theory still assumes that properties are crisp, while in nature they rarely are. Furthermore, Heisenberg's uncertainty principle (the more a quantity is accurately determined, the less accurately a conjugate quantity can be determined, which holds for position and momentum, time and energy) can be reduced to the Cauchy-Schwarz inequality, which is related to Pythagora's theorem, which is in turn related to the subsethood theorem, i.e. Fuzzy Logic. One is tempted to rewrite Quantum Mechanics using Fuzzy Theory instead of Probability Theory. After all, Quantum Mechanics, upon which our description of matter is built, uses probabilities mainly for historical reasons: Probability Theory was the only theory of uncertainty available at the time. Today, we have a standard interpretation of the world which is based on population thinking: we cannot talk about a single particle, but only about sets of particles. We cannot know whether a particle will end up here or there, but only how many particles will end up here or there. The interpretation of quantum phenomena would be slightly different if Quantum Mechanics was based on Fuzzy Logic: probabilities deal with populations, whereas Fuzzy Logic deals with individuals; probabilities entail uncertainty, whereas Fuzzy Logic entails ambiguity. In a fuzzy universe a particle's position would be known at all times, except that such a position would be ambiguous (a particle would be simultaneously "here" to some degree and "there" to some other degree). This might be viewed as more plausible, or at least more in line with our daily experience that in nature things are less clearly defined than they appear in a mathematical representation of them. The World of Objects Another aspect of common sense is that it deals with quantities and objects which are a tiny subset of what science deals with (or is capable of dealing with). The laws of the physical world are relatively simple and few. The "real" world is made of a finite set of solid objects that move in space and do not overlap. Each object has a shape, a volume, a mass distribution. For an adequate representation of the physical needs we can get by with Euclides' geometry, an ontology of space-temporal properties and a set of axioms about the way the world works. We need none of the complication of Quantum Mechanics and Relativity Theory. We need no knowledge whatsoever of elementary particles, nuclear and subnuclear forces, and so forth. Life is a lot easier for our senses than it is for laboratory physicists. What we need to know in order to survive is actually a lot less than what we need to know in order to satisfy our intellectual curiosity. We never really needed to know the gravitational laws in order to survive, as long as we were aware that objects tend to fall to the ground unless we put them on a table or in a pocket or hang them to the roof. We never really needed to be informed of the second law of Thermodynamics, as long as we realized that they can break, but they do not fix themselves. The American computer scientist Ernest Davis compiled a list of common sense domains. First, we have physical quantities, such as weight or temperature. They have values. And their values satisfy a number of properties: they can be ordered, they can be subdivided in partially ordered intervals, they can be assigned signs based on their derivatives, their relations can be expressed in the form of transition networks, their http://www.thymos.com/tat/common.html (10 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
behavior can be expressed in the form of qualitative differential equations. Then we have time and space. Time operators usually operate in a world of discrete, self-contained situations and events. Space entails concepts of distance, containment, overlapping, boundaries. Physics, in the view of common sense, is a domain defined by "qualitative" rather than quantitative laws, which express the behavior of physical quantities in the context of those temporal and spatial concepts. To this scenario one must add propositional attitudes (specifically the relationship between belief and knowledge), actions (the ability to plan) and socializing (speech acts). Equipped with this basic idea of the world, an agent should be able to go about its environment and perform intelligent actions. The Measure Space An important idea was introduced by the British computer scientist Pat Hayes around 1978 in the context of Artificial Intelligence when he envisioned a "measure space" for a physical quantity (length, weight, date, temperature, etc.). A measure space is simply a space in which an ordering relationship holds. Measurement spaces are usually conceived as discrete spaces, even if the quantities they measure are in theory continuous. In common use, things like birth dates, temperatures, distances, heights and weights are always rounded. For example, the height of a person is usually measured in whole centimeters (or inches), and omitting the millimeters, and it can be safely assumed that only heights over one meter and less than two meters are possible. This means that the measure space for people’s height is the set of natural numbers from 100 (centimeters) to 200 (centimeters). The measure space for driving speed can reasonably be assumed to be the set of numbers from 0 to 200 (kilometers). The measure space for a shirt’s size is sometimes limited to four values: small, medium, large, very large. The measure space for jeans’ size is a (very limited) set of pairs of natural numbers. The measure space for the age of a person is the set of natural numbers from 1 to 130. The measure space for the date of an historical event is the set of integer numbers from -3,000 (roughly the time writing was invented) to the number of the year we live in. The measure space for the date of a geological event is a much bigger set of integers. And so forth. A measure space is a discrete representation of a continuous space that takes into account only the significant values that determine boundaries of behavior. Hayes' program was more ambitious than just measurement spaces. Hayes set out to write down in the language of predicate logic everything that we take for granted about the world, all of our common-sense knowledge about physical objects. For example, we know that water is contained in something and that, if it overflows, it will run out, but it will not run upward. We know that wood floats in water but iron sinks. We know that a heavy object placed on top of a light object may crash it. We know that an object will not move if placed on a table, but it will fall if pushed too much beyond the edge. Etc. This is what Hayes called "naïve physics" and it is the physics that we employ at every single moment. Histories of the World During the 1980s, within Artificial Intelligence, several techniques have been proposed for refounding http://www.thymos.com/tat/common.html (11 of 16)25/07/2003 14:23:24
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Physics on a more practical basis. McCarthy's situation calculus represents temporally limited events as "situations" (snapshots of the world at a given time), by associating a situation of the world (a set of facts that are true) to each moment in time. Actions and events are represented mathematically as functions from states to states. An interval of time is a sequence of situations, a "chronicle" of the world. The history of the world is a partially ordered sequence of states and actions. A state is expressed by means of logical expressions that relate objects in that state. An action is expressed by a function that relates each state to another state. The property of states is permanence, the property of actions is change. Each situation is expressed by a formula of first-order predicate Logic. The advantage of this logical apparatus is that causal relations between two situations can now be computed. Unlike McCarthy's situations, Hayes' "histories" (connected pieces of space-time) have a restricted spatial extent, thereby avoiding some of the inconveniences of situations. Hayes' logistic approach was very influential in formalizing and axiomatizing common-sense knowledge. The elementary unit of measure for common sense is not the point, but the interval. Which interval makes sense depends on the domain: history is satisfied with years (and sometimes centuries), but birth dates require the day, and track and fields races need tenths of seconds. James Allen's representation of time, for example, is based on intervals, not instants. Intervals may be related in several ways: one being before, after or equal to another. The relationships between intervals differ from relationships between points. Two intervals can partially overlap. An interval can be open or closed. Points require Physics' differential equations, but intervals can be handled with a logic of time that deals with their ordering relationship. Qualitative Reasoning "Qualitative" reasoning is the discipline that aims at explaining the behavior of a physical system through something closer to common sense than Physics' dynamic equations. In "Qualitative" Physics, a physical system is conceived as made of parts that contribute to the overall behavior through local interactions, and its behavior is represented inside some variation of Hayes' measure space. Ultimately, qualitative reasoning is a set of methods for representing and reasoning with incomplete knowledge about physical systems. A qualitative description of a system allows for common-sense reasoning that overcomes the limitations of rigorous Logic. Qualitative descriptions capture the essential aspects of structure, function and behavior, at the expense of others. Since most phenomena that matter to ordinary people depend only on those essential aspects, qualitative descriptions are enough for moving about in the world.
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Several approaches are possible, depending on the preferred ontology: Benjamin Kuipers adopts qualitative constraints among state variables; Johan DeKleer focuses on the devices (pipes, valves, springs) connected in a network of constraints; Kenneth Forbus deals with processes by extending Hayes' notion of history. Ultimately, a system's behavior is almost always described by constraint propagation. DeKleer describes a phenomenon in a measure space through "qualitative differential equations", or "confluences". His "envisionment" is the set of all possible future behaviors. Forbus defines a "quantity space" as a partially ordered set of numbers. Common sense is interested in knowing that quantities "increase" and "decrease" rather than on formulas yielding their values in time. In other words, the sign of the derivative is more important than the exact value of a quantity. Kuipers formalizes qualitative analysis as a sequence of formal descriptions. From the structural description the behavioral description (or "envisionment") can be derived, and from this the functional description can be derived. In his quantity space, besides the signs of the derivatives, what matters most are critical or "landmarks" values, such as the temperature at which water undergoes a phase transition. Change is handled by discrete state graphs and qualitative differential equations. A qualitative differential equation is a quadruple of variables, quantity spaces (one for each variable), constraints (that apply to the variables) and transitions (rules to define the domain boundaries). Each of these three frameworks prescribes a number of constraint propagation techniques, which can be applied to a discrete model of the physical system. Physics is a science of laws of nature which are continuous and exact. Things move because they are subject to these laws. Qualitative Physics is a science of laws of common sense that are discrete and approximate. Things move because other things make them move. Qualitative Physics may be not suitable for studying galaxies and electrons, but can work wonders at analyzing a piece of equipment, a machine, and in general a physical system made of components. For example, it has been applied at diagnosing machine faults: a model of behavior of a system makes it easier to figure out what must be wrong in order for the system to work the way it is working, i.e. which component is not doing its job properly. Heuretics The physical world is only one part of the scenario. There is also the "human" world, the huge mass of knowledge that humans tend to share in a natural way: rain is wet, lions are dangerous, most politicians are crooks and carpets get stained. Heuristics is the proper name for most of what we call common sense. Heuristics is the body of knowledge that allows us to find quick and efficient solutions to complex problems without having to resort to mathematical logic. Heuristics is, for example, the set of "rules of thumbs" that most people employ in their daily lives. The intellectual power of our brain is rarely utilized, as in most cases we can find a rule of thumb that will make it unnecessary. We truly reason only when we cannot find any rule of thumb to help us. A human being who did not know any rules of thumb, who did not have any heuristics, would treat each single daily problem as a mathematical theorem to prove and would probably starve to death before understanding where and how to buy food. We tend to employ heuristics even when we solve http://www.thymos.com/tat/common.html (13 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
mathematical problems. And countless games (such as chess) are about our ability to apply heuristics, rather than mere mathematical reasoning Douglas Lenat is trying to develop a global ontology of common knowledge and a set of first principles (or reasoning methods) to work with it. Units of knowledge for common sense are units of "reality by consensus": all the things we know and we assume everybody knows; i.e., all that is implicit in our acts of communication. World regularities belong to this tacitly accepted knowledge. And "regularity" may be a key to understand how we construct and why we believe in heuristcs. Lenat’s principle of economy of communications states the need to minimize the acts of communication and maximize the information that is transmitted. Another open issue is whether common sense is learned or innate, or: to what extent it is learned and to what extent it is innate. If it is learned, how is it learned? George Polya was a Swiss mathematician who, in the 1940's, studied how mathematicians solve mathematical problems. Far from being the mechanical procedure envisioned by the proponents of the logistic program, he realized that solving a problem required heuristics. Later, he envisioned "Heuretics", a discipline that would aim at understanding the nature, power and behavior of heuristics: where it comes from, how it becomes so convincing, how it changes over time, etc. One of the intriguing properties of heuristics is, for example, the impressive degree to which we rely on it: the moment we realize that a rule of thumb, we abandon our line of reasoning. What makes us so confident about the effectiveness of heuristics? Maybe the fact that heuristics is "acquired effectiveness"? The scope of Heuretics is, ultimately, the scientific study of wisdom. Stupidity Artificial Intelligence has been researching human intelligence and machine intelligence, possibly abusing the term "intelligence" from the beginning. It can be amusing to focus for a few minutes on the opposed quantity, stupidity. Common sense seems to have a perfectly clear understanding of what stupidity is. Most people would agree at once that some statements are stupid. "Which is the shortest river in the world?" There is no shortest river, because one can always find a shorter stream of water, all the way down to the leak in your bath tub and to a single drop of water in the kitchen sink. While it makes sense to ask which is the longest river in the world, it makes no sense to ask which is the shortest one. As the length gets shorter, the set of rivers increases in size exponentially. " Is everybody here?" The question is stupid because if somebody is missing she won’t be able to answer the question. "Does everybody understand English?" exhibits the same type of stupidity. What do these questions have in common?
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Thinking About Thought: Consciousness, Life and Meaning
Further Reading Bobrow Daniel: QUALITATIVE REASONING ABOUT PHYSICAL SYSTEMS (MIT Press, 1985) Bobrow Daniel: ARTIFICIAL INTELLIGENCE IN PERSPECTIVE (MIT Press, 1994) Brachman Ronald: READINGS IN KNOWLEDGE REPRESENTATION (Morgan Kaufman, 1985) Davis Ernest: REPRESENTATION OF COMMON-SENSE KNOWLEDGE (Morgan Kaufman, 1990) Dubois Didier & Prade Henri: POSSIBILITY THEORY (Plenum Press, 1988) Dubois Didier, Prade Henri & Yager Ronald: READINGS IN FUZZY SETS (Morgan Kaufmann, 1993) Forbus Kenneth & DeKleer Johan: BUILDING PROBLEM SOLVERS (MIT Press, 1993) Gigerenzer Gerd & Todd Peter: SIMPLE HEURISTICS THAT MAKES US SMART (Oxford Univ Press, 1999) Gupta Anil & Belnap Nuel: THE REVISION THEORY OF TRUTH (MIT Press, 1993) Heyting Arend: INTUITIONISM (North Holland, 1956) Hobbs Jerry & Moore Robert: FORMAL THEORIES OF THE COMMONSENSE WORLD (Ablex Publishing, 1985) Kandell Abraham: FUZZY MATHEMATICAL TECHNIQUES (Addison Wesley, 1986) Kosko Bart: NEURAL NETWORKS AND FUZZY SYSTEMS (Prentice Hall, 1992) Kosko Bart: FUZZY THINKING (Hyperion, 1993) Kuipers Benjamin: QUALITATIVE REASONING (MIT Press, 1994) Lenat Douglas: BUILDING LARGE KNOWLEDGE-BASED SYSTEMS (Addison-Wesley, 1990) Lukaszewicz Witold: NON-MONOTONIC REASONING (Ellis Harwood, 1990) Marek Wiktor & Truszczynski Miroslav: NON-MONOTONIC LOGIC (Springer Verlag, 1991) Martin-Lof Per: INTUITIONISTIC TYPE THEORY (Bibliopolis, 1984) http://www.thymos.com/tat/common.html (15 of 16)25/07/2003 14:23:24
Thinking About Thought: Consciousness, Life and Meaning
Polya George: MATHEMATICS AND PLAUSIBLE REASONING (Princeton Univ Press, 1954) Savage Leonard: THE FOUNDATIONS OF STATISTICS (John Wiley, 1954) Shafer Glenn: A MATHEMATICAL THEORY OF EVIDENCE (Princeton Univ Press, 1976) Sowa John: PRINCIPLES OF SEMANTIC NETWORKS (Morgan Kaufman, 1991) Turner Raymond: LOGICS FOR ARTIFICIAL INTELLIGENCE (Ellis Horwood, 1985) Tversky Amos, Kahnemann Daniel & Slovic Paul: JUDGMENT UNDER UNCERTAINTY (Cambridge University Press, 1982) Weld Daniel & DeKleer Johan: QUALITATIVE REASONING ABOUT PHYSICAL SYSTEMS (Morgan Kaufman, 1990) Zimmermann Hans: FUZZY SET THEORY (Kluwer Academics, 1985)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Connectionism and Neural Machines (Hebb, McCulloch, Pitts, Selfridge, Rosenblatt, Widrow, Hoff, Hopfield, Fukushima, Kohonen, Grossberg, Rumelhart, Hinton, Sejnowsky, Smolensky, Churchland)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Artificial Neural Networks An artificial "neural network" is a piece of software or hardware that simulated the neural network of the brain. Several simple units are connected, with each unit connecting to any number of other units. The "strength" of the connections can fluctuate from zero strength to infinite strength. Initially the connections are set randomly. Then the network is either "trained" or forced to train itself. "Training" a network means using some kind of feedback to adjust the strength of the connections. Every time an input is presented, the network is told what the output should be and asked to adjust its connections accordingly. For example, the input could be a picture of an apple and the output could be the string of letters A-P-P-LE. The first time, equipped with random connections, the network will produce some random output. The requested output (A-P-P-L-E) is fed back and the network reorganizes its connections to produce such an output. Another image of an apple is presented as the input and the output is forced again to be the string AP-P-L-E. Every time this happens the connections are modified to produce the same output even if all images of apples are slightly different. The theory predicts that at some point the network will start recognizing images of apples even if they are all slightly different from the ones it saw before. A number of algorithms have been proposed for adjusting the strengths of the network based on the expected output. Such an algorithm must eventually "converge" to a unique and proper configuration of the neural network. The network can continue learning forever, but it must be capable of not forgetting what it has already learned. The larger the network (both in terms of units and in terms of connections) the easier to reach a point of stability. Artificial neural networks are typically used to recognize an image, a sound, a writing. But, since everything is ultimately a pattern of information, there is no limit to their applications. For example, they http://www.thymos.com/tat/neural.html (1 of 8)25/07/2003 14:23:38
Thinking About Thought: Consciousness, Life and Meaning
can be used to build expert systems. An expert system built with the technology of knowledge-based systems (a "traditional" expert system) relies on a knowledge base which represents the knowledge acquired over a lifetime by a specialist. An expert system built with neural network technology would be a neural network which has initiated with random values and trained with a historical record of "cases". Instead of relying on an expert, one would rely on a long list of previous cases in which a certain decision was made. If the network is fed this list and "trained" to learn that this long list corresponds to a certain action, the network will eventually start recommending that certain action for new cases that somehow match that "pattern". Imagine a credit scoring application: the bank experts in credit use some criteria for deciding whether a business is entitled to a loan or not. A knowledge-based system would rely on the experience of one such expert and use that knowledge to examine future applications. A neural network would rely on the historical record of loans and train itself from that record to examine future applications. The approach is almost completely opposite, even if it should lead to exactly the same behavior. Parallel Distributed Computing One can view a connectionist structure as a new form of computing, a new way of finding a solution to a problem. Traditionally, we think of problem solving as an activity in which a set of axioms (of things we know for sure) helps us figure out whether something else is true or false. We derive the "theorem" from the premises through a sequence of logical steps. There is one, well-defined stream of information that flows from the premises to the demonstration of the theorem. This is the approach that mathematicians have refined over the centuries. On the contrary, a connectionist structure such as our brain works in a non-sequential way: many "nodes" of the network can be triggered at the same time by another node. The result of the computation is a product of the parallel processing of many streams of information. There are no axioms and no rules of inference. There are just nodes that exchange messages all the time and adjust their connections depending on the frequency of those messages. No logic whatsoever, no reasoning, no intelligence required. Information does not flow: it gets propagated. Computing (if it can still be called "computing") occurs everywhere in the network, and it occurs all the time. The first reason to be intrigued by connectionist (or "neural") computing is that our brain does it, and, if our brain does it, there must be a reason. The second reason is that mathematicians soon started realizing that this form of computing does have advantages over the logical approach. There are many tasks that would be extremely difficult to handle with Logic, but are quite naturally handled by neural computation. For example, what our brain does best: recognizing patterns (whether a face or a sound). Connectionists have proven that everything that traditional Artificial Intelligence does can be done as well with neural networks. The idea of connectionism, of computing in a network rather than in a formal system, is revolutionizing our way of approaching computation. After all, very few real-world problems can be solved in the vacuum http://www.thymos.com/tat/neural.html (2 of 8)25/07/2003 14:23:38
Thinking About Thought: Consciousness, Life and Meaning
of pure logic. From weather forecast to finance, most situations involve countless factors that interact with each other at the same time. One can predict the future only if one knows all the possible interactions. Computational Models of the Brain In 1943 the American physiologist and mathematician Warren McCulloch, in cooperation with Walter Pitts, wrote a seminal paper that laid down the foundations for a computational theory of the brain. McCulloch transformed the neuron into a mathematical entity by assuming that it can only be in one of two possible states (formally equivalent to the zero and the one of computer bits). These "binary" neurons have a fixed threshold below which they never fire. They are connected to other binary neurons through connections (or "synapses") that can be either "inhibitory" or "excitatory": the former bring signals that keep the neuron from firing, the latter bring signals that push the neuron to fire. All binary neurons integrate their input signals at discrete intervals of time, rather than continuously. The model is therefore very elementary: if no inhibitory synapse is active and the sum of all excitatory synapses is greater than the threshold, the neuron fires; otherwise it doesn’t. This represents a rather rough approximation of the brain, but it can do for the purpose of mathematical simulation. Next, McCulloch and Pitts proved an important theorem: that a network of binary neurons is fully equivalent to a universal Turing machine, i.e., that any finite logical proposition can be realized by such a network, i.e., that every computer program can be implemented as a network of binary neurons. Two most unlikely worlds as the one of Neurophysiology and ther one of Mathematics had been linked. It took a few years for the technology to catch up with the theory. Finally, at the end of the Fifties, a few neural machines were constructed. Oliver Selfridge's "Pandemonium", Frank Rosenblatt's "Perceptron", Bernard Widrow's and Marcian Hoff's "Adaline" introduced the basic concepts for building a neural network. For simplicity purposes a neural network can be structured in layers of neurons, the neurons of each layer firing at the same time after the neurons of the previous layer have fired. The input pattern is fed to the input layer, whose neurons trigger neurons in the second layer, and so forth till neurons in the output layer are triggered and a result is produced. Each neuron in a layer can be connected to many neurons in the previous and following layer. In practice, most implementations had only three layers: the input layer, an intermediary layer and the output layer. After a little while, each layer has "learned" something, but at a different level of abstraction. In general, the layering of neurons plays a specific role. For example, the wider the intermediate layer, the faster but the less accurate the process of categorization, and viceversa. In many cases, learning is directed by feedback. "Supervised learning" is a way to send feedback to the neural network by changing synaptic strengths so as to reflect the error, or the difference between what the output is and what it should have been; whereas in "unsupervised" learning mode the network is able to learn categories by itself, without any exterrnal help. Whether supervised or not, a neural network can be said to have learned a new concept when the weights of the connections converge towards a stable configuration.
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Thinking About Thought: Consciousness, Life and Meaning
Nonsequential Programming What fascinated Computer Science since the beginning, was that neural networks were fundamentally different from the ruling paradigm of the Von Neumann computer: information was processed in parallel, rather than sequentially; the network could actually modify itself (i.e., learn), based on its performance, something no software program was capable of doing; information was spread across the network, rather than being localized in a particular storage place; the network as a whole could still function even if a piece of the network was not functioning, whereas in a computer every single byte of a program must be functioning for the whole to function; and so forth. The technology of neural networks promised to lead to a type of computer capable of learning, and, in general, of more closely resembling our brain. The brain is a neural network that exhibits one important property: all the changes that occur in the connections eventually "converge" towards some kind of stable state. For example, the connections may change every time I see a friend's face from a different perspective, but they "converge" towards the stable state in which I always recognize him as him. Some kind of stability is important for memory to exist, and for any type of recognition to be performed. Neural networks must exhibit the same property is they have to be useful for practical purposes and plausible as models of the brain. Several different mathematical models were proposed in the quest for the optimal neural network. The discipline of neural networks quickly picked up steam. More and more complex machines were built. Until in 1968 Marvin Minsky proved (or thought he proved) some intrinsic limitations of neural networks. All of a sudden, research on neural networks became unpopular and for more than a decade the discipline languished. Energy-based Models In 1982 the American phycisist John Hopfield revived the field by proving the second milestone theorem of neural networks. He developed a model inspired by the "spin glass" material, which resembles a onelayer neural network in which: weights are distributed in a symmetrical fashion; the learning rule is Hebbian; neurons are binary; and each neuron is connected to every other neuron. As they learn, Hopfield's nets develop configurations that are dynamically stable (or "ultrastable"). Their dynamics is dominated by a tendency towards a very high number of locally stable states, or "attractors". Every memory is a local "minimum" for an energy function similar to potential energy. Hopfield's argument, based on Physics, proved that, despite Minsky's critique, neural networks are feasible. Research on neural networks picked up again. Kunihiko Fukushima built the "Neocognitron", based on a model of the visual system. Geoffrey Hinton and Terrence Sejnowsky developed an algorithm for the "Boltzmann machine" based on Hopfield's. In that machine, Hopfield's learning rule is replaced with the rule of annealing in metallurgy (start off the system at very high "temperature" and then gradually drop the temperature to zero), which several mathematicians were proposing as a general-purpose optimization rule. In this model, therefore, units update their state based on a stochastic decision rule. The Boltzmann machine turned out to be even more stable than Hopfield's, as it will always ends in a global minimum (the lowest energy state). http://www.thymos.com/tat/neural.html (4 of 8)25/07/2003 14:23:38
Thinking About Thought: Consciousness, Life and Meaning
David Rumelhart's and Geoffrey Hinton's "back-propagation" algorithm (a gradient-descent algorithms), considerably faster than the Boltzmann machine, quickly became the most popular learning rule. The generalized "delta rule" was basically an adaptation of the Widrow-Hoff error correction rule to the case of multi-layered networks, by moving backwards from the output layer to the input layer. This was also the definitive answer to Minsky's critique, as it proved to be able to solve all of the unsolved problems. Hinton focused on gradient-descent learning procedures. Each connection computes the derivative, with respect to its strength, of a global measure of error in the performance of the network, and then adjusts its strength in the direction that decreases the error. In other words, the network adjusts itself to counter the error it made. Tuning a network to perform a specific task (i.e., recognizing that a round shape is a circle) is a matter of stepwise approximation. By the end of the decade, neural networks had established themselves as a viable computing technology, and a serious alternative to expert systems as a mechanical approximation of the brain. Psychological Models Computational models of neural activity now abound. From Eduardo Caianiello's neural equations to Stephen Grossberg's non-linear quantitative descriptions of brain processes, the number of mathematical theories on how neurons work almost exceeds the possibility of testing them. Now that the mathematics has been improved to the point of safety, the emphasis is moving towards psychological plausibility. At first the only requirement was that a neural network guaranteed to find a solution to every problem, but soon psychologists started requiring that it did so in a fashion similar to the way the human brain does it. Grossberg’s models, for example, are aware of Pavlov’s experiments on conditioning. (Grossberg's goal is a computational model of how a stable mechanism develops in the brain). Besides proving computationally that a neural network can learn, one has to build a plausible model of how the brain as a whole represents the world. In Teuvo Kohonen's "adaptive maps", nearby units responding similarly, thereby explaining how the brain represents the topography of a situation. His unsupervised architecture, inspired by Carl von der Malsburg's studies on self-organization of cells in the cerebral cortex, is capable of self-organizing in regions. Kohonen assumes that the overall synaptic resources of a cell are approximately constant (instead of changing in accordance with Hebb's law) and what changes is the relative efficacies of the synapses. The British computer scientist Igor Aleksander, the main designer of Magnus, has attempted to build a neural state machine that duplicates the most important features of a human being, from consciousness to emotions. Neurocomputing Neural networks belong to a more general class of processing systems, parallel distributed processors, and
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Thinking About Thought: Consciousness, Life and Meaning
neurocomputing is a special case of Parallel Distributed Processing, or PDP, whereby processing is done in parallel by a number of independent processors and control is distributed over all processes. All the models for neural networks can be derived as special cases of PDP systems, from simple linear models to thermodynamic models. The axiom of this framework is that all knowledge of the system is in the connections between the processors. This approach is better suited than traditional (sequential, Von Neumann) computing for pattern matching tasks such as visual recognition and language understanding. Formally: a neural net is a nonlinear directed graph in which each element of processing (each node) receives signals from other nodes and emits a signal towards other nodes, and each connection between nodes has a weight that can vary in time. The principles of neurocomputing can now be formulated in a more mathematical manner. A concept is represented not by a symbol stored at some memory location, but by an equilibrium state defined over a dynamic network of locally interacting units. Each unit encodes one of the many features relevant to recognizing the concept, and the connections between units are excitatory or inhibitory inasmuch as the corresponding features are mutually supportive or contradictory. A given unit can contribute to the definition of many concepts. The Road from Neurons to Symbols Computational models of neural networks have greatly helped in understanding how a structure like the brain can perform. Computational models of cognition have improved our understanding of how cognitive faculties work. But neither group has developed a theory of how neural processes lead to symbolic processes, of how electro-chemical reactions lead to reasoning and thought. A bridge is missing between the physical, electro-chemical, neural processes and the macroscopic mind processes of reasoning, thinking, knowing, etc., in general, the whole world of symbols. A bridge is missing between the neuron and the symbol. Several philosophers have tried to fill the gap. Paul Smolensky's "harmony" theory is one major effort in this direction. Smolensky has developed a theory of dynamic systems that perform cognitive tasks at a subsymbolic level. The task of a perceptual system can be viewed as the completion of the partial description of static states of an environment. Knowledge is encoded as constraints among a set of perceptual features. The constraints and features evolve gradually with experience. Schemata are collections of knowledge atoms that become active in order to maximize what he calls "harmony". The cognitive system is, de facto, an engine for activating coherent assemblies of atoms and drawing inferences that are consistent with the knowledge represented by the activated atoms. A harmony function measures the self-consistency of a possible state of the cognitive system. Such harmony function obeys a law that resembles simulated annealing (just like the Boltzmann machine): the best completion is found by lowering the temperature to zero. A more philosophical attempt, Patricia Churchland's "cognitive neuroscience" aims at a unified theory of cognition and neurobiology, of the computational theory of the mind and the computational theory of the brain. According to her program, the symbols of Fodor's mentalese should be somehow related to neurons, and abstract laws for cognitive processes should be reduced to physical laws for neural processes. http://www.thymos.com/tat/neural.html (6 of 8)25/07/2003 14:23:38
Thinking About Thought: Consciousness, Life and Meaning
Nonetheless, the final connection, the one between the connectionist model of the brain and the symbolprocessing model of the mind, is still missing. But, today, we do have a better understanding of how the brain works, and how we could build machines that simulate the brain. In the process, the concept of "intelligence" has changed quite a bit. The brain is intelligent not because of some central locus of processing, but because of its configuration and of the dynamics of that configuration. Remembering, reasoning and learning are different aspects of the same process and do not involve separate wills. Further Reading Aleksander Igor: IMPOSSIBLE MINDS (Imperial College Press, 1996) Anderson James & Rosenfeld Edward: NEURO-COMPUTING (MIT Press, 1988) Anderson James: NEURO-COMPUTING 2 (MIT Press, 1990) Anderson James: AN INTRODUCTION TO NEURAL NETWORKS (MIT Press, 1995) Arbib Michael: THE HANDBOOK OF BRAIN THEORY AND NEURAL NETWORKS (MIT Press, 1995) Bechtel William & Adele Abrahamsen: CONNECTIONISM AND THE MIND (MIT Press, 1991) Churchland Patricia: NEUROPHILOSOPHY (MIT Press, 1986) Clark Andy: MICROCOGNITION (MIT Press, 1989) Davis Steven: CONNECTIONISM (Oxford University Press, 1992) Grossberg Stephen: NEURAL NETWORKS AND NATURAL INTELLIGENCE (MIT Press, 1988) Hassoun Mohamad: FUNDAMENTALS OF ARTIFICIAL NEURAL NETWORKS (MIT Press, 1995) Haykin Simon: NEURAL NETWORKS (Macmillan, 1994) Hecht-Nielsen Robert: NEUROCOMPUTING (Addison-Wesley, 1989) Hertz John, Krogh Anders & Palmer Richard: INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION (Addison-Wesley, 1990) Kohonen Teuvo: SELF-ORGANIZING MAPS (Springer Verlag, 1995)
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Thinking About Thought: Consciousness, Life and Meaning
Levine Daniel: INTRODUCTION TO NEURAL AND COGNITIVE MODELING (Lawrence Erlbaum, 1991) McClelland James & Rumelhart David: PARALLEL DISTRIBUTED PROCESSING vol. 2 (MIT Press, 1986) Minsky Marvin: PERCEPTRONS; AN INTRODUCTION TO COMPUTATIONAL GEOMETRY (MIT Press, 1969) Rumelhart David & McClelland James: PARALLEL DISTRIBUTED PROCESSING VOL. 1 (MIT Press, 1986)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Consciousness: The Factory Of Illusions (James, Flanagan, Farthing, Nagel, Jackson, McGinn, Damasio, Edelman, Gray and Koch, Llinas, Harth, Varela, Crick, Churchland, Gazzaniga, Ornstein, Calvin, Winson, Hobson, Mead, Gibson, Kinsbourne, Dennett, Baars, Lycan, Eccles, Neisser, Ornstein)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Science’s Last Frontier Studies of the mind (in Psychology, Philosophy, Mathematics, Physics, etc.) have traditionally neglected consciousness (awareness, self-awareness). Such an omission is appalling, as consciousness, more than anything else, is "the" feature of the mind that makes it a mind. The twentieth century has witnessed prodigious scientific progress in many fields. This has brought about a better understanding of the world we inhabit, of the forces that drive it, of the relationships between the human race and the rest of the universe. Scientific explanations have been provided for most of the phenomena that were considered divine powers until a few decades ago. Little by little we have learned how the universe was born, and how it gave rise to the galaxies and the stars and ultimately to our planet; and what life is, how it survives, reproduces and evolves; and what the structure of the brain is, and how it works. The mystery is no longer in our surroundings: it is inside ourselves. What we still cannot explain is precisely that: "ourselves". We may have a clue to what generates reasoning, memory and learning. But we have no scientific evidence and no credible theory for the one thing that we really know very well: our consciousness, our awareness of being us, ourselves. No scientific theory of the universe can be said complete if it doesn't explain consciousness. We may doubt the existence of black holes, the properties of quarks and even that the Earth is round, but there is no way we can doubt that we are conscious. Consciousness is actually the only thing we are sure of: we are sure that "we" exist, and "we" doesn't mean our bodies but our consciousness. Everything else could be an illusion, but consciousness is what allows us to even think that everything else could be an illusion. It is the http://www.thymos.com/tat/consciou.html (1 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
one thing we cannot reject. If our theory of the universe that we have does not explain consciousness, then maybe we do not have a good theory of the universe. Consciousness is a natural phenomenon. Like all natural phenomena it should be possible to find laws of nature that explain it. Unfortunately, precisely consciousness, of all things in the universe, still eludes scientists. Physics has come a long way to explaining what matter is and how it behaves. Biology has come a long way to explain what life is and how it evolves. But no science has come even close to explaining what consciousness is, how it originates and how it works. As the physical and biological foundations of the mind begin to emerge, the mystery thickens. Neurobiology and neurophysiology tell us an enormous amount about the brain, but they cannot explain how conscious experience arises from its electrochemical activity. What Is Consciousness? What is consciousness? What is it to be aware? The more we think, the less we can define it. How does it happen? How does something in the brain (it is in the brain, isn't it?) lead to our emotions, feelings and thoughts? And why does it happen? Why were humans (and presumably to some extent many animals) endowed with consciousness, with the ability to know that they exist, that they live, that other people live, that they are part of this universe and that they will die? The mystery, from a biological point of view, is also why our inner life does not mirror completely, one to one, our external life. When we experience sensations related to interactions of our body with the world, our inner life can be said to mirror the environment, but when we think, sometimes we think things that never happen and will never happen. Why do we need to "think" at all? Paradoxes and weird properties of consciousness abound. Why can't I be aware of my entire being? We only have partial introspection. We have no idea of what many organs are doing in our body. Consciousness is limited to my head. Do I need hands and feet in order to be conscious? Is consciousness only determined by what is in the head, or is it affected also by every part of the body? Am still the same person if they cut my legs? If they transplant my heart? We can only be conscious of one thing at a time. There are many things that we are not conscious of. How do we select which thing we want to be conscious of? Why can I only feel my own consciousness and not other people's consciousness? Why can't I feel other people's feelings? Why can't anybody else feel my feelings? Conscious states are fundamentally different from anything else in nature because they are "subjective". They are not equally accessible to all observers.
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Thinking About Thought: Consciousness, Life and Meaning
Consciousness is a whole, unlike the body which is made of parts, unlike everything else which can be decomposed in more and more elementary units. Conscious states cannot be reduced to constituent parts. What is the self? The self seems to represent a sense of unity, of spatial and time unity: "my" self groups all the feelings related to my body, and it also groups all those feelings that occurred in the past. My body changed over the years, and my brain too. All the cells of the body change within seven years. Therefore my mind must have changed too. But the self somehow bestows unity on that continuously changing entity. If we consider that our bodies are ultimately made of elementary particles, and that the average lifetime of most elementary particles is a fraction of a second, we can say that our bodies are continuously rebuilt every second. The matter of our bodies changes all the time. The only thing that is preserved is the pattern of matter. And even that pattern changes slowly as we age. Not even the pattern is preserved accurately. What makes us think that we are still the same person? How can I still be myself? Why does consciousness exist at all? Did it evolve from non-conscious properties? In that case, why? What purpose does it serve? Could I be conscious of things that I am not conscious of? Am I in control of my consciousness? Is this conscious thought of mine only one of the many possible conscious thoughts I could have now, or is it the only conscious thought I could possibly have now? Is consciousness in control of me? This question is crucial to understanding whether there is a locus of consciousness in the brain, or whether consciousness is simply a side-effect of processes that occur in the brain. The most puzzling property is probably its opacity: we cannot know who and what is conscious. How widespread is consciousness? Who else is conscious besides me? Are other people conscious the same way I am? Are some people more conscious and others less conscious? Are some animals also conscious? Are all animals conscious? Are plants conscious? Can non-living matter also be conscious? Is everything conscious? Laws that protect animals are not clear about "what" makes an animal worth of protecting: killing a neighborhood cat because I don't like it is generally considered offensive, but killing a spider because I don't like it is absolutely normal. One can own a dog and file a suit against somebody who killed it, but one cannot own an ant and file a suit against somebody who stepped over it. Why slaughtering cows by the millions is a lawful practice and killing a pigeon in a square is a crime? Can things inside conscious things be conscious? Are planets and galaxies conscious? Are arms and legs conscious? The physicist Erich Harth has identified the following properties of consciousness: "selectivity (only a few neural processes are conscious); "exclusivity" (only one perception at the time can be conscious); "chaining" (one conscious thought leads to another, as in Hebb's "phase sequence"); "unitarity" (the sense of self). Whichever the classification, it is a fact that partiality, sequentiality, irreducibility, unity, opacity... are properties that set consciousness apart from any other natural phenomenon. And make it difficult, if not http://www.thymos.com/tat/consciou.html (3 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
impossible, to study with the traditional tools of Science. Degrees of consciousness? There is a level of consciousness that we don't achieve all the time, and some people may never or rarely achieve. Teenagers tend to watch movies and wear clothes and even eat food depending on which message prevails in marketing campaigns. The kids who don't follow the "trend" are considered "freaks", "weirdos". Truth is that they are probably more conscious than their friends, and they just realize that there is nothing special about that actor or that fast-food chain, it is just that a lot of money has been spent to promote them. As people grow up they tend to be more aware of why they do things. Some keep following the trends while others become more and more individualistic. The latter are invariably labeled as "eccentric": "eccentric" means that you use your brain instead of letting an external phenomenon condition your brain. The more "conscious" you are, the more eccentric they think you are. The Beatles, all Hollywood stars, Coca Cola and McDonalds are all examples of things that people like because they have been told to like them. The less conscious somebody is, the more dependent that person will become on those things. Society is built on a careful balance of thinkers and non-thinkers. Society relies on a few thinkers to break the rules and bring innovation, but at the same time relies on non-thinkers to perform the daily tasks that keep society alive. Business relies on a few people to bring innovation and on millions of non-thinkers to buy it. Capitalism, communism, fascism all rely on people not to think too much, otherwise the system would become highly unstable. If people thought, McDonalds and Coca Cola would be out of business, and nobody would listen to the Beatles or watch Hollywood hits. And probably very few people would work as hard as they do. It would be total anarchy… Not only there exist different levels of consciousness, but nature depends on a delicate balance of those levels. One problem is to assess where consciousness is "located" in the brain. A related problem is to understand how it is generated by brain processes. And that may be reduced to the "ontogenetic" problem of how consciousness "grows" during the lifetime of an individual. Another problem is to figure out what has it and what does not have it. This may be related to the "phylogenetic" problem of how it was created in the first place: did it evolve from non-conscious matter over million of years or was it born abruptly? An impossible science? It was the psychologist Karl Lashley who first warned that… the mind is never conscious. The mind can never perceive the processing that goes on in the brain when the mind is thinking something. When I think about myself, I am not conscious of what my brain is doing. Whatever it is that I am feeling, it is not what the brain is doing. I am not aware of the billion of electrochemical processes switching neurons on and off. http://www.thymos.com/tat/consciou.html (4 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
One can even suspect that it is plain impossible for a conscious being to understand what consciousness is. The American philosopher Thomas Nagel pointed out that one can only conceive of things as they appear to her and never as they are in themselves. We can only experience how it feels to be ourselves. We can never experience how it feels to be something else, for the simple reason that we are not something else. As Nagel wrote in a famous paper, we can learn all about the brain mechanisms of a bat's sonar system but we will never have the slightest idea of what it is like to have the sonar experiences of a bat. Understanding how the brain works may not be enough to understand consciousness. The Australian philosopher Frank Jackson used the example of a color-blind neuroscientist who can only see black and white and, no matter how much she knows about the neurophysiology of colors, will never know what red feels like. The British philosopher Colin McGinn has claimed that consciousness cannot be understood by beings with minds like ours. Inspired part by Russell and part by Kant, McGinn thinks that consciousness is known by the faculty of introspection, as opposed to the physical world, which is known by the faculty of perception. The relation between one and the other, which is the relation between consciousness and brain, is "noumenal", or impossible to understand: it is provided by a lower level of consciousness which is not accessible to introspection. In more technical words, consciousness does not belong to the "cognitive closure" of the human organism. Understanding our consciousness is beyond our cognitive capacities, just like a child cannot grasp social concepts or I cannot relate to a farmer's fear of tornadoes. McGinn notices that other creatures in nature lack the capability to understand things that we understand (for example, the general theory of relativity). There are parts of nature that they cannot understand. We are also creatures of nature, and there is no reason to exclude that we also lack the capability of understanding something of nature. We may not have the power of understanding everything, unlike what we often assume. Some explanations (such as where the universe comes from and what will happen afterwards and what is time and so forth) may just be beyond our mind's capabilities. Explanations for these phenomena may just be "cognitively closed" to us. Phenomenal consciousness may be one such phenomenon. Is our cognitive closure infinite? In other words: can we understand everything in the world? Is there something that we can't understand? McGinn thinks that our cognitive closure is not infinite, that there are things we will never be capale of understanding. And consciousness is one of them. "Mind may just not be big enough to understand mind". Idealism Of course, one possible answer is to turn things upside down. Instead of assuming the objective point of view that there is a universe, the universe is made of so many things, and one thing within it is the human race, and each member of the human race has consciousness that allows her or him to be aware of the universe, one could think backwards: what really exists is my consciousness. That's the only thing that really exists. Everything else is fabricated by my consciousness. My consciousness fabricates the illusion that there is a universe, that there are other beings, that there are things without consciousness. In reality,
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Thinking About Thought: Consciousness, Life and Meaning
all that exists is consciousness. I don't need to explain what consciousness is, because consciousness is the only thing that exists. These days, the prevailing assumption is however that the universe really exists, and therefore we have to accommodate consciousness and the rest of the universe in one theory of what it is to exist. Qualias The problem of phenomenal qualities has puzzled philosophers for centuries. There is no "red" around me, just particles. Where does the "red" that I see come from? That red exists in my mind, but it does not exist outside my mind. Red is in me, not in the world. How can a reality made of atoms of finite size be generating my feeling of something as uniform and continuous as the color red? The American philosopher Clarence Lewis called them "qualias" (from the Latin "quale", which is the dual of "quantum" and refers to the subjective aspect of a thing). Qualias are qualities that are subjective, directly perceived and known in an absolute way. The taste of something, the color of something, a pain or a desire are associated to qualias, to "feelings" of those things. Qualias are subjective: I cannot be sure that another person’s "red" is identical to my red. Qualias are known in an absolute way: in another world red could correspond to a different frequency of light, and we would have to change the branch of Physics that deals with colors, but what I see as "red" I would still see as red. Why does Nature present itself to my senses in two contradictory ways? If I believe my immediate perceptions, there is red. If I try to make sense of my perceptions, I have to work out a theory of Nature according to which there is no red, but only a vast mass of floating particles. As a matter of fact, the inscrutability of matter is yet another of the mysteries of consciousness. We would like to think that, if nothing else, we know what the world is. We may be puzzled by the nature of mind, but we do know what matter is. At closer inspection, even matter turns out to be a bit of a mystery. We cannot perceive, and therefore conceive, what matter ultimately is. Our mind presents us with a game of illusions, whereby the world is populated by objects and objects have shapes and colors. Science, on the other hand, tells us that all there are only particles and waves. We cannot perceive that ultimate reality of matter. Matter is inscrutable to our mind. We know what consciousness is because we feel it. We know what matter is because we sense it. Because we can sense it, we can build scientific theories on the nature of matter. But we cannot feel it, we cannot feel what matter ultimately is. Because we can only feel it, we cannot build scientific theories on the nature of consciousness. Although we can feel it. Thought vs sensations http://www.thymos.com/tat/consciou.html (6 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
At closer inspection, "consciousness" is a term that encompasses a number of phenomena: thought, the self (awareness of being), bodily sensations (such as pain and pleasure), emotions (anger, happiness, fear, love), phenomenal qualities (such as red or tall), thinking, cognition (reasoning, memory, learning, etc.), and perception (awareness of the others, of the world, of time). Terms are confusing, as they are probably used in different ways. Two of the greatest pioneers of studies on consciousness are exemplary. William James recognized only three forms of consciousness: the stream of consciousness (the overall phenomenon of being conscious), a specific event of the stream (a thought) and self-awareness (awareness of being conscious). Edmund Husserls (in his very convoluted language) also recognized three forms of consciousness (and hinted to more): the stream of consciousness, selfawareness, and the set of all mental events. Today, most classifications stop at two: there is a "narrative", "cognitive", "higher-level" consciousness, which is relatively detached from our bodily experience and which seems to rely on language, and there is an "experiential", "sensorial" consciousness, which has to do with sensations received from the senses, i.e. with our immediate bodily experience. There is widespread consensus that the latter may be common to many species, while the former could be an exclusive of humans. The former is what the British philosopher John Locke once defined as " the perception of what passes in a man's own mind", and that is what we call "thought". The latter is better defined as "sensations". There is growing consensus that "thought" requires some additional level of circuitry in the brain than mere "sensations". The mental and the conscious This classification leads to the relationship between consciousness and mind. Every conscious state is mental: but is every mental state also conscious? If you believe that brains have minds: can anything else have a mind? If you believe that minds are conscious: can anything else be conscious? If we focus on the concept, we realize that we don't really know what "mind" means. Does it mean all and only the feelings associated with brain processes? In that case at every instant there certainly are numerous brain processes that are not conscious. Does "mind" mean conscious? In which case some brain processes are not mental events. (Is the accidental twitching of a brain nerve a mental event?) Or is mind something in between the set of all brain processes and the set of all conscious processes? We tend to associate various unconscious processes to mental activities. For example, most of our daily decisions, from when to cross a street to reading the signs on the road, are actually unconscious, but nonetheless they involve countless brain processes, and some of them are crucial for our survival. Do they belong to the mind? Yes, because they can interact with the mind, unlike neural processes which cannot be perceived by the mind as such; and no, because we not aware of them as they occur. We can take consciousness as a primitive concept (just like "time", "space" and "matter"), that we all know what it means even if we cannot define it. We can define what the brain (or at least the neural system) is and what brain processes are. But the truth is that we can neither take "mind" to be a primitive concept nor http://www.thymos.com/tat/consciou.html (7 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
precisely define it. "Mind" turns out to be a rather unscientific term. If we draw a circle B for the set of all brain events, a circle M for the set of all mental events and a circle C for the set of conscious events, the most likely situation, given what we know of the brain and what we feel in the mind, is that C is fully contained inside M and M is fully contained inside B. (That does not mean that B, M and C are made of the same substance). While B could be (theoretically) precisely defined and C can be assumed to be a primitive, M can be anything between B and C, a circle almost as big as B or a circle almost as small as C. And some people may even claim that M is bigger than C, or smaller than B. In order to achieve a scientific approach to the problem, we must make sure we use "brain" when we mean "brain" (the physical stuff inside the skull), "consciousness" when we mean "conscious" and "mind" when we mean "mind". The problem is that, since we don't really know what the mind is, we don’t really know when we mean "mind". In order to keep a scientific approach to mental faculties, we should never talk about the mind at all. When we refer to mind, we are often interested in general questions such as "how can a living thing remember something" and "how can a living thing learn something". Such questions have two parts. The first part is about the mechanism that allows a piece of living matter to remember or learn something in the sense of being able to perform future actions based on it. The second part is about the awareness of remembering or learning something. The first part doesn't really require consciousness, and it may well be explained on a purely material basis. For what we know, even unconscious things (non-living matter) may be able to remember and learn. We are dealing with a process that can be summarized as: "matter modifies itself based on occurrences in the environment so that its future behavior will be different". Fascinating and intriguing, but far less mysterious than the other half of the problem: "... and, in the process, it is also aware of all of this". Again, the dichotomy is between the brain and consciousness, the mind is a useless intellectual complication. Progress in neurobiology and cognitive psychology has actually clarified quite a bit of the mechanisms that preside to memory and learning, language and reasoning; and machines have been built that mimic those processes. The other half of the problem is still as mysterious as it was centuries ago. How does a mental process give rise to awareness that the process is going on? It looks like by "mind" we always meant something physical, material, reducible to physical processes inside the brain, which could be reproduced in a laboratory, and possibly on beings made of a different substance. At the same time we also meant something that today's Science could never replicate in a laboratory: the awareness of that something physical going on inside us. For the purpose of Science, we should stop referring to both as "mind", we should focus on "brain" and "consciousness". The "mind" as in "mental faculties" is but a view of the brain at a higher level of organization (that of memory and learning, language and reasoning). Not all brain processes influence the mind, because not all microscopic events have an effect on the higher levels of the organization. Then explaining the mind will be reduced to explaining the brain, a program which is in progress right now. The Conscious and the Unconscious http://www.thymos.com/tat/consciou.html (8 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
James is responsible for articulating the "classical" theory of consciousness, the analog of Newton's classical Physics. To James, consciousness is a sequence of conscious mental states, each state being the experience of some content. Just like Newton saw a unitary and continuous space, James saw a unitary and continuous consciousness. James thought that the mind had an evolutionary purpose, just like Darwin thought that all features of the body had an evolutionary purpose. Thinking is useful for our survival, just like eating and mating. James treated consciousness like a function, not an entity. James was, in part, reacting to the theory of perception that dated from Helmholtz, that sense data from the senses are turned by the mind into percepts which are conscious experiences of the environment. James thought, instead, that the output of the brain process is guidance of action in the environment, not a conscious experience of the environment. Furthermore, a sensory act specifies not only the environment but also the self. Self (the "subjective") and environment (the "objective") are only two poles of attention. Each act of perception actually specifies both the self and the environment. For example, seeing something carries information about the layout of the environment, but also about our point of perspective, all perception is "perspectival" in character. This view, of course, must be complemented with the rest of mental life, which is not all conscious. The American psychologist Owes Flanagan does not believe in "one" consciousness, but in a group of "conscious" phenomena. Some of the processes of our body are unconscious and non perceived (e.g., the heartbeat), some are unconscious but perceived by other processes (sensors), and some are conscious, perceived by themselves. Consciousness is a heterogeneous set of processes, not a substance or an object. This is now a popular belief among psychologists, although many different strands exist and opinions differ on the relative "size" of conscious and unconscious processes. The American psychologist William Farthing believes that most of our mental life is unconscious and that consciousness is only the tip of the iceberg. Binding Brain and Consciousness Knowledge about the world is distributed around the brain. How it is then integrated into one unitary perception is the "binding" problem. This problem occurs at several levels. A sensory input is channeled through several different areas of the brain, each brain region focusing on one aspect of the input, but then somehow the mind perceives the whole input as something that happens at the same time in the same place, and it is a whole. The "binding" problem refers to how the brain creates the whole perception out of a sensory input that has been fragmented around the brain.
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Thinking About Thought: Consciousness, Life and Meaning
For example, a visual input is "split" so that one brain region analyzes the shape and one brain region analyzes the color. But somehow these separate pieces of information are joined again to produce the overall sensation of the image. At a higher level, different sensory inputs come together: the sound of an event is merged with the image of the event, or the smell of the event, or the touch of the event. There is an overall feeling of the situation. At an even higher level, the perception is merged with pre-existing memories and concepts. We don't only see a human being moving and speaking around us: we see our friend X talking to us. At the highest level, all of this complex system of feelings and knowledge "feels" unified in our consciousness. There is "one" feeling of "me" existing in a "world". Somehow all has been "bound" together into consciousness. There are different theories about where and how and when this ultimate form of "binding" could occur. Space-based binding is advocated by scientists who believe that there is a specific place in the brain where all the information is integrated together. In the 1990s, a competing paradigm has emerged which is based on time instead of space, and is therefore referred to as "time-based binding": there is no particular place where the integration occurs, because integration occurs over the entire brain, and is regulated by some periodic process. Space-based binding theories try to identify the "homunculus" in the brain that is responsible for running The working memory is a popular candidate for such a task, but no piece of the brain seems likely to show us the transformation of electrochemical processes into conscious processes. According to the Portoguese neurobiologist Antonio Damasio, instead, the story is more complex. There is not just one working memory: there is a whole system of "convergence zones". The brain has "convergence zones" and convergence zones are organized in a hierarchy: lower convergence zones pass information to higher convergence zones. Lower zones select relevant details from sensorial information and send summaries to higher zones, which successively refine and integrate the information. In order to be conscious of something a higher convergence zone must retrieve from the lower convergence zones all the sensory fragments that are related to that something. Therefore, consciousness of something occurs when the higher convergence zones fire signals back to lower convergence zones. The movie in the mind Damasio breaks the problem of consciousness into two parts: the "movie in the brain" kind of experience (how a number of sensory inputs are trasnformed into the continuous flow of sensations of the mind) and the self (how the sense of "owning" that movie comes to be). The "core" consciousness of the movie in the brain is essentially unchanged throughout a lifetime, and humans share it with other many species. The "extended" consciousness of the self is refined over a lifetime: an "owner" and "observer" of the movie is created within the core consciousness, in such a way that it seems to be located outside the brain, while it is part of the brain's neural processes and part of the movie itself which those neural processes generate. The more developed the sense of the self, the stronger http://www.thymos.com/tat/consciou.html (10 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
the impression that the movie in the mind is "my" experience of the world. There is overwhelming evidence that distinct parts of the brain work in concert to represent sensory input. Brain cells represent events occurring somewhere else in the body. Brain cells are "intentional", if you will. They are not only "maps" of the body: besides the topography, they also represent what is taking place in that topography. Indirectly, the brain also represents whatever the organism is interacting with, since that interaction is affecting one or more organs (e.g., retina, tips of the fingers, ears), whose events are represented in brain cells. The "movie in the mind" is a purely non-verbal process: language is not a prerequisite for this first level of consciousness. The "I" is a verbal process that arises from a second-order narrative capacity. The brain stem and hypothalamus are the organs that regulate "life", that control the balance of chemical activity required for living, the body's homeostasis. Consequently, they also represent the continuity of the same organism. Damasio believes that the self originates from these biological processes: the brain has a representation of the body and has a representation of the objects the body is interacting with, and therefore can discriminate self and non-self and then generate a "second order narrative" in which the self is interacting with the non-self (the external world). This second-order representation occurs mainly in the thalamus. More precisely, the neural basis for the self resides with the continuous reactivation of 1. the individual's past experience (which provides the individual's sense of identity) and 2. a representation of the individual's body (which provides the individual's sense of a whole). An important corollary is that the self is continuously reconstructed From an evolutionary perspective, we can presume that the sense of the self is useful to induce purposeful action based from the "movie in the mind". The self provides a survival advantage because the "movie in the mind" acquires a first-person character, i.e. it acquires a meaning for that first person, i.e. it highlights what is good and bad for that first person, a first person which happens to be the body of the organism, disguised as a self. This second-order narrative derives from the first-order narrative constructed from the sensory mappings. In other words, all of this is happening while the "movie" is playing. The sense of the self is created while the movie is playing by the movie itself. The thinker is created by the thought. The spectator of the movie is part of the movie. . Consciousness is an internal narrative, due to those mappings. The "I" is not telling the story: the "I" is created by stories told in the mind ("You are the music while the music lasts"). Consciousness as self-reference The idea of some form of "self-referential feedback" (of some kind of loop inside the brain) is firmly http://www.thymos.com/tat/consciou.html (11 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
rooted in modern space-based binding theories. Gerald Edelman's "reentrant maps" and Nicholas Humphrey's "sensory reverberating feedback loop" are variations on the same theme. The idea is that, somehow, the brain refers to itself, and this self-referentiality, somehow, unchains consciousness. Rather than "space-based", these theories tend to be "process-based", since they are not only looking for the place where the binding occurs but also for the way it occurs, and the process turns out to be much more important than the place. According to Edelman, consciousness is a natural development of the ability to build perceptual categories (such as "blue", "tall", "bird", "tree", "book"), the process that we normally call generalization. The brain can do this because neurons get organized by experience in maps, each neural map dealing with a feature of perceptions (color, shape, etc.). First of all, Edelman distinguishes between primary consciousness (imagery and sensations, basically being aware of things in the world) and higher-order consciousness (language and self-awareness). For primary consciousness to appear a few requirements must be met. It takes a memory, and an active type of memory, that does not simply store new information but also continuously reorganizes (or "recategorizes") old information. Then it takes the ability to learn, but learning is not only memorizing, it is also a way to rank stimuli, to assign value to stimuli (a new value will result in a new behavior, and that is what learning is about). Then it takes the ability to make the distinction between the self from the rest of the world, i.e. a way to represent what is part of the organism and what is not. Then it takes a way to represent chronology, to order events in time. Finally, it takes a maze of "global reentrant pathways" (i.e., forms of neural transmission that let signals travel simultaneously in both directions) connecting all these anatomical structures. Primary consciousness arises from "reentrant loops" that interconnect "perceptual categorization" and "value-laden" memory ("instincts"). In general, cognitive functions emerge from reentrant processes. Consciousness therefore arises from the interaction of two parts of the neural system that differ radically in their anatomical structure, evolution, organization and function: the one responsible for categorizing (external stimuli) and the one responsible for "instinctive" behavior (i.e., homeostatic control of behavior). Consciousness emerges as the product of an ongoing categorical comparison of the workings of those two kinds of nervous system. From an evolutionary point of view, the milestone moment was when a link emerged between category and value, between those two different areas of the brain, that is when the basis for consciousness was laid. A higher-level consciousness (being aware of itself), probably unique to humans, is possible if the brain is also capable of abstracting the relationship between the self and the nonself, and this can only happen through social interaction, and this leads naturally to the development of linguistic faculties. Edelman actually identifies the regions that are assigned to define self within a species (the amygdala, the hippocampus, the limbic system, the hypothalamus) and those that operate to define nonself (the cortex, the thalamus and the cerebellum). Note that concept formation preceded language. Language was enabled by anatomical changes. With the http://www.thymos.com/tat/consciou.html (12 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
advent of language what changed is that concepts became absolute, independent of time. And semantics preceded syntax: acquiring phonological capacities provided the means for linking the preexisting conceptual operations with the emerging lexical operations. In Edelman's picture, consciousness is liberation from the present. All animals still live in the present, simply reacting to stimuli. Only humans can think about the past and about the future. Time-based Binding Time-based binding does not look for the "place" but for the "time" at which the binding of our conscious experience occurs. The German physicist Christof Koch discovered in 1989 that at, any given moment, very large number of neurons oscillate in synchrony, reflecting something that was captured by the senses, but only one pattern is amplified into a dominant 40 Hz oscillation, and that is the "thing" the individual is conscious of. Out of so many oscillations of synchronized cells in the brain, one is special and happens to have a frequency of 40 Hz. The American neurophysiologists Charles Gray then hypothesized that the memory of something is generated by a stream of oscillating networks. Separate brain regions (corresponding to different categories of features) send out nervous impulses at the same frequency and the perception of an object is created by the superimposed oscillation. The brain uses frequency as a means to integrate separate parts of a perception. This way the limited capacity of the brain can handle the overwhelming amount of objects that the world contains (the number of objects we see in a lifetime exceeds the number of neurons in the brain that would be needed to store them as images). This theory is compatible with both Damasio's and Edelman's theories, as they all posit some type of "synchrony" for consciousness of something to emerge. According to these theories, it is time, not space, that binds. It almost marks a revival of gestalt" psychology (the oscillation is, for pratical purposes, a gestalt). The Colombian neurophysiologist Rodolfo Llinas has intepreted this finding as a scanning system that sweeps across all regions of the brain every 1.25 thousandths of a second (40 times a second). The region of the brain containing the information about a sensation constitutes the "context" of a conscious experience. The 40Hz oscillation provides the "binding" of such content into a unified cognitive act. This wave of nerve pulses is sent out from the thalamus and triggers all the synchronized cells in the cerebral cortex that are recording sensory information. The cells then fire a coherent wave of messages back to the thalamus. Only cortex cells that are active at that moment respond to the request from the thalamus. Consciousness originates from this loop between thalamus and cortex, from the constant interaction between them. Consciousness is generated by the dialogue (or "resonating activity") between thalamus and cortex.
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Thinking About Thought: Consciousness, Life and Meaning
Consciousness is simply a particular case of the way the brain works. Other brain regions have their own temporal binding code. The motor system, for example, works at 10 cycles per second (which means that movements only occur ten times a second, not continuously). Every function is controlled by a rhythmic system that occurs automatically, regardless of what is happening to the body. Consciousness happens to be the phenomenon generated by that specific rhythmic system that operates on the brain itself. Besides the 40-cycle-per-second, the brain has a number of natural oscillatory states: at 2 cycles per second it is sleeping. The brain's function is to create images: at 2 cycles per second it creates dreams; at 40 cycles per second it creates images that represent the outside world as perceived by the senses. In other words, the brain is always working independently of what is happening outside: during sleep, i.e. in the absence of sensorial data, that work is called "dreaming"; during the day, in the presence of sensorial data, it is called thought. The difference is that the brain’s automatic dreaming is conditioned by the senses: when the senses are bombarded by external stimuli, the brain can generate only some types of thought, just like the body can generate only some types of movement. At every instant, the brain is dealing with both reality and phantasy. "A person's waking life is a dream modulated by the senses". The American neuroscientist Paul Churchland has provided a detailed description of how the brain perceives sensory input (in particular vision) through what he calls "vector coding". He claims that consciousness must be based on a "recurrent" network and Llina's 40 Hz oscillation in the cortex is a convenient candidate for a brainwide recurrent network. That brainwide recurrent network would be able to unify the distinct senses in one consciousness. In this sense, therefore, consciousness does not require language and nonlinguistic animals can be conscious too. Coscniousness is biological, not social (its contents may be social, such as language). Reverberating loops What Edelman and Llinas have in common is the belief that higher mental functions originates from a process of loops that reverberate through the brain (in particular, between the thalamus and the cortex, the thalamus being the source of so many crucial signals and the cortex being the newer, more sophisticated part of the brain). They differ in the specific mechanisms but they both focus on the fact that regions of the brain are connected in a bidirectional way and that they "resonate" to each other, they are somehow in synch. There are other models that exploit the same paradigm. In 1995 the Chilean neurologist Francisco Varela has claimed that there is a primary consciousness common to all vertebrates. This primary consciousness is not self-awareness but merely experience of a unitary mental state. Varela thinks that it is due to a process of "phase locking": brain regions resonate, their neurons firing in synchrony, and create a cell assembly that integrates many different neural events (perceptions, emotions, memory, etc). This coherent oscillation of neurons is primary consicousness. The British biochemist and Nobel laureate Francis Crick (the one who discovered the DNA) also http://www.thymos.com/tat/consciou.html (14 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
subscribes to the view that synchronized firing in the range of 40 Hertz in the areas connecting the thalamus and the cortex might explain consciousness; that consciousness arises from the continuous dialogue between thalamus and cortex. Awareness of something requires "attention" (being aware of one object rather than another), and attention requires "binding" (banding together all neurons that represent aspects of the object). Crick believes that binding occurs through a synchronous (or "correlated") firing of different regions of the brain. During attention, all the neurons that represent features of an object fire together. It is not just the frequency of firing of the neurons that matters, but the moments when they fire. The main difference between Llinas and Crick is in their background. Crick studied visual awareness and so is interested in consciousness that arises from external stimuli. Llinas, on the contrary, is more interested in consciousness that does not arise from external stimuli (what we call "thought").
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Baars Bernard: A COGNITIVE THEORY OF CONSCIOUSNESS (Cambridge Univ Press, 1988) Baars Bernard: IN THE THEATER OF CONSCIOUSNESS (Oxford Univ Press, 1997) Blackmore Susan: THE MEME MACHINE (Oxford Univ Press, 1999) Calvin William: HOW BRAINS THINK (Basic, 1996) Cannon Walter: THE WISDOM OF THE BODY (Norton, 1939) Cohen, Jonathan & Schooler, Jonathan: SCIENTIFIC APPROACHES TO CONSCIOUSNESS (Erlbaum, 1997) Churchland Paul: ENGINE OF REASON (MIT Press, 1995) Damasio Antonio: DESCARTES' ERROR (G.P. Putnam's Sons, 1995) Damasio Antonio: THE FEELING OF WHAT HAPPENS (Harcourt Brace, 1999) Dennett Daniel: CONSCIOUSNESS EXPLAINED (Little & Brown, 1991) Dennett Daniel: KINDS OF MINDS (Basic, 1998) http://www.thymos.com/tat/consciou.html (15 of 17)25/07/2003 14:23:59
Thinking About Thought: Consciousness, Life and Meaning
Dretske Fred: NATURALIZING THE MIND (MIT Press, 1995) Eccles John: EVOLUTION OF THE BRAIN (Routledge, 1991) Edelman Gerald: THE REMEMBERED PRESENT (Basic, 1989) Edelman Gerald: BRIGHT AIR BRILLIANT FIRE (Basic, 1992) Farthing, G.William: THE PSYCHOLOGY OF CONSCIOUSNESS (Prentice-Hall, 1992) Flanagan Owen: THE SCIENCE OF THE MIND (MIT Press, 1991) Flanagan Owen: CONSCIOUSNESS RECONSIDERED (MIT Press, 1992) Gazzaniga Michael: SOCIAL BRAIN (Basic, 1985) Gazzaniga Michael: NATURE's MIND (Basic, 1992) Gazzaniga Michael: THE MIND’s PAST (Univ of California Press, 1998) Gibson James Jerome: THE ECOLOGICAL APPROACH TO VISUAL PERCEPTION (Houghton Mifflin, 1979) Greenfield Susan: JOURNEY TO THE CENTERS OF THE MIND (W.H.Freeman, 1995) Harth Erich: CREATIVE LOOP (Addison-Wesley, 1993) Hobson Allan: THE CHEMISTRY OF CONSCIOUS STATES (Little & Brown, 1994) Humphrey Nicholas: CONSCIOUSNESS REGAINED (Oxford Univ Press, 1983) Humphrey Nicholas: A HISTORY OF THE MIND (Simon & Schuster, 1993) Ingebo-Barth, Denise: THE CONSCIOUS STREAM (Universal Publisher, 2000) Lycan William: CONSCIOUSNESS AND EXPERIENCE (MIT Press, 1996) McGinn Colin: THE PROBLEM OF CONSCIOUSNESS (Oxford Univ Press, 1991) McGinn Colin: THE MYSTERIOUS FLAME (Oxford Univ Press, 1991) Mead, George Herbert: MIND SELF AND SOCIETY (Univ of Chicago Press, 1934) http://www.thymos.com/tat/consciou.html (16 of 17)25/07/2003 14:23:59
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Mead, George Herbert: THE PHILOSOPHY OF THE ACT (Univ of Chicago Press, 1938) Nagel Thomas: MORTAL QUESTIONS (Cambridge Univ Press, 1979) Nagel Thomas: THE VIEW FROM NOWHERE (Oxford Univ Press, 1986) Neisser Ulric: CONCEPTS AND CONCEPTUAL DEVELOPMENT (Cambridge University Press, 1987) Norretranders Tor: THE USER ILLUSION (Viking, 1998) Ornstein Robert: MULTIMIND (Houghton Mifflin, 1986) Ornstein Robert: EVOLUTION OF CONSCIOUSNESS (Prentice Hall, 1991) Scott Alwyn: STAIRWAY TO THE MIND (Copernicus, 1995) Tye Michael: THE METAPHYSICS OF MIND (Cambridge University Press, 1989) Tye Michael: TEN PROBLEMS OF CONSCIOUSNESS (MIT Press, 1995) Unger Peter: IDENTITY, CONSCIOUSNESS AND VALUE (Oxford Univ Press, 1991) Winson Jonathan: BRAIN AND PSYCHE (Anchor Press, 1985)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind The History of Consciousness (Porges, Popper, Arbib, Mithen, Mead, Humphrey, Armstrong, Jaynes, Donald, Hameroff, Deacon, CairnsSmith)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Origin of Consciousness How and when and why did consciousness develop? Opinions vary. Julian Jaynes believes that it is a recent phenomenon, Eccles thinks that it arose with the advent of mammalian neocortex, about 200 million years ago, the biologist Lynn Margulist things that it was a property of even simple unicellular organisms of several billion years ago. There is growing consensus that it somehow owes its existence to the fact that humans evolved in a highly connected group, that it is related to the need to communicate with or differentiate from peers. The idea that consciousness is closely related to language is pervasive. The influential Austrian philosopher Karl Popper thought that, phylogenetically speaking, consciousness emerged with the faculty of language, and, ontogenetically speaking, it emerges during growth with the faculty of language. Michael Arbib advanced the hypothesis that first language developed, as a tool to communicate with other members of the group in order to coordinate group action; then communication evolved beyond the individual-to-individual sphere into the self sphere. Their intuitions and findings are consistent with the view held by the American biologist George Herbert Mead, that consciousness is a product of socialization among biological organisms. Language simply provides the medium for its emergence. The mind is socially constructed, society constitutes an individual as much as the individual constitutes society.
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Thinking About Thought: Consciousness, Life and Meaning
The mind emerges through a process of internalization of the social process of communication, for example by reflecting to oneself the reaction of other individuals to one's gestures. The minded organism is capable of being an object of communication to itself. Gestures, which signal the existence of a symbol (and a meaning) that is being communicated (i.e., recalled in the other individual), constitute the building blocks of language. "A symbol is the stimulus whose response is given in advance". Meaning is defined by the relation between the gesture and the subsequent behavior of an organism as indicated to another organism by that gesture. The mechanism of meaning is therefore present in the social act before the consciousness of it emerges. Consciousness is not in the brain, but in the world. It refers to both the organism and the environment, and cannot be located simply in either. What is in the brain is the process by which the self gains and loses consciousness (analogous to pulling down and raising a window shade). The philosopher Daniel Dennett offers an even more detailed route to consciousness: consciousness evolved from non-consciousness to reasoning and then to deal with memes. Again, memes represent culture. The psychologist Nicholas Humphrey agrees that the function of consciousness is that of social interaction with other consciousnesses. Consciousness gives every human a priviliged picture of her own self as a model for what it is like to be another human. Consciousness provides humans with an explanatory model of their own behavior, and this skill is useful for survival: in a sense, the best psychologists are the best survivors. . Humphrey speculates that, by exploring their own selves, humans gained the ability to understand other humans; by understanding their own minds, they understood the minds of the individuals they shared their life with. The American anthropologist Terrence Deacon takes a "semiotic" approach to consciousness. He distinguishes three types of consciousness, based on the three types of signs: iconic, indexical and symbolic. The first two types of reference are supported by all nervous systems, therefore they may well be ubiquitous among animals. But symbolic reference is different because, in his view, it involves other individuals, it is a shared reference, it requires the capability to communicate with others. It is, therefore, exclusive to linguistic beings, i.e. to humans. Such symbolic reference includes the self: the self is a symbolic self. The symbolic self is not reducible to the iconic and indexical references. The self is not bounded within a body, it is one of those "shared" references. With very few exceptions there seems to be general consensus that consciousness arose with the need for communication. A minority sees consciousness as useful to find solutions to practical problems. The philosopher David Malet Armstrong, for example, argues that the biological function of consciousness is to sophisticate the mental processes so that they yield more interesting action. The truth is that today consciousness hardly contributes to survival. We often get depressed because we are http://www.thymos.com/tat/consc2.html (2 of 4)25/07/2003 14:24:13
Thinking About Thought: Consciousness, Life and Meaning
conscious of what happens to us. We get depressed just thinking of future things, such as death. Consciousness often results in less determination and perseverance. Consciousness cannot be the ultimate product of Darwinian evolution towards more and more sophisticated survival systems, because it actually weakens our survival system. Consciousness' apparent uselessness for survival could be easily explained if we tipped our reference frame. It is generally assumed that humans' ancestors had no consciousness and consciousness slowly developed over evolutionary time. Maybe it goes the other way around: consciousness has always existed, and during evolution most species have lost part of it. Being too self-aware does hurt our chances of surviving and reproducing. Maybe evolution is indirectly improving species by reducing their selfawareness. The Bicameral Mind The studies conducted in the 1970's by the American psychologist Julian Jaynes first gave credibility to the idea that consciousness may be a recent acquisition of our mental life, or at least that consciousness was not always what it is today, that it was and still is evolving.
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Arbib Michael: METAPHORICAL BRAIN 2 (Wiley, 1989) Cairns-Smith A. G.: EVOLVING THE MIND (Cambridge University Press, 1995) Deacon Terrence: THE SYMBOLIC SPECIES (W.W. Norton & C., 1997) Donald Merlin: ORIGINS OF THE MODERN MIND (Harvard Univ Press, 1991) Hameroff Stuart: ULTIMATE COMPUTING: BIOMOLECULAR CONSCIOUSNESS AND NANOTECHNOLOGY (Elsevier Science, 1987) Jaynes Julian: THE ORIGIN OF CONSCIOUSNESS IN THE BREAKDOWN OF THE BICAMERAL MIND (Houghton Mifflin, 1977) Euan Macphail: THE EVOLUTION OF CONSCIOUSNESS (Oxford UnivPress, 1998) Mead George Herbert: MIND, SELF AND SOCIETY (Univ of Chicago Press, 1934)
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Mithen Steven: THE PREHISTORY OF THE MIND (Thames and Hudson, 1996) Popper Karl: KNOWLEDGE AND THE BODY-MIND PROBLEM (Routledge, 1994)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind The Physics of Consciousness (Walker, Froehlich, Marshall, Zohar, Pribram, Culbertson, Stapp, Wolf, Herbert, Lockwood, Penrose, Searle, Chalmers, Eccles)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Quantum Consciousness An approach to consciousness based on Physics has been advocated by several thinkers. Quantum Theory has been particularly intriguing for scientists eager to provide a physical explanation of consciousness. Loosely speaking, the point is that consciousness is unlikely to arise from classical properties of matter (the more we understand the structure and the fabric of the brain, the less we understand how consciousness can occur at all), which are well known and well testable. But Quantum Theory allows for a new concept of matter altogether, which may well leave cracks for consciousness, for something that is not purely material or purely extra-material. Of course, the danger in this way of thinking is to relate consciousness and Quantum only because they are both poorly understood: what they certainly have in common is a degree of "magic" that makes them both mysterious and unattainable. On the other hand, it is certainly true that all current neurobiological descriptions of the brain are based on Newton's Physics, even if it is well known that Newton's Physics has its limitations. First of all, Newton's Physics is an offshoot of Descartes division of the universe in matter and spirit, and it deals only with matter. Secondly, neurobiologists assume that the brain and its parts behave like classical objects, and that quantum effects are negligible, even while the "objects" they are studying get smaller and smaller. What neurobiologists are doing when they study the microstructure of the brain from a Newtonian perspective is equivalent to organizing a trip to the Moon on the basis of Aristotle's Physics, neglecting Newton's theory of gravitation. No wonder most neurobiologists reach the conclusion that Physics cannot explain consciousness, since they are using a Physics that 1. was designed to study matter and leave out consciousness and that 2. does not work in the microworld. Not surprisingly, it has been claimed that all current neurobiological models http://www.thymos.com/tat/consc3.html (1 of 6)25/07/2003 14:24:28
Thinking About Thought: Consciousness, Life and Meaning
are computationally equivalent to a Turing machine. Similarities between mind and quantum theory undoubtedly abound. The unity of consciousness is a favorite example. A conscious state is the whole of the conscious state and cannot be divided into components (I can't separate the feeling of red from the feeling of apple when I think of a red apple). Newton's Physics is less suitable than Quantum Theory for dealing with such a system, especially since Bell's Theorem proved that everything is always interacting. Indeterminate behavior (for example, free will) is another favorite, since Heisenberg's principle allows for some unpredictability in nature that Newton's Physics ruled out. And, of course, the mind/body duality reminds Physicists of the wave/particle duality. Quantum Physics also solves, to some extent, Descartes' dualism: in Quantum Physics, matter is ultimately not a solid substance. Quantisizing the Mind The true pioneer of this field is the biologist Alfred Lotka, who in 1924, when Quantum Theory had barely been born, proposed that the mind controls the brain by modulating the quantum jumps that would otherwise lead to a completely random existence. The first detailed quantum model of consciousness was probably the American physicist Evan Walker's synaptic tunneling model (1970), in which electrons can "tunnel" between adjacent neurons, thereby creating a virtual neural network overlapping the real one. It is this virtual nervous system that produces consciousness and that can direct the behavior of the real nervous system. The real nervous system operates by means of synaptic messages. The virtual one operates by means of the quantum effect of tunneling (particles passing through an energy barrier that classically they should not be able to climb). The real one is driven by classical laws, the virtual one by quantum laws. Consciousness is therefore driven by quantum laws, even if the brain's behavior can be described by classical laws. Later theories will share the view that the brain "instantiates" not one but two systems: a classical one and a quantum one. The second one could be responsible for the properties of mental life (such as consciousness) that are not easily reduced to the properties of the classical brain. The beauty of Quantum Theory is that it allows for "nonlocal" properties and provides a framework to explain how entities get "entangled", precisely the phemomena that brain processes are not enough to explain. A Physics of Consciousness In 1986 John Eccles, the British neurophysiologist who discovered neurotransmitters, has speculated that synapses in the cortex respond in a probabilistic manner to neural excitation, a probability that could well be governed by quantum uncertainty given the extremely small size of the synapsis'"microsite" that emits the neurotransmitter. If this is true, Eccles speculates that an immaterial mind (in the form of "psychons") controls the quantum "jumps" and turns them into voluntary excitations of the neurons that account for body motion.
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Thinking About Thought: Consciousness, Life and Meaning
There is also a physical model of consciousness that invokes other dimensions. The unification theories that attempt at unifying General Relativity (i.e. gravitation) and Quantum Theory (i.e., the weak, electrical and strong forces) typically add new dimensions to the four ones we experience. These dimensions differ from space in that they are bound (actually, rolled up in tiny tubes) and in that they only exist for changes to occur in particle properties. Saul-Paul Sirag's hyperspace, for example, contains many physical dimensions and many mental dimensions (time is one of the dimensions they have in common). Condensate consciousness Possibly the most popular candidate to yield quantum consciousness has been Bose-Einstein condensation (theoretically predicted in 1925 and first achieved in a gas in 1995). The most popular example of BoseEinstein condensation is superconductivity. The fascination with Bose-Einstein condensates is that they are the most highly ordered structures in nature (before their discovery by Albert Einstein and Satyendranath Bose, that record was owned by crystals). The order is such that each of their constituents appears to occupy all their space and all their time: for all purposes the constituents of a Bose-Einstein condensate share the same identity. In other words, the constituents behave just like one constituent (the photons of a laser beam behave just like one photon) and the Bose-Einstein condensate behaves like one single particle. Another odd feature of Bose-Einstein condensates is that they seem to possess a primitive form of free will. A Bose-Einstein condensate is the equivalent of a laser, except that it is the atoms, rather than the photons, that behave identically, as if they were a single atom. Technically speaking, as temperature drops each atom's wave grows, until the waves of all the atoms begin to overlap and eventually merge. After they merged, the atoms are located within the same region in space, they travel at the same speed, they vibrate at the same frequency, etc.: they become indistinguishable. The atoms have reached the lowest possible energy, but Heisenberg's principle makes it impossible for this to be zero energy: it is called "zero-point" energy, the minimum energy an atom can have. The intriguing feature of a Bose-Einstein condensate is that the many parts of a system not only behave as a whole, they become whole. Their identities merge in such a way that they lose their individuality. Bose-Einstein condensation can normally be achieved only at very low temperatures. In the late 1960s, the British physicist Herbert Froehlich proved the feasibility and even the likelihood of Bose-Einstein condensation at body temperatures in living matter (precisely, in cell membranes). This opened the doors to the possibility that all living systems contain Bose-Einstein condensates. Precisely, electrical charged molecules of living tissues behave like electric dipoles. When digestion of food generates enough energy, all molecular dipoles line up and oscillate in a perfectly coordinate manner, which results in a Bose-Einstein condensate. Biological oscillators of this kind are pervasive in nature: living matter is made of water and other biomolecules equipped with electrical dipoles, which react to external stimuli with a spontaneous breakdown of their rotational symmetry. http://www.thymos.com/tat/consc3.html (3 of 6)25/07/2003 14:24:28
Thinking About Thought: Consciousness, Life and Meaning
The biological usefulness of such biological oscillators is that, like laser light, they can amplify signals and encode information (e.g., they can "remember" an external stimulus). Most importantly, coherent oscillations are crucial to many processes of integration of information in the brain. Quantum Self Theory In 1989 the British phychiatrist Ian Marshall showed similarities between the holistic properties of condensates and those of consciousness, and suggested that consciousness may arise from the "excitation" of such a Bose-Einstein condensate. In Marshall's hypothesis, the brain contains a Froehlich-style condensate, and, whenever the condensate is excited by an electrical field, conscious experience occurs. The brain would maintain dynamical coherence (i.e., be able to organize millions of neuronal processes into the coherent whole of thought) thanks to an underlying quantum coherent state (the Bose-Einstein condensate). Furthermore, Marshall thinks that the collapse of a wave function is not completely random, as predicted by Quantum Theory, but exhibits a preference for "phase difference". Such "phase differences" are the sharpest in Bose-Einstein condensates. This implies that the wave function tends to collapse towards BoseEinstein condensates, i.e. that there is a universal tendency towards creating the living and thinking structures that populate our planet. Marshall views this as an evolutionary principle built in our universe. In other words, the universe has an innate tendency towards life and consciousness. They are ultimately due to the mathematical properties (to the behavior) of the quantum wave function, which favors the evolution of life and consciousness. Marshall thinks we "must" exist and think, in accordance with the strong anthropic principle (that things are the way they are because otherwise we would not exist). Marshall can then solve the paradox of "adaptive evolution", discovered in 1988 by John Cairns: some bacteria can mutate very quickly, way too quickly for Darwin's theory to be true. If all genes mutated at that pace, they would mostly produce mutations that cannot survive. What drives evolution is natural selection, which prunes each generation of mutations. But natural selection does not have the time to operate on the very rapid mutations of these bacteria. There must be another force at work that "selects" only the mutations that are useful for survival. Marshall thinks that the other force is the wave function's tendency towards choosing states of life and consciousness. Each mutation is inherently biased towards success. His wife, the American philosopher Danah Zohar, has expanded on this idea. Zohar views the theory of Bose-Einstein condensation as a means to reduce mind/body duality to wave/particle duality. The wave aspect of nature yields the mental, the particle aspect of nature yields the material.
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Thinking About Thought: Consciousness, Life and Meaning
Zohar is fascinated by the behavior of bosons. Particles divide into fermions (such as electrons, protons, neutrons) and bosons (photons, gravitons, gluons). Bosons are particles of "relationship", as they are used to interact. When two systems interact (electricity, gravitation or whatever), they exchange bosons. Fermions are well-defined individual entities, just like large-scale matter is. But bosons can completely merge and become one entity, more like conscious states do. Zohar claims that bosons are the basis for the conscious life, and fermions for the material life. The properties of matter would arise from the properties of fermions. Matter is solid because fermions cannot merge. On the other hand, the properties of mind would arise from the properties of bosons: they can share the same state and they are about relationships. This would also explain how there can be a "self". The brain changes all the time and therefore the "self" is never the same. I am never myself again. How can there be a "self"? Zohar thinks that the self does change all the time, but quantum interference makes each new self sprout from the old selves. Wave functions of past selves overlap with the wave function of the current self. Through this "quantum memory" each new "quantum self" reincarnates past selves. Conscious observer Drawing from Quantum Mechanics and from Bertrand Russell's idea that consciousness provides a kind of "window" onto the brain, the philosopher Michael Lockwood advanced a theory of consciousness as a process of perception of brain states. First he noted that Special Relativity implies that mental states must be physical states (mental states must be in space given that they are in time). Then Lockwood interpreted the role of the observer in Quantum Mechanics as the role of consciousness in the physical world (as opposed to a simple interference with the system being observed). Lockwood argued that sensations must be intrinsic attributes of physical states of the brain: in quantum lingo, each observable attribute (e.g., each sensation) corresponds to an observable of the brain. Consciousness scans the brain to look for sensations. It does not create them, it just seeks them.
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Chalmers David: THE CONSCIOUS MIND (Oxford University Press, 1996) Culbertson James: THE MINDS OF ROBOTS (University of Illinois Press, 1963) Culbertson James: SENSATIONS MEMORIES AND THE FLOW OF TIME (Cromwell Press, 1976) Eccles John: EVOLUTION OF THE BRAIN (Routledge, 1989) http://www.thymos.com/tat/consc3.html (5 of 6)25/07/2003 14:24:28
Thinking About Thought: Consciousness, Life and Meaning
Eccles John: THE SELF AND ITS BRAIN (Springer, 1994) Globus Gordon: THE POSTMODERN BRAIN (John Benjamins, 1995) Herbert Nick: ELEMENTAL MIND (Dutton, 1993) Lockwood Michael: MIND, BRAIN AND THE QUANTUM (Basil Blackwell, 1989) Marshall I.N., Zohar Danah: QUANTUM SOCIETY (William Morrow, 1994) Nagel Thomas: MORTAL QUESTIONS (Cambridge Univ Press, 1979) Penrose Roger: THE EMPEROR'S NEW MIND (Oxford Univ Press, 1989) Penrose Roger: SHADOWS OF THE MIND (Oxford University Press, 1994) Pribram Karl: LANGUAGES OF THE BRAIN (Prentice Hall, 1971) Pribram Karl: BRAIN AND PERCEPTION (Lawrence Erlbaum, 1990) Searle John: THE REDISCOVERY OF THE MIND (MIT Press, 1992) Stapp Henry: MIND, MATTER AND QUANTUM MECHANICS (Springer-Verlag, 1993) Whitehead Alfred: MODES OF THOUGHT (Macmillan, 1938) Wolf, Fred Alan: MIND INTO MATTER (Moment Point, 2001) Yasue Kunio & Jibu Mari: QUANTUM BRAIN DYNAMICS AND CONSCIOUSNESS (John Benjamins, 1995) Zohar Danah: QUANTUM SELF (William Morrow, 1990)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind The Self and Free Will: Do We Think Or Are We Thought? (Ornstein, Gazzaniga, Dennett, Parfit, Lazarus, Parfit, Carlson, Bernard)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Self Consciousness is more than just being aware of being: it comes with a strong notion: the distinction between self and non-self. I know that I am myself, but I also know that I am not anybody else, and that nobody else is me. I know that I am myself, and I know that I was myself yesterday and the day before and the year before and forty years ago. Consciousness carries a sense of identity, of me being me The development of the self, Richard Lazarus holds, is a fundamental event for the emotional life. Emotions depend on an organizing principle in which the self is distinguished from the non-self: only after that principle has become established can evaluations of benefits and harms be performed. Differentiation of self and other is a fundamental property of living organisms (even plants use protein discrimination mechanisms, and most organisms could not survive without the ability to distinguish alien organisms). The self is not even a simple concept. The biologist Ulric Neisser, one of the father founders of Ecological Realism, identified five kinds of self-knowledge: the ecological self (situated in the environment), the "interpersonal self" (situated in the society of selves), both based on perception, the private self, the conceptual self and the narrative (or "remembered") self. The American philosopher Thomas Nagel noted that consciousness cannot be "counted": schizophrenic patients have neither one nor two consciousnesses. It appears that brain hemispheres cannot compete, even when they have been separated: they have been programmed to work in tandem. Robert Ornstein is not alone in believing that identity is an illusion. In his opinion, to start with, consciousness and the mind are two distinct entities. Different regions of the mind behave independently of consciousness, as proved by the fact that sometimes consciousness realizes what has been decided after it
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Thinking About Thought: Consciousness, Life and Meaning
has already happened. The self is only a part of the mind, and not always connected with the rest of it. The self shares the mind with other minds. Minds take hold of consciousness depending on the needs of the moment. Each mind tends to run the organism for as long as possible. The self only occasionally notices what is going on. Continuity of the mind is an illusion: we are not the same person all the time. Different selves within the brain fight for control over the next action. Michael Gazzaniga believes that the self is only an "interpreter" of the conclusions that the brain processes have reached. Daniel Dennett also has difficulties with the self. In his "multiple draft" theory, consciousness is simply the feeling of the overall brain activity. Whichever draft, whichever "narrative" dominates is my current "I". But the dominant draft could be changing every second. Dennett is opposed to the idea that there is an enduring mind because it would imply that there is a place in the brain where that mind resides. He thinks that such "cartesian theater" is absurd and that the mind is implemented by multiple parallel drafts. The philosopher Derek Parfit believes that the self "is" the brain state. As the brain state changes all the time, the self cannot be the same, there cannot be a permanent "self". "I" do not exist. What exists is a brain state that right now is "me". The next brain state will also be a self, distinct from the previous one. There is a chain of successive selves, each somehow linked through memory to the previous one. Each self is distinct from the previous ones and future ones. The "I" is a mere illusion. There is no person that all those selves share. Derek Parfit believes in a Buddhist-like set of potential consciousnesses, each with its own flow of feelings, although at each time the one which dominates gives me the illusion of having only one consciousness and one identity. The grounded self The existence of a unitary and continuous self is emphatically claimed by the American psychologist Richard Carlson. He believes that the self is a biological feature. Following William James and Ulrich Neisser, Carlson thinks that every act of perception specifies both a perceiving self and a perceived object. Seeing something is not only seeing that object: it is also seeing it from a certain perspective. The perspective implies a "seer". There is no act of perception of an object without a subject. The subject is as much part of perception as the object. This co-specification of self and object is useful for adding the "first person" to the information-processing paradigm of mental processes, which cannot traditionally deal with the self. Carlson's fundamental move is to distinguish between the content and the object of a mental state: content and object are not the same thing, because the content includes both the object and the subject. The "mode" of content specifies the self, the "aboutness" of content specifies the object (the environment). Following John Searle's analysis of speech acts language, Carlson further distinguishes between the content of a mental state and the "noncontent" of that mental state. The "noncontent" includes the purpose of the mental state (for example, the degree of commitment), and even its "implementation" properties (for http://www.thymos.com/tat/self.html (2 of 10)25/07/2003 14:24:48
Thinking About Thought: Consciousness, Life and Meaning
example, the duration of the state, etc). A mental state has content and noncontent, and noncontent is as important as content. This analysis serves to elucidate that there is more than just an object in an act of perception. There is more than just a scene in a visual perception: there is a subject that is seeing, there is a purpose of seeing (for example, "I am spying" versus "I am gazing") and there is a duration. Following James Gibson, Carlson thinks that mental representations must have a "performatory" character, must have to do with our body, must be about performing an action in the environment. Most cognitive skills are not conscious, or nonconscious (eg, understanding language). Most cognitive activity is routine. Consciousness is necessary only when learning the skill. After it has been learned, it quickly becomes routine, unconscious routine. Introspection is actually difficult for experts, who often cannot explain why they do what they do. Most of our cognitive activity comes from a specific kind of learning: skill acquisition. Consciousness has to do with acquiring cognitive skills, which in turn depend on experiencing the world. Skill acquisition occurs by restructuring, as in cognitive models such as John Anderson's. Specifically, The function of working memory is to form intentions, goals, purposes. Goals get organized in structures that capture the hierarchical structure of action. The bottom line is that cognition is embodied and situated: it is always about our body and/or our environment. Symbols and the mental processes that operate on them are grounded in sensory-motor activity. There is continuity between symbolic awareness and perceptual-enactive awareness because symbolic representation is performatory: it is useful precisely because it is about action; because symbols are grounded in action. Contrary to Dennett and Gazzaniga, Carlson reaches the conclusion that the continuity of consciousness is not only real, it is an ecological necessity, because the self is cospecified by perception, and perception is driven by changes in the world, and those changes are continuous. Cognition is grounded in one's point of view, and that point of view is grounded in an environment, and this two-fold grounding process is continuous. Identity: who am I? Every year 98% of the atoms of my body are replaced: how can I claim to be still the same person that I was last year, or, worse, ten years ago? What is (where lies) my identity? What is "my" relationship to the metabolism of my body? Derek Parfit once proposed a thought problem: what happens to a person who is destroyed by a scanner in http://www.thymos.com/tat/self.html (3 of 10)25/07/2003 14:24:48
Thinking About Thought: Consciousness, Life and Meaning
London and rebuilt cell by cell in New York by a replicator that has received infinitely detailed information from the scanner about the state of each single cell, including all of the person's memories? Is the person still the same person? Or did the person die in London? What makes a person such a person: bodily or psychological continuity? If a person's matter is replaced cell by cell with equivalent cells is the person still the same person? If a person's psychological state (memory, beliefs, emotions and everything) is replaced with an equivalent psychological state is the person still the same person? The question eventually asks what is "a life": is it a continuum of bodily states, whereby one grows from a child to an adult, or is it a continuum of psychological states? Or both? Or none? The most obvious paradox is: how can reality be still the same as we grow up? Do two completely different brains see the same image when they are presented with the same object? If the brains are different, then the pattern of neural excitement created by seeing that object will be completely different in the two brains. How can two completely different brains yield the same image in the two brains? The logical conclusion is "no, the tree I see is not the tree you see, we just happen to refer to it the same way so it is not important what exactly we see when we look at it". But then how can we see the same image yesterday, today and tomorrow? Our brain changes all the time. Between my brain of when I was five years old and my brain of today there is probably nothing in common: every single cell has changed, connections have changed, the physical shape of the brain has changed. The same object causes a different pattern in my brain today than it did in my brain forty years ago. Those are two different brains, made of different cells, organized in different ways: the two patterns are physically different. Nonetheless, it appears to me that my toys still look the same. But they shouldn't: since my brain changed, and the pattern they generate has changed, what I see today should be a different image than the one I saw as a five-year old. How is it that I see the same thing even if I have a different brain? This thought experiment almost seem to prove that "I" am not in my brain, that there is something external to the brain that does not change over time, that the brain simply performs computations of the image but the ultimate "feeling" of that image is due to a "soul" that is external to the brain and does not depend on cells or connections. On the other hand, it is easy to see that what we see is not really what we think we see. We have to keep in mind that when we recognize something as something, we rarely see/feel/hear/touch again exactly the same thing we already saw/felt/heard/touched before. I recognize somebody's face, but that face cannot possibly be exactly the same image I saw last time: beard may have grown, a pimple may have appeared, hair may have been trimmed, a tan may have darkened the skin, or, quite simply, that face may be at a different angle (looking up, looking down, turned half way). I recognize a song, but the truth is that the same song never "sounds" the same: louder, softer, different speakers, static, different echo in the room, different position of my era with respect to the speakers. I recognize that today the temperaturs is "cold", but if we measured the temperature to the tenth decimal digit it is unlikely that we would get the exact same number that I got the previous time I felt the same cold. What we "recognize" is obviously not a physical quantity: a image, a sound, a temperature never repeat themselves. What is it then that we recognize when we recognize a face, a song or a temperature? Broadly speaking, it is a concept. We build concepts of our sensory experience, we store those concepts for future use, and we matched the
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Thinking About Thought: Consciousness, Life and Meaning
stored concepts with any new concept. When we do this comparison, we try to find similarity and identity. If the two concepts are similar enough, we assume that they are identical, that they are the same thing. If they are not similar enough, but they are more similar than the average, then we can probvably establish that they belong to a common super-concept (they are both faces, but not the same face; they are both songs, but not the same song; and so forth). We have a vast array of concepts which are organized in a hierarchy with many levels of generalization (your face to face of you and siblings to faces of that kind to face to ... to body part to ...). A sensory experience is somehow translated into a concept and that concept is matched with existing concepts and eventually located at some level of a hierarchy of concepts. If it is close enough to an existing concept of that hierarchy at that level, it is recognized as the same concept. Whatever the specific mechanism, it is obvious that what we recognize is not a physical quantity (distribution of colors, sound wave or temperature) but a concept, that somehow we build and compare with previously manufactured concepts. Add to these considerations the fact that experience molds the brain: I am not only my genome, I am also the world around me. And I change all the time according to what is happening in the world. "I am" what the world is doing. Identity is probably a concept. I have built over the years a concept of myself. My physical substance changes all the time, but, as long as it still matches my concept of myself, I still recognize it as myself. The importance of being warm When speculating about consciousness, identity and free will, it is important not to forget what bodies are and how they work. Among the many bizarre features of living organisms, one is often overlooked: each living organism can live only within a very narrow range of temperature. Temperature is one of the most crucial survival factors. Temperature also happens to be an important source of "identity": water and ice are made of the same atoms, it's the temperature that determines whether you are water or you are ice. It's the temperature that determines whether your body is dead or alive, and it's the temperature that determines whether you are lying and shivering in bed or are playing soccer outside. Our identity does change with the temperature of our body (from no identity to "regular" identity to delirious identity). Most of what our body does has nothing to do with writing poems or making scientific discoveries: it is about maintaining a stable temperature. Free Will Is consciousness merely an "observer" of what is going on in the brain (of neural processes), or is consciousness a "creator" as well of neural processes?
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Thinking About Thought: Consciousness, Life and Meaning
Some scientists (and Albert Einstein with them) have argued that consciousness must be fabricated by reality, that what we feel is simply an unavoidable consequence of the state of the universe, that we are simply machines programmed by the rest of the universe. Other scientists believe the opposite, that consciousness fabricates reality, that we have the power to alter the course of the events. They believe in free will. Do we think or are we thought? The question, while popular, is misleading. The question is, in a sense, already an answer: the moment we separate the "I" and the body, we have subscribed to dualism, to the view that spirit and matter are separate and spirit can control matter. A free will grounded in matter is not easy to picture because we tend to believe in an "I" external to our body that controls our body. But, in a materialist scenario, the "I" is supposed to be only the expression of brain processes. If that is the case, then "free will" is not about the "I" making a decision: the "I" will simply reflect that decision. What makes the decision is the brain process. This does not mean that free will can't exist. It just needs to be redefined: can a brain process occur that is not completely caused by other physical processes? In a materialist scenario, free will does not require consciousness: consciousness is an aspect of the brain process that "thinks". The question is whether that brain process has free will. If consciousness is indeed due to a physical process, if consciousness is ultimately material, does this preclude free will? For centuries we have considered free will an exclusive property of the soul, mainly because 1. we deemed the soul to be made of spirit and not matter, and 2. nothing in Physics allows for free will of matter. If we now recognize that consciousness is a property of matter(possibly one that occurs only in some special form and configuration of matter, but nonetheless ultimately matter), the second statement must be examined carefully because the possibility of free will depends on its truth: if motion of matter is controlled only by deterministic laws, then free will is an illusion; if matter has a degree of control over its own motion, then free will is a fact. The question is not whether we have free will, but whether the laws of our universe (i.e., Physics) allow for free will. Purpose Why do living things do what they do?
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Thinking About Thought: Consciousness, Life and Meaning
The purposiveness of living organisms is simply a consequence of evolution by natural selection. Living organisms have a fundamental goal, survival, and have inherited a repertory of behaviors to achieve that goal. But the concept of "survival" can be better qualified as self-regulation. The 19th-century French psychologist Claude Bernard "discovered" the self-regulating nature of living organisms. Bernard realized that each living organism is a system built to maintain a constant internal state in the face of changing external conditions. The regulation of this "mieliu interieur" is life itself, because it is this stable state that gives the organism its independence from the environment, its identity. This is the dividing line that separates animate and inanimate matter: inanimate matter obeys Newton's laws of cause and effect, animate matter tends to maintain its state no matter what external forces are applied. Unlike objects, whose state is changed when a force is applied, the state of a living organism is not changed by an external force. The living organism, as long as it is alive, maintains its state constant. The "purposeful" behavior of a living organism is the reaction to environmental forces: the organism needs to act in order to continuously restore its state. A body seems to "want", "intend", "desire" to maintain its internal state (either by eating, moving, sleeping, etc), a state that, ultimately, is a combination of chemical content and temperature. Living bodies appear to act purposedly, but they are simply reacting to the environment. For Bernard "freedom" is independence from the environment. Control of the internal state allows a living organism to live in many different environments. The living organism is "free" in that is not a slave of its environment. Bernard's idea of self-regulation extended to all living organisms. Humans are not the only ones to have "goals". Animate behavior "is" control of perception. Will, not necessarily free: a materialistic view of free will The problem with free will is that it does not fit too well with the scientific theories of the universe that have been developing over the last three centuries. While those theories are fairly accurate in predicting all the natural phenomena we deal with, they don't leave much room for free will. Particles behave the way they behave because of the fundamental laws of nature and because of what the other particles are doing; not because they can decide what to do. Since we are, ultimately, collections of particles, free will is an embarassment of Physics. On the other hand, a simple look at the behavior of even a fly seems to prove that free will is indeed a fact and is pervasive. Free will is a fundamental attribute of life. A robot that moved but only repeating a mechanical sequence of steps would not be considered "alive". Life has very much to do with unpredictability of behavior, not just with behavior. Or, better, behavior is behavior inasmuch as it is unpredictable to a degree; otherwise it is simply "motion". Whether it is indeed "free" or not, "will" (the apparent ability of an ant to decide in which direction to move) appears to be an inherent feature of life, no matter how primitive life is. A theory of life that does not predict free will is not a good theory of life. Somehow, "free" will must be a product of the chemistry http://www.thymos.com/tat/self.html (7 of 10)25/07/2003 14:24:48
Thinking About Thought: Consciousness, Life and Meaning
of life, at some very elementary level. In other words, obtaining the right chemical mix in the laboratory would not be enough: that mix must also exhibit the symptoms of free will. The origin of free will, therefore, appears to be life itself. Free will and randomness Free will is often associated to randomness: a being has free will if it can perform "random" actions, as opposed to actions rigidly determined by the universal clockwork. In other words, free will can exist only if the laws of nature allow for some random solutions, solutions that can be arbitrarily chosen by our consciousness. If no randomness exists in nature, then every action (including our very conscious thoughts) is predetermined by a formula and free will cannot exist. In their quest for the source of randomness in human free will, both neurophysiologists like John Eccles and physicists like Roger Penrose have proposed that quantum effects are responsible for creating randomness in the processes of the human brain. Whether chance and free will can be equated (free will is supposed to lead to rational and deterministic decisions, not random ones) and whether Quantum Theory is the only possible source of randomness is debatable. Since we know that a lot of what goes on in the universe is indeed regulated by strict formulas, the hope for free will should rely not so much in randomness as in "fuzzyness". It is unlikely that the laws of nature hide a competely random property; on the other hand, they could be "fuzzy", in that they may prescribe a behavior but with a broad range of possible degrees. Free will and Physics Whether we exercise it or not we do have free will: at every point in time we can choose what to do next. Do animals also have free will? Or are they mechanisms, machines, that move according to formulas? There is no evidence that at any point in time one can predict the next move of a chicken or an ant. No matter how simple and unconscious animals seem to be, their behavior is still largely unpredictable. You can guess what the chicken will want to do, but you can never be sure, and you can never guess the exact movements. There are infinite paths an ant can follow to go back to the nest and the one it will follow cannot be predicted. At every point of that path the ant can choose where to do next. Two ants will follow two different paths. Each ant seems to have its own personality. Even the movement of mono-cellular organisms is unpredictable to some extent. No matter how small and simple the organism, a degree of free will seems to be there. Free will seems to be a property of life. What triggers the next move of bacteria, ants and chicken is not just a Newtonian formula. If they are machines, then these machines do not obey classical Physics. There is a degree of freedom that every living organism seems to enjoy. And it doesn't require a sophisticated brain. There is a degree of freedom that just shouldn't be there, if Newton was right.
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Thinking About Thought: Consciousness, Life and Meaning
If these are machines, they are machines that cannot be explained with our Mechanics because at every point in time there are many possible time evolutions and all seem to be possible, and none can be exactly predicted, pretty much like a quantum wave. There is something missing in our Mechanics to account for free will of the machine. Free will and choice As usual, some misconception may arise from vague definitions. Is free will the consciousness of making one action out of so many possible ones, or is free will the ability to select one action out of so many possible ones? Why do we claim that a machine has no free will? Usually, because a machine can solve only the problems that we program it to solve. We, on the other hand, can solve novel problems in unpredictable situations (or, at least, give them a try). And that's because we can make actions that we have never done before and that nobody ever told us to do, whereas a machine can only do what it has been programmed to do. This narrower definition of free will is interesting because it actually refers to the "architecture" and not really to the awareness or any other special property of human minds. Machines are built to solve specific problems in specific situations, simply because that is what humans are good at: building machines that solve specific problems in specific situations: we humans like to "design" a machine, to write the "specifications", etc. This is not the way nature built us. Nature built us on a different principle and it is no surprise that we behave differently. Since in nature we never know what the next problem and situation will be like, nature built us a "Darwinian" machines: our brains generate all the time a lot of possible actions and then pursue the ones that are "selected" by the environment (the specific problem and situation). Nature built us on a different principle than the one we use to build machines. The main difference between our mind and a machine is their archectures. The lack of free will in machines is not a limit of machines: it is a limit of our mind. If we built a machine the same way nature builds its cognitive beings, i.e. with the same type of architecture, it would be a rather different machine, capable of generating a huge amount of random behaviors and then picking the one that best matches the current problem and situation. One can even envision a day when machines built with a "Darwinian" architecture (descendants of today's genetic algorithms and neural networks) will "out-free will" us, will exhibit even more free will than we do. After all, most of the times we simply obey orders (we obey publicity when we shop, we obey record labels when we sing a tune, we obey our mother's education all day long), whereas a machine would have no conditioning. And it may be able to generate a lot more alternatives than our brain does. Free will is simply a folk nome for the Darwinian architecture of our mind. The substance of our brain may not be the reason that we have free will and machines do not. It may be possible to build machines that also exhibit free will, even if they are built out of electronic components. Do we think or are we thought? Further Reading http://www.thymos.com/tat/self.html (9 of 10)25/07/2003 14:24:48
Thinking About Thought: Consciousness, Life and Meaning
Carlson Richard: EXPERIENCED COGNITION (Lawrence Erlbaum, 1997) Cziko Gary: THE THINGS WE DO (MIT Press, 2000) Dennett Daniel: KINDS OF MINDS (Basic, 1998) Lazarus Richard: EMOTION AND ADAPTATION (Oxford Univ Press, 1991) Ornstein Robert: MULTIMIND (Houghton Mifflin, 1986) Parfit Derek: REASONS AND PERSONS (Oxford Univ Press, 1985)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Memories (Conscious and Unconscious) (Bartlett, Broadbent, Tulving, Damasio, Lenneberg, Wittgenstein, Rosch, Lakoff, Fauconnier, Keil, Piaget, Karmiloff-Smith, Hughlings Jackson, Hobson, Jouvet, Winson, Snyder)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Memories are Made of This The mind’s cognitive faculties depend to a great extent on memory. The mind would not truly be a mind if we couldn’t learn and remember at all. Memory is more than storage. Memory is also recognition. We are capable of recognizing a tree as a tree even if we have never seen that specific tree before. Not two trees are alike. And even a specific tree never appears the same to us, as the perspective, the wind, the lighting can all dramatically change its appearance. In order to recognize a tree as a tree, and as a specific tree, we use our "memory". Whenever we see something, we ransack our memory looking for "similar" information. Without memory we would not see trees, but only patches of green. The process of thinking depends on the process of categorizing: the mind deals with concepts, and concepts exist because memory is capable of organizing experience into concepts. The mind looks like, ultimately, as a processor of concepts. The mind's functioning is driven by memory, which is capable of organizing knowledge into concepts. So much so that, inevitably, a theory of memory becomes a theory of concepts, and a theory of concepts becomes a theory of thought. Cognition revolves around memory. All cognitive faculties use memory and would not be possible without memory. They are, in fact, but side effects of the process of remembering. There is a fundamental unity of cognition, organized around the ability to categorize, to create concepts out of experience. Memory's task is easily summarized: to remember past experience. But, unlike the memory of a computer, which can remember exactly its past experience, human memory never remembers exactly.
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Thinking About Thought: Consciousness, Life and Meaning
The most peculiar feature of how memory is, perhaps, the fact that it is so bad at remembering. Our memory does not only forget most of the things that happen, but, even when it remembers, it does a lousy job of remembering. Memory of something is almost always approximate. Many details are forgotten right away. If we want to remember a poem by heart, we have to repeat it to ourselves countless times. And sometimes memory is also very slow: sometimes it takes a long time to retrieve a detail of a scene, sometimes it will take days before the name of a person comes back to mind. Rather than accessing memories by calendar day or person's name, we seem to access them by associations, which is a much more complicated way to navigate in the past. It is hard to think of something without thinking also of something else. It is hard to focus on a concept and not think of related concepts. And the related concepts that come to mind when we focus on a concept are usually things we care about, not abstract ideas. If we focus on "tree", we may also remember a particular hike in the mountains or an event that occurred on/by a tree. We build categories, we relate categories among them, we associate specific episodes with categories. For an entity that was supposed to be just a storage, anomalies abound. For example, we cannot count very easily. Do you know how your home looks like? Of course. How many windows does it have? You have looked at your home thousands of times, but you cannot say for sure how many windows it has. If you see a flock of birds in the sky, you can tell the shape, the direction, the approximate speed... but not how many birds are in the flock, even if there are only six or seven. Another weird feature of our memory is that it is not very good at remembering the temporal order of events: we have trouble remembering if something occurred before or after something else. On the other hand, our memory is good at ordering objects in space and at counting events in time. Human memory is a bizarre device that differs in a fundamental way from the memory of machines: a camera or a computer can replicate a scene in every minute detail; our memory was just not designed to do that. What was our memory designed to do? The Reconstructive Memory A startling feature of our memory is that it does not remember things the way we perceived them. Something happens between the time we see or hear a scene and the time that scene gets stored in memory. I can tell you the plot of a novel even if I can't tell you a single sentence that was in the novel. If I tell you the plot twice, I will use different words. It would be almost impossible to use the same words. Nobody can remember all the sentences of a book, but everybody can remember what the "story" is. Compare with a computer. A computer can memorize the book page by page, word by word. Our memory does not memorize that way. It is not capable of memorizing a book page by page, word by word. On the other hand, it is capable of so many other things that a computer is not capable of. For example, we can http://www.thymos.com/tat/memory.html (2 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
recognize a plot, told by somebody else, as the plot of the same novel. That person's version of the plot and our version of the plot probably do not share a single sentence. Nonetheless, we can recognize that they are the same story. No computer can do that, no matter how big its memory is. Size is obviously not the solution. In the 1930's, the British psychologist Frederic Bartlett developed one of the earliest models of memory. Bartlett studied how memory "reconstructs" the essence of a scene. We can easily relate the plot of a movie, and even discuss the main characters, analyze the cinematography, and so forth, but we cannot cite verbatim a single line of the movie. We stored enough information about the movie that we can tell what it was about and perform all sorts of reasoning about it, but we cannot simply quote what a character said at one point or another. What Bartlett discovered is that events are not stored faithfully in memory: they are somehow summarized into a different form, a "schema". Individuals do not passively record stories verbatim, but rather actively code them in terms of schemas, and then can recount the stories by retranslating the schemas into words. Each new memory is categorized in a schema which depends on the already existing schemas. In practice, only what is strictly necessary is added. When a memory must be retrieved, the corresponding schema provides the instructions to reconstruct it. That is the reason why recognizing an object is much easier in its typical context than in an unusual context. The advantage of the "reconstructive" memory is that it can fit a lot of information in a relatively narrow space. Any memory that tried to store all the scenes, text and sound of a movie would require an immense amount of space. But our memory stores only what is indispensable for reconstructing the plot and other essential features of the movie, thereby losing lots of details but at the same time saving a lot of space. Reconstructing And Making Sense The mechanism of "reconstructing" the memory of an event is still largely a mystery. There is more involved than a simple "retrieval" of encoded information. The fact that memory is not a linear recording of sensory input reveales that something helps memory make sense of the past. When memory reconstructs an event, it must have a way to do so in a "meaningful" way. The memory of an event is not just a disordered set of memories more or less related to that event, it is one flowing sequence of memories which follow one from the other. Sometimes you can't finish relating the plot of a novel because you "forgot" a key part of it: the truth is that you forgot all of it and you are reconstructing it, and while reconstructing it you realized that something must be missing. You can't reconstruct reality because you have an inner sense of what reality must be like. You may know how the novel ends and how it goes up to a point, and then you realize that something is necessary in order to join that point to the ending. Your reconstructive memory knows that something is missing in the reconstruction because the reconstruction does not yet "make sense". The fascination of movies or novels is that you have to put together reality until it makes sense again, you have to find the missing elements so that the story gets "explained". Our brain has a sense of what makes http://www.thymos.com/tat/memory.html (3 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
sense and what does not. The Partitioning of Memory The works of Miller (1956), Broadbent (1957), Newell (1958) and Chomsky (1957), that all came out in the second half of the 1950s, established a new paradigm in Psychology, broadly referred to as "cognitivism", which was de facto a precursor to cognitive science and ended the supremacy of behaviorism. Where behaviorism was only interested in the relationship between input (stimuli) and output (behavior), cognitivism focused on the processing that occurs between the input and the output Herbert Simon and Alan Newell argued that the human mind is a symbolic processor and Noam Chomsky advanced a theory of language based on modules inside the mind which are capable of symbolic processing. The standard model that became popular in the late 1950's, due particularly to the work of the British psychologist Donald Broadbent (the father founder of cognitive Psychology) and the American psychologist George Miller, was based on the existence of two types of memory: a "short-term memory", limited to few pieces of information, capable of retrieving them very quickly and subject to decaying also very quickly; and a "long-term memory", capable of large storage and much slower in both retrieving and decaying. Items of the short-term memory move to the long-term memory after they have been "rehearsed" long enough. The idea was already implicit in William James’ writings, but Broadbent also hypothesized that short-term memory may be just a set of pointers to blocks of information located in the long-term memory. Broadbent also stated the principle of "limited capacity" to explain how the brain can focus on one specific object out of the thousands perceived by the retina at the same time. The selective character of attention is due to the limited capacity of processing by the brain. In other words, the brain can only be conscious of so many events at the same time. What actually gets the attention is complicated to establish, because Broadbent found out that attention originates from a multitude of attentional functions in different subsystems of the brain. Broadbent's model of memory (also known as the "filter theory") reflected at least two well-known features of memory: information about stimuli is temporarily retained but it will fade unless attention is turned quickly to it; the unattended information is "filtered out" without being analyzed. He drew a distinction between a sensory store of virtually unlimited capacity and a categorical short-term store of limited capacity. This is the way that a limited-capacity system such as human memory can cope with the overwhelming amount of information available in the world. At the same time, George Miller’s experiments proved that the short-term memory can hold only up to seven "chunks" of information and therefore provided an order of magnitude for it. It wasn’t clear, though, the "size" of a chunk: is the entire car a chunk of information, or is each wheel a chunk, or...? In Broadbent’s model, a chunk is a pointer to something that already exists. Therefore a chunk can be even very "big", as long as it is already in memory. Its "size" is not important (in short-term memory, it is only a http://www.thymos.com/tat/memory.html (4 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
pointer). This is consistent with experiments in which short-term memory proves to be capable of holding familiar images, but not of images never seen before. The British psychologist Alan Baddeley showed that a unitary short-term memory does not account for memory disorders and replaced short-term memory with a "working memory" that has basically three components: a short-term memory for verbal information, a short-term memory for visual information, and a control system. Today, it appears that neurons in the prefrontal cortex (the newest part of the brain, from an evolutionary standpoint) can draw data from other regions of the brain and hold them for as long as needed. The prefrontal cortex is unique in having a huge number of connections with the sensory system and with lower brain centers. The prefrontal cortex could be the locus of a "working memory", in which decisions, planning and behavior take place. Types of Memory Experiments conducted in the 1970s by the Canadian psychologist Endel Tulving and his associate Daniel Schacter proved that "intension" (such as concepts) and "extension" (such as episodes) are dealt with by two different types of memory: episodic memory contains specific episodes of the history of the individual, while semantic memory contains general knowledge (both concepts and facts) applicable to different situations. Episodic memory, which receives and stores information about temporally-dated episodes and spacetemporal relations among them, is a faithful record of a person's experience. Semantic memory, instead, is organized knowledge about the world. Tulving believes these memory systems are physically distinct because they behavior is significantly different. In episodic memory, for example, the recall of a piece of information depends on the conditions ("cues") under which that piece of information has been learned (an explicit or implicit reference to it). There are at least two more aspects of memory that fall neither into the intensions or extensions. Procedural memory allows us to learn new skills and acquire habits. Implicit memory is "unconscious" memory, memory without awareness: unlike other types of memories, retrieval cues do not bring about a recollection of them. Implicit memories are weakly encoded memories which can nonetheless affect conscious thought and behavior. Implicit memories are not lost: they just cannot be retrieved. Amnesia is the standard condition of human memory: most of what happens is not recorded in a form that can be retrieved. In the first years, because of incompletely developed brain structures, most memories are lost or warped. Nonetheless, memories of childhood are preserved without awareness of remembering. Implicit memory is the one activated in "priming" events, or in the identification of words and objects. That makes a grand total of four different types of memory: procedural, semantic, episodic and implicit. Tulving also devised a scheme by which memory can associate a new perception or thought to an old memory: the remembering of events always depends on the interaction between encoding and retrieval http://www.thymos.com/tat/memory.html (5 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
conditions (or compatibility between the "engram" and the "cue"). Things are more complicated than Broadbent’s generation thought, but the standard model is still a good approximation of what we know. Categories Arguably the most important function of memory is categorization. The rings of a tree or the scratches on a stone can be said to "remember" the past, but human memory can do more: it is capable of using the literal past to build abstractions that are useful to predict the future. It is able to build generalizations. Actually, categorization is the main way that humans make sense of their world. For example, if we analyze the grammar of our language, the basic mechanisms of meaning-bearing are processes of categorization. One can even wonder whether all living beings, or at least many of them, need to do some level of categorization in order to deal with the world. Eric Lenneberg has argued that all animals organize the sensory world through a process of categorization. They exhibit propensities for responding to categories of stimuli, not to single specific stimuli. In humans this process of categorization becomes "naming", the ability to assign a name to a category. But even in humans the process of categorization is still a process whose function is to enable "similar" response to "different" stimuli. Traditionally, categories were conceived as being closed by clear boundaries and defined by common properties of their members. The psychologist Jerome Bruner was influential in conceiving categories as sets of features: a category is defined by the set of features that are individually necessary and jointly sufficient for an object to belong to it. In order words, one can write down the rules that specify what is necessary and sufficient for a member to belong to a category. This seems to be the case for nominal types (the one invented by us, such as "mother" or "triangle"), but not for natural types. As the great Austrian philosopher Ludwig Wittgenstein pointed out (in 1953), a category like "game" does not fit the classical idea (both cards and chess and football are sports, but they have very little in common). A dog that does not bark or a dog with three legs or a vegetarian dog would probably still be considered a dog, even if it violates the set of features we usually associate with the concept of a dog. What unites a category is "family resemblance", plus sets of positive and negative examples. Its boundaries are not important: they can be extended at any time. Prototype Theory The traditional view that categories are defined by common properties of their members was quickly replaced by Rosch's theory of prototypes. As we all know, the best way to teach a concept is to show an example of it. Eleanor Rosch noted that some members of a category seem to be better examples of the category than others. Not all members are alike, even if they share all the same features of the category. This implies that http://www.thymos.com/tat/memory.html (6 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
the features by themselves are not enough to determine the category. It also implies that there may be a "best" example of the category, what she called the "prototype" of the category. In the 1970s, she founded her early theory on two basic principles of categorization: 1. the task of category systems is to provide maximum information with the least cognitive effort; and 2. the perceived world comes as structured information. In other words, we do categorization because it helps save a lot of space in memory and because the world lends itself to categorization. Concepts promote a cognitive economy by partitioning the world into classes, and therefore allow the mind to substantially reduce the amount of information to be remembered and processed. In Rosch's theory of prototypes, a concept is represented through a prototype which expresses its most significant properties. Membership of an individual in a category is then determined by the perceived distance of resemblance of the individual to the prototype of the category. Next, Rosch unified a number of experimental findings and proposed that thought in general is organized around a privileged level of categorization. In the 1950s, the psychologist Roger Brown had noted that children tend to learn concepts at a level which is not the most general and not the most specific (say, "chair", rather than "furniture" or "armchair"); and, in the 1960s, the anthropologist Brent Berlin, in his studies on colors and on plants and animals naming, had reached a similar conclusion that applies on categories used by adults. The point was that we can name objects in many different ways: a cat is also a feline, a mammal, an animal, and it is also a specific variety of cat, but we normally call it "a cat". The level at which we "naturally" name objects is the level of what Brown termed "distinctive action". The actions we perform on flowers are pretty much all the same, and certainly different from the actions that we perform on a cat (e.g., one we smell and one we pat). But the actions we perform on two different varieties of cats or two different types of flowers are the same (we pat both the same way, we smell both the same way). Our actions tell us that a cat is a cat and a flower is a flower, but they can’t tell us that a rose is not a lily. "Cat" and "flower" represent a "natural" level of categorization. Berlin had found that people categorize plants at the same "basic level" anywhere in the world (which roughly corresponds to the genus in biology). It is a level at which only shape, substance and pattern of change are involved, while no technical details are required. Rosch extended his ideas to artifacts and she found that we also classify artifacts at a "basic level" where technical details are not essential. We first create categories of "chair" and "car", and only later we specialize and generalize those categories (to "armchair", "furniture", "sport car", etc). At the basic level we can form a mental image of the category. We can form a mental image of "chair", but not of "furniture". We can form a mental image of "car", but not of "vehicle". We have a motor program for interacting with "chair", but not with "furniture". We have a motor program for interacting with "car", but not with "vehicle". Categorization initially occurs based on our interaction with the object. Meaning is in the interaction between the body and the world. Rosch postulated a level of abstraction at which the most basic category cuts are made (i.e., where "cue validity" is maximized), which she called the "basic" level. Categories are not merely organized in a hierarchy, from more specific to more general. There is one level of the hierarchy that is somewhat
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Thinking About Thought: Consciousness, Life and Meaning
privileged when it comes to perception of form, movement of body parts, organization of knowledge, etc. "Chair" and "car" are examples of basic categories. We can form a mental picture of them. We have a motor program for dealing with them. They are the first ones learned by children. The category of "furniture", for example, is different: I cannot visualize it, I do not have a motor program to deal with it, and it takes some time for a child to learn it. Generalization tends to proceed upwards from this level, and specialization proceeds downward from this level. Superordinate categories are more abstract and more comprehensive. Subordinate categories are less abstract and less comprehensive. The most fundamental perception and description of the world occurs at the level of basic (or natural) categories. Rosch also realized that categories occur in systems, not alone, and they depend on the existence of contrasting categories within the same system. Each contrasting category limits a category (e.g., if a category for birds did not exist, the category for mammals would probably be bigger). At the basic level, categories are maximally distinct, i.e. they maximize perceived similarity among category members and minimize perceived similarities across contrasting categories. Technically, one can use the notion of "cue validity": the conditional probability that an object falls in a particular category given a specific feature. Category cue validity is the sum of all the individual cue validities of the features associated with a category. The highest cue validity occurs at the basic level. The lowest cue validities occur for superordinate categories. This model of categorization, albeit extremely popular for a while, turned out to be another gross approximation. But the basic model remains a reference point for most researchers: categories are organized in a taxonomic hierarchy, categories in the middle are the most basic, and knowledge is mainly organized at the basic level. Fuzzy Concepts Later, Rosch recognized that categories are not mutually exclusive (an object can belong to more than one category to different degrees), i.e. that they are fundamentally ambigous. This led to the use of fuzzy logic in studying categorization. For example, the American linguist George Lakoff borrowed ideas from Wittgenstein's familyresemblance theory, Rosch's prototype theory and Lotfi Zadeh's theory of fuzzy quantities for his theory of "cognitive models". Lakoff started off by demolishing the traditional view of categories: that categories are defined by common features of their members; that thought is the disembodied manipulation of abstract symbols; that concepts are internal representations of external reality; that symbols have meaning by virtue of their correspondence to real objects. Through a number of experiments, Lakoff first proved that categories depend on two more factors: the bodily experience of the categorizer and what Lakoff calls the "imaginative processes" (metaphor, metonymy, mental imagery) of the categorizer. http://www.thymos.com/tat/memory.html (8 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
Lakoff's theory is based on the assumption of "embodiment of mind": there is no green in the world, green has to do with the relationship between my body (my eye, my retina, my brain) and the world. Meaning cannot be in the world, because things are not in the world, they are in the relationship between us and the world. His close associate, the American philosopher Mark Johnson, had shown that experience is structured in a meaningful way prior to any concepts: some schemas are inherently meaningful to people by virtue of their bodily experience (e.g., the "container" schema, the "part-whole" schema, the "link" schema, the "centerperiphery" schema). We "know" these schemas even before we acquire the related concepts because such "kinesthetic" schemas come with a basic logic that is used to directly "understand" them. Thus Lakoff argued that thought makes use of symbolic structures which are meaningful to begin with (they are directly understood in terms of our physical experience): "basic-level" concepts (which are meaningful because they reflect our sensorimotor life) and kinesthetic image schemas (which are meaningful because they reflect our spatial life). Other meaningful symbolic structures are built up from these elementary ones through imaginative processes such as metaphor. As a corollary, everything we use in language, even the smallest unit, has meaning. And it has meaning not because it refers to something, but because it is either related to our bodily experience or because it is built on top of other meaning-bearing elements. Thought is embodiment of concepts via direct and indirect experience. Concepts grow out of bodily experience and are understood in terms of it. The core of our conceptual system is directly grounded in bodily experience. This explains why Rosch’s basic level is what it is: the one that reflects our bodily nature. Meaning is based on experience. With Putnam, "meaning is not in the mind". But, at the same time, thought is imaginative: those concepts that are not directly grounded in bodily experience are created by imaginative processes such as metaphor. In summary, knowledge is organized into categories by what Lakoff calls "idealized cognitive models". Each model employs four kinds of categorizing processes: propositional (which specifies elements, their properties and relations among them in a manner similar to frames); image-schematic (which specifies spatial images in a manner similar to Ronald Langacker’s image schemas); metaphoric (which maps a propositional or image-schematic model in one domain to a model in another domain); and metonymic (which maps an element of a model to another element of the same model). Some models are classical (in that they yield categories that have rigid boundaries and are defined by necessary and sufficient conditions), some models are scalar (they yield categories whose members have only degrees of membership). All models are embodied, i.e. they are linked with bodily experience. Models build what the French linguist Gilles Fauconnier calls "mental spaces", interconnected domains that consist of elements, roles, strategies and relations between them. Mental spaces allow for alternative views of the world. The mind needs to create multiple cognitive spaces in order to engage in creative thought. Lakoff argues that the conceptual system of a mind, far from being one gigantic theory of the world, is http://www.thymos.com/tat/memory.html (9 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
normally not consistent. In the late 1970s, it became apparent that we have available in our minds many different ways of making sense of situations. We constantly keep alternative conceptualizations of the world. The Origin of Categories The German philosopher Immanuel Kant held the strong belief that experience is possible only if we have knowledge, and knowledge evolves from concepts. Some concepts must therefore be native. We must be born with an infrastructure that allows us to learn concepts and to build concepts on top of concepts. Chomsky proved something similar for language: that human brains are designed to acquire a language, that they contain a "universal grammar" ready to adopt the specific grammar of whatever language we are exposed to. We speak because our brain is meant to speak. Kant, in a sense, stated the same principle for thinking in general: we think in concepts because we are meant to think in concepts. Our mind creates categories because it is equipped with some native categories and a mechanism to build categories on top of existing categories. Just like Chomsky said that grammar is innate and universal, so one can claim that some concepts are innate and universal. Conceptual Holism Inspired by Willard Quine's holism, Frank Keil argues that concepts are always related to other concepts. No concept can be understood in isolation from all other concepts. Concepts are not simple sets of features. Concepts embody "systematic sets of causal beliefs" about the world and contain implicit explanations about the world. Concepts are embedded in theories about the world, and they can only be understood in the context of such theories. In particular, natural kinds (such as "gold") are not defined by a set of features or by a prototype: they derive their concept from the causal structure that underlies them and explains their superficial features. They are defined by a "causal homeostatic system", which tends to stability over time in order to maximize categorizing. Nominal kinds (e.g., "odd numbers") and artifacts (e.g., "cars") are similarly defined by the theories they are embedded in, although such theories are qualitatively different. There is a continuum between pure nominal kinds and pure natural kinds with increasing well-definedness as we move towards natural kinds. What develops over time is the awareness of the network of causal relations and mechanisms that are responsible for the essential properties of a natural kind. The theory explaining a natural kind gets refined over the years. The Mind’s Growth The fundamental feature of the mind is that it is not always the same. Just like every other organ in the http://www.thymos.com/tat/memory.html (10 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
body, it undergoes growth. It is not only a matter of memory getting "bigger": the "quality" of the thought system changes in a significant way. What we are capable of doing with our minds changes dramatically during the growth of the mind from childhood to adulthood. It is more than just learning about the environment: the mind literally "grows" into something else, capable of new types of actions. The brain, as well as the rest of the body, undergoes a massive change in shape and volume. Somehow, in the brain's case, this also results in significant new skills. The debate between "nature" and "nurture" (between "nativism" and "constructivism") has never reached conclusive evidence one way or the other, but Sigmund Freud's greatest intuition may turn out to be that humans are born with instinct and then experience shapes the mind, i.e. nature and nurture coexist and interact. Constructivism In the 1930s the Swiss psychologist Jean Piaget provided an important framework to study the growth of mind. The biological context of his ideas is that living beings are in constant interaction with their environment, and survival depends on maintaining a state of equilibrium between the organism and the environment. The organism has to regulate its own behavior in order to continuously adapt to the information flow from the environment. At the same time the behavior of the organism shapes the environment, and, of course, the aim of the organism is to shape the environment so as to maximize the chances of maintaining the vital equilibrium. Cognition, therefore, is but self-regulation (or self-organization). A dynamic exchange between organism and environment is also the basis of his theory of knowledge, which he labeled "genetic epistemology". The cognitive process, the self-regulation, consists in a loop of assimilation and accomodation. This process occurs in stages. The development of children's intellect proceeds from simple mental arrangements to progressively more complex ones not by gradual evolution but by sudden rearrangements of mental operations that produce qualitatively new forms of thought. Cognitive faculties are not fixed at birth but evolve during the lifetime of the individual. First a child lives a "literal", sensorymotor life, in which knowledge of the world is only due to her actions in it. Slowly, the mind creates "schemas" of behavior in the world. Autonomous, self-regulated functioning of "schemas" lead to interiorized action. The child begins to deal with internal symbols and introspection. Then the child learns to perform internal manipulations on symbols that represent real objects, i.e. internal action on top of external action. Finally, the mental life extends to abstract objects, besides real objects. This four-step transition leads from a stage in which the dominant factor is perception, which is irreversible, to a stage in which the dominant is thought, which is reversible. Language appears between the sensorymotor and the symbolic stages, and is but one of the particular elements of symbolic thought. http://www.thymos.com/tat/memory.html (11 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
On the contrary of Jerry Fodor's innate "language of thought", symbolic representation is constructed during child development. The mind’s growth is due to the need to maintain a balance between the mind and its knowledge of the world. Rationality is the overall way in which an organism adapts to its environment. Rationality occurs when the organism needs to solve a problem, i.e. when the organism needs to reach a new form of balance with its environment. Once that balance has been achieved, the organism proceeds by instinct. Rationality will be needed only when the equilibrium is broken again. In conclusion, Piaget does not recognize any innate knowledge: only a set of sensory reflexes and three processes (assimilation, accomodation and equilibration). These processes are very general, not specific to any domain (the same processes are supposed to operate on development of language, reasoning, physics, etc). The child is a purely sensorymotor device. Piaget's stance is almost behavioristic, except that he grants the child an inner growth. Some nativism Modern studies severely undermine Piaget's model of cognitive development. In particular, Piaget's theory is inadequate to explain how children learn language. Without any a-priori knowledge of language, it would be terribly difficult to learn the theory of language that any child learns. The British psychologist Annette Karmiloff-Smith, a student of Piaget, has proposed a model of child development that bridges Fodor's nativism (built-in knowledge) and Piaget's constructivism (learning), i.e. innate capacities of the human mind and subsequent representational changes. Karmiloff-Smith envisions a mind that is both equipped with some innate capacities and that grows through a sequence of subsequent changes. Karmiloff-Smith's child is genetically pre-wired to absorb and organize information in an appropriate format. Each module develops independently, as proved by children who exhibit one mental disorder but are perfectly capable in other ways. Karmiloff-Smith's starting point is Fodor's model of the mind (that the mind is made of a number of independent, specialized modules), but, based on evidence of brain's plasticity (the brain can restructure itself to adapt to an early damage), Karmiloff-Smith believes that modules are not static and "grow" during child's development, and that new modules are created during child's development ("gradual modularization"). She points out that children display from the very beginning a whole array of cognitive skills, albeit still unrelated and specific (for example, identifying sounds, imitating other people's movements, recognizing the shapes of faces). Therefore, the child must be born with a set of pre-wired modules that account for these cognitive skills.
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Thinking About Thought: Consciousness, Life and Meaning
Somehow, during development the modules start interacting and working together and adult life takes shape. Initially, children learn by instinct, or at least "implicitly". Then their thinking develops, and consists of redescribing the world from an implicit form to more and more explicit forms, to more and more verbal knowledge. Naturally, the environment that drives the mind's growth also includes the other individuals. Education and playing are forms of influencing the evolution of the thought system of a child. Karmiloff-Smith notes a thread that is common to several spheres of cognition: the passage from procedural non-expert to the automatic (nonprocedural) expert also involves a parallel passage from implicit to explicit knowledge (from executing mechanically to understanding how it works). Child development is not only about learning new procedures, it is about building theories of why those procedures do what they do. This "representational redescription" occurs through three stages: first the child learns to become a master of some activity; then she analyzes introspectively what she has learned; and, finally, she reconciles her performance with her introspection. At this point the child has created a "theory" of why things work the way they work. Therefore Karmiloff-Smith admits cognitive progress like Piaget, but her "representational redescription" occurs when the child has reached a stable state (mastery), whereas in Piaget's model progress only occurs when the child is in a state of disequilibrium. This process involves re-coding information from one representational format (the procedural one) to another (a quasi-linguistic format). There are therefore different levels at which knowledge is encoded (in contrast with Fodor's language of thought). The same "redescription" process operates within each module, but not necessarily at the same pace. In each field, children acquire domain-specific principles that augment the general-purpose principles (such as representational redescription) that guide their cognitive life. The cultural context determines which modules arise. Finally, mapping across domains is a fundamental achievement by the child's mind. In 1991 another developmental psychologist, Patricia Greenfield, has modified this theory by showing that initially the child's mind has no modules, only a general-purpose learning system, then modules start developing. The Interpretation of Dreams The bizarre, irrational nature of dreams, where reality gets warped and laws of nature are turned upside down, and why we remember them at all, are some of the most puzzling mysteries of the mind. Dreaming is a process that absorbs a lot of energy; therefore, it must serve a purpose, possible an important one. http://www.thymos.com/tat/memory.html (13 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
Sigmund Freud's 1900 theory of dreams stood on the following principles: 1. Dreams are composed of sensory images; and 2. Free associations are evoked in the dreamer's mind by these images. He concluded that dreams rely on memories and that they are assembled by the brain to deliver a meaning. Meaning of dreams are hidden and reflect memories of emotionally meaningful experiences. The classical world of Psychology was a world in which actions have a motive, i.e. the reason for an action is its motive. Motives are mental states, hosted in our minds and controlled by our minds. Motives express an imbalance in the mind, between desire and reality: action is an attempt to regenerate balance by changing the reality to match our desire. This view was more mechanistic than the average psychologist would dare to admit, but it did match the expectations of ordinary folks. Freud's revolution was in separating this mechanism of goal-directed action from the awareness of it. Freud suggested that motives are sometimes unconscious, that we may not be aware of the motives that drive our actions. There is a repertory of motives that our mind, independent of our will, has created over the years, and they participate daily in determining our actions. Our conscious motives, the motives that we can count, represent only a part of our system of desires. Freud interpreted dreams accordingly. A dream is only apparently meaningless: it is meaningless if interpreted from the conscious motives. However, the dream is a perfectly logical construction if one considers also the unconscious motives. It appears irrational only because we cannot access those unconscious motives. Freud' fundamental thesis was hidden (unconscious!): that all mental life is driven by motives (desires). Freud never justified it and spent the rest of his life analyzing the content of dreams for the purpose of eliciting the unconscious motives (i.e., of "interpreting" the dream), focusing on sexual desires (a prime example of censored motives in his age) and childhood traumas (which somehow he believed were more prone to generate repressed motives). Freud never even tried to explain the mechanism by which repression of motives operates (by which the unconscious is created, by which some motives are selected over others as undesirable and then such motives are repressed but kept alive and active) and the mechanism by which unconscious morives reemerge during sleep (by which sleep transforms those repressed motives into a flow of scenes). Freud's work had an unfortunate consequence on neuroscience: scientists became more interested in the "content" of dreams than in the "form" of dreaming. Scientists were looking for the "meaning" of dreams, rather than for the "source" of dreams. Scientists studying dreams behaved like doctors analyzing symptoms of a desease, rather than like physicists looking for the causes of a natural phenomenon. This historical accident basically caused dreams to remain outside the sphere of science for seven decades. (Freud's impact, incidentally, has always been larger in the arts than in the sciences). The Interpretation of Dreaming Much more important was a finding that remained neglected for almost a century: at the end of the 19th http://www.thymos.com/tat/memory.html (14 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
century the British neurologist John Hughlings Jackson realized that a loss of a brain function almost always results in the gain in another brain function. Typically what is gained is heightened sensations and emotions. Jackson, virtually a contemporary of Darwin, explained this phenomenon with the view that the brain's functions have different evolutionary ages: newer ones took over older ones, but the older ones are still there, we just don't normally need to use them as the newer ones are more powerful. When we lose one of the newer features, then the older features of the brain regain their importance. Jackson had the powerful intuition that a single process was responsible for a "balance" of brain states. An important discovery (probably the one that opened the doors of the neurobiology of dreams) occurred in 1953: during sleep, the brain enters a state of "rapid eye movement". It turns out that this is the state in which dreaming occurs. REM sleep recurs regularly. A brain enters REM sleep 4 or 5 times per night, at approximately 90 minute intervals, and each period lasts about 20 minutes. In 1962 the French physiologist Michel Jouvet observed that REM sleep is generated in the pontine brain stem (or "pons"). In other words, Jouvet localized the trigger zone for REM sleep and dreaming in the brain stem. REM sleep exhibits four main properties: ❍
A low level of brain activity
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Inhibition of muscle tone
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Waves of excitation from the pons
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Rapid eye movement
The waves of excitation are probably the cause of everything else. The pons sends signals and excites eye muscles (causing rapid eye movement), the midbrain (causing a low level of brain activity), and the thalamus. The thalamus contains structures for visual, auditory, tactile and so forth cognition. The thalamus then excites the cortex. The cortex therefore receives a valid sensory signal from the thalamus and interprets it as if it were coming from the eye, ears, etc. During REM sleep several areas of the brain are working frantically, and some of them are doing exactly the same job they do when the brain is awake. The only major difference is that the stimuli they process are now coming from an internal source rather than from the environment: during dreams the sensory input comes from the sensory cortex. In 1977 the American neurophysiologist Allan Hobson proved that, far from being the center of production of dreams as Freud imagined, higher brain functions such as memory and emotion are simply responding to a barrage of stimulations that are generated from the brainstem. Dreams are made of this
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Thinking About Thought: Consciousness, Life and Meaning
There are three main categories of explanation for dreams. The simplest explanation is that dreams are just an evolutionary accident. By accident we have five fingers rather than four. By accident we dream while we sleep. Another explanation is that they are fossils of a previous form of mind, accidental remnants of previous brain processes. Yet another explanation is that they are a window on some kind of processing that goes on in the brain while we sleep. Imagine that somebody is filing a lot of newspaper clippings in folders and that you are standing in front of him: you will see a rapid sequence of titles flashing in front of your eyes. While you understand each of them, the flow of titles is cryptic: it may form, by mere chance, stories, but stories that you cannot understand. In reality the sequence of titles is not random, because the person who is filing the titles is following a logic (for example, they are filed in chronological order, or in order of importance, or by subject matter). It is just that you are only a spectator. This could be exactly what is happening to our consciousness while we are sleeping. The brain is rapidly processing a huge amount of information in whatever order and our consciousness sees flashes of the bits that are being processed. These bits seem to compose stories of their own, and no wonder that the stories look weird if not undecipherable. This third hypothesis is based on neurophysiological findings. The brain, far from being asleep, is very active during sleep. Most nerve cells in the brain fire all the time, whether we are awake or asleep. There is growing consensus among neurobiologists that remembering and forgetting occur during dreams, that REM sleep is important for consildating long-term memories. Traditionally, neurophysiologists have studied brain activity during sleep, and neglected its awake states. But it turns out that they are surprisingly similar. The genetic meaning of dreams Jouvet was also a pioneer of the theory that dreams have a function: to derive crucial action patterns from the genetic program of the individual. REM sleep provides a means to combine genetic instructions with experience. Sleep and dreaming are a survival strategy. Jouvet thinks that a dream is the vehicle employed by an organism to cancel or archive the day's experiences on the basis of a genetic program. This explanation would also reconcile the dualism between hereditary and acquired features: how much of what we know is innate and how much is acquired by experience? In Jouvet’s scenario, an hereditary component is activated daily to decide how new data must be acquired. More than Freud's pathological theory of dreaming, this resembles the theory of the Swiss psychologist Carl Jung, that dreams reflect the "collective unconscious", a shared repertory of archaic experience represented by "archetypes" which spontaneously emerge in all minds. One only has to adapt Jung's thought to genetics. The universal archetypes envisioned by Jung could be predispositions by all human brains to create some myths rather than others, just like, according to Chomsky, all human brains inherit a predisposition towards acquiring language.
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Thinking About Thought: Consciousness, Life and Meaning
The American neurobiologist Jonathan Winson expressed this concept in a more general way: dreams represent "practice sessions" in which animals (not only humans) refine their survival skills. REM sleep helped the brain "remembering" important facts without having to add cortical tissues. During REM sleep the brain (specifically, the hippocampus) processes information that accumulated during the day. In particular, during REM sleep the brain relates recent memories to old memories, and derives "tips" for future behavior. Dreams are a window on this "off-line processing" of information. The neocortex processes sensory input and sends it to the hippocampus, that acts as a gateway to the limbic system. The limbic system mediates between sensory input and motor output. Initially, the hippocampus is needed to retrieve information stored in long-term memory, but, after about three years, the brain somehow learns how to access directly such information. Dreams may explain how this happens. During REM sleep, the time when we dream, the neocortex is working normally, except that movement in the body is inhibited. Most mammals, except for primates, exhibit a theta rhythm in the hippocampus (about 6 times per second) only on two occasions: whenever they perform survival-critical behavior, and during REM sleep. From this evidence, Winson deduced that REM sleep must be involved in survival-critical behavior. Early mammals had to perform all their "reasoning" on the spot ("on-line"). In particular they had to integrate new information (sensory data) with old information (memories) immediately to work out their strategies. Winson speculates that at some point in evolution brains invented a way to "postpone" processing sensory information by taking advantage of the hippocampus: REM sleep. Theta rhythm is the pace at which that ("off-line") processing is carried out. Instead of taking input from the sensory system, the brain takes input from memory. Instead of directing behavior, the brain inhibits movement. But the kind of processing during REM sleep is the same as during the waking state. Winson speculates that this off-line processing is merging new information with old memories to produre strategies for future behavior. Theta rhythm disappeared in primates, but REM sleep remained as a fundamental process of brains. In humans, therefore, REM sleep, i.e., dreams corresponds to an off-line process of integration of old information with new information. Dreaming is an accidental feature that let us "see" some of the processing, although only some: a dream is not a story but a more or less blind processing of the day's experience. Winson goes as far as to suggest that all long-term memory may be constructed through this off-line process (i.e., during REM sleep). During sleep, the hippocampus would process the day's events and store important information in long-term memory. There is a biologically relevant reason to dream: a dream is an ordered processing of memory which interprets experience that is precious for survival. Dreaming is essential to learning. Winson relates this off-line process that operates during sleep with Freud's subconscious. Freud was right that dreams are the bridge between the conscious and the unconscious, although that bridge is of a different http://www.thymos.com/tat/memory.html (17 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
nature. The Freudian "subconscious" becomes the phylogenetically ancient mechanism involving REM sleep, in which memories and strategies are formed in the cortex. Similarly, in 1983 Francis Crick proposed that the function of dreams is to "clear the circuits" of the brain, otherwise there would not be enough space to register each day's events. We can summarize these ideas as follows. The brain, in the face of huge daily sensory stimulation, must: ❍
understand what matters
❍
understand what does not matter
❍
remember what will still matter
❍
forget what will never matter again
Dreams help out. The ultimate purpose of dreams is to populate long-term memory, to help us learn. We dream hypothetical situations so that we will be prepared to face real situations of the same kind. When a waking situation occurs, it has probably already been played at least once in our dreams, and we know what to expect. By dreaming, we train our brain: dreams are mental gymnastics. It's like saying that, in order to see something, we must first create the vision of that something in our mind. What is still missing is the physical link between dreams and genome. Neurotransmitters (such as animenes and cholines) act on the surface (the membrane) of the cell, whereas genes lie in the center (the nucleus) of the cell. But the messenger molecules transfer information from the membrane to the nucleus and viceversa. Allan Hobson has hypothesized that neurotransmitters may interact with messenger molecules and therefore affect the work of genes. Whether driven by the genetic program or not, what the brain does during sleep is consolidating memories that have been acquired during the day. Dreaming, far from being an eccentric manifestation of irrationality, is at the core of human cognition. Dreams are made of consciousness Whether sleeping or awake, the brain does pretty much the same thing. The dreaming brain employs the same systems and processes of the awake brain, except that those processes are not activated by stimuli from the outside world; that the outcome of those processes does not result in (significant) body movements; and that self-awareness and memory are dormant. Allan Hobson summarized it as: the input, the output, the processor and the working space of the awake brain are replaced by something else. What makes a difference is the neurotransmitters that travel through the brain. What differs between wake
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and sleep is very little, but enough to alter dramatically the outcome: during sleep the brain is bombarded by erratic pulses from the brain stem and flooded with nervous system chemicals of a different sort. Neurotransmitters make brain circuits more or less sensitive. Aminergic neurotransmitters originate in the brain stem and terminate in the amygdala. Cholinergic neurotransmitters originate in the forebrain and terminate in the cortex. During waking states, the brain is controlled by the aminergic neurotransmitters, made of molecules called "amines". During sleep, the brain is controlled by the cholinergic neurotransmitters, made of a molecule called "acetylcholine". Cholinergic chemicals free the system used for cognition and behavior. They paralyze the body by sending pulses to the spinal chord, even if motor neurons are always in motion. The idea is that wake and sleep are two different chemical systems hosted in the same "processor". These two chemical systems are in dynamic equilibrium: if one retracts, the other advances. This means that our consciousness can fluctuate between two extremes, in which either of the chemical systems totally prevails (neither is ever completely absent). This also means that the brain states of wake and sleep are only two extremes, between which there exists a continuum of aminergic-cholinergic interactions, and therefore a continuum of brain states. This system can be said to control the brain. It resides in the brain stem and from there it can easily control both the lower brain (senses and movement) and the upper brain (feelings and thought). When it doesn't work properly, when the balance of chemicals is altered, mental diseases like delirium occur. It is not surprising that diseases such as delirium are so similar to dreams: they are driven by exactly the same phenomenon. Hobson claims that the brain is in awake, dream or (non REM) sleep mode depending on whether amines are prevailing, cholines are prevailing or amines and cholines are "deadlocked". Three factors account for the brain behavior at any time: activation energy (amount of electrical activity), information source (internal or external) and chemical system (amines or cholines). When activation energy is high, the information source is external and the mode is aminergic: the brain is awake. As activation energy decreases, the external information source fades away and amines and cholines balance each other: the brain falls asleep. When activation energy is high, the information source is internal and the mode is cholinergic: the brain is dreaming. During an hallucination: activation energy is high, the information source is internal and the mode is aminergic. In a coma: activation energy is low, the information source is internal and the mode is cholinergic. The extremes are rare and usually traumatic. Normally, both external and internal sources contribute to the cognitive life, and both amines and cholines contribute to the brain state. The interplay of external and internal sources means that our perceptions are always mediated by our memory. Hobson thinks that our brains do not merely react (to stimuli), they also anticipate. The internal source tells us what to expect next, and thus helps us cope with the external source. Emotions are, in a http://www.thymos.com/tat/memory.html (19 of 26)25/07/2003 14:25:11
Thinking About Thought: Consciousness, Life and Meaning
sense, a measure of how well the internal source matches the external source: anxiety is caused by a major mismatch, whereas contentness is a sign of matching sources. When we dream, the spinal cord is paralyzed and the senses are disconnected. This is because of the cholinergic neurotransmitters that come from the brain stem. Hobson believes that sleep has the function to reinforce and reorganize memory: ultimately, to advance them from short-term memory to long-term memory. Amines are necessary for recording an experience, cholines consolidate memory. Hobson deduces that during REM sleep memory is consolidated. The aminergetic system is responsible for attention, focus, awareness. The cholinergetic system is responsible for the opposite process: focus on nothing, but scan everything. As for the content of dreams, Hobson thinks that they reflect a biological need to keep track of place, person (friend, foe or mate) and time. He draws the conclusion from considerations about what is typical (and bizarre) of dreams: disruptions in orientation. The bottom line is that dreams are meaningful: the mind makes a synthetic effort to provide meaning to the signals that are generated internally (during a dream, memory is even "hypermnesic", i.e. is intensified). Wishes are not the cause of the dreaming process, although, once dreaming has been started by the brain stem, wishes may be incorporated in the dream. Therefore, Hobson thinks that dreams need not be interpreted: their meaning is transparent. Or, equivalently, dreams must be interpreted in the realm of neurophysiology, not psychology. The interplay between the aminergic and the cholinergic systems may be responsible for all conscious phenomena (for Hobson, dreams are as conscious as thinking) and ultimately for consciousness itself. After all, conscious states fluctuate continuously between waking and dreaming. Dreams, far from being subjective, are "impersonal necessities forced on brain by nature". An evolution necessity The American psychiatrist Fred Snyder was the first one (in the 1960s) to advance the notion that, from an evolutionary perspective, REM sleep came first and dreams came later. First bodies developed the brain state of REM sleep, which was retained because it had a useful function for survival (for example, because it kept the brain alert and ready to react to emergencies even during sleep), and then dreams were engrafted upon REM sleep. REM sleep was available and was used to host dreams. Dreaming evolved after a physical feature made them possible, just like language evolved after an anatomical apparatus that was born for whatever other reason. Dreaming, just like language, is an "epiphenomenon". The psychologist Anthony Stevens has provided a practical explanation for why some animals started dreaming: dreaming emerged when oviparous animals evolved into viviparous animals. By dreaming, the brain could augment its performance with some "off-line" processing. This made possible to limit the size of the brain while leaving brain activity free to grow. Brains, and thus heads, would remain small enough http://www.thymos.com/tat/memory.html (20 of 26)25/07/2003 14:25:11
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to pass through the maternal pelvis. In Winson's scenario, dreams helped us survive a long time before our mind was capable of providing any help at all. And dreams, unlike higher consciousness, are likely to be common to many species. The mind could well be an evolution of dreaming, which happened in humans and not in other species. First the brain started dreaming, then dreams took over the brain and became the mind, which could be viewed as a continuous dream of the universe. This hypothetical history of the mind does not differ too much from the one in which the mind was created by memes. The relationship between memes and dreams is intuitive, and the psychologist Joseph Campbell indirectly summarized it with his celebrated aphorism that "a myth is a public dream, a dream is a private myth". Of how real dreams are and how dreamy reality is The experience of a dream may feel so utterly bizarre for today's mind, but we have to go back millions of years to realize that it is probably far less bizarre than it appears to us today. It is likely that millions of years ago our waking life was not too different from our dreaming life. Consciousness in dreams is a series of flashes which are fragmented and very emotional. It is likely that awake consciousness had exactly the same character: mostly nothing would happen to our consciousness (no thinking, no emotions, just mechanic, instinctive behavior) but situations would present suddenly that would arouse strong feelings and require immediate action. Our awake life "was" a series of emotionally charged flashes, just like dreams. The difference between being awake and dreaming was only the body movement. As we rehearsed the day's events during dreams, we would feel that the sensations are perfectly normal. Today our consciousness has acquired a different profile: it has evolved to a more or less smooth flow of thoughts, in which strong emotions don't normally figure prominently. We think when we are commuting on a bus or while we are shopping in the mall, and the most violent emotion is being upset about the price of a shirt or suddenly realizing we just missed our stop. They are peanuts compared with the emotion of being attacked by a tiger or of being drawn by strong currents towards the waterfall. Our awake consciousness has changed and dreams have remained the same. The brain is still processing off-line, during sleep, our day's events with the same cerebral circuits that we had millions of years ago, and therefore it is still generating the same flow of emotionally-charged flashes of reality. When the brain is awake, reality does not impinge on those circuits in the same way it did in the hostile, primitive environment of million of years ago. The world we live in is, by and large, friendly (free of mortal foes and natural catastrophes). But when danger does appear (a mortal foe or a natural catastrophe), then our awake life becomes just like a dream: "it was a nightmare", "it didn't feel real", etc. In those rare and unfortunate circumstances (that hopefully most of us will never experience) our waking life feels just like a dream: flashes of reality, violent emotions, apparent incoherence of events, etc. Because of the society that we have built and the way we have tamed and harnessed nature's unpredictability through civilization, our brain does not receive the sudden and violent stimuli it used to. This is what makes most of the difference between being awake and dreaming. It is not a different http://www.thymos.com/tat/memory.html (21 of 26)25/07/2003 14:25:11
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functioning of the brain, it is a different functioning of the world around us. The collective memory of Myths The American anthropologist Joseph Campbell found that a few themes are ubiquitous in myths around the world. Myths recur in different civilizations and evolve from one civilization to the next one. There is a continuum of myth. At the origin of a myth there is an archetype, which works as a "memory deposit". Mythology seems to be a system of entities conceived to mirror the human condition. The rites are "physical formulae" in human flesh, unlike mathematical formulae that are written in symbols, but they are also formulae that describe natural laws of the universe. Myth appears to be a system to organize knowledge about the environment and pass it on to others, in particular to future generations. The reason this system works is that it somehow takes advantage of the way the human brain works. A myth is so constructed that, once inserted in a human brain, it will provoke the desired reaction. It does not require thinking. In a sense, it "tells" you what to do, without having to prove that it is the right thing to do. It shows you the consequences, or the rewards, so you are prepared for them; or it shows you the dangers and so it saves you from experimenting them in real life. For example, when the Sumerian city yields the myth of the city of god what matters is not the historical record but the subliminal message: build such a city! The creator of the myth must craft the myth in such a way that it will trick the brain into wanting to achieve a goal. The "creator", naturally, is not one specific author, but rather the chain of humans who use and adapt the myth to their conditions. The myth evolves over many generations and eventually gets "designed" to perform his task in a very efficient way, just like any organ of the body. Campbell calls myth "the spiritual resources of prehistoric man" and insists on the "spiritual unity" of the human race: the spiritual history of the human race has unfolded roughly in the same way everywhere. Campbell also implies that myth, just like language and just like genes, obeys a grammar. Just like language and just like genes, myths have evolved from more primitive myths. Just like language and just like genes, myths are universal, shared by all humans. Just like language and just like genes, myth tells the story of mankind, as it follows the spread of races in the continents and their adaptation to new natural pressures. Campbell's viewpoint contrasts with that of the anthropologist Jamez Frazer's idea that the similarity of myth is due to similar causes operating on similar brains in different places and times. But there may just be a little bit of truth in both views. A neuroscience of Myths Chomsky showed that brains are "pre-wired" for learning language. Circumstances will determine which particular language you will learn, but the reason you will learn a language is that your brain contains a "universal grammar" that is genetically prescribed. The structure of the human brain forces the brain to learn to speak.
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Dreams seem to be the antichamber to learning, whereby the brain processes experience and decides what has to be stored for future use. Again, this depends on the genetic programming of the brain. What is learned depends on the structure of the brain, which in turn depends on the genetic program that created the brain, which in turn was determined over millions of years by evolution. Basically, it looks like brains learn what they have been programmed to learn by evolution. Human brains have been programmed by evolution to learn some things rather than others. If this is true, than myths could have a simple explanation: they are the simple ideas that the structure of our brain can accomodate. The universal archetypes envisioned by Jung and Campbell could well be predispositions by all human brains to create some myths rather than others, just like, according to Chomsky, all human brains inherit a predisposition towards acquiring language. If myths arise in the mind because the brain has been programmed to create them, then, to some extent, we think what we have been programmed to think. Down this path of genetic determination of our beliefs, one could wonder if genetic differences between the races can account for slightly different behavior. Do Italians speak Italian and French speak French because their brains developed in slightly different ways over thousands of years of independent evolution? Did Arabs develop Islam and Europeans Christianity because their brains are slightly different, and the myths they can create are slight variations of the myth of God? How plastic is our mind, and how strong is the hand of fate? Child's play Why do children play? Isn't that also a way of rehearsing real-life situations based on the genetic repertory? Doesn't play also have the irrational quality of dreams? Isn't playing a way to accelerate the same kind of learning that occurs during dreaming? Could it be that at the beginning of our life everything is but a dream, and then slowly reality takes over (thanks to social interaction) and dreams are relegated to sleep? Joking What have joking and dreaming in common? Apparently nothing, but they both belong to the category of acts that do not seem to have a useful funtion. Like dreaming, joking seems to be a pointless waste of energies. Like dreaming, joking is some kind of playing with our experience. Like dreaming, joking is process of rearranging our experience in a somewhat irrational way. Like dreams, jokes do not necessarily require linguistic skills, but normally occur in a linguistic context. More than dreams, actually, jokes tend to rely on language. More than dreams, jokes seem to have developed in humans to a level far more sophisticated than in any other species. We see animals play and laugh, but the gap between a comedian and two lion cubs wrestling in the grass is enormous.
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First, we may want to ponder whether human dreams too are so much more complex than other species’ dreams. Second, we may want to ascribe this complexity to the acquisition of language. Third, we may want to use what we know about dreams to explain why we make jokes at all. While there is no biological evidence to support the idea that jokes have a specific function for our learning and survival, one wonders why we enjoy so much making them. Woody Allen once said that comedy is tragedy plus time: when something tragic occurs, it is inappropriate to make fun of it, but months or years later it may be perfectly appropriate. If I trip on something and break my leg, I am in no mood to hear a joke about it, but it is more than likely that years later somebody will mock me on this subject. Jokes refer to past experience, and usually refer to tragic experience. If not tragic, then significant in some way. The point is that, indirectly, jokes help us learn and remember. Jokes help us rehearse survival techniques in the environment. Jokes help us prepare for reality. Jokes tell us which situations we should avoid at all costs. Jokes, like dreams, are a brain's way to train itself without risking its life. The Evolution of Memories Memory is not a storage, because it cannot recall events exactly the way they were. Memories change all the time, therefore memory is not a static system, it is a dynamic system. Memory is pivotal for the entire thought system of the individual. Therefore, memory is about thought, it is not limited to remembering. Memory stores and retrieves thoughts. Memory can be viewed as an evolving population of thoughts. Thoughts that survive and reproduce are variations of original thoughts, and somehow "contain" those original thoughts, but adapted to the new circumstances. Memories are descendents of thoughts that occurred in the past. Thoughts are continuously generated from previous one, just like the immune system generates antibodies all the time and just like species are created from previous ones. Memory, far from being a static storage, is changing continuously. It's not a location, it is the collective process of thinking. Every thought contains memories. Further Reading Baddeley Alan: YOUR MEMORY (MacMillan, 1982) Baddeley Alan: WORKING MEMORY (Clarendon Press, 1986) Baddeley Alan: HUMAN MEMORY (Simon & Schuster, 1990) Barsalou Lawrence: COGNITIVE PSYCHOLOGY (Lawrence Erlbaum, 1992)
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Bartlett Frederic Charles: REMEMBERING (1932) (Cambridge Univ Press, 1967) Broadbent Donald: PERCEPTION AND COMMUNICATION (Pergamon, 1958) Broadbent Donald: DECISION AND STRESS (Academic Press, 1971) Bruner Jerome: A STUDY OF THINKING (Wiley, 1956) Campbell Joseph: PRIMITIVE MYTHOLOGY: THE MASKS OF GODS (Viking, 1959) Collins Alan: THEORIES OF MEMORY (Lawrence Erlbaum, 1993) Crowder Robert: PRINCIPLES OF LEARNING AND MEMORY (Erlbaum, 1976) Estes William: CLASSIFICATION AND COGNITION (Oxford University Press, 1994) Fauconnier Gilles: MENTAL SPACES (MIT Press, 1994) Flanagan Owen: DREAMING SOULS (Oxford Univ Press, 1999) Greene Robert: HUMAN MEMORY (Lawrence Erlbaum, 1992) Hobson J. Allan: THE DREAMING BRAIN (Basic, 1989) Hobson Allan: THE CHEMISTRY OF CONSCIOUS STATES (Little & Brown, 1994) Jouvet Michel: LE SOMMEIL ET LE REVE (Jacob, 1992) Jung Carl: THE ARCHETYPES OF THE COLLECTIVE UNCONSCIOUS (1936) Karmiloff-Smith Annette: BEYOND MODULARITY (MIT Press, 1992) Keil Frank: CONCEPTS, KINDS AND COGNITIVE DEVELOPMENT (Cambridge University Press, 1989) Lakoff George: WOMEN, FIRE AND DANGEROUS THINGS (Univ of Chicago Press, 1987) Lenneberg Eric: BIOLOGICAL FOUNDATIONS OF LANGUAGE (Wiley, 1967) Piaget Jean: EQUILIBRATION OF COGNITIVE STRUCTURES (University of Chicago Press, 1985) Reiser Morton: MEMORY IN MIND AND BRAIN (Basic, 1990)
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Roediger Henry: VARIETIES OF MEMORY AND CONSCIOUSNESS (Lawrence Erlbaum, 1989) Rosch Eleanor: COGNITION AND CATEGORIZATION (Erlbaum, 1978) Schacter Daniel & Tulving Endel: MEMORY SYSTEMS (MIT Press, 1994) Schacter Daniel: SEARCHING FOR MEMORY (Basic Books, 1996) Schanks David: HUMAN MEMORY: A READER (Oxford Univ Press, 1997) Snyder Frederick: EXPERIMENTAL STUDIES OF DREAMING (Random House, 1967) Tulving Endel: ORGANIZATION OF MEMORY (Academic Press, 1972) Tulving Endel: ELEMENTS OF EPISODIC MEMORY (Oxford Univ Press, 1983) Tulving Endel: OXFORD HANDBOOK OF MEMORY (Oxford Univ Press, 2000) Winson Jonathan: BRAIN AND PSYCHE (Anchor Press, 1985) Wittgenstein Ludwig: PHILOSOPHICAL INVESTIGATIONS (Macmillan, 1953)
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Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Memories (Conscious and Unconscious) (Hughlings Jackson, Hobson, Jouvet, Winson, Snyder, Flanagan)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Interpretation of Dreams The bizarre, irrational nature of dreams, where reality gets warped and laws of nature are turned upside down, and why we remember them at all, are some of the most puzzling mysteries of the mind. Dreaming is a process that absorbs a lot of energy; therefore, it must serve a purpose, possible an important one. Sigmund Freud's 1900 theory of dreams stood on the following principles: 1. Dreams are composed of sensory images; and 2. Free associations are evoked in the dreamer's mind by these images. He concluded that dreams rely on memories and that they are assembled by the brain to deliver a meaning. Meaning of dreams are hidden and reflect memories of emotionally meaningful experiences. The classical world of Psychology was a world in which actions have a motive, i.e. the reason for an action is its motive. Motives are mental states, hosted in our minds and controlled by our minds. Motives express an imbalance in the mind, between desire and reality: action is an attempt to regenerate balance by changing the reality to match our desire. This view was more mechanistic than the average psychologist would dare to admit, but it did match the expectations of ordinary folks. Freud's revolution was in separating this mechanism of goal-directed action from the awareness of it. Freud suggested that motives are sometimes unconscious, that we may not be aware of the motives that drive our actions. There is a repertory of motives that our mind, independent of our will, has created over the years, and they participate daily in determining our actions. Our conscious motives, the motives that we can count, represent only a part of our system of desires. Freud interpreted dreams accordingly. A dream is only apparently meaningless: it is meaningless if interpreted from the conscious motives. However, the dream is a perfectly logical construction if one
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considers also the unconscious motives. It appears irrational only because we cannot access those unconscious motives. Freud' fundamental thesis was hidden (unconscious!): that all mental life is driven by motives (desires). Freud never justified it and spent the rest of his life analyzing the content of dreams for the purpose of eliciting the unconscious motives (i.e., of "interpreting" the dream), focusing on sexual desires (a prime example of censored motives in his age) and childhood traumas (which somehow he believed were more prone to generate repressed motives). Freud never even tried to explain the mechanism by which repression of motives operates (by which the unconscious is created, by which some motives are selected over others as undesirable and then such motives are repressed but kept alive and active) and the mechanism by which unconscious morives reemerge during sleep (by which sleep transforms those repressed motives into a flow of scenes). Freud's work had an unfortunate consequence on neuroscience: scientists became more interested in the "content" of dreams than in the "form" of dreaming. Scientists were looking for the "meaning" of dreams, rather than for the "source" of dreams. Scientists studying dreams behaved like doctors analyzing symptoms of a desease, rather than like physicists looking for the causes of a natural phenomenon. This historical accident basically caused dreams to remain outside the sphere of science for seven decades. (Freud's impact, incidentally, has always been larger in the arts than in the sciences). The Interpretation of Dreaming Much more important was a finding that remained neglected for almost a century: at the end of the 19th century the British neurologist John Hughlings Jackson realized that a loss of a brain function almost always results in the gain in another brain function. Typically what is gained is heightened sensations and emotions. Jackson, virtually a contemporary of Darwin, explained this phenomenon with the view that the brain's functions have different evolutionary ages: newer ones took over older ones, but the older ones are still there, we just don't normally need to use them as the newer ones are more powerful. When we lose one of the newer features, then the older features of the brain regain their importance. Jackson had the powerful intuition that a single process was responsible for a "balance" of brain states. An important discovery (probably the one that opened the doors of the neurobiology of dreams) occurred in 1953: during sleep, the brain enters a state of "rapid eye movement". It turns out that this is the state in which dreaming occurs. REM sleep recurs regularly. A brain enters REM sleep 4 or 5 times per night, at approximately 90 minute intervals, and each period lasts about 20 minutes. In 1962 the French physiologist Michel Jouvet observed that REM sleep is generated in the pontine brain stem (or "pons"). In other words, Jouvet localized the trigger zone for REM sleep and dreaming in the brain stem. REM sleep exhibits four main properties: ❍
A low level of brain activity
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❍
Inhibition of muscle tone
❍
Waves of excitation from the pons
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Rapid eye movement The waves of excitation are probably the cause of everything else. The pons sends signals and excites eye muscles (causing rapid eye movement), the midbrain (causing a low level of brain activity), and the thalamus. The thalamus contains structures for visual, auditory, tactile and so forth cognition. The thalamus then excites the cortex. The cortex therefore receives a valid sensory signal from the thalamus and interprets it as if it were coming from the eye, ears, etc. During REM sleep several areas of the brain are working frantically, and some of them are doing exactly the same job they do when the brain is awake. The only major difference is that the stimuli they process are now coming from an internal source rather than from the environment: during dreams the sensory input comes from the sensory cortex. In 1977 the American neurophysiologist Allan Hobson proved that, far from being the center of production of dreams as Freud imagined, higher brain functions such as memory and emotion are simply responding to a barrage of stimulations that are generated from the brainstem. Dreams are made of this There are three main categories of explanation for dreams. The simplest explanation is that dreams are just an evolutionary accident. By accident we have five fingers rather than four. By accident we dream while we sleep. Another explanation is that they are fossils of a previous form of mind, accidental remnants of previous brain processes. Yet another explanation is that they are a window on some kind of processing that goes on in the brain while we sleep. Imagine that somebody is filing a lot of newspaper clippings in folders and that you are standing in front of him: you will see a rapid sequence of titles flashing in front of your eyes. While you understand each of them, the flow of titles is cryptic: it may form, by mere chance, stories, but stories that you cannot understand. In reality the sequence of titles is not random, because the person who is filing the titles is following a logic (for example, they are filed in chronological order, or in order of importance, or by subject matter). It is just that you are only a spectator. This could be exactly what is happening to our consciousness while we are sleeping. The brain is rapidly processing a huge amount of information in whatever order and our consciousness sees flashes of the bits that are being processed. These bits seem to compose stories of their own, and no wonder that the stories look weird if not undecipherable.
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Thinking About Thought: Consciousness, Life and Meaning
This third hypothesis is based on neurophysiological findings. The brain, far from being asleep, is very active during sleep. Most nerve cells in the brain fire all the time, whether we are awake or asleep. There is growing consensus among neurobiologists that remembering and forgetting occur during dreams, that REM sleep is important for consildating long-term memories. Traditionally, neurophysiologists have studied brain activity during sleep, and neglected its awake states. But it turns out that they are surprisingly similar. The genetic meaning of dreams Jouvet was also a pioneer of the theory that dreams have a function: to derive crucial action patterns from the genetic program of the individual. REM sleep provides a means to combine genetic instructions with experience. Sleep and dreaming are a survival strategy. Jouvet thinks that a dream is the vehicle employed by an organism to cancel or archive the day's experiences on the basis of a genetic program. This explanation would also reconcile the dualism between hereditary and acquired features: how much of what we know is innate and how much is acquired by experience? In Jouvet’s scenario, an hereditary component is activated daily to decide how new data must be acquired. In particular, Jouvet showed that psychological differences across individuals are maintained by a sort of continuous reprogramming that takes place during REM sleep. This process wipes out "certain aspects of what we have learned", while reinforcing the "unconscious reactions that are the basis of personality". (Research seems to indicate that different individuals each have a different sleep pattern, but patterns of eye movements in identical twins are similar). More than Freud's pathological theory of dreaming, this resembles the theory of the Swiss psychologist Carl Jung, that dreams reflect the "collective unconscious", a shared repertory of archaic experience represented by "archetypes" which spontaneously emerge in all minds. One only has to adapt Jung's thought to genetics. The universal archetypes envisioned by Jung could be predispositions by all human brains to create some myths rather than others, just like, according to Chomsky, all human brains inherit a predisposition towards acquiring language. The adaptive value of dreams The American neurobiologist Jonathan Winson expressed this concept in a more general way: dreams represent "practice sessions" in which animals (not only humans) refine their survival skills.
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Thinking About Thought: Consciousness, Life and Meaning
REM sleep helped the brain "remembering" important facts without having to add cortical tissues. During REM sleep the brain (specifically, the hippocampus) processes information that accumulated during the day. In particular, during REM sleep the brain relates recent memories to old memories, and derives "tips" for future behavior. Dreams are a window on this "off-line processing" of information. The neocortex processes sensory input and sends it to the hippocampus, that acts as a gateway to the limbic system. The limbic system mediates between sensory input and motor output. Initially, the hippocampus is needed to retrieve information stored in long-term memory, but, after about three years, the brain somehow learns how to access directly such information. Dreams may explain how this happens. During REM sleep, the time when we dream, the neocortex is working normally, except that movement in the body is inhibited. Most mammals, except for primates, exhibit a theta rhythm in the hippocampus (about 6 times per second) only on two occasions: whenever they perform survival-critical behavior, and during REM sleep. From this evidence, Winson deduced that REM sleep must be involved in survival-critical behavior. Early mammals had to perform all their "reasoning" on the spot ("on-line"). In particular they had to integrate new information (sensory data) with old information (memories) immediately to work out their strategies. Winson speculates that at some point in evolution brains invented a way to "postpone" processing sensory information by taking advantage of the hippocampus: REM sleep. Theta rhythm is the pace at which that ("offline") processing is carried out. Instead of taking input from the sensory system, the brain takes input from memory. Instead of directing behavior, the brain inhibits movement. But the kind of processing during REM sleep is the same as during the waking state. Winson speculates that this off-line processing is merging new information with old memories to produre strategies for future behavior. Theta rhythm disappeared in primates, but REM sleep remained as a fundamental process of brains. In humans, therefore, REM sleep, i.e., dreams corresponds to an off-line process of integration of old information with new information. Dreaming is an accidental feature that let us "see" some of the processing, although only some: a dream is not a story but a more or less blind processing of the day's experience. Winson goes as far as to suggest that all long-term memory may be constructed through this off-line process (i.e., during REM sleep). During sleep, the hippocampus would process the day's events and store important information in long-term memory. There is a biologically relevant reason to dream: a dream is an ordered processing of memory which interprets experience that is precious for survival. Dreaming is essential to learning. http://www.thymos.com/tat/dreams.html (5 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
Winson relates this off-line process that operates during sleep with Freud's subconscious. Freud was right that dreams are the bridge between the conscious and the unconscious, although that bridge is of a different nature. The Freudian "subconscious" becomes the phylogenetically ancient mechanism involving REM sleep, in which memories and strategies are formed in the cortex. We dream to remember and to forget Similarly, Hobson things that the ultimate purpose of dreams is to populate long-term memory, to help us learn. We dream hypothetical situations so that we will be prepared to face real situations of the same kind. When a waking situation occurs, it has probably already been played at least once in our dreams, and we know what to expect. By dreaming, we train our brain: dreams are mental gymnastics. It's like saying that, in order to see something, we must first create the vision of that something in our mind. In a sense, we dream what is worth remembering. By contrast, in 1983 Francis Crick proposed that the function of dreams is to "clear the circuits" of the brain, otherwise there would not be enough space to register each day's events. We can summarize these ideas as follows. The brain, in the face of huge daily sensory stimulation, must: ❍
understand what matters
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understand what does not matter
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remember what will still matter
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forget what will never matter again Dreams help eliminate useless memories. Therefore, according to Crick, we dream what is worth forgetting. What is still missing is the physical link between dreams and genome. Neurotransmitters (such as animenes and cholines) act on the surface (the membrane) of the cell, whereas genes lie in the center (the nucleus) of the cell. But the messenger molecules transfer information from the membrane to the nucleus and viceversa. Allan Hobson has hypothesized that neurotransmitters may interact with messenger molecules and therefore affect the work of genes. Whether driven by the genetic program or not, what the brain does during sleep is
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Thinking About Thought: Consciousness, Life and Meaning
consolidating memories that have been acquired during the day. Dreaming, far from being an eccentric manifestation of irrationality, is at the core of human cognition. Dreams are made of consciousness Whether sleeping or awake, the brain does pretty much the same thing. The dreaming brain employs the same systems and processes of the awake brain, except that those processes are not activated by stimuli from the outside world; that the outcome of those processes does not result in (significant) body movements; and that self-awareness and memory are dormant. Allan Hobson summarized it as: the input, the output, the processor and the working space of the awake brain are replaced by something else. What makes a difference is the neurotransmitters that travel through the brain. What differs between wake and sleep is very little, but enough to alter dramatically the outcome: during sleep the brain is bombarded by erratic pulses from the brain stem and flooded with nervous system chemicals of a different sort. Neurotransmitters make brain circuits more or less sensitive. Aminergic neurotransmitters originate in the brain stem and terminate in the amygdala. Cholinergic neurotransmitters originate in the forebrain and terminate in the cortex. During waking states, the brain is controlled by the aminergic neurotransmitters, made of molecules called "amines". During sleep, the brain is controlled by the cholinergic neurotransmitters, made of a molecule called "acetylcholine". Cholinergic chemicals free the system used for cognition and behavior. They paralyze the body by sending pulses to the spinal chord, even if motor neurons are always in motion. The idea is that wake and sleep are two different chemical systems hosted in the same "processor". These two chemical systems are in dynamic equilibrium: if one retracts, the other advances. This means that our consciousness can fluctuate between two extremes, in which either of the chemical systems totally prevails (neither is ever completely absent). This also means that the brain states of wake and sleep are only two extremes, between which there exists a continuum of aminergic-cholinergic interactions, and therefore a continuum of brain states. This system can be said to control the brain. It resides in the brain stem and from there it can easily control both the lower brain (senses and movement) and the upper brain (feelings and thought). When it doesn't work properly, when the balance of chemicals is altered, mental diseases like delirium occur. It is not surprising that diseases such as delirium are so similar to dreams: they are driven by exactly the same phenomenon. Hobson claims that the brain is in awake, dream or (non REM) sleep mode depending on whether amines are prevailing, cholines are prevailing or amines and cholines are http://www.thymos.com/tat/dreams.html (7 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
"deadlocked". Three factors account for the brain behavior at any time: activation energy (amount of electrical activity), information source (internal or external) and chemical system (amines or cholines). When activation energy is high, the information source is external and the mode is aminergic: the brain is awake. As activation energy decreases, the external information source fades away and amines and cholines balance each other: the brain falls asleep. When activation energy is high, the information source is internal and the mode is cholinergic: the brain is dreaming. During an hallucination: activation energy is high, the information source is internal and the mode is aminergic. In a coma: activation energy is low, the information source is internal and the mode is cholinergic. The extremes are rare and usually traumatic. Normally, both external and internal sources contribute to the cognitive life, and both amines and cholines contribute to the brain state. The interplay of external and internal sources means that our perceptions are always mediated by our memory. Hobson thinks that our brains do not merely react (to stimuli), they also anticipate. The internal source tells us what to expect next, and thus helps us cope with the external source. Emotions are, in a sense, a measure of how well the internal source matches the external source: anxiety is caused by a major mismatch, whereas contentness is a sign of matching sources. When we dream, the spinal cord is paralyzed and the senses are disconnected. This is because of the cholinergic neurotransmitters that come from the brain stem. Hobson believes that sleep has the function to reinforce and reorganize memory: ultimately, to advance them from short-term memory to long-term memory. Amines are necessary for recording an experience, cholines consolidate memory. Hobson deduces that during REM sleep memory is consolidated. The aminergetic system is responsible for attention, focus, awareness. The cholinergetic system is responsible for the opposite process: focus on nothing, but scan everything. As for the content of dreams, Hobson thinks that they reflect a biological need to keep track of place, person (friend, foe or mate) and time. He draws the conclusion from considerations about what is typical (and bizarre) of dreams: disruptions in orientation. The bottom line is that dreams are meaningful: the mind makes a synthetic effort to provide meaning to the signals that are generated internally (during a dream, memory is even "hypermnesic", i.e. is intensified). Wishes are not the cause of the dreaming process, although, once dreaming has been started by the brain stem, wishes may be incorporated in the dream. Therefore, Hobson thinks that dreams need not be interpreted: their meaning is http://www.thymos.com/tat/dreams.html (8 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
transparent. Or, equivalently, dreams must be interpreted in the realm of neurophysiology, not psychology. The interplay between the aminergic and the cholinergic systems may be responsible for all conscious phenomena (for Hobson, dreams are as conscious as thinking) and ultimately for consciousness itself. After all, conscious states fluctuate continuously between waking and dreaming. Dreams, far from being subjective, are "impersonal necessities forced on brain by nature". An evolutionary necessity The American psychiatrist Fred Snyder was the first (in the 1960s) to advance the notion that, from an evolutionary perspective, REM sleep came first and dreams came later. First bodies developed the brain state of REM sleep, which was retained because it had a useful function for survival (for example, because it kept the brain alert and ready to react to emergencies even during sleep), and then dreams were engrafted upon REM sleep. REM sleep was available and was used to host dreams. Dreaming evolved after a physical feature made them possible, just like language evolved after an anatomical apparatus that was born for whatever other reason. Dreaming, just like language, is an "epiphenomenon". The psychologist Anthony Stevens has provided a practical explanation for why some animals started dreaming: dreaming emerged when oviparous animals evolved into viviparous animals. By dreaming, the brain could augment its performance with some "offline" processing. This made possible to limit the size of the brain while leaving brain activity free to grow. Brains, and thus heads, would remain small enough to pass through the maternal pelvis. In Winson's scenario, dreams helped us survive a long time before our mind was capable of providing any help at all. And dreams, unlike higher consciousness, are likely to be common to many species. The mind could well be an evolution of dreaming, which happened in humans and not in other species. First the brain started dreaming, then dreams took over the brain and became the mind, which could be viewed as a continuous dream of the universe. This hypothetical history of the mind does not differ too much from the one in which the mind was created by memes. The relationship between memes and dreams is intuitive, and the psychologist Joseph Campbell indirectly summarized it with his celebrated aphorism that "a myth is a public dream, a dream is a private myth". An evolutionary accident In contrast to Jouvet, Hobson and Winson, the American philosopher Owen Flanagan thinks http://www.thymos.com/tat/dreams.html (9 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
that both sleep and consciousness are products of evolution, but consciousness during sleep (dreaming) is merely an accident of nature, a side effect of the two. Both consciousness and sleep have a clear biological function, but dreams don't. During sleep, the brain stocks up neurotransmitters that will be used the next day. By accident, pulses that originate from this stockpiling chore (coming from the brain stem) also reactivate more or less random parts of memory. Unaware that the body is actually sleeping, the sensory circuits of the cerebral cortex process these signals as if they were coming from outside and produce a chaotic flow of sensations. Thus we dream. Dreams are just the noise the brain makes while working overnight. If Flanagan is correct, dreams are meaningless and pointless. Of course, indirectly, dreams tell us something about how our mind works, because, after all, whatever we perceive while we dream is the product of what is in our memory and of how our cerebral cortex processes those memories. But the usefulness of the dream-narrative is really limited to an almost "diagnostic" purpose. As our cerebral cortex tries to make sense of that chaotic input, we can learn something about its cognitive functioning, just like by running the engine of a car when it is not moving we can learn something about a noise it makes on the freeway (but the engine running while the car is not moving has no hidden meaning). Of how real dreams are and how dreamy reality is The experience of a dream may feel so utterly bizarre for today's mind, but we have to go back millions of years to realize that it is probably far less bizarre than it appears to us today. It is likely that millions of years ago our waking life was not too different from our dreaming life. Consciousness in dreams is a series of flashes which are fragmented and very emotional. It is likely that awake consciousness had exactly the same character: mostly nothing would happen to our consciousness (no thinking, no emotions, just mechanic, instinctive behavior) but situations would present suddenly that would arouse strong feelings and require immediate action. Our awake life "was" a series of emotionally charged flashes, just like dreams. The difference between being awake and dreaming was only the body movement. As we rehearsed the day's events during dreams, we would feel that the sensations are perfectly normal. Today our consciousness has acquired a different profile: it has evolved to a more or less smooth flow of thoughts, in which strong emotions don't normally figure prominently. We think when we are commuting on a bus or while we are shopping in the mall, and the most violent emotion is being upset about the price of a shirt or suddenly realizing we just missed our stop. They are peanuts compared with the emotion of being attacked by a tiger or of http://www.thymos.com/tat/dreams.html (10 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
being drawn by strong currents towards the waterfall. Our awake consciousness has changed and dreams have remained the same. The brain is still processing off-line, during sleep, our day's events with the same cerebral circuits that we had millions of years ago, and therefore it is still generating the same flow of emotionally-charged flashes of reality. When the brain is awake, reality does not impinge on those circuits in the same way it did in the hostile, primitive environment of million of years ago. The world we live in is, by and large, friendly (free of mortal foes and natural catastrophes). But when danger does appear (a mortal foe or a natural catastrophe), then our awake life becomes just like a dream: "it was a nightmare", "it didn't feel real", etc. In those rare and unfortunate circumstances (that hopefully most of us will never experience) our waking life feels just like a dream: flashes of reality, violent emotions, apparent incoherence of events, etc. Because of the society that we have built and the way we have tamed and harnessed nature's unpredictability through civilization, our brain does not receive the sudden and violent stimuli it used to. This is what makes most of the difference between being awake and dreaming. It is not a different functioning of the brain, it is a different functioning of the world around us. The collective memory of Myths The American anthropologist Joseph Campbell found that a few themes are ubiquitous in myths around the world. Myths recur in different civilizations and evolve from one civilization to the next one. There is a continuum of myth. At the origin of a myth there is an archetype, which works as a "memory deposit". Mythology seems to be a system of entities conceived to mirror the human condition. The rites are "physical formulae" in human flesh, unlike mathematical formulae that are written in symbols, but they are also formulae that describe natural laws of the universe. Myth appears to be a system to organize knowledge about the environment and pass it on to others, in particular to future generations. The reason this system works is that it somehow takes advantage of the way the human brain works. A myth is so constructed that, once inserted in a human brain, it will provoke the desired reaction. It does not require thinking. In a sense, it "tells" you what to do, without having to prove that it is the right thing to do. It shows you the consequences, or the rewards, so you are prepared for them; or it shows you the dangers and so it saves you from experimenting them in real life. For example, when the Sumerian city yields the myth of the city of god what matters is not the historical record but the subliminal message: build such a city! The creator of the myth must craft the myth in such a way that it will trick the brain into wanting to achieve a goal. The "creator", naturally, is not one specific author, but rather the chain of humans who use and adapt the myth to their conditions. The myth evolves over many generations and eventually gets "designed" to perform his task in a very efficient way, just like any organ of the body. Campbell calls myth "the spiritual resources of prehistoric man" and insists on the "spiritual unity" of the human race: the spiritual history of the human race has unfolded roughly in the same way everywhere. http://www.thymos.com/tat/dreams.html (11 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
Campbell also implies that myth, just like language and just like genes, obeys a grammar. Just like language and just like genes, myths have evolved from more primitive myths. Just like language and just like genes, myths are universal, shared by all humans. Just like language and just like genes, myth tells the story of mankind, as it follows the spread of races in the continents and their adaptation to new natural pressures. Campbell's viewpoint contrasts with that of the anthropologist Jamez Frazer's idea that the similarity of myth is due to similar causes operating on similar brains in different places and times. But there may just be a little bit of truth in both views. A neuroscience of Myths Chomsky showed that brains are "pre-wired" for learning language. Circumstances will determine which particular language you will learn, but the reason you will learn a language is that your brain contains a "universal grammar" that is genetically prescribed. The structure of the human brain forces the brain to learn to speak. Dreams seem to be the antichamber to learning, whereby the brain processes experience and decides what has to be stored for future use. Again, this depends on the genetic programming of the brain. What is learned depends on the structure of the brain, which in turn depends on the genetic program that created the brain, which in turn was determined over millions of years by evolution. Basically, it looks like brains learn what they have been programmed to learn by evolution. Human brains have been programmed by evolution to learn some things rather than others. If this is true, than myths could have a simple explanation: they are the simple ideas that the structure of our brain can accomodate. The universal archetypes envisioned by Jung and Campbell could well be predispositions by all human brains to create some myths rather than others, just like, according to Chomsky, all human brains inherit a predisposition towards acquiring language. If myths arise in the mind because the brain has been programmed to create them, then, to some extent, we think what we have been programmed to think. Down this path of genetic determination of our beliefs, one could wonder if genetic differences between the races can account for slightly different behavior. Do Italians speak Italian and French speak French because their brains developed in slightly different ways over thousands of years of independent evolution? Did Arabs develop Islam and Europeans Christianity because their brains are slightly different, and the myths they can create are slight variations of the myth of God?
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How plastic is our mind, and how strong is the hand of fate? A history of concepts One could argue that ancient gods simply represent concepts. As concepts were forming in human minds, human minds expressed them as concepts. And their interaction yielded religions. Ancient gods represented qualities, mountains, rivers, forces of nature, emotions. Gods were vehicles for natural forces to express themselves. Gods were created for each new phenomenon or discovery. Ancient religions were systems of concepts: they classified and organized concepts through a network of legends (symbolic narratives) and a series of rites (symbolic actions) in a manner not too different from Minsky’s "frame" (a legend expressing the function of the force in nature and in relation to other forces, a rite expressing the attributes of the force). They were "local" (each culture developed different sets based on local circumstances). As lower concepts gave rise to higher, more complex, concepts, old gods were replaced by new gods (e.g., the god of thunder or of the Nile was replaced by the god of fertility or of harvest). New gods were created as the mind progressed from purely narrative/literal concepts to more and more abstract concepts. At some point there arose the concept of all concepts, the concept of Nature itself, the concept of the supreme power and of everything that exists, of the force that is behind all other forces. Thus monotheistic religion was born. God became not the vehicle for a force but "the" force itself. Religion is, ultimately, a way to pass culture (a system of concepts) on to future generations: Islam has a concept that women are inferior beings; Christianity has a concept that we are all equal, etc. People of different religions have not only different rites (physical lives) but also different mental lives, because they think according to different conceptual systems. There is no one-to-one correspondence between Roman gods and Indian gods, and that explains why ancient Rome and ancient Indian were completely different societies: they had completely different concepts, people thought in completely different manners. The monotheistic religion represents a major leap forward in cognitive skills. Just like the zero enabled higher mathematics and the roman arch enabled taller buildings, so the singlegod religion enabled higher thinking. Child's play Why do children play? Isn't that also a way of rehearsing real-life situations based on the http://www.thymos.com/tat/dreams.html (13 of 15)25/07/2003 14:25:32
Thinking About Thought: Consciousness, Life and Meaning
genetic repertory? Doesn't play also have the irrational quality of dreams? Isn't playing a way to accelerate the same kind of learning that occurs during dreaming? Could it be that at the beginning of our life everything is but a dream, and then slowly reality takes over (thanks to social interaction) and dreams are relegated to sleep? Joking What have joking and dreaming in common? Apparently nothing, but they both belong to the category of acts that do not seem to have a useful funtion. Like dreaming, joking seems to be a pointless waste of energies. Like dreaming, joking is some kind of playing with our experience. Like dreaming, joking is process of rearranging our experience in a somewhat irrational way. Like dreams, jokes do not necessarily require linguistic skills, but normally occur in a linguistic context. More than dreams, actually, jokes tend to rely on language. More than dreams, jokes seem to have developed in humans to a level far more sophisticated than in any other species. We see animals play and laugh, but the gap between a comedian and two lion cubs wrestling in the grass is enormous. First, we may want to ponder whether human dreams too are so much more complex than other species’ dreams. Second, we may want to ascribe this complexity to the acquisition of language. Third, we may want to use what we know about dreams to explain why we make jokes at all. While there is no biological evidence to support the idea that jokes have a specific function for our learning and survival, one wonders why we enjoy so much making them. Woody Allen once said that comedy is tragedy plus time: when something tragic occurs, it is inappropriate to make fun of it, but months or years later it may be perfectly appropriate. If I trip on something and break my leg, I am in no mood to hear a joke about it, but it is more than likely that years later somebody will mock me on this subject. Jokes refer to past experience, and usually refer to tragic experience. If not tragic, then significant in some way. The point is that, indirectly, jokes help us learn and remember. Jokes help us rehearse survival techniques in the environment. Jokes help us prepare for reality. Jokes tell us which situations we should avoid at all costs. Jokes, like dreams, are a brain's way to train itself without risking its life. The Evolution of Memories Memory is not a storage, because it cannot recall events exactly the way they were. Memories change all the time, therefore memory is not a static system, it is a dynamic system. Memory is pivotal for the entire thought system of the individual. Therefore, memory is about thought, it is not limited to remembering. Memory stores and retrieves thoughts.
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Memory can be viewed as an evolving population of thoughts. Thoughts that survive and reproduce are variations of original thoughts, and somehow "contain" those original thoughts, but adapted to the new circumstances. Memories are descendents of thoughts that occurred in the past. Thoughts are continuously generated from previous one, just like the immune system generates antibodies all the time and just like species are created from previous ones. Memory, far from being a static storage, is changing continuously. It's not a location, it is the collective process of thinking. Every thought contains memories. Further Reading Campbell Joseph: PRIMITIVE MYTHOLOGY: THE MASKS OF GODS (Viking, 1959) Flanagan Owen: DREAMING SOULS (Oxford Univ Press, 1999) Hobson J. Allan: THE DREAMING BRAIN (Basic, 1989) Hobson Allan: THE CHEMISTRY OF CONSCIOUS STATES (Little & Brown, 1994) Jouvet Michel: LE SOMMEIL ET LE REVE (Jacob, 1992) Jouvet, Michel: THE PARADOX OF sLEEP: THE STORY OF DREAMING (MIT Press, 1999) Jung Carl: THE ARCHETYPES OF THE COLLECTIVE UNCONSCIOUS (1936) Snyder Frederick: EXPERIMENTAL STUDIES OF DREAMING (Random House, 1967) Winson Jonathan: BRAIN AND PSYCHE (Anchor Press, 1985)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Emotion (Mandler, Sloman, Buck, Klopf, DeSousa, Lazarus, Jauregi, Damasio)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Feeling and Thinking Emotion appears to be a key component in the behavior of conscious beings. To some extent, consciousness "is" emotion. There is probably no recollection, no thinking and no planning that occurs without feeling emotions. We are either happy or sad or afraid or something else all the time. There is rarely a moment in our day when we are not feeling an emotion. William James conceived mental life as a "stream of consciousness", each state of consciousness possessing both a cognitive aspect and a feeling aspect. Whether all of consciousness is just emotion or whether emotion is a parallel, complementary facility of the mind, is debatable. But it can be argued that we would not consider conscious a being who cannot feel emotions, no matter how intelligent it is and no matter how much its body resembles ours. On the other hand, we ascribe emotions to beings that we don't consider as "conscious": dogs, birds, even fish and tarantulas. Are the intensities of their emotions (of fear, for example) as strong as ours, regardless of whether their level of self-awareness is comparable to ours? Is emotion a more primitive form of consciousness, that in humans developed into full-fledged self-awareness? Is emotion an organ, just like feet and tails, that a species may or may not have, but which has no relevance to consciousness? When turning to emotions, the first problem facing us is that most studies on them are from a psychological perspective. Little research has been done from a biological perspective. Emotions have been traditionally neglected by scientists researching the mind, as if they were a secondary aspect (or simply a malfunction) of the brain activity. The fact is surprising because emotions have so much to do with our being "aware", with differentiating intelligent life from dead matter and non-
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Thinking About Thought: Consciousness, Life and Meaning
intelligent life. While the relationship between "feeling" and "thinking" is still unclear, it is generally agreed that all beings who think also feel. That makes feelings central to an understanding of thinking. That emotions may not be so peripheral a notion as the scant literature on them would imply is a fact suspected since ancient times, but only recently science has focused on their function, their evolution and their behavior. In other words: how did the ability to feel emotions originate, why did it originate and how does it influence our mind's overall functioning? Emotions as Survival Instinct The answers can be summarized, once again, as: emotions are a product of evolution, they exist because they favor our species in natural selection. What emotions seem to do is help us make fast decisions in crucial situations. Emotions are inferential short-cuts. If I am afraid of a situation, it means that it is dangerous: the emotion of fear has already helped me make up my mind about how to approach that situation. If I were not capable of fear, my brain would have to analyze the situation, infer logically what is good and what is bad in it for me, and finally draw a conclusion. By that time, it may be too late. Fear helps act faster than if we used our logical faculties. This is reflected by the way emotions are generated. The central processor for emotions is the brain structure called "amygdala" The thalamus normally connects senses to cortex and cortex to muscles. But the amygdala provides a much faster shortcut for decision making: the route from senses to amygdala to thalamus to muscles is much faster than going through the cortex. The American neurophysiologist Joseph LeDoux believes that there exist specialized brain circuits (neural maps) for each emotion. Such circuits create as many "shortcuts" to decision making. Emotions as communication Emotions are also the fastest way that we can communicate with members of our group, another activity that is critical to survival. The American psychiatrist Allan Hobson thinks that emotions are signals between animals of the same species that communicate one's brain state to another. Emotions probably predate language itself as a form of communication. Gregory Bateson coined a term, "kinesics", for paralinguistic body comunication, such as facial expression. Kinesics is about emotions. It may well be that body communication existed before language was invented, and that it was the main form of communication. Facial expression is inevitable like language and universal like language. Emotion as Rationality Aaron Sloman has reduced the argument about emotions to simple mathematical terms. Let us look at an "agent" (whether a human, an animal, a robot or a piece of software), which is limited and intelligent and must act in a complex environment. A "complex" environment may well include a very large number of http://www.thymos.com/tat/emotion.html (2 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
factors. In fact, it may be made of an "infinite" number of factors, if one starts counting every little detail that may have an influence. Our agent, which is limited, would never reach a conclusion on what to do if it blindly analyzed all factors. Therefore, in order to survive (to move at all, actually) it must be endowed with mechanisms that cause emotions. In other words, emotions are the result of constraints by the environment on the action of the intelligent being. An emotional state is created by a situation, through a somewhat mysterious chemical reaction in the nerve system. A cognitive state is created by a number of situations and by a thinking process that relates those situations and draws some kind of conclusion. The relation between emotional states and cognitive states is reduced to the need to draw conclusions when cognition would face combinatorial explosion of possible reasoning threads. Ronald DeSousa expresses this fact in a different way: emotions play the same role as perceptions, i.e. they contribute to create beliefs and desires. Beliefs and desires are necessary elements of any logical system: one attempts to satisfy desires by acting in the environment according to one's beliefs about the environment. DeSousa believes that emotions are learned like a language. And, like any language, they have their own grammar, i.e. their syntax and semantics (an idea also advanced by Sloman). Just like the meaning of words ultimately derives from the sentences in which they can be used, the semantics of emotions derives from the scenarios in terms of which they have been learned. Emotions can therefore be studied in a formal way just like any other language. The complementarity between reason and emotion becomes what he calls "axiological rationality", yet another way to express the fact that emotions determine what is salient, i.e. can restrict the combinatorial possibilities that reason has to face in the real world. Emotion as Homeostasis Ross Buck proposed an elegant decomposition of human behavior. In his view, our behavior is the product of several systems of organization which belong to two big families. The first one is the family of innate special-purpose processing systems (reflexes, instincts, etc.). In general their function is "bodily adaptation" to the environment. In general, their approach is not analytic but holistic and syncretic: they don't "reduce" the situation to its details, they treat it as a whole. In Buck's view, these processes are innate, we don't need to learn them. The second family contains acquired general-purpose processing systems. In general their function is to make sense of the environment. Their approach is sequential and analytic. The former family is associated with the right hemisphere of the brain and is responsible for emotional expression; the latter is associated with the left hemisphere and is responsible for symbolic thinking. The two families cooperate in determining the body's behavior. What is even more interesting about Buck's analysis is actually the advantage of emotions in communication between humans. Communication of emotions turns out to be a biologically shared signal system. It was created through the evolutionary process and it is part of every human being. It means that it is very easy to communicate an emotion: we immediately recognize the meaning of another human's emotion. On the contrary, communicating a theorem is not easy at all, and often requires special skills.
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Thinking About Thought: Consciousness, Life and Meaning
Besides bodily adaptation, therefore, emotions have the important function of speeding up communication of crucial information among members of the same species. If emotion is, ultimately, a reaction to a situation in the environment, it can be assumed to be a "measure" relative to that situation, and what is communicated is precisely that measure. But a measure of what? Buck thinks that emotions always originate from motives that must be satisfied: the emotion is a measure of how far they have been satisfied. For example, fear is a measure of safety. A more appropriate way of referring to adaptation is "homeostasis", which is the process of searching for a balance. If something changes in the environment, all the organisms that depend on that environment will react somehow to recreate the equilibrium they need to survive. This process of continuous search for equilibrium is called "homeostasis". Most scientists who have studied emotions agree with Buck that the ultimate function of emotions is homeostasis. Emotion as Heterostasis Harry Klopf is a notable exception. His view is just the opposite: organisms are not hiding in the environment, trying to minimize action and change; they actively seek stimulation. If homeostasis is the seeking of a steady-state condition, "heterostasis" is the seeking of maximum stimulation. According to Klopf, all parts of the brain are independently seeking positive stimulation (or "pleasure") and avoiding negative stimulation (or "pain"). Klopf also thinks that cognition and emotion coexist and complement each other, but their relative roles are significantly different: emotion provides the sense of what the organism needs, cognition provides the means for achieving those needs. Emotion as Cognition The common theme underlying all of these studies is that emotions are not as irrational as they seem to be; quite the opposite, actually. George Mandler had a powerful intuition. Let's assume that, of all the information available in the environment, the mind is mainly interested in environmental regularities. Then most of its processing can be reduced to: there is a goal (e.g.: "eat"), there is a need (e.g.: "food") and there is a situation (e.g.: "a plantation of bananas"). Based on known regularities of the environment, the mind can determine what it needs to achieve its goal in the current situation. The emotion (e.g.: "desire bananas") simplifies this process. The function of emotions is to provide the individual with the most general view of the world that is consistent with current needs, goals and situations. Richard Lazarus has provided a synthesis of all of these themes. He agrees that the final goal of our emotions is to help the organism survive in the environment. Emotions arise from the relationship between the individual and its environment, or, better, the regularities of its environment. Emotion requires an appraisal of the situation and its consequences. For example,such an appraisal may lead to fear if the situation turns out to be dangerous. Emotions are genetically determined, but they can change during a lifetime: both biological and social variables may alter our set of emotions, and this explains why emotions change through the various stages of life. http://www.thymos.com/tat/emotion.html (4 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
Ultimately, emotions express the personal meaning of an individual's experience. The meaning of each emotion is about the significance of the triggering event (the situation) for the well-being of the individual. Each emotion is defined by a set of benefits and harms in the relationship between individual and environment, and that set is constructed by a process of appraisal. Appraisal is key to emotion. Each type of emotion is distinguished by a pattern of appraisal factors. Since appraisal is the fundamental process for the occurrence of emotion, Lazarus believes that cognition is a requisite for emotion: a cognitive process (an appraisal) must occur before one can have an emotion. Emotion as Communication Between the Brain and the Self All of these models tend to neglect the relation between emotion and awareness. They also tend to make too abstract the obvious relation between emotion and the body. A synthesis that directly refers to consciousness and the body has been proposed by Jose Jauregui. Jauregui, like E.O. Wilson, views sociology as a branch of biology. In his opinion, the same emotional system controls social, sexual and individual behavior. Such emotional system originates from the neural organization of the brain: emotions are rational and predictable events. Jauregui believes that the brain is a computer, but introduced the novelty of emotions as the direct product of that computer's processing activity. It is emotions, not reason, that directs and informs the daily actions of individuals. Jauregi begins by separating the brain and the self: the brain is aware of what is going on in the digestive system of the body, but will inform the self only when some correction/action is necessary. Normally, an individual is not aware of her digestive processes. Her brain is always informed, though. The communication channel between the brain and the self is made of emotions. The brain can tune the importance of the message by controlling the intensity of the emotions. Far from being an irrational process, the emotional life is mathematically calculated to achieve exactly the kind and level of response needed. Feelings are subjective and inaccessible, but they also are objective and precise. The self has no idea of the detailed process that was going on in the body and of the reason why that process must be corrected. The brain's emotional system, on the other hand, is a sophisticated and complex information-processing system. The brain is a computer programmed to inform the self (through emotions) of what must be done to preserve her body and her society. It is through emotions that the brain informs the self of every single detail in the body that is relevant for survival. There almost is no instant without an emotion that tells the individual to do something rather than something else. "For human beings the reality that ultimately matters is the reality of their feelings". The self keeps a level of freedom: while it cannot suppress the (emotional) messages it receives from the brain, it can disobey them. The brain may increase the intensity of the message as the self disobeys it and a painful conflict may arise. The brain and the self are not only separate, but they may fight each other. In conclusion, only the self can be conscious and feel, but the brain has control of both consciousness and
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Thinking About Thought: Consciousness, Life and Meaning
feelings. If we view the brain as a computer, the hardware is made of the neural organization. There are two types of software, though: bionatural (knowledge about the natural world) and biocultural (such as a language or a religion). A program has three main components: the sensory, the mental and the emotional systems. Any sensory input can be translated automatically by the brain into a mental (idea) or emotional (feeling) message; and viceversa. Both biocultural and bionatural programs exert emotional control over the body. Jauregi distinguishes five systems of communication: the natural system (the sender is a natural thing, such as a tree), the cultural system (the sender is culture, something created by humans), the somatic system (the sender is the individual's own body), the imaginary system (the sender is imagination) and the social system (the sender is another individual). The human brain is genetically equipped to receive and understand all five kinds of messages. What ultimately matters is the emotional translations of sensory inputs. Emotion as Body Representation Similar conclusions are reached by the neurobiological studies of Antonio Damasio, who is focusing on the relation between memory, emotions and consciousness. What is novel about his approach is the distinction between emotions and "feelings". A feeling is a private experience of an emotion, that cannot be observed by anybody else. An emotion is the brain process that we perceive as a feeling. An emotion can be observed by others because it yields visible effects (whether the facial expression or a movement) and because it arises from a brain process that can be observed and measured. The difference is crucial. Emotions are fixed genetically, to a large extent: evolution has endowed us with a basic repertory of emotions that help us survive. My personality (which is mostly shaped by my interaction with the environment) may determine how I express and react to those emotions, but the emotions that occur in me are the same of my whole species. Emotion is a genetically-driven response to a stimulus: when that stimulus occurs (for example, a situation of danger), a region of the brain generates an emotion (fear) that is spread through the brain and the body via the nervous system and therefore causes a change in the state of both the brain and the rest of the body. This change of state is meant to somehow cope with the stimulus. Some emotions are acquired during development (eg, through social interaction) but they too are grounded in the universal, primary emotions of the species. Therefore the relationship between the individual and the environment that has been posited by many thinkers as the cause of emotions is here reduced to the interaction between the body and the brain, which is only indirectly related to the interaction between the organism and the environment. Emotion is, indeed, about homeostatic regulation, is indeed about maintaining equilibrium, but the equilibrium is, more specifically, between external stimuli and internal representations. Feelings, on the contrary, are "perceptions", except that they are a special kind of perceptions. Damasio argues that feelings are views of the body's internal organs. This follows from his view of what the mind is: the mind is about the body. The neural processes that I experience as "my mind" are about the representation of my body in the brain. Mental life requires the existence of a body, and not only because it http://www.thymos.com/tat/emotion.html (6 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
has to be contained in something: mental life "is" about the body. Feelings express this function of the mind. This also explains why we cannot control the feelings of emotions: we can't because we can't change the state of our body, or, better, we can control emotions to the extent that we can change the state of our body that caused that emotion. Of course, that representation of the body is always present in the brain, but it is mostly dormant. It takes a specific stimulus to trigger it and generate an emotion, which in turn will yield a feeling. William James had already argued that feelings are a reflection of a change in the state of the body. Damasio gives it a detailed model: first an external stimulus triggers certain regions of the brain, then those regions cause an emotion, then the emotion spreads around the body and causes a change in the state of the body, and finally the "mind" perceives that change of state as a feeling. Since feelings are percepts, they must be considered as cognitive as any other percept, as cognitive as an image or as a word. Damasio's claim is intuitively true if one considers that the emotional system is spread throughout the body: emotions react to states of all sorts of organs (a huge number of events can trigger an emotion, say, of pain) and operate in turn on all sorts of action, from facial expression to limb movement. Emotions are not only about the brain, they are certainly about the whole body. Somatic markers According to Damasio, the only thing that matters is what goes on in the brain. The brain maintains a representation of what is going on in the body. A change in the environment may result in a change in the body. This is immediately reflected in the brain's representation of the body state. The brain also creates associations between body states and emotions. Finally, the brain makes decisions by using these associations, whether in conjunction or not with reasoning. The brain evolved over millions of years for a purpose: it was advantageous to have an organ that could monitor, integrate and regulate all the other organs of the organism. The brain's original purpose was, therefore, to manage the wealth of signals that represent the state of the body ("soma"), signals that come mainly from the inner organs and from muscles and skin. That function is still there, although the brain has evolved many other functions (in particular, for reasoning). Damasio has identified a region of the brain (in the right, "non-dominant" hemisphere) that could be the place where the representation of the body state is maintained. At least, Damasio's experiments show that, when the region is severely damaged (usually after a stroke), the person loses awareness of the left side of the body. The German neurologist Kurt Goldstein haD noticed in the 1930s that the consequence of right hemisphere lesions is indifference. The brain links the body changes with the emotion that accompanies it. For example, the image of a tiger with the emotion of fear. By using both inputs, the brain constructs new representations that encode perceptual information and the body state that occurred soon afterwards. Eventually, the image of a tiger and the emotion of fear, as they keep occurring together, get linked in one brain event. The brain stores the http://www.thymos.com/tat/emotion.html (7 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
association between the body state and the emotional reaction. That association is a "somatic marker". Somatic markers are the repertory of emotional learning that we have acquired throughout our lives and that we use for our daily decisions. The somatic marker records emotional reactions to situations. Former emotional reactions to similar past situations is just what the brain uses to reduce the number of possible choices and rapidly select one course of action. There is an internal preference system in the brain that is inherently biased to seek pleasure and avoid pain. When a similar situation occurs again, an "automatic reaction" is triggered by the associated emotion: if the emotion is positive, like pleasure, then the reaction is to favor the situation; if the emotion is negative, like pain or fear, then the reaction is to avoid the situation. The somatic marker works as an alarm bell, either steering us away from choices that experience warns us against or steering us towards choices that experience makes us long for. When the decision is made, we do not necessarily recall the specific experiences that contributed to form the positive or negative feeling. In philosophical terms, a somatic marker plays the role of both belief and desire. In biological terms, somatic markers help rank "qualitatively" a perception. In other words, the brain is subject to a sort of "emotional conditioning". Once the brain has "learned" what the emotion associated to a situation, the emotion will influence any decision related to that situation. The brain areas that monitor body changes begin to respond automatically whenever a similar situation arises. It is a popular belief that emotion must be constrained because it is irrational: too much emotion leads to "irrational" behavior. Instead, Damasio shows that a number of brain-damage cases in which a reduction in emotionality was the cause for "irrational" behaviour. Somatic markers help make "rational" decisions, and help making them quickly. Emotion, far from being a biological oddity, is actually an integral part of cognition. Reasoning and emotions are not separate: in fact, they cooperate. Damasio believes that the brain structures responsible for emotion and the ones responsible for reason partially overlap, and this fact lends physical, neural evidence to his hypothesis that emotion and reason cooperate. Those brain structures also communicate directly with the rest of the body, and this suggests the importance of their operations for the organism's survival. Emotion as change of body state The lessons of William James and Antonio Damasio provide a new framework for the study of emotions. There is evidence that specific circuits in the brain are devoted to handling emotions. These regions communicate the "emotion" to the rest of the body via the bloodstream and the nervous system. The effect is to cause a change in the state of the body. So the emotion is really an "amplifier" of a signal that came from either the body itself or from the external world (itself mediated by the senses, which are part of the body). Ultimately, the emotion looks like a loop: a change of state in the body causes an emotion that causes a change of state in the body. http://www.thymos.com/tat/emotion.html (8 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
The consensus is that the state change caused by the emotion is, somehow, a direct response to the state change that caused the emotion. The emotion is trying to maintain the "status quo" in the face of destabilizing news. The emotion is a mechanism to regulate the body, and the regulation is "homeostatic" in nature, i.e. it aims at maintaining a stable state That "stable" state has to do, ultimately, with survival of the organism. All emotions can be reduced to the basic emotions of "pain" and "pleasure", of negative and positive reward. Both pain and pleasure guide the organism towards the actions that maximize its chances of survival. The brain is endowed with another mechanism for survival, the one that we call "cognition". The brain analyze the world and make decisions about it. Emotion and cognition work towards the same goal on parallel tracks. The advantage of emotion over cognition is that it provides a short-cut: instead of analyzing every single stimulus separately, it allows the organism to react to different stimuli with the same action. Fear is the reaction to any kind of danger, even if they are completely different events. Emotion enables similar response to different stimuli, without any need to "think" about it. The disadvantage of emotion is that sometimes the short-cut is not perfect: it may lead us to "over-react". Where does this "short-cut" mechanism come from? If its purpose is survival of the organism, it was probably selected by evolution. Emotion encodes a logic of survival that was developed over the course of the evolution of species. Neurologists like Peter Lang believe that it all started with simple emotions related to brain circuits; that two separate "motivational" systems coexist in the brain, one ("appetitive" system) leading us towards stimuli that cause pleasure, and one ("defensive" system) steering us away from stimuli that cause pain. From these elementary emotions of pleasure and pain, that corresponded to motivations for approach and avoidance, evolved into the varied repertory of emotions of today's humans as the brain's circuitry grew larger and more complex. It is a fact that, evolutionarily speaking, the brain components that preside over emotions are older. First brains started feeling emotions, then they started thinking. Emotion as Memory The more emotions are analyzed from a biological perspective, the more apparent it is that emotion is not a separate subsystem of the mind, but a pervasive feature of it. It has a specific evolutionary function and a crucial role in our daily actions. Emotions are key to learning and behavior, because fear conditioning imprints emotional memories that are quite permanent. The relationship between emotion and memory goes beyond fear, but fear is the emotion that has been studied more extensively. As a matter of fact, fear seems to be a common ground for (at least) all vertebrates. The effects of fear on memory are powerful. John Aggleton has offered a model of how memories about fearful experiences are created in the brain by interactions among the amygdala, the http://www.thymos.com/tat/emotion.html (9 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
thalamus and the cortex. Emotional memory (stored in the amygdala) differs from declarative memory (which is mediated by the hippocampus and the cortex). Emotional memory is primitive, in the sense that only contains simple links between cues and responses. A noise in the middle of the night is enough to create a state of anxiety, without necessarily bringing back to mind full consciousness of what the origin of that noise can be. This actually increases the efficiency (at least the speed) of the emotional response. Emotional and declarative memories are stored and retrieved in parallel. Adults cannot recall childhood traumas because in children the hippocampus has not yet matured to the point of forming conscious memories, but the emotional memory is there. Emotions are the brain's interpretation of reactions to changes in the world. Emotional memories involving fear can never be erased. The prefrontal cortex, amygdala and right cerebral cortex form a system for reasoning that gives rise to emotions and feelings. The prefrontal cortex and the amygdala process a visual stimulus by comparing it with previous experience and generate a response that is transmitted both to the body and to the back of the brain. So the brain contains a reasoning system for the emotional memory and one for the declarative memory, that perform in different manners and use different circuits. It is like saying that we have not one but two brains, that operate in parallel on the same input but may generate completely different output. Darwinian emotions? The amygdala has been recognized as a major center for the creation of emotions. For example, animals whose amygdala was removed showed no emotions. It turns out, though, that the neurons of the amygdala are continuously generating what appear to be emotional states, just like the heart beats all the time. This goes against our belief that emotions are due to our reaction to external stimuli. Instead we seem to be producing emotions all the time, regardless of the external stimuli. Whenever modern Science finds itself in this situation, Darwin's specter arises: are emotions just like antibodies, neurons and thoughts? Are they produced randomly all the time and then the environment (the situation) "selects" which ones have to survive? The Complexity of Emotions Two mysteries remain. The first is relative to consciousness: why do I also have to "feel" the emotion? Couldn't the brain just send a signal to the organs without bothering me? Why am I aware of it? A possibility is that being aware of an emotion means that the self can preempt the mechanic activation of a response in cases in which it would be counterproductive. Sometimes fear or hunger can lead us to actions that we may regret. If we were not aware of our emotions, we would not be able to stop the consequent actions. The second mystery is how did we come to build such complex feelings as, say, love. Love for a child is http://www.thymos.com/tat/emotion.html (10 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
relatively easy to explain. But love for a woman is often a rather contorted and turbulent affair. Most of the emotions we feel during a day would be hard to be categorized as simple "fear" or "love" or "pain". They seem to be grounded on such simple, primitive emotions, but then they exhibit a degree of complexity above that. Are they "evolutionary" consequences of primitive emotions (just like a human brain is the evolutionary consequence of very primitive nervous systems), which are now part of our genetic program, or are they "social" consequences of interaction with other emotional beings: are they innate or acquired? How is a complex emotion formed from more elementary emotions? And, again, one more "why": what is the advantage of building more and more complex emotions? Could it be that more complex emotions express a better balance of reason and instinct? For a theory of emotions I have an inner life, which is not a bodily life. Within this inner life (which is customary to call "mind") different types of things occur. I think. I feel emotions. I dream. As neurophysiologists make progress on the functioning of the brain, it is beginning to appear that there is a difference between emotions and thinking. Emotions are often not desired: they occur because of external stimuli. I don't have much control over them, but they are not spontaneous: I can always relate them to an external event. Emotions have no logical construct, no flow, no time dimension. They simply happen and slowly fade away or change into other emotions: their only dimension is their intensity. The main difference between emotions and thought is that thoughts do have a time dimension and can evolve over time. Thoughts can be controlled: I can decide if I want to think or not, and what I want to think. But they can also be spontaneous, just like emotions. Both emotions and thought result in behavior. Therefore, my behavior is driven by both emotions and thought, by both controlled and non controlled inner behavior. Thought also results in emotions, albeit of a different type (like depression or anxiety). Cognition sort of mediates between emotions and thought. Emotions help organize the world in the mind, and that is what thought operates upon. Each emotion changes the mind and how deeply the emotion changes the mind depends on how intense the emotion is. That "change" is a change in cognition. Thought can also generate a change in cognition, but we can fairly assume that even thought needs to generate an emotion before a meaningful, lasting change is performed on cognition. Basically, we can assume that nothing changes in our mind unless an emotion is created. The emotion is what causes the mind to reorganize itself. If this is indeed the case, then one is faced with the fact that emotion, cognition and thought repeat themselves virtually ad infinitum. Senses cause sensations, which cause cognitive events, which cause thought, which cause higher-level emotions, which cause higher-level cognitive events, which cause thought, which cause even higher-level emotions, etc. The process gets weaker and weaker as it moves higher, and in most cases it actually never reaches the second level (in a significant way, at least). This process is a process similar to resonance that continues virtually forever, although is stops quickly being meaningful, especially if new sensations start another chain of events. http://www.thymos.com/tat/emotion.html (11 of 15)25/07/2003 14:26:42
Thinking About Thought: Consciousness, Life and Meaning
Sometimes the reaction to sensations is almost nil. There is almost no thinking. Nonetheless, emotions play the key role of being preconditions to cognition. The self and free will operate at the level of "thought". Somehow cognition enables not only the "linguistic" form of consciousness which is thought, but also the self-reflection and the initiative that uniquely characterize thought. The question, from an almost evolutionary viewpoint, is whether thoughts are simply an evolution of emotions: language enabled us to control emotion and to develop something equivalent to emotion but more subtle. Or whether they are two different aspects, and they always were different. Free will is an important variable in this equation. There is no doubt that the ability to decide what I do has to play a key role in a definition of thought. But note that free will is almost the opposite of emotions: emotions are beyond "our" control. The machinery of "mind", or "cognition" (memory, learning, reasoning, language), is at the service of our primary inner life: thoughts and emotions (and even dreams). The machinery of "mind" is really a mediator between our primary inner life and our bodily life. I can remember an event, and then feel an emotion or think about that event. Viceversa, I may be thinking of something and recall an event. My inner life needs a physical support to be stored and retrieved. My current inner life needs a physical support to communicate with my previous inner life. The time dimension of thinking is implemented in the physical support. That physical support is the brain. A similar relationship applies to thought and consciousness. There is one skill, capability, that brains have, and there is the feeling associated to it. By "thought" we normally mean the capability of thinking, of putting memories and words and images together. By "consciousness" we really mean (among other things) the feelings associated with thinking. Thought is therefore also a "mediator": between consciousness and the brain. Do emotions need a brain to occur? Presumably they don't need a brain as complex as ours. I feel pain in my foot. I feel anguish in my heart. There really isn't any need for an additional piece of body. We assume that the brain is the place where emotions communicate with the "I", and that would explain why emotions also need a brain. Sensations, feelings and emotions are confusing terms that are often applied to the same things. Some emotions are localized and some emotions are not localized. The pain in my foot is localized, but my fear of death, my career ambitions and my desire of learning are not localized. Most emotions correspond to bodily needs, but some correspond to more abstract entities that have to do with thought itself. You need to be a thinking subject to desire to learn. Career ambitions refer to a vast complex system of values that has been built with thought. Even my fear of death is really a fear of "inner" death, not of bodily death, and therefore refers again to thought.
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Thinking About Thought: Consciousness, Life and Meaning
This distinction may prove essential to an understanding of emotions. Some emotions (let's call them "bodily emotions") are localized and refer to the life of body parts. Some emotions (let's call them "inner" emotions) are not localized and refer to the inner life of thought. If thought is an evolution of emotions, then these are emotions about emotions. Consciousness (inner life): ❍
Linguistic consciousness = Thought
❍
Non-linguistic consciousness = Emotions
❍
Sense-generated emotions (which we will abbreviate as "sensations", a particular type of emotions)
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Thought-generated emotions (which we will abbreviate as "emotions" tout court)
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Dreams
Mind as an evolution of emotions If emotions are the basic constituent of consciousness and they have "evolved" over the millennia, a possible and plausible explanation of where our mind comes from goes like this. The earliest unicellular organisms were capable of irritability and excitability. That is the basic survival tool. The basic sensors of those organisms may have evolved into more sophisticated sensors, capable of more than just binary "good/bad" discrimination: a range of "emotions" was born. If consciousness (to some degree) is ubiquitous in nature, then one can assume that those "emotions" were associated with real emotions, even if they were very limited. Emotions existed from the very beginnings of life, and that it evolved with life. It became more and more complex as organisms became more and more complex. Emotion detects and identifies meaning in the outside world and directs attention to that meaning. A great evolutionary advantage. Early hominids had feelings, although their feelings, while much more sophisticated than the ones of bacteria, were still rather basic, probably limited to fear, pain, pleasure, etc. In mammals and birds emotions were related to sounds (i.e., fear to screaming). Early hominids had a way to express through sounds their emotions of fear and pain and pleasure. Emotions were a factor, a skill, that helped in natural selection. Minds were always busy thinking in very basic terms about survival, about how to avoid danger and how to create opportunities for food.
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What set hominids apart from other mammals was the ability to manufacture tools. We can walk and we can use our hands in ways that no other animal can. The use of tools (weapons, clothes, houses, fire) relieved us from a lot of the daily processing that animals use their minds for. Our minds could afford to be "lazy". Instead of constantly monitoring the environment for preys and predators, our minds could afford to become "lazy". Out of that laziness modern consciousness was born. As mind had fewer and fewer practical chores, it could afford to do its own "gymnastics", rehearsing emotions and constructing more and more complex ones. As more complex emotions helped cope with life, individuals who could generate and deal with them were rewarded by natural selection. Emotions followed a Darwinian evolution of their own. That process is still occurring today. Most animals cannot afford to spend much time philosophizing: their minds are constantly working to help them survive in their environment. Since tools were doing most of the job for us, our minds could afford the luxury of philosophizing, which is really mental gymnastics (to keep the mind in good shape). In turn, this led to more and more efficient tools, to more and more mental gymnastics. As emotions grew more complex, sounds to express them grew more complex. It is not true that other animals cannot produce complex sounds. They cannot produce "our" set of complex sounds, but they could potentially develop sound systems based on their sounds. They don't need sound systems because they don't produce complex emotions. They have the sounds that express the emotions they feel. Human language developed to express more and more complex emotions. The quantity and quality of sounds kept increasing. Language trailed consciousness. This process continues today, and will continue for as long as tools allow more time for our minds to think. The software engineer son of a miner is "more" conscious than her father. And his father was more conscious than his ancestor who was a medieval slave. Consciousness is a product of having nothing better to do with our brain. Further Reading Aggleton John: THE AMYGDALA (Wiley-Liss, 1992) Buck Ross: THE COMMUNICATION OF EMOTION (Guilford Press, 1984) Damasio, Antonio: THE FEELING OF WHAT HAPPENS (Harcourt Brace, 1999) Damasio Antonio: DESCARTES' ERROR (G.P. Putnam's Sons, 1995) Darwin Charles: The Expression of Emotions in Man and Animals (1872) DeSousa Ronald: THE RATIONALITY OF EMOTION (MIT Press, 1987) Ekman Paul: THE NATURE OF EMOTION (Oxford Univ Press, 1994)
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Goldstein Kurt: THE ORGANISM: A HOLISTIC APPROACH TO BIOLOGY (American Book, 1934) James William: PRINCIPLES OF PSYCHOLOGY (1890) Jauregui Jose: THE EMOTIONAL COMPUTER (Blackwell, 1995) Klopf Harry: THE HEDONISTIC NEURON (Hemisphere, 1982) Lane Ricahrd & Nadel Lynn: COGNITIVE NEUROSCIENCE OF EMOTION (Oxford Univ Press, 2000) Lazarus Richard: EMOTION AND ADAPTATION (Oxford Univ Press, 1991) Lazarus Richard & Lazarus Bernice: PASSION AND REASON (Oxford Univ Press, 1994) LeDoux Joseph: THE EMOTIONAL BRAIN (Simon & Schuster, 1996) Mandler George: MIND AND BODY (Norton, 1984) Oatley Keith & Jenkins Jennifer: UNDERSTANDING EMOTIONS (Blackwell, 1996) Ortony Andrew, Clore Gerald & Collins Allan: THE COGNITIVE STRUCTURE OF EMOTIONS (Cambridge Univ Press, 1988 Picard Rosalind: AFFECTIVE COMPUTING (MIT Press, 1997) Wundt Wilhelm: GUNDRISS DER PSYCHOLOGIE (Entgelmann, 1896)
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Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind ` Machine Intelligence (Hilbert, Goedel, Traski, Wiener, Ashby, Shannon, Weaver, Cannon, Brillouin, Turing, Deutsch, Kolmogorov, Chaitin, Searle, Dreyfus, Winograd, Penrose, McCarthy, Winston, Michalski, Mitchell, DeJong, Carbonell, Lenat, Langley, Rosenbloom, Brooks)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Machinery of the Mind Is the mind a machine? And, if it is, can we build one mechanically? The fascination with the idea of building an artificial mind dates from centuries ago. Naturally, before building an artificial mind one must know what kind of machine the human mind is like. The limit to this endeavour seems to be the complexity of the machines we are capable of building. Descartes compared the mind to water fountains, Freud to a hydraulic system, Pavlov to the telephone switchboard and Wiener to the steam engine. Today, our favorite model is the electronic computer. Each of these represented the most advanced technology of the time. The computer does represent a quantum leap forward, because it is the first machine that can be programmed to perform different tasks (unlike, say, dishwashers or refrigerators, which can only perform one task). There is very little similarity between a computer and a brain. They are structurally very different. The network of air conditioning conducts in a high-rise building is far more similar to a brain than the printed circuits of a computer. The main reason to consider the electronic computer a better approximation of the brain is functional, not structural: the computer is a machine that can achieve a lot of what a brain can achieve. But that alone cannot be the only reason, as machines capable of representing data and http://www.thymos.com/tat/machine.html (1 of 17)25/07/2003 14:27:02
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computing data could be built out of biological matter or even crystals. The real reason is still that the computer is the most complex machine we ever built. We implicitly assume that the brain is the most complex thing in the world and that complexity is what defines its uniqueness. Not knowing how it works, we simply look for very complex apparati. Our approach has not changed much since the times of Descartes. We just have a more complex machine to play with. It is likely that some day a more complex machine will come by, probably built of something else, and our posterity will look at the computer the same incredulous way that today we look at Descartes’ water fountains. Human Logic The history of Logic starts with the Greeks. Pythagoras' theorem stands as a paradigm that would influence all of western science: a relationship between physical quantities that is both abstract and eternal. It talks about a triangle, a purely abstract figure which can be applied to many practical cases, and it states a fact that is always true, regardless of the weather, the season, the millennium. Euclides built the first system of Logic when he wrote his "Elements" (around 350 BC). From just five axioms (there is a stright line between two points, a straight line can be extended to infinite, there is a circle with any given center and radius, all right angles are equal, two parallel lines never meet), he could deduct a wealth of theorems by applying the same inference rule over and over again. Then, of course, Aristotle wrote his "Organon" and showed that we employ more than one syllogism (more than one kind of reasoning). After centuries of Roman indifference and of medieval neglect, Logic resumed its course. Studies on logic, from the "Dialectica" of the French philosopher Abelard (800 AD) to the "Introductiones Logicam" of the English philosopher William of Shyreswood (1200 AD), had actually been studies on language. Logic was truly reborn with the "Summa Totius Logicae" of another Englishman, William Ockham (1300 AD), who discussed how people reason and learn. Three centuries later the "Novum Organum" (1620) of Francis Bacon and the "Discours de la Methode" (1937) of Rene' Descartes hailed the analytic method over the dialectic method and therefore started the age of modern Science. The German mathematician Gottfried Leibniz emphasized the fact that reasoning requires symbols in his "De Arte Combinatoria" (1676) and co-discovered calculus with Isaac Newton. In 1761 the Swiss mathematician Leonhard Euler showed how do to symbolic logic with diagrams. The British philosopher John Stuart Mill tried to apply logic outside of science in his "System of Logic" (1843). Nonnumerical algebra was formalized by the British mathematician Augustus De Morgan in "The Foundations of Algebra" (1844).
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Another Englishman, George Boole, was so fascinated by the progress of symbolic logic that in "The Laws Of Thought" (1854) claimed that logic could be applied to thought in general: instead of solving mathematical problems such as equations, one would be able to derive a logical argument. Boole's ideas evolved into "propositional logic" and then "predicate logic", which fascinated philosopher-mathematicians such as Gottlob Frege in Germany, Giuseppe Peano in Italy, Charles Sanders Peirce in the United States, and Bertrand Russell in Britain. Thought became more and more formalized. Frege's "Foundations of Arithmetic" (1884) and "Sense and meaning" (1892), Peano's "Arithmetices Principia Nova Methodo Exposita" (1889), and Russell's "Principia Mathematica" (1903) moved philosophy towards an "axiomatization" of thought. Formal Systems David Hilbert, a German mathematician of the beginning of the 20th century, is credited as first advancing the question of whether a mechanical procedure exists for proving mathematical theorems (in 1928). His goal was to reduce Mathematics to a more or less blind manipulation of symbols through a more or less blind execution of formal steps. Implicit in Hilbert's program was already the idea that such a procedure could be carried out by a machine. The discipline of formal systems was born, with the broad blueprint that a formal system should be defined by a set of axioms (facts that are known to be true) and a set of inference rules (rules on how to determine the truth or falsity of a new fact given the axioms). By applying the rules on the axioms, one could derive all the facts that are true. A formal system employs the language of propositions (statements that can only be true or false and can be combined by binary operators such as "not", "and" and "or") and predicates (statements with a variable that can be quantified existentially or universally, i.e. can be only true or false relative to "at least" one value of the variable or "for every" value of the variable). For example, the fact that Piero Scaruffi is a 45-year old writer could be expressed as: "writer (Piero) AND age (Piero, 45)". The fact that teachers are poor can be expressed with the expression: "FOR EVERY x, teacher (x) -> poor (x)"; that translates as: every individual that satisfies the predicate "teacher" also satisfies the predicate "poor". The fact that some teachers are obnoxious can be expressed as: "FOR AT LEAST ONE x teacher(x) -> obnoxious (x)". The language of Logic is not very expressive but it lends itself to logical reasoning, i.e. deduction. This generation of mathematicians basically pushed logical calculus to the forefront of the tools employed to investigate the world. The apparatus of formal systems became the apparatus that one must use to have any scientific or philosophical discussion. Implicit in their program was the belief that
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the laws of logic "were" the laws of thought. Incompleteness Unfortunately, a number of logical paradoxes refused to disappear, no matter how sophisticated Logic became. All of them, ultimately, are about selfreference. Oldest was the liar's paradox: the sentence "I am lying" is true if false and false if true. Bertrand Russell came up with the brilliant paradox of the class of classes that do not belong to themselves: such a class belongs to itself if it does not belong to itself and viceversa. This paradox is also known as the paradox of the barber who shaves all barbers who do not shave themselves. A variation on these paradoxes is often used to prove the impossibility of an omnipotent God: if God can do anything, can he build a rock that is so heavy that even s/he cannot lift it? Hilbert was already aware of these paradoxes, but several proposals had been made to overcome them. And several more will be proposed later. (An elegant solution to these paradoxes was found in 1986 thanks to John Barwise's "Situation Theory"). Nevertheless, Hilbert and others felt that Logic was capable of proving everything. Hilbert's goal was to find the procedure that would solve all possible problems. By applying that procedure, even non-mathematicians would prove difficult mathematical theorems. Hilbert was aware that, by applying inference rules of Logic to the facts that are known to be true, one could list all the other facts that follow to be true. The power of Logic seemed to be infinite. It made sense to imagine that Logic was capable of proving anything. The dream of a purely mechanical procedure for solving mathematical problems was shattered by yet another paradox, the one known as Goedel's theorem. In 1931 the (Czech-born) Austrian mathematician Kurt Goedel proved that any formal system (containing the theory of numbers, i.e. arithmetics) contains a proposition that cannot be proved true or false within that system (i.e., an "undecidable" proposition). Intuitively, Goedel's reasoning was that the statement "I cannot be proved" is true if and only if it cannot be proved; therefore in every system there is always at least one statement that cannot be proved, the one that says "I cannot be proved". Neither the proposition nor its negation can be proved within the system. We can't know whether it is true or false. Predicate Logic, for example, is undecidable. Therefore any formal system built on Predicate Logic happens to be built on shaky foundations. And that includes pretty much all of classical
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Logic. The conclusion to be drawn from Goedel’s theorem is catastrophic: the very concept of truth cannot be defined within a logical system. It is not possible to list all the propositions that are true. Hilbert had reduced Logic to a mechanical procedure to generate all the propositions that can be proven to be true in a theory. The dual program, of reducing Logic to a mechanical procedure to prove theorems (to prove if a proposition is true), is impossible because of Goedel’s theorem (since it is not always possible to prove that a proposition is true). This came to be known as the "decision problem". Note that Hilbert was looking for an "algorithm" (a procedure), not a formula. For centuries most of science and mathematics had focused on formulas. The mighty apparatus of Physics was built on formulas. All natural sciences were dealing with formulas. Hilbert, indirectly, started the trend away from formulas and towards algorithms, a trend that would become one of the silent leitmotivs of this century. A formula permits to compute a result directly from some factors by applying mathematical operations in the sequence prescribed by the priority rules of operators. An algorithm prescribes a step-by-step procedure for achieving the result. It is made of finite steps, and the steps are ordered. Each step can be a mathematical operation or a comparison or a change in the sequence of steps. Each step can be conceived of as an "instruction" to an ideal machine capable of carrying out those elementary steps. Truth and Meaning One more notion was necessary to complete the picture: meaning. What did all this mean in the end? Aristotle had realized the importance of "truth" for logical reasoning and had offered his definition: a proposition is true, if and only if it corresponds with the facts. This is the "correspondence theory of truth". Frege had founded Logic on truth: the laws of logic are the laws of truth. Truth is Frege's unit of meaning. In fact, it was Frege who introduced "true" and "false", the so called "truth values". Frege regarded logical propositions as expressing the application of a concept to an object, as in "author(piero)" that states that Piero is an author. Indirectly, he partitioned the universe into concepts and objects, equated concepts with mathematical functions and objects with mathematical terms. The proposition "Piero is an author" has a concept "author" that is applied to a term "Piero". All of this made sense because, ultimately, a proposition was either true or false, and that could be used to think logically. According to Aristotle, this proposition is true, than its meaning is that the person referred to as Piero is an author; and vicevera.
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Hilbert had taken this course of action to the extreme consequences. Hilbert had emancipated Logic from reality, by dealing purely with abstractions. In 1935 the Polish mathematician Alfred Tarski grounded Logic back into reality. He gave "meaning" to the correspondence theory of truth. Logic is ultimately about truth: how to prove if something is true or false. But what is "truth"? Tarski was looking for a definition of "truth" that would satisfy two requirements, one practical and one formal: he wanted truth to be grounded in the facts, and he wanted truth to be reliable for reasoning. The second requirement was easily expressed: true statements must not lead to contradictions. The first requirement was more complicated. How does one express the fact that "Snow is white" is true if and only if snow is white? Tarski realized that "snow is white" is two different things in that sentence. They are used at different levels. A proposition p such as "snow is white" means what it states. But it can also be mentioned in another sentence, which is exactly the case when we say that "p is true". The fact that "p" is true and the sentence "p is true" are actually two different things. The latter is a "meta-sentence", expressed in a metalanguage. In the metalanguage one can talk about elements of the language. The liar's paradox, for example, is solved because "I am lying" is a sentence at one level and the fact that I am telling the truth when I am lying is a sentence at a different level; the contradiction is avoided by considering them at two different levels (language and metalanguage). Tarski realized that truth within a theory can be defined only relative to another theory, the metatheory. In the metatheory one can define (one can list) all the statements that are true in the theory. Tarski introduced the concepts of "interpretation" and "model" of a theory. A theory is a set of formulas. An interpretation of a theory is a function that assigns a meaning (a reference in the real world) to each of its formulas. Every interpretation that satisfies all formulas of the theory is a model for that theory. For example, the formulas of Physics are interpreted as laws of nature. The universe of physical objects becomes a model for Physics. Ultimately, Tarski’s trick was to build models of the world which yield interpretations of sentences in that world. The important fact is that all semantic concepts are defined in terms of truth, and truth is defined in terms of satisfaction, and satisfaction is defined in terms of physical concepts. The meaning of a proposition turns out to be the set of situations in which it is true. What Tarski realized is that truth can only be relative to something. A concept of truth for a theory (i.e., all the propositions that are true in that theory) can be defined only in another theory, its "meta-theory", a theory of that theory. All paradoxes, including Goedel’s, can then be overcome, if not solved. Life goes on.
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Tarski grounded meaning in truth and in reference, a stance that would set the stage for a debate that is still ongoing. The Turing Machine The two great visionaries of computation, the British mathematician Alan Turing and the Hungarian mathematician John Von Neumann, had a number of influential ideas. Among the many, in 1936 Turing formalized how a machine can perform logical calculus, and, a few years later, Von Neumann explored the possibility that a machine could be programmed to make a copy of itself. In other words, Turing laid the foundations for the discipline of building an intelligent machine, and Von Neumann laid the foundations for the discipline of building a self-reproducing machine. Turing defined computation as the formal manipulation of symbols through the application of formal rules (Hilbert's view of Logic), and devised a machine that would be capable of performing any type of computation (Hilbert's dream). Hilbert's ideas can be expressed in terms of mathematical "functions". A predicate can always be made correspond to a function. For example, "age (Person,Number)" corresponds to the function "Number= age(person)"; and viceversa. The advantage of using functions instead of predicates is that it is easier to manipulate functions than predicates. For example, the American mathematician Alonzo Church showed how two functions can be compared. A function can be defined in an "extensional" way (the pairs of input and output values) or in an "intensional" way (the computational procedure it performs). Comparing two extensional definitions can take forever (there can be infinite pairs of inpur and output). In order to compare two intensional definitions, Church invented the "Lambda abstraction", which provides rules to transform any function in a canonical form. Once they are in canonical form, two functions can be easily compared. In the language of functions, Hilbert's goal was to find a mechanical procedure to build all computable (or "recursive") functions. So a recursive function is defined by an algorithm, which in turn can be implemented by a computer program. Recursive functions correspond to programs of a computer. Not surprisingly, it turns out that a predicate is decidable (can be proved true or false) if and only if the corresponding function is recursive, i.e. computable. Turing realized this and, when he set himself to find a mechanical procedure to perform logical proofs, he basically set himself to invent the computer (at least conceptually). His thought experiment, the "Turing Machine", is the algorithm that Hilbert was looking for, and it turns out it is also the general algorithm that computers carry out every day.
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A Turing Machine is capable of performing all the operations that are needed to perform logical calculus: read current symbols, process them, write new symbols, examine new symbols. Depending on the symbol that it is reading and on the state in which it is, the Turing machine decides whether it should move on, turn backwards, write a symbol, change state or stop. Turing's machine is an automatic formal system: a system to automatically compute an alphabet of symbols according to a finite set of rules. Church argued that everything that is computable in nature can be computed with a Turing machine. But there can be infinite Turing machines, depending on the rules to generate new symbols. So Turing described how to build a machine that would simulate all possible Turing machines. The "universal Turing machine" is a Turing Machine capable of simulating all possible Turing Machines. It contains a sequence of symbols that describes the specific Turing machine that must be simulated. For each computational procedure, the universal machine is capable of simulating a machine that performs that procedure. The universal machine is therefore capable of computing any computational function. In other words, since the universal Turing machine is a machine capable of performing any other machine, it is capable of solving all mathematical problems. A computer is nothing but a Turing machine with a finite memory. When Von Neumann neatly divided the data from the instructions ( instructions are executed one at the time by the "processor" and they operate on data kept in a "memory"), he simply interpreted for engineers the concepts of the universal Turing machine: a computer can solve any problem if it is fed the appropriate program. That architecture was to become the architecture of the computer and today’s sequential computers (the most common varieties) are still referred to as "Von Neumann architectures". Ultimately, Turing reduced Hilbert’s program to manipulation of symbols: logic is nothing more than symbol processing. Indirectly, he turned the computer into the culminating artifact of Hilbert’s formal program. Turing showed that rational machines are feasible. Furthermore, he showed that one can build a rational machine that can perform "any" rational task. Incidentally, the physicist David Deutsch has recently (1985) generalized Turing's ideas and defined a "quantum" machine in which Turing states can be linear combinations of states. The behavior of a quantum machine is a linear combination of the behavior of several Turing machines. A quantum machine can only compute recursive functions, just like Turing's machine, but it turns out to be much faster in solving problems that exhibit some level of parallelism. In a sense, a quantum computer is capable of decomposing a
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problem and delegating the sub-problems to copies of itself in other universes. Cybernetics Cybernetics is the science of control and communication. Cybernetics was born out of the passion and excitement generated by the spread of complex mechanical and electrical machines, whose functioning was largely based on control processes. Cybernetics found similarities between some of those processes and some biological processes. The concepts introduced by cybernetics built a bridge between machines and nature, between "artificial" systems and natural systems. For example, most machines employ one type of feedback or another. Feedback, by sending back the output as an input, helps control the proper functioning of the machine. The self-regulatory character of the human nervous system had been emphasized since the 1920s by the Russian physiologist Nicholas Bernstein. He concluded that, given the complexity of the human motor system, movement could not possibly be "commanded" by a central processor. Instead, he thought that movement was achieved by continually analyzing sensory inputs and adjusting motor output consequently. When I extend the arm to grab something, I have not computed exactly the trajectory and speed of my movement, I am recomputing it every second as my arm approaches the object. There is no computer in the brain that calculates the exact trajectory for the arm and the hand and the fingers in order to reach the glass. There is a continuous dialogue between the senses and the arm, the hand and the fingers, so that the trajectory is adjusted as motion proceeds. The American mathematician Norbert Wiener (who founded Cybernetics in 1947) first recognized the importance of "feedback" (a term that he coined) for any meaningful behavior in the environment: a system that has to act in the environment must be able to continuously compare its performed action with the intended action and then infer the next action from their difference. This is what all living organisms do all the time in order to survive. Feedback is the action of feeding a system its past performance. Given past performance, the system can adjust future performance. All systems in nature (animals, plants, ecosystems, etc) exhibit feedback. Feedback is the basis of life. As Bernstein had asserted, we could not even coordinate our limbs if we were not capable of using feedback. Feedback is crucial for "homeostasis", the phenomenon (described in the 1930s by the American biologist Walter Cannon) by which an organism tends to compensate variations in the environment in order to maintain its internal stability; i.e., by which an organism adapts to the environment. Homeostasis
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consists in environment temperature temperature survival.
maintaining a constant internal state in reaction to the and through action on the environment. For example, body is controlled by perspiring and shivering (one lowers the and the other one increases it). And homeostasis is crucial for
Given the number of factors that must be taken into account for any type of action in the real world, it is not surprising that the brain evolved to use feedback, rather than accurate computation, to guide motion. It is not a coincidence that feedback turns out to be as crucial also for the performance of machines in their environment. From James Watt’s steam engine on, machines have been designed so as to be able to control themselves. A control system is a system that uses feedback to achieve some kind of steady state. A thermostat is a typical control system: it senses the temperature of the environment and directs the heater to switch on or off; this causes a change in the temperature, which in turn is sensed by the thermostat; and so forth. This loop of action and feedback, of sensing and controlling, realizes a control system. A control system is therefore capable of achieving a "goal", is capable of "purposeful" behavior. Living organisms are control systems. Most machines are also control systems. Next, Wiener emphasized that communication in nature is never perfect: every message carries some involuntary "noise" and in order to understand the communication the original message must be restored. This led to a statistical theory of amount of information. Wiener understood the essential unity of communication, control and statistical mechanics, which is the same whether the system is an artificial system or a biological system. This unified discipline became "Cybernetics". A cybernetic system is a system that achieves an internal homeostatic control through an exchange of information between its parts. The British neurologist Ross Ashby also placed emphasis on feedback. Both machines and living beings tend to change to compensate variations in the environment, so that the combined system is stable. For living beings this translates into "adaptation" to the environment. The "functioning" of both living beings and machines depends on feedback processes to the extent that feedback allows the system to self-organize. Ashby emphasized the power of self-organizing systems, systems made of a very high number of simple units which can evolve autonomously and adapt to the environment by virtue of their structure. Ashby believed that in every isolated system subject to constant forces "organisms" arise that are capable of adapting to their environment. As his
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principle of self-organization ambitiously states: "in any isolated system, life and intelligence inevitably develop". The American electrical engineer William Powers extended these ideas to a hierarchical organization of control systems. First of all, he realized that a control system controls what it senses: it controls its input (the perception), not its output (the behavior). A thermostat controls the temperature, not the gas consumed by the heater. Organisms change their behavior, but they do it in order to control a perception. Behavior is the control of perception. Next, he envisioned a system which is made of a pyramid of control systems, each one sending its output to some "lower-level" control systems. The lowest level in the hierarchy is made of control systems that use sensors to sense the environment and effectors to act on the environment, and some "reference level" to determine what they have to maintain constant. For example, a thermostat would sense the environment's temperature, effect the heater and maintain constant the measured temperature. At a higher level, a control system senses and effects the reference level of lower-level control systems. An engine could direct a thermostat to maintain a certain temperature. The reference level of the lower level is determined by the control systems of the higher level. Living organisms are made of such hierarchies of control systems. "Instinctive" behavior is the control system (organized in a hierarchy) that the organism inherits at birth. They determine internally what parameters have to be maintain constant, and at which magnitude. Behavior is a backward chain of behaviors: walking up the hierarchy one finds out why the system is doing what it is doing (e.g., it is keeping the temperature at some many degrees because the engine is running at so many RPMs because… etc etc). The hierarchy is a hierarchy of goals (goals that have to be achieved in order to achieve other goals in order to achieve other goals in order to…) This hierarchy inevitably extends outside the system and into the environment. A machine is part of a bigger machine which is part of a factory which is part of an economy which is part of a society which is part… The goal of a component of the machine is explained by a chain of higher-level goals that extend into society. In the case of living organisms, the chain of goals extends to their ecosystem, and ultimately to the entire system of life. Algorithms and Automata Cybernetics implied a paradigm shift from the world of continuous laws to the world of algorithms. Physical sciences had been founded on equations that were continuous, but Cybernetics could not describe any feedback-based process with one continuous equation. The most natural way to describe such a process was to break it down into the sequence of its constituent steps, one of which refers ("feeds back") to a previous one. Every mechanical process http://www.thymos.com/tat/machine.html (11 of 17)25/07/2003 14:27:02
Thinking About Thought: Consciousness, Life and Meaning
could then be interpreted as a sequence of instructions that the machine must carry out. Indirectly, the complex clockwork of a watch is carrying out the sequence of instructions to compute the time. The watch is, in a sense, an automaton that performs an algorithm to compute the time. The effect of an algorithm is to turn time’s continuum into a sequence of discrete quanta, and, correspondingly, to turn an analog instrument into a digital instrument. A watch, for example, is the digital equivalent of a sundial: the sundial marks the time in a continuous way, the watch advances by seconds. The digital world (of discrete quantities) differs from the analog world (of continuous quantities) in a fundamental way when it comes to precision. An analog instrument can be precise, and there is no limit to its precision. A digital instrument can only be approximate, its limit being the smallest magnitude it can measure (seconds for a watch, millimeters for a ruler, centigrades for a thermometer, etc.). For the purpose of "recognizing" a measurement, though, a digital reading is often better: while two analog values can be so close that they can be confused, two digital values are unambigously either identical or different. In the context of continuous values, it is difficult to decide whether a value of 1.434 and a value of 1.435 should be considered as the same value with a little noise or two different values; whereas in the context of binary values (the binary universe being a special case of digital universe), a value is unambigously either zero or one. This feature has been known even before compact discs replaced vinyl records (the Morse code was an early application of the concept). An analog instrument will probably never measure a one as a one or a zero as a zero (it will yield measurements that are very close to one or very close to zero), whereas a digital instrument cannot measure anything else than a zero or a one because its scale does not have any other value (e. g., a digital watch cannot measure 0.9 seconds because its scale is in seconds). This limitation often translates into an advantage. What is implicit in a cybernetic scenario is that the world is driven by algorithms, rather than by continuous physical laws. Similar conclusions were reached in Linguistics (Chomsky’s generative grammar is run by an algorithm) and in Cognitive Ccience (a production system is run by an algorithm). An algorithm is a deterministic process in the form of a sequence of logical steps. A computer program simply implements an algorithm. Reducing the laws of nature to algorithms is like reducing Nature to a world of automata. Information Theory Since 1949, when they published their influential book, the electrical engineer Claude Shannon and Warren Weaver worked to free the physicists' definition of entropy from its thermodynamic context and apply it to Information Theory. They defined entropy (which is often taken as a measure http://www.thymos.com/tat/machine.html (12 of 17)25/07/2003 14:27:02
Thinking About Thought: Consciousness, Life and Meaning
of disorder) as the statistical state of knowledge about a question: the entropy of a question is related to the probability assigned to all the possible answers to that question. Shannon's entropy measures the uncertainty in a statistical ensemble of messages. The second law of Thermodynamics, one of the fundamental laws of the universe, responsible for our dying among other things, states that an isolated system always tends to maximize its entropy (i.e., things decay). Since entropy is a measure of the random distribution of atoms, maximizing it entails that the distribution has to become as homogeneous as possible. The more homogeneous, the less informative a distribution of probabilities is. Therefore, entropy, a measure of disorder, is also a measure of the lack of information. Leon Brillouin explored further into the relationship between information and entropy, with his "negentropy principle of information". He defined information as the amount of uncertainty which exists before a choice is made. Information turns out to be the difference between the entropy of the observed state of the system and its maximum possible entropy. The more information was assimilated in the thermodynamic jargon, the more scientists were able to formulate predications and deterministic laws about it. For example, Brillouin proved that the minimum entropy cost for obtaining one bit of information is 10 to the -23 joules per degree K. In summary, a theory of information turns out to be the dual of a theory of entropy: if information is ultimately a measure of order, entropy is ultimately a measure of disorder, and, indirectly, a measure of the lack of information. Whether unifying machine processes and natural processes, or unifying quantities of Information Theory and quantities of Thermodynamics, the underlying theme was that of finding commonalties between artificial systems and natural systems. This theme caught up speed with the invention of the computer. Algorithmic Information Theory "Algorithmic Information Theory", as formulated in the 1960s by the Russian mathematician Andrei Kolmogorov, is a scientific study of the concept of complexity. Complexity is basically defined as quantity of information, which means that Algorithmic Information Theory is the discipline that deals with the quantity of information in systems. The complexity of a system is defined as the shortest possible description of it; or, equivalently, the least number of bits of information necessary to describe the system. It turns out that this means: "the shortest algorithm that can simulate it"; or, equivalently, as the size of the shortest program
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Thinking About Thought: Consciousness, Life and Meaning
that computes it. For example, the complexity of "pi" is the ratio between a circumference and its diameter. The emphasis is therefore placed on sequences of symbols that cannot be summarized in any shorter way. Algorithmic Information Theory looks for the shortest possible message that encodes everything there is to know about a system. Objects that contain regularities have a description that is shorter than themselves. Algorithmic Information Theory represents an alternative to Probability Theory when it comes to study randomness. Probability Theory cannot define randomness. Probability Theory says nothing about the meaning of a probability: a probability is simply a measure of frequency. On the other hand, randomness can be easily defined by Kolmogorov: a random system is one that cannot be compressed. Incidentally, every system has a finite complexity because of the Bekenstein bound. In Quantum Theory the Bekenstein bound (due to the physicist Jacob Bekenstein) is a direct consequence of Heisenberg’s uncertainty principle: there are upper limits on the number of distinct quantum states and on the rate that changes of state can occur. In other words, the principle of uncertainty indirectly sets an upper limit on the information density of a system, and that upper limit is expressed by the Bekenstein bound. Physicists seem to be fascinated with the idea of quantifying the complexity of the brain and even the complexity of a human being. Frank Tipler estimated the storage capacity of the human brain at 10 to the 15th power and the maximum amount of information stored in a human being at 10 to the 45th power (a number with 45 zeros). Freeman Dyson computed the entropy of a human being at 10 to the 23th. Another important concept is that of "randomness". A random sequence is one that cannot be compressed any further. Gregory Chaitin proved that randomness is pervasive. His "Diophantine" equation contains 17,000 variables and a parameter which can take the value of any integer number. By studying it, Chaitin achieved a result as shocking as Goedel's theorem: there is no way to tell whether, for a specific value of the parameter, the equation has a finite or infinite number of solutions. That means that the solutions to some mathematical problems are totally random. Artificial Intelligence
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading
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Thinking About Thought: Consciousness, Life and Meaning
Arbib Michael: METAPHORICAL BRAIN (Wiley, 1972) Arbib Michael: METAPHORICAL BRAIN 2 (Wiley, 1989) Arbib Michael: BRAINS MACHINES AND MATHEMATICS (Springer Verlag, 1987) Ashby Ross: DESIGN FOR A BRAIN (John Wiley, 1952) Barr Avron & Feigenbaum Ed: HANDBOOK OF ARTIFICIAL INTELLIGENCE (William Kaufmann, 1982) Bernstein Nicholas: GENERAL BIOMECHANICS (1926) Boden Margaret: PHILOSOPHY OF ARTIFICIAL INTELLIGENCE (Oxford, 1990) Brillouin Leon: SCIENCE AND INFORMATION THEORY (Academic Press, 1962) Brooks Rodney & Luc Steels: THE ARTIFICIAL LIFE ROUTE TO ARTIFICIAL INTELLIGENCE (Lawrence Erlbaum, 1995) Cannon Walter: THE WISDOM OF THE BODY (Norton, 1939) Carbonell Jaime: MACHINE LEARNING (MIT Press, 1989) Charniak Eugene: ARTIFICIAL INTELLIGENCE PROGRAMMING (Lawrence Erlbaum, 1987) Cohen Fred: IT'S ALIVE (Wiley, 1994) Dreyfus Hubert: WHAT COMPUTERS CAN'T DO (Harper & Row, 1979) Dreyfus Hubert & Dreyfus Stuart: MIND OVER MACHINE (Free Press, 1985) Feigenbaum Edward: COMPUTERS AND THOUGHT (MIT Press, 1995) Frost Richard: INTRODUCTION TO KNOWLEDGE BASED SYSTEMS (MacMillan, 1986) Genesereth Michael & Nilsson Nils: LOGICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE (Morgan Kaufman, 1987) Graubard Stephen: THE ARTIFICIAL INTELLIGENCE DEBATE (MIT Press, 1988) Hofstadter Douglas: GOEDEL ESCHER BACH (Vintage, 1980) Holland John Henry: ADAPTATION IN NATURAL AND ARTIFICIAL SYSTEMS (MIT Press,
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1992) Koza John: GENETIC PROGRAMMING (MIT Press, 1992) Langton Christopher: ARTIFICIAL LIFE (MIT Press, 1995) Levy Steven: ARTIFICIAL LIFE (Pantheon, 1992) Li Ming & Vitanyi Paul: AN INTRODUCTION TO KOLMOGOROV COMPLEXITY (SpringerVerlag, 1993) Luger George: COMPUTATION AND INTELLIGENCE (MIT Press, 1995) Maes Patti: DESIGNING AUTONOMOUS AGENTS (MIT Press, 1990) Michalski Ryszard, Carbonell Jaime & Mitchell Tom: MACHINE LEARNING I (Morgan Kaufman, 1983) Michalski Ryszard, Carbonell Jaime & Mitchell Tom: MACHINE LEARNING II (Morgan Kaufman, 1986) Newell Allen & Simon Henry: HUMAN PROBLEM SOLVING (Prentice-Hall, 1972) Nilsson Nils: THE MATHEMATICAL FOUNDATIONS OF LEARNING MACHINES (Morgan Kaufmann, 1990) Nilsson Nils: PRINCIPLES OF ARTIFICIAL INTELLIGENCE (Tioga, 1980) Pearl Judea: HEURISTICS (Addison Wesley, 1984) Powers William: BEHAVIOR: THE CONTROL OF PERCEPTION (Aldine, 1973) Rucker Rudy: INFINITY AND THE MIND (Birkhauser, 1982) Russell Stuart Jonathan: THE USE OF KNOWLEDGE IN ANALOGY AND INDUCTION (Pitnam, 1989) Russell Stuart Jonathan & Norvig Peter: ARTIFICIAL INTELLIGENCE (Prentice Hall, 1995) Searle John: THE REDISCOVERY OF THE MIND (MIT Press, 1992) Shannon Claude & Weaver Warren: THE MATHEMATICAL THEORY OF COMMUNICATION (Univ of Illinois Press, 1949)
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Shapiro Stuart Charles: ENCYCLOPEDIA OF ARTIFICIAL INTELLIGENCE (John Wiley, 1992) Simon Herbert Alexander: MODELS OF THOUGHT (Yale University Press, 1979) Simon Herbert Alexander: THE SCIENCES OF THE ARTIFICIAL (MIT Press, 1969) Tarski Alfred: LOGIC, SEMANTICS, METAMATHEMATICS (Clarendon, 1956) Turing Alan: PURE MATHEMATICS (Elsevier Science, 1992) Turing Alan: MECHANICAL INTELLIGENCE (Elsevier Science, 1992) Von Neumann John: THE COMPUTER AND THE BRAIN (Yale Univ Press, 1958) Von Neumann John: THEORY OF SELF-REPRODUCING AUTOMATA (Princeton Univ Press, 1947) Wiener Norbert: CYBERNETICS (John Wiley, 1948) Winograd Terry & Flores Fernando: UNDERSTANDING COMPUTERS AND COGNITION (Ablex, 1986)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Language: What We Speak (Whorf, Nelson, Vygotsky, De Saussure, Chomsky, Pinker, Jackendoff, Lenneberg, Deacon, Lieberman, Fillmore, Dowty, Schank, Katz, Gazdar, Montague, Wierzbicka, Langacker, Fauconnier, Peirce, Morris, Preto, Thom, Gregory, Dennett, Hoffmeyer, Sebeock, Fetzer)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Hidden Metaphysics of Language Language is obviously one of the most sophisticated cognitive skills that humans possess, and one of the most apparent differences between the human species and other animal species. No surprise, then, that language is often considered the main clue to the secrets of the mind. After all, it is through language that our mind expresses itself. It is with language that we can study the mind. A few scientists believe that language is even more than a tool to speak: it is "thought" itself. In the 1950's, the American linguist Benjamin Lee Whorf extended the view of his teacher, the German-born Edward Sapir, that language and thought influence each other. Language is used to express thought, but language also shapes thought. In particular, the structure of the language has an influence on the way its speakers understand the environment. Language influences thought because it contains what Sapir had called "a hidden metaphysics", which is a view of the world, a culture, a conceptual system. Language contains an implicit classification of experience. Whorf restated Sapir's view in his principle of "linguistic determinism": grammatical and categorial patterns of language embody cultural models. Every language is a culturally-determined system of patterns that creates the categories by which individuals not only communicate but also think. The American psychologist Katherine Nelson, whose studies focus on the stages of cognitive development in a child, has discovered that language is crucial to the formation of the adult mind: language acts as the medium through which the mind becomes part of a culture, through which the shared meanings of society take over the individualistic meanings of the child's mind. Society takes over the individual mind, and it does so through language. The ultimate goal of our mind, since we were born, through our studying, working, making friends, writing books, etc., is to be social. http://www.thymos.com/tat/language.html (1 of 19)25/07/2003 14:27:22
Thinking About Thought: Consciousness, Life and Meaning
This brings back to mind Lev Vygotsky's theory of the mediating language: that language provides a semiotic mediation of knowledge and therefore guides the child's cognitive growth. In general, cognitive faculties are internalized versions of social processes. This also implies, incidentally, that cognition developed in different ways depending on the cultural conditions. Human language and animal language It is often claimed that language is "the" exclusive feature of humans. Language is actually quite widespread in Nature in its primitive form of communication (all animals communicate and even plants have some rudimentary form of interaction), although it is certainly unique to humans in its human form (but just like, say, chirping is unique to birds in its "birdy" form). Is human language really so much more sophisticated than other animals' languages? Birds and monkees employ a sophisticated system of sounds to alert of intruders. The loudness and the frequency are proportional to the distance and probably to the size of the intruder. Human language doesn't have such a sophisticated way of describing an intruder. Is it possible that human language evolved in a different way simply because we became more interested in other things, than in describing the size and distance of an intruder? Language is very much a mirror image of the cognitive capabilities of the animal. One can notice that there are three levels of human language: the "what", the "where", the "why". What are you doing is about the present. Where are you going is about the future. Why are you going there is about the relationship between past and future. These are three different steps of communication. Organisms could communicate simply in the present, by telling each other what they are doing. This is what most machines do all the time when they get connected. Living organisms also move. Bees dance to other bees in order to communicate the position of a location. Humans certainly exploit motives all the time. Without a motive a description is incomplete. It is common in Southeast Asia to greet people by asking "what are you doing?" The other person will reply "I am rowing the boat". The next question will be "where are you going?"And the last question will be "why are you going there?" With these three simple questions the situation has been fully analyzed, as far as human cognition goes. This does not mean that there could not be a fourth level of communication, that we humans simply don't exhibit because it is beyond our cognitive capabilities. There are other features that are truly unique to humans: clothes, artifacts, and, first and foremost, fire. Have you ever seen a lion wear the fur of another animal? light a fire to warm up? build a utensil to scratch its back? Why humans do all of these things? Are they a consequence of our cognitive life, or is our cognitive life a consequence of these skills? Language creates the mind http://www.thymos.com/tat/language.html (2 of 19)25/07/2003 14:27:22
Thinking About Thought: Consciousness, Life and Meaning
Two questions remain. The first one is: where does language come from? We can answer the first question by relating these findings to neurobiologists such as Gerald Edelman who believe that a mind is a particular set of connections in the brain: if language changes the mind, then it must be capable of changing the connections in the brain. Why would it do that? Because, as Baldwin noticed, species capable of learning are better at evolving. If language is such an efficient tool for learning that shapes an entire system of thought in a few years, then it must certainly be useful to survival and evolution. Language is more than just sound. Language is sound (or vision, when you are reading) with a structure, and therefore packs more information than just sound. This was a crucial invention: that you can use sound as a vehicle to carry more information than the sound itself. The tip probably came from Nature itself: Nature speaks to us all the time. The noise of a river or the noise of an avalanche create concepts in our minds, besides the representation of those sounds. Brain connections are modified at two levels: first to reflect the stimuli of the noise, and then to reflect what we can derive from the noise. Our brain can learn at two levels: there is a noise in that direction, and it is a river (meaning, for example, water to drink). Stimuli modify connections both at the level of perception and at the level of concepts. Languageexploits this simple fact. (Yes, the same is true of cinema, but our bodies are not equipped with an organ to make images the way we are equipped with an organ to make sounds, and the invention of writing required a lot less technological knowledge than television or cinema, but in the future we may end up carrying our portable image-maker so that we can show what happened in images instead of telling it in words). The second question is: how does language do what it does to our brain connections? The answer may be that we are more poets than we think: in order to deliver feelings, poets use a vehicle called "metaphor". Metaphor is more pervasive than we think, and it may well be the foundation of language (some linguists even claim that all language is metaphorical). Metaphor is a powerful tool to shape a mind because it finds "connections" between things in the mind and the new connections enable the mind to "see" the world differently. A lot of studies have been done on the way the mind creates language, from Chomsky's grammars to neurolinguistics. Unfortunately, very few studies follow the opposite direction: how does language create the mind (not from mind to language, but from language to mind). Anomalies of Language How we learn language, how we generate sentences and how we understand them are still largely unexplained phenomena. Language is more than just sounds. Language has a structure, and carries meaning. The structure of any natural language is so complex that no machine has been able to fully master one yet. We really do not know how a child can learn a language at all. Its complexity should make it impossible at the outset.
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If we analyze the way language works, we can draw two opposite conclusions: on one hand, the power of language looks overwhelming, on the other, its clumsiness is frustrating. On one hand, we know that on average western languages are about 50% redundant: we would not lose any expressive power if we gave up 50% of our language. We can guess the meaning of most sentences from a fragment of them. We also know that professional translators are able to translate a speech with minimal or no knowledge of the topic the speech is about. On the other hand, we tend to believe that humans have developed amazing capabilities for communicating: language, writing, even television, but the truth is that human communication is rather inefficient: two computers can simply exchange in a split second an image or a text, pixel by pixel or character by character, without any loss of information, whereas a human must describe to another human the image in a lengthy way and will certainly miss some details. Two computers could even exchange entire dictionaries, in the event they do not speak the same language. They could exchange in a few seconds their entire knowledge. Humans can only communicate part of the information they have, and even that takes a long time and is prone to misunderstandings. Furthermore, why is it that we can accurately describe a situation, but not our inner life of emotions? Language is so rich when it comes to the external world, but so poor and inefficient when it comes to my inner life. Generative Grammar We can't even define what a language is. What is the English language? Nobody has a definition for the English language. If you want to find out whether a word is English or not, you have to check a dictionary and hope that the author of that dictionary did not miss any word (in fact, almost all of them do miss some words). If you want to find out whether a sentence is English, the single words are not enough. A foreign word can actually show up in an English sentence. For example, "bambino is not an English word" is a perfectly valid English sentence that everybody understands. Even words that are not words in any language can figure in an English sentence: "xgewut is not a meaningful word" is an English sentence. What makes a sentence English? At the turn of the 19th century, the Swiss linguist Mongin-Ferdinand De Saussure was asking precisely this kind of questions. He distinguished the "parole" (an actual utterance in a language) from the "langue" (the entire body of the language), and set out to study the latter. Building on those foundations, in 1957 the American linguist Noam Chomsky started a conceptual revolution. He was reacting to "structural" linguists, who were content with describing and classifying languages, and to behaviorists, who thought that language was learned by conditioning. At the time, all scientific disciplines were being influenced by a new propensity towards formal thinking that had its roots as much in Computer Science as in Hilbert's program in Mathematics. Chomsky extended the idea of formal mathematical systems to Linguistics: he realized that logical formalism could be employed to express the grammar of a language; and that the grammar of a language "was" the http://www.thymos.com/tat/language.html (4 of 19)25/07/2003 14:27:22
Thinking About Thought: Consciousness, Life and Meaning
specification for the entire language. Chomsky's idea was therefore to concentrate on the study of grammar, and specifically syntax, i.e. on the rules that account for all valid sentences of a language. His assumption was that the number of sentences in a language is potentially infinite, but there is a system of rules that defines which sentences can potentially be built and determines their meaning, and that system of rules is what identifies a language and differentiates it from other languages. That system of rules is the grammar of the language. One of Chomsky's goals was to explain the difference between "performance" (all sentences that an individual will ever use) and "competence" (all sentences that an individual can utter, but will not necessarily utter). We are capable of saying far more than we will ever say in our entire lifetime. And we understand sentences that we have never heard before. We can tell right away whether a sentence is correct or not, even when we don't understand its meaning. We don’t learn a language by memorizing all possible sentences of it. We learn, and subsequently use, an abstraction that allows us to deal with any sentence in that language. That abstraction is the grammar of the language. Chomsky therefore argued for a "deductive" approach to language: be able to derive all possible sentences of a language (whether they have been used or not) from an abstract structure (its "generative" grammar). Chomsky also argued for the independence of syntax from semantics, as the notion of a well-formed sentence in the language is distinct from the notion of a meaningful sentence. A sentence can make perfect sense from a grammatical point of view, while being absolutely meaningless (such as "the table eats cloudy books"). Phrase Structure Language is a set of sentences, each sentence is a finite string of words from a lexicon, and a grammar is the set of rules that determine whether a sentence belongs to that grammar’s language. And, dually, the rules of the grammar are capable of generating (by recursive application) all the valid sentences in that language: the language is "recursively numerable". When analyzing a sentence (or "parsing" it), the sequence of rules applied to the sentence builds up a "parse tree". This type of grammar, so called "phrase-structure grammar", turns out to be equivalent to a Turing machine, and therefore lends itself to direct implementation on the computer. The phrase-structure approach to language is based on "immediate constituent analysis": a phrase structure is defined by the constituents of the sentence (noun phrase, verb phrase, etc.). Initially, Chomsky thought that a grammar needs to have a tripartite structure: a sequence of rules to generate phrase structure, a sequence of morpho-phonemic rules to convert strings of morphemes into strings of phonemes, and a sequence of transformational rules that transform strings with phrase structure into new strings to which the morpho-phonemic rules can apply. Whatever the set of rules, the point is that analyzing language was transformed into a mechanical process of generating more and more formal strings, just like when trying to prove a mathematical theorem. The underlying principle was that all the http://www.thymos.com/tat/language.html (5 of 19)25/07/2003 14:27:22
Thinking About Thought: Consciousness, Life and Meaning
sentences of the language (which are potentially infinite) can be generated by a finite (and relatively small) number of rules, through the recursive application of such rules. And this fit perfectly well with computer science. Transformational Grammar Even more momentous was the intuition that two levels of language were needed: an underlying "deep structure", which accounts for the fundamental syntactic relationships among language components, and a "surface structure", which accounts for the sentences that are actually uttered. The latter gets generated by transformations of elements in the deep structure. For example, "I wrote this book" and "This book was written by me" use the same constituents ("I", "to write", "book") and they are in the same relationship: but one is an active form and the other is a passive form. One gets transformed into the other. Their deep structure is the same, even if their surface structures are different. Many sentences may exhibit the same deep structure. The phrase structure produces the "deep structure" of a sentence. That needs to be supplemented by a transformational component and a morpho-phonemic component, which together transform the deep structure into the surface structure of the sentence (e.g. active or passive form). Technically, the deep structure of a sentence is a tree (the phrase marker), that contains all the words that will appear in its surface structure. Understanding language, basically, consists in transforming surface structures into deep structures. In Chomsky's "standard theory" a grammar is made of a syntactic component (phrase structure rules, lexicon and transformational component), a semantic component (that assigns a meaning to the sentence) and a phonologic component (which transforms it into sounds). In the end, every sentence of the language is represented by a quadruple structure: the D-structure (the one generated by phrase-structure rules), the S-structure (obtained from the D-structure by applying transformational rules), the P-structure (a phonetic structure) and a "logical form". The logical form of a sentence is the semantic component of its representation, usually in the guise of a translation into firstorder Predicate Logic of the "meaning" of the sentence. These four structures define everything there is to know about the sentence: which grammar rules it satisfies, which transformational rules yield its external aspect, which rules yield the sounds actually uttered by the speaker, and finally the meaning of what is said. Chomsky's computational approach had its flaws. To start with, each Chomsky grammar is equivalent to a Turing machine. Because of Godel's theorem, the processing of a Turing machine may never come to an end. Therefore, a grammar may never find the meaning of a valid sentence, but we have no evidence that our brain may never find the meaning of a valid sentence in our language. Therefore, some conclude that Chomsky's grammars are not what our brain uses. Also, it is a mystery how we can learn the grammar of our own language: if the grammar is computational in nature, as Chomsky thought, then it can be proved mathematically that no amount of correct examples of sentences are enough to learn a language. It is mathematically impossible for a child to have learned the language it speaks!
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Universal Grammar An important assumption lies at the core of Chomsky's theory. Chomsky implied that we have some innate knowledge of what a grammar is and how it works. Then experience determines which specific language (i. e., grammar) we will learn. When we are taught a language, we don't memorize each sentence word by word: eventually, we learn the grammar of that language, and the grammar enables us to both understand and utter more sentences that we have ever heard. Somehow our brains refuse to learn a language by memorizing all possible sentences, our brains tend to infer a grammar from all those sentences. Chomsky led us to believe that our brains are pre-configured to deal with grammars, that there exists some kind of universal linguistic knowledge. The brain is primed for language development, grammatical principles are innate and universal. Formally stated, Chomsky decomposes a user's knowledge of language into two components: a universal component (the "universal grammar"), which is the knowledge of language possessed by every human, and a set of parameter values and a lexicon, which together constitute the knowledge of a particular language. The ability to understand and utter language is due to the universal grammar that is somehow encoded in the human genome. A specific grammar is learned not in stages, as Piaget thought, but simply by gradually fulfilling a blueprint that is already in the mind. Children do not learn, as they do not make any effort. Language "happens" to a child. The child is almost unaware of the language acquisition process. Learning to speak is not different from growing, maturing and all the other biological processes that occur in a child. A child is genetically programmed to learn a language, and experience will simply determine which one. The way a child is programmed is such that all children will learn language the same way. Language acquisition is not only possible: it is virtually inevitable. A child would learn to express himself even if nobody taught her a language. Chomsky’s belief in innate linguistic knowledge is supported by a mathematical theorem proved by E. Gold: a language cannot be learned from positive examples only. A grammar could never be induced from a set of the sentences it is supposed to generate. But the grammar can correctly be induced (learned) if there is a (finite) set of available grammars to choose from. In that case the problem is to identify the one grammar that is consistent with the positive examples (with the known sentences), and then the set can be relatively small (the grammar can be learned quickly). . Later, Chomsky (inspired by John Ross) advanced a theory of "government binding" that would reduce differences between languages to a set of constraints, each one limiting the number of possible variants. Grammar develops just like any other organ in the body: an innate program is started at birth but it is conditioned by experience; still, it is constrained in how much it can be influenced by experience. Just like an arm will be an arm regardless of what happens during growth, but frequent exercise will make its muscles stronger. Growth is deterministic to some extent: its outcome can fluctuate, but within limits. Chomsky's view of innate linguistic knowledge has found support from biologists and psychologists. The http://www.thymos.com/tat/language.html (7 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
Canadian psychologist Steven Pinker claims that children are "wired" to pay attention to certain patterns and to perform some operations with words. All languages share common features, suggesting that natural selection favored certain syntactic structures. Pinker identified fifteen modules inside the human mind, organs that account for instincts that all humans share. Our genetic program specifies the existence and growth of the language organs, and those organs include at least an idea of what a language is. These organs are roughly the same for all humans, just like hands and eyes are roughly the same. This is why two people can understand each other even if they are using sentences that the other has never heard before. In biological words, the universal grammar is the linguistic genotype. Its principles are invariant for all languages. The values of some parameters can be "selected" by the environment out of all valid values. This pseudo-Darwinian process is similar to what happens with other growth processes. The model used by Gerald Edelman both in his study of the immune system (the viruses select the appropriate antibodies out of those available) and in his study of the brain (experience selects the useful neural connections out of those available at birth) is quite similar. A disturbing consequence of this theory is that our mental organs determine what we are capable of communicating, just like our arms or legs determine what movements we are capable of. Just like there are movements that our body can't make, there are concepts that our language could not communicate. Wedding Biology and Linguistics In the following years, a number of psychologists, linguists and philosophers corroborated the overall picture of Chomsky’s vision. The American linguist Ray Jackendoff thinks that the human brain contains innate linguistic knowledge and that the same argument can be extended to all facets of human experience: all experience is constructed by unconscious, genetically determined principles that operate in the brain. These same conclusions can be applied to thought itself, i.e. to the task of building concepts. Concepts are constructed by using some innate, genetically determined, machinery, a sort of "universal grammar of concepts". Language is but one aspect of a broader characteristic of the human brain. According to Eric Lenneberg, language should be studied as an aspect of man's biological nature, in the same manner as anatomy. Chomsky's universal grammar is to be viewed as an underlying biological framework for the growth of language. Genetic predisposition, growth and development apply to language faculties just like to any other organ of the body. Behavior in general is an integral part of an organism's constitution. Another implication of the standard theory (and particularly of its transformational component) is on the structure of the mind. The transformations can be seen as corresponding to mental processes, performed by mental modules (as in Fodor's computational theory of the mind), each independent of the others and each guided by elementary principles.
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Thinking About Thought: Consciousness, Life and Meaning
Cased-based Grammars Either because they did not agree with his vision of the human mind, or because they considered unnatural the limits of his grammars, or because they devised mathematically more efficient models, other thinkers rejected or modified Chomsky's theory. One powerful idea that influenced many thinkers is that the deep structure of language is closer to the essence of concepts than to the syntax of a specific language. For example, "case-frame grammar" (developed in the late Sixties by the American linguist Charles Fillmore) assumes that each sentence represents explicitly the relationships between concepts and action. The emphasis is placed on "cases". Traditional cases (such as the ones used by German or Latin) are purely artificial, because the same sentence can be rephrased altering the cases of its constituents: "Piero" in "Piero wrote this book" and "this book was written by Piero" appears in two different cases. But its role is always the same, regardless of how we write the sentence. That role is the real "case", in Fillmore’s lingo. These cases are universal, they are not language-specific. My relationship towards the book I wrote is the same in every language of the world, regardless of how a specific syntax allows me to express such relationship. Fillmore concluded that a universal underlying set of case-like relations plays a fundamental role in determining syntactic and semantic relations in all languages. In Fillmore’s grammar, therefore, a sentence is represented by identifying such cases. Sentences that deliver the same meaning with different words, but that describe essentially the same scene, get represented in the same way, because they exhibit the same items in the same cases. Fillmore's approach started a whole new school of thought. Drawing from the Aristotelic classification of state, activity and eventuality, David Dowty proposed that the modal operators "do", "become" and "cause" be used as the foundations for building the meaning of every other verb. Within a sentence, the various words have "roles" relative to the verb. A thematic role is a set of properties that are common to all roles that belong to that thematic role. A thematic role can be then seen as a relationship that ties a term with an event or a state. And this allows one to build a mathematical calculus (a variant of the lambda calculus) on thematic roles. Analogously, Ray Jackendoff proposed that the meanings of all verbs be reduced to a few space-time primitives, such as "motion" and "location". Conceptual Dependency The culmination of this school was, in the Seventies, Roger Schank's "conceptual dependency" theory, whose tenet is that two sentences whose meaning is equivalent must have the same representation. This goal can be achieved by decomposing verbs into elementary concepts (or semantic primitives). Sentences describe things that happen, i.e. actions. While every language provides for many different actions (usually expressed as verbs), it turns out that most of them can be defined in terms of simpler ones. For example, "to deliver" is a combination of "to move" and other simpler actions. In other words, a http://www.thymos.com/tat/language.html (9 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
number of primitive actions can be used to form all complex actions. In analyzing language, one can therefore focus on those primitive actions. Therefore, a verb can be decomposed in terms of more primitive concepts. Now, each action entails roles which are common to all languages. For example, "to move" requires an agent who causes the move to happen, an object to be moved, an old location and a new location, possibly a timeframe, etc. Sometimes the roles are not explicitly stated in a sentence, but they can be derived from the context. Whether they are stated in the sentence or implicit in the context, those roles always exist. And they exist for every language that has that concept. "To move" may be translated in different words in different languages, but it always require a mover, an object, etc. An important corollary is that any two sentences that share the same meaning will have exactly the same representation in conceptual dependency, regardless of how much is left implicit by each one, regardless of how each is structured. If they refer to the same mover and the same object and the same location and the same timeframe, two different sentences on "moving" will have identical representations. Conceptual dependency reveals things that are not explicit in the surface form of the utterance: additional roles and additional relations. They are filled in through one’s knowledge of lexical semantics and domain heuristics. These two components help infer what is true in the domain. Conceptual dependency represented a major departure from Chomskyan analysis, which always remained relatively faithful to the way a sentence is structured. Schank’s analysis considers negligible the way words have been assembled and shifts the emphasis on what is being described. If nothing else, this is presumably closer to the way our memory remembers them. Semantics In Chomsky's linguistic world, the "meaning" of a sentence was its logical form. Somehow, at the end of the process of parsing a sentence, a logical translation would be produced which allowed for mathematical processing, and that logical form "was" considered to be the meaning of the sentence. This turned out to be naif. Sentences like "Prostitutes appeal to Pope", "Panda mating fails - veterinarian takes over", "Soviet virgin lands short of goal again" (actual newspaper headlines reported by Keith Devlin) are "ambigous". Language does that. In every language one can build a sentence that is perfectly valid but not clear at all. Solving ambiguities is often very easy. If the third sentence is encountered in the context of the development of Siberia, one may not even notice the ambiguity. The context usually solves the ambiguity. A related problem is that of "anaphora". The sentence "He went to bed" is ambigous in a different way but still ambigous: technically speaking, "he" could be any of the 3 billion males who live on this planet. In practice, all we have to do is read the previous sentences to find out who "he" is. The context, again, helps us figure out the meaning of a sentence. Not to mention expressions such as "Today is an important day" or "Here it is 5 o'clock": when and where http://www.thymos.com/tat/language.html (10 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
are these sentences occurring? Thanks to linguistic phenomena like ambiguity and anaphora, understanding a discourse requires more than just figuring out the syntactic constituents of each sentence. In fact, even understanding the syntactic constituents may require more than syntax: the "lies" in "Reagan wins on budget but more lies ahead" is a noun (plural of "lie") or a verb (third person of "to lie")? The scope of semantics is beyond the single word and the way the words related to each other. The Math of Grammars Many researchers thought this was insufficient for a semantics of language and set out to improve Chomsky’s model. In the 1960's, the American linguist Jerrold Katz provided what was one the most extensive studies on semantics. His basic tenet is that two components are necessary for a theory of semantics. The first one is a dictionary, which provides for every lexical item (i.e., for every word) a phonological description, a syntactic classification ("grammatical marker", e.g. noun or verb) and a specification of its possible distinct senses ("semantic marker", e.g. "light" as in color and "light" as the opposite of heavy). The second one is a set of " projection rules" that determine how the meaning of a sentence can be composed from the meaning of its constituents. Projections rules, therefore, produce all valid interpretations of a sentence. These studies led to increasingly formal approaches to the study of language. But first-order Predicate Logic, the most commonly used logic, quickly proved to be too limited to handle the subtleties of language. Gerald Gazdar's "generalized phrase-structure grammar", for example, was meant as an improvement over Chomsky's grammars. It made use of a logic called "Intensional Logic". Gazdar abandoned the transformational component and the deep structure of Chomsky's model and focused on rules that analyze syntactic trees rather than generate them. The rules translate natural language sentences in an intensional logic (another variant of the "lambda calculus"). This way, the semantic interpretation of a sentence can be derived directly from its syntactic representation. Gazdar defined 43 rules of grammar, each one providing a phrase-structure rule and a semantic-translation rule that show how to build an intensional-logic expression from the intensional-logic expressions of the constituents of the phrase-structure rule. Gazdar’s system was fundamentally a revision of Katz’s system from Predicate Logic to Intensional Logic. The advantage of this approach is that Gazdar's grammar can exhibit mathematical properties that, unlike Chomsky's grammar, can be scientifically tested and falsified. Intensional Semantics Richard Montague developed the most sophisticated of intensional-logic approaches to language. His intensional logic employs all sorts of advanced logical tools: type hierarchy, higher-order quantification, lambda abstraction for all types, tenses and modal operators; and its model theory is based on coordinate semantics. http://www.thymos.com/tat/language.html (11 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
In this intensional logic the sense of an expression determines its reference. The intensional logic makes explicit the mechanism by which this can happen. Reality consists of two truth values, a set of entities, a set of possible worlds and a set of points in time. A function space is constructed inductively from these elementary objects. The logic determines the possible sorts of functions from possible indices (sets of worlds, times, speakers, etc.) to their denotations (or extensions). These functions represent the sense of the expression. In other words, sentences denote extensions in the real world. A name denotes the infinite set of properties of its reference. Common nouns, adjectives and intransitive verbs denote sets of individual concepts and their intensions are the properties necessarily shared by all those individuals. Montague's semantics is truth-conditional (to know the meaning of a sentence is to know what the world must be for the sentence to be true, the meaning of a sentence is the set of its truth conditions), modeltheoretic and uses possible worlds (the meaning of a sentence depends not just on the world as it is but on the world as it might be, i.e. on other possible worlds). Through a rigorously mechanical process, a sentence of natural language can be translated into an expression of the intensional logic. The model-theoretic interpretation of this expression serves as the interpretation of the sentence. Rather than proving a semantic interpretation directly on syntactic structures, Montague provides the semantic interpretation of a sentence by showing how to translate it into formulas of intensional logic and how to interpret semantically all formulas of that logic. Montague assigns a set of basic expressions to each category and then defines 17 syntactic rules to combine them to form complex phrases. An analysis tree shows graphically how a meaningful expression is constructed from basic expressions. The tree shows all applications of syntactic rules down to the level of basic expressions. The translation from natural language to intensional logic is then performed by employing a set of 17 translation rules that correspond to the syntactic rules. Syntactic structure determines semantic interpretation. Montague exploited to the maximum the fact that categorial grammars provide a unity of syntactic and semantic analyses. Grammatical Semantics Anna Wierzbicka has an even more extreme view of semantics. Language is a tool to communicate meaning: semantics is the study of meaning encoded in language and syntax is a piece of semantics. Corresponding to the three types of tools employed by language to convey meaning (words, grammatical constructions and illocutionary devices), Linguistics can be divided into lexical semantics, grammatical semantics and illocutionary semantics. The division in syntax, semantics and pragmatics makes no sense because every element and aspect of language carries meaning. Meaning is an individual's interpretation of http://www.thymos.com/tat/language.html (12 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
the world. It is subjective and depends on the social and cultural context. Therefore, semantics encompasses lexicon, grammar and illocutionary structure. Her "grammatical semantics" is divided in semantics of syntax and semantics of morphology. A metalanguage is defined to express the meaning of an expression. Wierzbicka has been trying to build semantics from elementary concepts. There exist a broad variety of semantic differences among languages (even emotions seem to be cultural artifacts), but a few semantic primitives have been proposed. Such universal semantic primitives make up a semantic metalanguage that could be used to explicate all other concepts in all languages. Cognitive Grammar Ronald Langacker is a founder of the field of "cognitive" linguistics. Since 1976, he has been developing "cognitive grammar. Rather than sentences and grammatical rules, his grammar is built on image schemas, which are schemas of visual scenes. It therefore represents a major departure from the logical, Chomskyan tradition. Langacker makes three fundamental assumptions: that language is symbolic in nature, that a linguistic community creates linguistic conventions, and that grammar is a speaker's knowledge of linguistic conventions. In his theory, only a semantic and a phonological components are recognized, mediated by a symbolic component. This approach directly reflects the semiological function of language: to build symbols for concepts (semantics) by means of sounds (phonology). Grammar reduces to these symbolic relationships between semantic structures and phonological structures. Langacker takes issue with the prevalent view that language is an infinite set of well-formed sentences or any other algorithm-generated set. To him, a language is a psychological phenomenon which eventually resides in neural activity. Chomsky's generative grammar is merely a platonic ideal. A speaker's linguistic knowledge is contained in a set of cognitive units, which are originated by a process of reinforcement of recurring features (or schematization), or, identically, by a process of patterns of neural activity. These units are therefore grounded in daily experience and are employed by speakers in automatic fashion: a unit is a whole that does not need to be broken down in constituents to be used. Phonological units, for example, range from the basic sounds of language (such as the "t" of the English language or the "r" of the French language) to familiar phrases and proverbs. Units form a hierarchy, a schema being instantiated in subschemas. A linguistic category may be represented by a network of quite dissimilar schemas, clustered around a prototype. A grammar is but an inventory of such units. Nouns and verbs are central to grammatical structure because of the archetypal status of a cognitive model (the "billiard-ball model") whose elements are space, time, matter and energy. That is a world in which discrete physical objects move around in space thanks to some form of energy, in particular the one http://www.thymos.com/tat/language.html (13 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
acquired through interactions with other objects. Matter spreads in space and energetic interactions occur in time. Objects and interactions are instantiated, respectively, in space and time. Objects and interactions are held to be the prototypes, respectively, for the noun and verb grammar categories. These categories differ primarily in the way they construe a situation, i.e. their primary semantic value is "imagic", has to do with the capability to construe situations. Mental Spaces A similar change in perspective is advocated by the French linguist Gilles Fauconnier. Fauconnier's focus is in the interaction between grammar and cognition, which translates into the interaction between syntax/semantics and mental spaces. The mind is capable of making connections between domains and Fauconnier investigates the kinds of cognitive connections that are possible: pragmatic functions (such as that between an author and her book), metonymy, metaphor, analogy, etc. Some domains are cognitively accessible from others and meaning is to be found in these interactions. Which reflect in primis the organization of thought itself: a basic tenet of Fauconnier's theory is that linguistic structure reflects not the structure of the world but the structure of our cognitive life. The idea is that, as the speaker utters one sentence after the other, she is in fact constructing mental spaces and the links among them, resulting in a network of mental spaces. Mental spaces, in particular, facilitate reasoning: while logic-based semantics (Chomskyan logical form, Montague's semantics, situation semantics) assume that language provides a meaning that can be used for reasoning, Fauconnier assumes that language builds the same kind of mental spaces from the most basic level of meaning construction all the way up to discourse and reasoning. Mental spaces allow for alternative views of the world. Fauconnier thinks that the mind needs to create multiple cognitive spaces in order to engage in creative thought. Fauconnier's theory provides the abstract tools ("accessing", "spreading" and "viewpoint") for the dynamics of mental space construction and linking. The Origin of Language Charles Darwin observed that languages seem to evolve the same way that species evolve, but, just like with species, he failed to propose what the origin of language was. Today, we have growing evidence that his intuition was correct. Languages evolved just like species, through little "mistakes" that were introduced by each generation. It is not surprising that the evolutionary trees drawn by biologists (based on DNA similarity) and linguists (based on language similarity) are almost identical. Jones concludes that language may date back to the beginning of mankind. What is puzzling, then, is not the evolution of modern languages from primordial languages: it is how nonlinguistic animals evolved into a linguistic animal such as the human being. It's the "evolution of language" http://www.thymos.com/tat/language.html (14 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
from non-language, not the "evolution of languages" from pre-existing languages. Several biologists and anthropologists believe that language was "enabled" by accidental evolution of parts of the brain and possibly other organs. The American biologist Philip Lieberman views the brain as the result of evolutionary improvements that progressively enabled new faculties. In particular, rapid vocal communication influenced the evolution of the brain. Human language is a relatively recent evolutionary innovation that came about when speech and syntax were added to older communication systems. Speech allowed humans to overcome the limitations of the mammalian auditory system and syntax allowed them to overcome the limits of memory. Coevolution The American anthropologist Terrence Deacon believes that language and the brain coevolved, evolved together influencing each other step by step. In his opinion, language did not require the emergence of a language organ. Language originated from symbolic thinking, an innovation which occurred when humans became hunters because of the need to overcome the sexual bonding in favor of group cooperation. Both the brain and language evolved at the same time through a series of exchanges. Languages are easy to learn for infants not because infants can use innate knowledge but because language evolved to accomodate the limits of immature brains. At the same time, brains evolved under the influence of language through the Baldwin effect. Language caused a reorganization of the brain, whose effects were vocal control, laughter and sobbing, schizophrenia, autism. As a consequence, Deacon rejects the idea of a universal grammar a` la Chomsky, of innate linguistic knowledge. There is an innate human predisposition to language, but it is due to the coevolution of brain and language and it is altogether different from the universal grammar envisioned by Chomsky. What is innate is a set of mental skills (ultimately, brain organs) which translate into natural tendencies, which translate into some universal structures of language. Another way to describe this is to view language as a "meme". Language is simply one of the many "memes" that invade our mind, and, because of the way the brain is, the meme of language can only assume such and such a structure, not because the brain is pre-wired to such a structure but because that structure is the most natural for the organs of the brain (such as short-term memory and attention) that are affected by it. Chomsky's universal grammar is an outcome of the evolution of language in our mind during our childhood. There is no universal grammar in our genes, or, better, there are no language genes in our genome. The way language is structured reflects its evolution. Deacon recognizes a hierarchy of meaning. The lower levels (iconic and indexical) are based on the process of recognition and on associative learning. The highest level (symbolic) are based on a stable network of interconnected meanings. Symbols refer to the world but also refer to each other. The individual symbol is meaningless: what has meaning is the symbol http://www.thymos.com/tat/language.html (15 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
within the vast and ever changing semantic space of all other symbols. Linguistic darwinism
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Allen James: NATURAL LANGUAGE UNDERSTANDING (Benjamin Cummings, 1995) Bach Emmon: CATEGORIAL GRAMMARS (Reidel, 1988) Bar-Hillel Yehoshuas: LANGUAGE AND INFORMATION (Addison Wesley, 1964) Bickerton Derek & Calvin William: LINGUA EX MACHINA (MIT Press, 2000) Bresnan Joan: MENTAL REPRESENTATIONS OF GRAMMATICAL RELATIONS (MIT Press, 1982) Chierchia Gennaro: MEANING AND GRAMMAR (MIT, 1990) Chierchia Gennaro: DYNAMICS OF MEANING (Univ of Chicago Press, 1995) Chomsky Noam: SYNTACTIC STRUCTURES (Mouton, 1957) Chomsky Noam: ASPECTS OF THE THEORY OF SYNTAX (MIT Press, 1965) Chomsky Noam: REFLECTIONS ON LANGUAGE (Pantheon, 1975) Chomsky Noam: THE LOGICAL STRUCTURE OF LINGUISTIC THEORY (University of Chicago Press, 1975) Chomsky Noam: RULES AND REPRESENTATIONS (Columbia Univ Press, 1980) Chomsky Noam: THEORY OF GOVERNMENT AND BINDING (MIT Press, 1982) Chomsky Noam: KNOWLEDGE OF LANGUAGE (Greenwood, 1986) Churchland Paul: ENGINE OF REASON (MIT Press, 1995) Darwin Charles: LANGUAGES AND SPECIES (1874) http://www.thymos.com/tat/language.html (16 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
Deacon Terrence: THE SYMBOLIC SPECIES (W.W. Norton & C., 1997) De Saussure Mongin-Ferdinand: COURSE IN GENERAL LINGUISTICS (1916) Dennett Daniel: KINDS OF MINDS (Basic, 1998) Devlin Keith: GOODBYE DESCARTES (John Wiley, 1997) Donald Merlin: ORIGINS OF THE MODERN MIND (Harvard Univ Press, 1991) Dowty David: WORD MEANING AND MONTAGUE GRAMMAR (Reidel, 1979) Dowty David: INTRODUCTION TO MONTAGUE SEMANTICS (Reidel, 1981) Fauconnier Gilles: MENTAL SPACES (MIT Press, 1994) Fauconnier Gilles & Eve Sweetser: SPACES, WORLDS, AND GRAMMAR (Univ of Chicago Press, 1996) Fetzer James: ASPECTS Of ARTIFICIAL INTELLIGENCE (Kluwer, 1988) Fetzer James: ARTIFICIAL INTELLIGENCE (Kluwer, 1990) Gazdar Gerald: GENERALIZED PHRASE STRUCTURE GRAMMAR (MIT Press, 1985) Goddard Cliff & Wierzbicka Anna: SEMANTIC AND LEXICAL UNIVERSALS (Benjamins, 1994) Gregory Richard: MIND IN SCIENCE (Cambridge Univ Press, 1981) Hoffmeyer Jesper: SIGNS OF MEANING IN THE UNIVERSE (Indiana Univ. Press, 1996) Jackendoff Ray: SEMANTICS AND COGNITION (MIT Press, 1983) Jackendoff Ray: SEMANTIC STRUCTURES (MIT Press, 1990) Jackendoff Ray: LANGUAGES OF THE MIND (MIT Press, 1992) Katz Jerrold: AN INTEGRATED THEORY OF LINGUISTIC DESCRIPTIONS (MIT Press, 1964) Katz Jerrold: SEMANTIC THEORY (Harper & Row, 1972)
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Katz Jerrold: THE METAPHYSICS OF MEANING (MIT Press, 1990) Lehnert Wendy: STRATEGIES FOR NATURAL LANGUAGE LANGUAGE (Lawrence Erlbaum, 1982) Langacker Ronald: FOUNDATIONS OF COGNITIVE GRAMMAR (Stanford Univ Press, 1986) Lenneberg Eric: BIOLOGICAL FOUNDATIONS OF LANGUAGE (Wiley, 1967) LePore Ernest: NEW DIRECTIONS IN SEMANTICS (Academic Press, 1987) Levinson Stephen: PRAGMATICS (Cambridge Univ Press, 1983) Lieberman Phipip: THE BIOLOGY AND EVOLUTION OF LANGUAGE (Harvard Univ Press, 1984) Loritz Donald: HOW THE BRAIN EVOLVED LANGUAGE (Oxford Univ Press, 1999) Lycan William: LOGICAL FORM IN NATURAL LANGUAGE (MIT Press, 1984) Montague Richard: FORMAL PHILOSOPHY (Yale University Press, 1974) Morris Charles: FOUNDATIONS OF THE THEORY OF SIGNS (University Of Chicago Press, 1938) Nelson Katherine: LANGUAGE IN COGNITIVE DEVELOPMENT (Cambridge University Press, 1996) Peirce Charles: COLLECTED PAPERS (Harvard Univ Press, 1931) Pinker Steven: THE LANGUAGE INSTINCT (William Morrow, 1994) Pinker, Steven: HOW THE MIND WORKS (Norton, 1997) Sapir Edward: LANGUAGE (1921) Schank Roger: CONCEPTUAL INFORMATION PROCESSING (North Holland, 1975) Searle John: SPEECH ACTS (Cambridge Univ Press, 1969) Searle John: EXPRESSION AND MEANING (Cambridge Univ Press, 1979) Sebeok Thomas Albert: CONTRIBUTION TO A DOCTRINE OF SIGNS (Indian Univ, 1976) Thom Rene': SEMIOPHYSICS (Addison-Wesley, 1990) http://www.thymos.com/tat/language.html (18 of 19)25/07/2003 14:27:23
Thinking About Thought: Consciousness, Life and Meaning
Van Benthem Johan: A MANUAL OF INTENSIONAL LOGIC (Univ Of Chicago Press, 1988) Van Benthem Johan: LANGUAGE IN ACTION (MIT Press, 1995) Vygotsky Lev: THOUGHT AND LANGUAGE (MIT Press, 1964) Whorf Benjamin Lee: LANGUAGE, THOUGHT AND REALITY (MIT Press, 1956) Wierzbicka Anna: SEMANTICS, CULTURE, AND COGNITION (Oxford University Press, 1992) Wierzbicka Anna: THE SEMANTICS OF GRAMMAR (Benjamins, 1988)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Metaphor: How We Speak (Mitten, Black, Lakoff, MacCormac, Arbib, Kittay, Martin, Way)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Standing for Something Else Metaphor is not just a poet's tool to express touching feelings. Metaphor is pervasive in our language. "Her life is a nightmare", "My room is a jungle", "She is a snake", "This job is a piece of cake", etc.: we communicate all the time metaphorically. The reason metaphor is so convenient is that it allows us to express a lot starting with very little: metaphor is a linguistic device to transfer properties from one concept to anoether. Metaphor is so pervasive that every single word of our language may have originated from a metaphor. Some thinkers have even suggested that all language may be metaphorical. Given the importance of language among our mental faculties, some thinkers go even beyond and maintain that metaphor is a key element of reasoning and thinking in general. In other words, being able to construct and understand metaphors (to transfer properties from a "source" to a "destination", from "nightmare" to "marriage", from "jungle" to "room", etc.) may be an essential part of being a mind. Founding his theory on archeology, i.e. on evidence from prehistory, the British archeologist Steven Mithen, while researching prehistorical civilizations, has become convinced that metaphor was pivotal for the development of the human mind. A special case of metaphor is metonymy, which occurs when a term is used to indicate something else, e.g. "the White House" to mean "the president of the United States" (as in "the White House has pledged not to increase taxes") rather than the building itself. Metonymy differs from metaphor in that metaphor is a way to conceive something in terms of another thing, whereas metonymy is a way to use something to stand for something else (i.e., it also has a referential function).
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Thinking About Thought: Consciousness, Life and Meaning
The study of metaphor presents a number of obvious problems: how to determine its truth value (literally, metaphors are almost always false) and how to recognize an expression as a metaphor (metaphors have no consistent syntactic form). It is also intriguing that metaphor seems to violate so blatantly Grice's conversational rules: if the speaker tries to make communication as "rational" as possible, why would she construct a metaphor instead of just being literal? The answer lies in the true nature of metaphor. The Dynamics of Language Early studies on metaphor by linguists focused on the analogical reasoning that any metaphor implies. Max Black was influential in moving metaphor from the level of words to the level of concepts. His "interactionist" theory of metaphor (dating from the 1960s, and inspired by the pioneering work of Ivor Richards in the 1930s) views metaphor not as a game of words, but as a cognitive phenomenon that involves concepts. In literal language, two concepts can be combined to obtain another concept without changing the original concepts (e.g., "good" and "marriage" form "good marriage"). In metaphorical language, two concepts are combined so that they form a new concept (e.g., marriage as a nightmare) and additionally they change each other (both "marriage" and "nightmare" acquire a different meaning, one reflecting the nightmarish aspects of marriage and the other one reflecting the marriage-like quality of a nightmare). They trade meaning. Predications that are normally applied to one are now also possible on the other, and viceversa. A metaphor consists in a transaction between two concepts. The interpretation of both concepts is altered. Black viewed metaphor as a means to reorganize the properties of the destination. First of all, a metaphor is not an isolated term, but a sentence. A metaphorical sentence (e.g., "marriage is a nightmare") involves two subjects. The secondary subject (e.g., "nightmare") comes with a system of associated stereotyped information (or "predication"). That stereotyped information is used as a filter on the principal subject (e. g., "marriage"). There arises a "tension" between the two subjects of the metaphor. That tension is also reflected back to the secondary subject. Black emphasized that metaphorizing is related to categorizing (the choice of a category in which to place an object is a choice of perspective), but is distinguished from it by an incongruity which causes a reordering and a new perspective. A crucial point is that metaphor does not express similarities: it creates similarity. Metaphors act on the organization of the lexicon and the model the world. Finally, Black argued that language is dynamic: over time, what is literal may become metaphoric and viceversa. Michael Arbib, one of the many who have argued that all language is metaphorical, based his theory of language on Black's interactionist model. http://www.thymos.com/tat/metaphor.html (2 of 9)25/07/2003 14:33:36
Thinking About Thought: Consciousness, Life and Meaning
At the other extreme, James Martin does not believe that the process of comprehending a metaphor is a process of reasoning by analogy. A metaphor is simply a linguistic convention within a linguistic community, an "abbreviation" for a concept that would otherwise require too many words. There is no need for transfer of properties from one concept to another. In his theory, a number of primitive classes of metaphors (metaphors that are part of the knowledge of language) are used to build all the others. A metaphor is therefore built and comprehended just like any other lexical entity. Martin's is a purely "syntactic" model of metaphor. Metaphorical Thought As the French linguist Michel Breal had already pointed out at the turn of the century, metaphor is often indispensable to express a concept for which words just do not exist in the language. Entire domains are mapped in other domains for lack of appropriate words. For example, the domain of character is mapped into the domain of temperature: a hot temper, a cold behavior, a warm person, etc. Breal realized that metaphors literally shape language. A broader analysis of metaphor was carried out during the 1970's and 1980's by the American linguist George Lakoff. The two fundamental conclusions of his analysis are that: (1) all language is metaphorical and (2) all metaphors are ultimately based on our bodily experience. Metaphor shapes our language as well as our thought, and it does so by grounding concepts in our body. It provides an experiential framework in which we can accommodate abstract concepts. Thanks to metaphor, we can reduce (and therefore understand) abstract concepts to our physical experiences and to our relationship with the external world. Metaphor is therefore an intermediary between our conceptual representation of the world and our sensory experience of the world (an approach that resembles Kant's schema). Metaphor is not only ubiquitous in our language, it is also organized in conceptual systems: concepts of love are related to concepts of voyage, concepts of argument are related to concepts of war, and so forth. It is not only one word that relates to another word: it is an entire conceptual system that is related to another conceptual system. This organization of a conceptual systems forms a "cognitive map". Metaphor projects the cognitive map of a domain (the vehicle) onto another domain (the tenor) for the purpose of grounding the latter to sensory experience via the cognitive map of the former. The entire conceptual castle of our mind relies on this creation of abstractions by metaphor from the foundations of our bodily experience in the world. Lakoff grew up at a time when there was solid agreement about what metaphors are. Metaphor is a linguistic expression favorite by poets that is not used in the literal sense and expresses a similarity. But he quickly started realizing that we use metaphors all the time, and that we use them in a far more encompassing manner. For example, we express love in terms of a journey (as in "our marriage isn't going http://www.thymos.com/tat/metaphor.html (3 of 9)25/07/2003 14:33:36
Thinking About Thought: Consciousness, Life and Meaning
anywhere"), or time in terms of money (as in "a waste of time"). Love is not similar to a journey, and time is not similar to money. Furthermore, abstract concepts (such as "love") are defined by metaphors. If we take the metaphors away all is left is the roles (e.g., the lovers and the type of relationship). The system of metaphors built around that abstraction (e.g., all the metaphorsthat we use about love) tell us how to reason about that abstraction. This led Lakoff to reason that: metaphor is not in the words, it is in the ideas; it is part of ordinary language, not only of poetry; it is used for reasoning. Meaning is in the mind, not in the world. Once metaphor is defined as the process of experiencing something in terms of something else, metaphor turns out to be pervasive, and not only in language but also in action and thought. The human conceptual system is fundamentally metaphorical in nature, as most concepts are understood in terms of other concepts. Language comprehension always consists in comprehending something in terms of another. All our concepts are of metaphorical nature and are based on our physical experience. Lakoff has analyzed numerous domains of human knowledge and invariably detected the underlying metaphors. Theories, for example, are treated as buildings (a theory has "foundations" and is "supported" by data, theories are "fragile" or "solid"). Mathematics itself is a metaphor (Trigonometry is a metaphor for talking about angles) We understand the world through metaphors, and we do so without any effort, automatically and unconsciously. It doesn't require us to think, it just happens and it happens all the time. Most of the time we are thinking metaphorically without even knowing it. Our mind shares with the other minds a conventional system of metaphor. This is a system of "mappings", of referring one domain of experience to another domain, so that one domain can be understood through another domain which is somehow more basic. Normally, a more abstract domain is explained in terms of a more concrete domain. The more concrete the domain, the more "natural" it is for our minds to operate in them. Metaphors are used to partially structure daily concepts. They are not random, but rather form a coherent system that allows humans to conceptualize their experience. Again, metaphors create similarities. Lakoff defined three types of metaphor: "orientational" (in which we use our experience with spatial orientation), "ontological" (in which we use our experience with physical objects), "structural" (in which natural types are used to define other concepts). Every metaphor can be reduced to a more primitive metaphor. Language was probably created to deal only with physical objects, and later extended to non-physical objects by means of metaphors. Conceptual metaphors transport properties from structures of the physical world to non-physical structures. Reason, in general, is not disembodied, it is shaped by the body.
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Our conceptual system is shaped by positive feedback from the environment. As Edward Sapir and Benjamin Whorf had already argued before him, language reflects the conceptual system of the speaker. Lakoff emphasized that metaphor is not only a matter of words, but a matter of thought, that metaphor is central to our understanding of the world and the self. Lakoff shows how a small number of metaphors can define a whole system of thought. Even ritual is viewed by Lakoff as a crucial process in preserving and propagating cultural metaphors. And the reason that metaphor is so pervasive is that it is biological: our brains are built for metaphorical thought. Our brains evolved with "high-level" cortical areas taking input from "lower level" perceptual and motor areas. As a consequence, spatial and motor concepts are the natural basis for abstract reason. It turns out that "metaphor" refers to a physiological mechanism, to the ability of our brain to employ perceptual and motor inferential processes in creating abstract inferential processes. Metaphorical language is nothing but one aspect of our metaphorical brain. Metaphors are Fuzzy In 1985, Earl MacCormac attempted to formalize these intuitions in a unified theory of metaphor which has broad implications for meaning and truth. MacCormac rejects the "tension" theory (which locates the difference between metaphor and analogy in the emotional tension generated by the juxtaposition of anomalous referents), or Monroe Beardsley's "controversion" theory (which locates that difference in the falsity produced by a literal reading of the identification of the two referents) or the "deviance" theory (which locates that difference in the ungrammaticality of the juxtaposition of two referents). A metaphor is recognized as a metaphor on the basis of the semantic anomaly produced by the juxtaposition of referents. And this also means that metaphor must be distinct from ordinary language (as opposed to the view that all language is metaphorical). MacCormac adopts Philip Wheelwright's 1962 classification of metaphors into "epiphors" (metaphors that express the existence of something) and "diaphors" (metaphors that imply the possibility of something). Diaphor and epiphor measure the likeness and the dissimilarity of the attributes of the referents. A diaphor can become an epiphor (when the object is found to really exist) and an epiphor can become a literal expression (when the term has been used for so long that people have forgotten its origin). Metaphor is a process that exists at three levels: a language process (from ordinary language to diaphor to epiphor back to ordinary language); a semantic and syntactic process (its linguistic explanation); and a cognitive process (to acquire new knowledge). Therefore a theory of metaphor requires three levels: a surface (or literal) level, a semantic level and a cognitive level. The semantics of metaphor can then be formalized using the mathematical tool of fuzzy logic. Literal truth, figurality and falsity can be viewed as forming a continuum of possibilities rather than a discrete set of http://www.thymos.com/tat/metaphor.html (5 of 9)25/07/2003 14:33:36
Thinking About Thought: Consciousness, Life and Meaning
possibilities. The figurality of the metaphorical language, in particular, can be viewed as a continuum of "partial" truths that extends from absolute falsehood to absolute truth. These partial truths can be represented by fuzzy values. This is expresses by a real number on a scale from zero to one: zero is absolute falsehood, the interval from zero to a certain value represents falsehood, the interval from that value to another value represents diaphor, the interval from that value to another value represents epiphor, and the last interval to one represents truth (with one representing absolute truth). Metaphor are born as diaphors and, as they become more and more familiar through commonplace use, slowly mutate into diaphors, thereby losing their "emotive tension" Language can then be represented mathematically as a hierarchical network in n-dimensional space with each of the nodes of the network a fuzzy set (defining a semantic marker). When unlikely markers are juxtaposed, the degrees of membership of one semantic marker in the fuzzy set representing the other semantic marker can be expressed in a four-valued logic (so that a metaphor is not only true or false). MacCormac also sketched the idea that metaphors are speech acts in Austin's sense. Metaphors both possess meaning and carry out actions. An account of their meaning must include an account of their locutionary and perlocutionary forces. Finally, the third component of a theory of meaning for metaphors (besides the semantic and speech act components) is the cultural context. In concluding, the meaning of metaphors results from the semantic aspects of communication, culture and cognition. MacCormac claims that, as cognitive processes, metaphors mediate between culture and mind, influencing both cultural and biological evolution. Metaphor as Meaning Yet another theory was disclosed in 1987 by Eva Kittay. Drawing from Black's interactionist theory, and its vision of metaphor's dual content (literal and metaphorical, "vehicle" and "topic"), and from Ferdinand de Saussure's theory of signs, Kittay developed a "relational" theory of meaning for metaphor: the meaning of a word is determined by other words that are related to it by the lexicon. Meaning is not an item, it is a field. A semantic field is a group of words that are semantically related to each other. Metaphor is a process that transfers semantic structures between two semantic fields: some structures of the first field create or reorganize a structure in the second field. The meaning of a word consists of all the literal senses of that word. A literal sense consists of a conceptual content, a set of conditions, or semantic combination rules (permissible semantic combinations of the word, analogous to Fodor's selection-restriction rules), and a semantic field indicator (relation of the conceptual content to other concepts in a content domain). An interpretation of an utterance is any of the senses of that utterance. Projection rules combine lower-level units into higher-level units according to their semantic combination rules. A first-order interpretation of an utterance is derived from a valid http://www.thymos.com/tat/metaphor.html (6 of 9)25/07/2003 14:33:36
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combination of the first-order meanings of its constituents. Second-order interpretation is a function of firstorder interpretation and expresses the intuitive fact that what has to be communicated is not what is indicated by the utterance's literal meaning. Kittay outlines the formal conditions for recognizing an utterance as a metaphor. An explicit cue to the metaphorical nature of an utterance is when the first-order and the second-order interpretation point to two distinct semantic fields. Equivalently, an incongruity principle (incongruity between a focus and a frame) can be used. The cognitive force of metaphor comes from a reconceptualization of information about the world that has already been acquired but possibly not conceptualized. Kittay agrees that metaphor may well be one of the primary ways in which humans organize their experience. Kittay's vision is radical: metaphorical meaning is not reducible to literal meaning. Metaphor can be viewed as second-order meaning. Metaphor as Knowledge Ellen Cornell Way realized that metaphor is a generalized concept which includes both the tenor and the vehicle concepts. The metaphor "marriage is a nightmare" is a generalization that includes both "marriage" and "nightmare" ("unpleasant things that happen to you whether you want them or not"). Way actually believes that metaphor is the way we assimilate new. The system of categories is not fixed: new categories can be created, and the mechanism to create a new category is metaphor, precisely by generalization (or "supertype"). Way's theory of metaphor is based on Black's interactionist model: metaphor involves a transfer of knowledge and actually creates similarity. The formalism in which she expressed the supertype theory is based on a modified version of Sowa's conceptual graphs. In her model, sentences translate into conceptual graphs, and conceptual graphs relate the concepts of the sentence to a type hierarchy. She claims that what determines whether speech is literal or figurative is the particular perspective of the type hierarchy that is reflected in the speech. Way expresses this perspective with a "mask" (in Sowa’s sense) on the type hierarchy. If the perspective invoked by the context complies with the classification of natural kinds (such as "water", "gold", "bird", etc), speech is literal. The type hierarchy changes dynamically because of the continuous change in cultural and social conventions. Therefore, what is literal and what is metaphorical may also change. Metaphor as physiological organization Borrowing from the work of Stevan Harnad, who thinks that sensory experience is recorded as a http://www.thymos.com/tat/metaphor.html (7 of 9)25/07/2003 14:33:36
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continuous engram whereas a concept derived from sensory experience is recorded by discrete engrams, Bipin Indurkhya thinks that metaphor originated from the interaction between sensory-based and conceptbased representations in the brain, which are structurally different. Indurkhya's theory highlights the key role of the metaphorical process in human thought. Metaphor as conceptual blending Gilles Fauconnier's theory of mental spaces constitutes a natural generalization of metaphor, where the number of conceptual spaces that blend is only two: the one described by the metaphor (the "tenor") and the one which provides the description (the "vehicle"). Fauconnier adds two more spaces to deal with metaphors: the "generic" space, which represents all the shared concepts that are required by tenor and vehicle, which are necessary not only to understand the metaphor but to mediate between the tenor and the vehicle; and the "blend" space, which contains the solution, the concept generated by the metaphor. The tenor and the vehicle are reconciled thanks to the generic space and this reconciliation produces the blend space. Metaphorical ignorance There is one weakness in the experimental praxis of linguists: they only study people who are fluent in a language. If you want to study chaxipean, you go to Chaxipe and talk to chaxipeans. They are the world experts in chaxipean. Most of our ideas on language, categorization and metaphors come from studying people who are fluent in a language. But the brain of a person who is not fluent in that language should be working the same way. My "use" of the German language, though, is not the same as a native German's. I stay away from metaphors in a language like German that I barely understand. Using a metaphor in German sounds scary to me. I stick to simple sentences whose meaning is transparent. I don't say "their marriage is going nowhere": I say "their marriage is not good". I reduce all concepts to elementary concepts of good and bad, ugly and beautiful, etc. This goes against the claim that metaphor is useful to express meaning in a more efficient way. People who do not master a language should use metaphor precisely to compensate that deficiency. Instead, we tend to do the opposite: if we don't master a language, we avoid metaphors. Metaphorical language requires mastering the language skills first, and is proportional to those skills. This is what the traditional theory predicted (metaphor is for poets, language specialists). There is a grain of truth in it, which is not accounted for by any of the modern theories of metaphor.
Further Reading
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Arbib Michael: CONSTRUCTION OF REALITY (Cambridge University Press, 1986) Black Max: MODELS AND METAPHORS (Cornell Univ Press, 1962) Fauconnier Gilles: MENTAL SPACES (MIT Press, 1994) Breal Michel: ESSAY DE SEMANTIQUE (1897) Hintikka Jaakko: ASPECTS OF METAPHOR (Kluwer Academics, 1994) Kittay Eva: METAPHOR (Clarendon Press, 1987) Indurkhya Bipin: METAPHOR AND COGNITION (Kluwer Academic, 1992) Lakoff George: METAPHORS WE LIVE BY (Chicago Univ Press, 1980) Lakoff George: MORE THAN COOL REASON (University of Chicago Press, 1989) Lakoff George: WOMEN, FIRE AND DANGEROUS THINGS (Univ of Chicago Press, 1987) Lakoff George: PHILOSOPHY IN THE FLESH (Basic, 1998) MacCormac Earl: A COGNITIVE THEORY OF METAPHOR (MIT Press, 1985) Martin James: A COMPUTATIONAL MODEL OF METAPHOR INTERPRETATION (Academic Press, 1990) Mithen Steven: THE PREHISTORY OF THE MIND (Thames and Hudson, 1996) Ortony Andrew: METAPHOR AND THOUGHT (Cambridge Univ Press, 1979) Way Ellen Cornell: KNOWLEDGE REPRESENTATION AND METAPHOR (Kluwer Academic, 1991)
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Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Pragmatics: Why We Speak (Reddy, Grice, Austin, Searle, Sadock, Sperber and Wilson)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Use of Language In 1979 the linguist Michael Reddy dubbed "conduit metaphor" the idea, deeply entrenched in popular thinking, that the mind contains thoughts that can be treated like objects. That metaphor views linguistic expressions as vehicles for transporting ideas along a conduit which extends from the speaker to the listener. These vehicles are strings of words, each of which contains a finite amount of a substance called meaning: the speaker assembles the meaning, loads the vehicle and sends it along the conduit. The listener receives the vehicle, unloads it and unscrambles the meaning. Reddy thinks otherwise: the transfer of thought is not a deterministic, mechanical process. It is an interactive, cooperative process. Language is a much more complicated affair than it appears. Syntax, metaphor, semantics are simply aspects of how we interpret and construct sentences. But first and foremost language is a game that we engage with other speakers. A lot more information is exchanged through the "use" we make of language. The Austrian philosopher Ludwig Wittgenstein argued that to understand a word is to understand a language and to understand a language is to master the linguistic skills. A word, or a sentence, has no meaning per se. It is not the meaning, it is the "use" of language that matters. The discipline of pragmatics studies aspects of meaning that cannot be accounted for by semantics alone, but have to do with the way language is used. Ultimately, Pragmatics’ goal is to understand the "reason" of a speech. What are the speaker’s motif and goal? For example, semantics can account for the meaning of the sentence "do you know what time it is?", but not for the fact that an answer is required (the speaker’s intention is to learn what time it is). The way language is used has to do with the context: there is no speech without a context. For example, the
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same sentence may be used for two different purposes in two different contexts: "do you know what time it is?" may be a request (equivalent to "what time is it?") or a reproach (as in "you are very late"). The only way to discriminate what that sentence really means is to analyze the context. The issues of pragmatics can therefore be summarized essentially in the relationship between language and context. Because context is the key element, pragmatic studies focus on "indexicals", " implicatures" and "presuppositions". Indexicals are terms such as "I", "today", "now" whose referents depend on the context: "I am a writer" is true if I am Piero Scaruffi, but it is false if I am Sharon Stone. Just like "I" may refer to any person in the world, "today" may refer to any day of the year and "here" to any place in the universe. Only the context can fix the meaning of indexicals. Implicatures are the facts that are implied by the sentence: "the Pope held mass in St. Peter’s square" implies that the Pope is alive. Presuppositions are the facts that are taken for granted, for example the fact that humans die and a job earns money. The purpose of a speech in a given context is to generate some kind of action. There is an "intention" to the speech and to the way the speech is structured. Pragmatics studies intentional human action. Intentional action is action intended to achieve a goal, though some kind of plan, given some beliefs about the state of things. This results in "speech acts" that carry out, directly or indirectly, the plan. Therefore pragmatics deals with beliefs, goals, plans and ultimately with speech acts, unlike syntax and semantics which deal, respectively, with the structure of a sentence and with the isolated meaning of the sentence. Language as Cooperation In 1967 the British philosopher Paul Grice had an influential intuition: that language is based on a form of cooperation among the speakers. For language to be meaningful, both the speaker and the hearer must cooperate in the way they speak and in the way they listen. The way they do it, is actually very simple: people always choose the speech acts that achieve the goal with minimum cost and highest efficiency. Language has meaning to the extent that some conventions hold within the linguistic community. Those conventions help the speaker achieve her goal. The participants of a conversation cooperate in saying only what makes sense in that circumstance. Grice was influential in emphasizing the linguistic interplay between the speaker, who wants to be understood and cause an action, and the listener. This goes beyond syntax and semantics. A sentence has a timeless meaning, but also an occasional meaning: what the speaker meant to achieve when she uttered it. Grice's four maxims summarize those conventions: provide as much information as needed in the context, but no more than needed (quantity), tell true information (quality), say only things that are relevant to the context (relation), avoid ambiguity as much as possible (manner). The significance of an utterance includes both what is said (the explicit) and what is implicated (the implicit). Grice therefore distinguished between the "proposition expressed" from the "proposition implied", or the "implicature". Implicatures exhibit properties of cancellability (the implicature can be removed without creating a contradiction) and calculability (an implicature can always be derived by reasoning under the assumption that the speaker is observing pragmatic principles). http://www.thymos.com/tat/pragmati.html (2 of 5)25/07/2003 14:33:51
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Grice’s maxims help the speaker say more than what she is saying. They do so through implicatures which can be implied by the utterance. Grice distinguishes two types of implicatures, depending on how they arise. Conventional implicatures are determined by linguistic constructions in the utterance. Conversational implicatures follow from maxims of truthfulness, informativeness, relevance and clarity that speakers are assumed to observe. Conversational implicatures can be discovered through an inferential process: the hearer can deduct that the speaker meant something besides what he said by the fact that what he said led the hearer believe in something and the speaker did not do anything to stop him from thinking it. The fundamental intuition was that there is more to a sentence than its meaning. A sentence is "used" for a purpose. As a matter of fact, Jerrold Sadock distinguished semantic sense from interpreted sense (meaning from use), as two different aspects of language.
The Logic of Speech Acts In the Fifties, the philosopher the British Philosopher John Langshaw Austin had started a whole new way of analyzing language by viewing it as a particular case of action: "speech action". Austin introduced a tripartite classification of acts performed when a person speaks. Each utterance entails three different categories of speech acts: a "locutionary" act (the words employed to deliver the utterance), an "illocutionary" act (the type of action that it performs, such as warning, commanding, promising, asking), and a "perlocutionary" act (the effect that the act has on the listener, such as believing or answering). A locutionary act is the act of producing a meaningful linguistic sentence. An illocutionary act sheds light on why the speaker is uttering that meaningful linguistic sentence. A perlocutionary act is performed only if the speaker's strategy succeeds. Austin believed that any locutionary act (phonetic act plus phatic act plus rhetic act) is part of a discourse which bestows an illocutionary force on it. All language is therefore an illocutionary act. In the Seventies, the American philosopher John Searle developed a formal theory of the conditions that preside to the genesis of speech acts. Searle classifies such acts in several categories, including "directive acts", "assertive acts", "permissive acts" and "prohibitive acts". And showed that only assertive acts can be treated with classical logic. To Searle, illocutionary acts, acts performed by a speaker when she utters a sentence with certain intentions (e.g., statements, questions, commands, promises), are the minimal units of human communication. An illocutionary act consists of an illocutionary force (e.g., statement, question, command, promise) and a propositional content (what it says). Ultimately, Searle believes that the illocutionary force of sentences is what determines the semantics of language. The Logic of Relevance
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Dan Sperber and Deirdre Wilson have shown that "relevance" constraints a discourse's coherence and enables its understanding. Relevance is a relation between a proposition and a set of contextual assumptions: a proposition is relevant in a context if and only if it has at least one contextual implication in that context. The contextual implications of a proposition in a context are all the propositions that can be deduced from the union of the proposition with the context. A universal goal in communication is that the hearer is out to acquire relevant information. Another universal goal is that the speaker tries to make his utterance as relevant as possible. Understanding an utterance then consists in finding an interpretation which is consistent with the principle of relevance. The principle of relevance holds that any act of ostensive communication also includes a guarantee of its own optimal relevance. This principle is proven to subsume Grice's maxims. Relevance can arise in three ways: an interaction with assumptions which yields new assumptions, the contradiction of an assumption which removes it, additional evidence for an assumption which strengthens the confidence in it. Implicatures are either contextual assumptions or contextual implications that the hearer must grasp to recognize the speaker as observing the principle of relevance. The process of comprehending an utterance is reduced to a process of hypothesis formation and confirmation: the best hypothesis about the speaker's intentions and expectations is the one that best satisfies the principle of relevance. The idea that language can make sense only if speaker and listener cooperated recurs often in modern literature. The American philosopher Donald Davidson points out that language transmits information. The speaker and the listener share a fundamental principle to make such transmission as efficient as possible. Such "principle of charity" asserts that the interpretation to be chosen is the one in which the speaker is saying the highest number of true statements. During the conversation the listener tries to build an interpretation in which each sentence of the speaker is coupled with a truth-equivalent sentence. Language, far from being a mechanical process of constructing sentences and absorbing sentences, is a subtle process of cooperating with the other speaker to achieve the goal of communicating. Further Reading Austin John Langshaw: HOW TO DO THINGS WITH WORDS (Oxford Univ Press, 1962) Davis Steven: PRAGMATICS (Oxford University Press, 1991) Gazdar Gerald: PRAGMATICS (Academic Press, 1979) Green Georgia: PRAGMATICS (Lawrence Erlbaum, 1996) Grice H. Paul: STUDIES IN THE WAY OF WORDS (Harvard Univ Press, 1989)
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Levinson Stephen: PRAGMATICS (Cambridge Univ Press, 1983) Sadock Jerrold: TOWARD A LINGUISTIC THEORY OF SPEECH ACTS (Academic Press, 1974) Searle John: SPEECH ACTS (Cambridge Univ Press, 1969) Sperber Dan & Wilson Deirdre: RELEVANCE, COMMUNICATION AND COGNITION (Blackwell, 1995) Wittegenstein Ludwig: PHILOSOPHICAL INVESTIGATIONS (1958)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Meaning: A Journey to the CEnter of the Mind (Tarski, Kripke, Barwise & Perry, Quine, Churchland, Dummett, Hintikka, Johnson-Laird, Putnam, Fodor, Davidson, Lycan)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Meaning of Meaning: knowing what things are In our time it is common and fashionable to ask "what is the meaning of life?" The problem is that we don't even know the answer to the simpler question: "what is meaning?" What do we mean when we say that something means something else? Meaning is intuitively very important. We all assume that what matters is the meaning of something, not the something per se. But then nobody really knows how to define what "meaning" means. The symbol "LIFE" per se is not very interesting, but the thing it means is very interesting. Grammatical principles are innate and universal. Everybody is born with the ability to learn language. But our language ability depends not only on symbolic utterance (on constructing grammatically-correct sentences), but also on our ability to make use of symbolic utterance, to connect the idea with some action. Spoken language is not even that essential: we can communicate with gestures and images. This happens since birth, as linguistic and nonlinguistic information (e.g.,visual) are tied from the beginning. What matters is the ability to comprehend. As a matter of fact, in a baby, comprehension is ahead of utterance. Since meaning is first and foremost "about" something, an obvious component of meaning is what philosophers call "intentionality": the ability to refer to something else. The word "LIFE" refers to the phenomenon of life. Far from being an exclusive of the human mind, meaning in this broad sense is rather pervasive in nature. One could even claim that everything in nature refers to everything else, as it would probably not exist without the rest of the universe. Certainly, a shadow refers to the object that makes it, and a crater refers to the meteor that created it. But "meaning" in the human mind also involves being aware of it, and in this narrow sense "meaning" could be an exclusive of the human mind. There are, therefore, at least two components of meaning: intentionality and awareness. Something refers to http://www.thymos.com/tat/meaning.html (1 of 9)25/07/2003 14:34:10
Thinking About Thought: Consciousness, Life and Meaning
something else, and I am aware of this being the case. There is another piece of the puzzle. First you wonder how things in our mind (mainly language) relate to things in the world. Then you realize that you don't even know what you refer to! Think of water, a fairly innocent subject: what does the concept of "water" refer to? The substance? The chemical compound H2O? Something liquid and transparent that is found in rivers and in the rain? Imagine that in another world there is a substance that looks and behaves just like water, but is made of a different chemical compound. When I and a person of that world think of water, are we referring to the same thing or to two different things? What is a clock? An object whose function is that of marking the time (which could be a sundial)? Or an object whose structure is round, has two hands and 12 numbers (which could be a toy clock that does not perform any actual function)? Meaning affects two complementary aspects of our mind: language (i.e., the way we communicate meaning to other thinking beings) and concepts (i.e., the way we store meaning for future reference). As the British philosopher Paul Grice noted, there are two different meanings to the word "meaning": "what did she mean" and "what does that refer to". The meaning of a speaker is what he intended to say. There is an intention to take into account. The meaning of a word relating to a natural phenomenon is what it refers to (the meaning of "water" is the substance water). It is intuitive that meaning must be central to understanding the mind, but what is its relationship with it? Is meaning independent of the mind, or is it tightly related to the mind? Is it a product of the mind? Or is the mind a product of meaning? Do things have meaning regardless of whether we think of them, or does meaning arise from nothing when we think? And why do things mean in the first place? Intension and Extension: what is a concept? A fundamental step in the modern conception of meaning came with Gottlob Frege's distinction between "sense" and "reference", which led to the distinction between "intension" and "extension". The "referent" of a word is the object it refers to, the "sense" of that word is the way the referent is given. For example, "the star of the morning" and "the star of the evening" have two different senses but the same referent (they both refer to the planet Venus). A more important example: propositions of classical Logic can only have one of two referents, true or false. The "extension" of a concept is all the things that belong to that concept. For example, the extension of "true" is the set of all the propositions that are true. The "intension" of that concept is the concept itself. For example, the extension of "red" is all the objects that are red, whereas the intension of "red" is the fact of being red. There is an intuitive relationship between sense and intension, and between reference and extension. But the relationship between sense and reference is not intuitive at all, as proved by the difficulty in handling indexicals (words such as "I") and demonstratives (such as "this"). The proposition "I am Piero Scaruffi" is true or false depending on who utters it. The proposition "I am right and you are wrong" has http://www.thymos.com/tat/meaning.html (2 of 9)25/07/2003 14:34:10
Thinking About Thought: Consciousness, Life and Meaning
two completely opposite meanings depending on who utters it. A number of alternatives to Frege’s analysis have been proposed over the decades: Saul Kripke's and Hilary Putnam's casual theory of reference (which assumes a causal link between a word and what it stands for), Kripke's distinction of rigid designators and non-rigid designators in the context of possible worlds, and Montague's intensional logic (in which the sense of an expression is supposed to determine its reference). These are all different views on how sense and reference relate. More than just a name? Do meanings exist? "Nominalism" is a centuries-old philosophical faith according to which "universals" exist only in our mind and language. We tend to assign them a reality of their own when, in reality, they are just conventions used by our minds and our language. At the other end of the spectrum, Plato claimed that ideas exist in a world of their own, independent of our material world. Possible World Semantics It all started with the great Polish mathematician Alfred Tarski, who based his "model-theoretic" semantics (models of the world yield interpretations of sentences in that world) on his "correspondence theory of truth" (a statement is true if it corresponds to reality), so that the meaning of a proposition is, basically, the set of situations in which it is true. In the Sixties, Saul Kripke expanded the "model-theoretic interpretation" to Modal Logic. Modal Logic is a logic that adds two more truth values, "possible" and "necessary" (also know as "modal" values) to the two traditional ones, "true" and "false". Kripke defined modality through the notion of possible worlds: a property is necessary if it is true in all worlds, a property is possible if it is true in at least one world. Thanks to these two operators, it is possible to discriminate between sentences that are false but have different intensions. In classical Logic, sentences such as "Piero Scaruffi is the author of the Divine Comedy" and "Piero Scaruffi is Michelle Pfeiffer’s lover" have the same extension, because they are both false. In Modal Logic they have different extensions, because the former is impossible (because I was not alive at the time), whereas the latter is also false but could be true. Also, Modal Logic avoids paradoxes that classical Logic cannot deal with. For example, the sentence "all mermaids are male" is intuitively false, but classical Logic would consider it true (because mermaids do not exist and the implication is reduced to the negation of mermaids, which is true, OR the second term, yielding always a result of true). In Modal Logic this sentence is false in the world where mermaids do exist. The advantage of Kripke's semantics is that it can interpret sentences that are not extensional (that do not satisfy Leibniz's law), such as those that employ opaque contexts (to know, to believe, to think) and those http://www.thymos.com/tat/meaning.html (3 of 9)25/07/2003 14:34:10
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that employ modal operators. Put bluntly, Kripke's semantics can interpret all sentences that can be reduced to "it is possible that" and "it is necessary that". The trick is that in his semantics a statement that is false in this universe can be true in another universe. The truth values of a sentence are always relative to a particular world. A proposition does not have a truth value, but a set of truth values, one for each possible world. Tarski's theory is purely extensional (for each model the truth of a predicate is determined by the list of objects for which it is true), whereas Kripke's modal logic is intensional. An extensional definition would actually be impossible, since the set of objects is infinite. In Kripke’s possible worlds, interesting things happen to names. Proper names and definite descriptions are designators. A non-rigid designator is a term that changes its referent across possible worlds. Proper names are rigid designators, i.e. in every possible world they designate the same object ("Piero Scaruffi" is always the same person). Kripke (unlike Frege) carefully distinguished the meaning of a designator and the way its reference is determined (which are both "sense" in Frege). Then he put forth his "causal theory of naming": names are linked to their referents through a causal chain. A term applies directly to an object via a connection that was set in place by the initial naming of the object. Initially, the reference of a name is fixed by some operation (e.g., by description), then the name is passed from speaker to speaker basically by tradition. A name is not identified by a set of unique properties satisfied by the referent: the speaker may have erroneous beliefs about those properties or they may not be unique. If a scientist discovered that water in not H20, water would still be called water and would still be what it is today. Kripke rejects the view that either proper or common nouns are associated with properties that serve to select their referents. Names are just "rigid designators". Both proper and common names have a referent, but not a Fregean sense. The property cannot determine the reference as the object might not have that property in all worlds. For example, gold may not be yellow in all worlds. Analogously, Jerry Fodor argued in favor of two types of meaning: one is the "narrow content" of a mental representation, which is a semantic representation, is purely mental and does not depend on anything else; and the other is the "broad content", a function that yields the referent in every possible world, and depends on the external world. Narrow content is a conceptual role. As in Wilfrid Sellars, a role is a purely syntactic property, as they occur in formal systems. Meaning needs both narrow and broad contents. In the Eighties, the American mathematicians John Barwise's and John Perry have proposed "situation semantics", a relation theory of meaning: the meaning of a sentence provides a constraint between the utterance and the described situation. Sentences stand for situations, rather than for truth values. Properties and relations are primitive entities. Situations are more flexible than Kripke's possible worlds because they don't need to be coherent and don't need to be maximal. Just like mental states. Holism: meaning is relative http://www.thymos.com/tat/meaning.html (4 of 9)25/07/2003 14:34:10
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The American philosopher Willard Quine was the messiah of holism. Quine's "underdetermination" theory originated in the sciences. He was profoundly influenced by an argument put forth by the French physicist Pierre Duhem: that hypotheses cannot be tested in isolation from the whole theoretical network in which they appear. Quine argued that an hypothesis is verified true or false only relative to background assumptions. For every empirical datum there can be an infinite number of theories that explain it. Science simply picks the combination of hypotheses that seems more plausible. When a hypothesis fails, the scientist can always modify the other hypotheses to make it hold. There is no certain way to determine what has to be changed in a theory: any hypothesis can be retained as true or discarded as false by performing appropriate adjustments in the overall network of assumptions. No sentence has special epistemic properties that safeguard it from revision. Ultimately, science is but self-conscious common sense. Language is a special case. An empirical datum is a discourse and a theory is its meaning. There are infinite interpretations of a discourse depending on the context. A single word has no meaning, its referent is "inscrutable". The meaning of language is not even in the mind of the speaker. It is a natural phenomenon related to the world of that speaker. Quine thinks that the meaning of a statement is the method that can verify it empirically. But verification of a statement within a theory depends on the set of all other statements of the theory. Each statement in a theory partially determines the meaning of every other statement in the same theory. In particular, the truth of a statement cannot be assessed as a function of the meaning of its words. Words do not have an absolute meaning. They have a meaning only with respect to the other words they are connected to in the sentences that we assume to be true. Their meaning can even change in time. In general, the structure of concepts is determined by the positions that their constituents occupy in the "web of belief" of the individual. Meaning has no meaning. The only concept that makes sense for interpreting sentences is truth. A sentence can be true or false, but what it refers to is not meaningful. Paul Churchland's attitude towards meaning is as holistic as Quine's, but Churchland interprets Quine's network of meanings as a space of semantic states, whose dimensions are all observable properties. Each expression in the language is equivalent to defining the position of a concept within this space according to the properties that the concept exhibits in that expression. The semantic value of a word derives from its place in the network of the language as a whole Verificationism: meaning is reality The British philosopher Michael Dummett has criticized holism because it cannot explain how an individual can learn language. If the meaning of a sentence only exists in relationship to the entire system of sentences in the language, it would never be possible to learn it. For the same reason it is not possible to
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understand the meaning of a theory, if its meaning is given by the entire theory and not by single components. Dummett's theory of meaning is instead a variant of intuitionistic logic: a statement can be said to be true only when it can be proved true in a finite time (it can be "effectively decided", similar to the intuitionistic "justified"). Similarly, Jaakko Hintikka proposed a "game-theoretical semantics", whereby the semantic interpretation of a sentence is reduced to a game between two agents. The semantics searches truth through a process of falsification and verification. The truth of an expression is determined through a set of domain-dependent rules which define a "game" between two agents: one agent is trying to validate the expression, the other one is trying to refute it. The expression is true if the truth agent wins. Unlike Dummett's verificationist semantics, Hintikka's is still a "truth-conditional" semantics. Philip Johnson-Laird also believes that the meaning of a sentence is the way of verifying it. In his "procedural" semantics, a word's meaning is the set of conceptual elements that can contribute to build a mental procedure necessary to comprehend any sentence including that word. Those elements depend on the relations between the entity referred by that word and any other entity it can be related to. Rather than atoms of meanings, we are faced with "fields" of meaning, each including a number of concepts that are related to each other. The representation of the mental lexicon handles the intensional relations between words and their being organized in semantic fields. Externalism: meaning is in the society Hilary Putnam attacked model-theoretic semantics from another perspective: in his opinion, it fails as a theory of meaning because meaning does not stand in the relationship between symbols and the world. Putnam argued that "meaning is not in the mind" with his thought experiment of the "twin earths". Putnam imagines a world called "Twin Earth" exactly like Earth in every respect except that the stuff which appears and behaves like water, and is actually called "water", on Twin Earth is a chemical compound XYZ. If one Earth and one Twin Earth inhabitants, identical in all respects, think about "water", they are thinking about two different things, while their mental states are absolutely identical. Putnam concludes that the content of a concept depends on the context. Meanings are not in the mind, they also depend on the objects that the mind is connected to. Meaning exhibits an identity through time but not in its essence (such as the momentum, which is a different thing for Newton and Einstein but expresses the same concept). An individual's concepts are not scientific and depend on the environment. Most people know what gold is, and still they cannot explain what it is and even need a jeweler to assess whether something is really gold or a fake. Still, if some day we found out that Chemistry has erred in counting the electrons of the atom of gold, this would not change what it is. The meaning of the word "gold" is not its scientific definition, but the social meaning that a community has given it. It is not true that every individual has in its mind all the knowledge needed to understand the referent of a word. There is a subdivision of competence among human beings and the referent of a word is due to their cooperation. Truth-conditional Semantics: meaning is truth http://www.thymos.com/tat/meaning.html (6 of 9)25/07/2003 14:34:10
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Today, the American philosopher Donald Davidson is the main proponent of "truth-conditional semantics", which reduces a theory of meaning to a theory of truth. Tarski simply replaced the universal and intuitive notion of "truth" with an infinite series of rules which define truth in a language relative to truth in another language. Davidson would rather assume that the concept of "truth" need not be defined, that it be known to everybody. Then he can use the correspondence theory of truth to define meaning: the meaning of a sentence is defined as what would be if the sentence were true. The task for a theory of meaning then becomes to generate all meta-sentences (or "T-sentences") for all sentences in the language through a recursive procedure. This account of meaning relies exclusively on truth conditions. A sentence is meaningful in virtue of being true under certain conditions and not others. To know the meaning of a sentence is to know the conditions under which the sentence would be true. A theory of a language must be able to assign a meaning to every possible sentence of the language. Just like Chomsky had to include a recursive procedure in order to explain the speaker's unlimited ability to recognize sentences of the language, so Davidson has to include a recursive procedure in order to explain the speaker's unlimited ability to understand sentences of the languages. Natural languages exhibit an additional difficulty over formal languages: they contain deictic elements (demonstratives, personal pronouns, tenses) which cause the truth value to fluctuate in time and depend on the speaker. Davidson therefore proposes to employ a pair of arguments for his truth predicate, one specifying the speaker and one specifying the point in time. In other words, Davidson assigns meanings to sentences of a natural language by associating the sentences with truth-theoretically interpreted formulas of a logical system (their "logical form"). In that tradition Lycan's theory of linguistic meaning also rests on truth conditions. All other aspects of semantics (verification conditions, use in language games, illocutionary force, etc.) are derived from that notion. A sentence is meaningful in virtue of being true under certain conditions and not others. Lycan basically refines Davidson's meta-theory. Instead of assigning only a pair of arguments to the truth predicate, Lycan defines truth as a pentadic relation with reading (the logical form), context (truth is relative to a context of time and speaker, as specified by some assignment functions), degree (languages are inherently vague, and sentences normally contain fuzzy terms and hedges), and idiolect (the truth of a sentence is relative to the language of which it is a grammatical string). Further Reading Barwise John & Perry John: SITUATIONS AND ATTITUDES (MIT Press, 1983) Barwise Jon: THE SITUATION IN LOGIC (Cambridge Univ Press, 1988) Bunge Mario: TREATISE ON BASIC PHILOSOPHY (Reidel, 1974-83)
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Castaneda Hector-Neri: THINKING, LANGUAGE, EXPERIENCE (University of Minnesota Press, 1989) Churchland Paul: SCIENTIFIC REALISM AND THE PLASTICITY OF MIND (Cambridge Univ Press, 1979) Davidson Donald: INQUIRIES INTO TRUTH AND INTERPRETATION (Clarendon Press, 1984) Dummett Michael: ELEMENTS OF INTUITIONISM (Oxford University Press, 1977) Dummett Michael: TRUTH AND OTHER ENIGMAS (Harvard Univ Press, 1978) Dummett Michael: SEAS OF LANGUAGE (Clarendon, 1993) Engelmore Robert: BLACKBOARD SYSTEMS (Academic Press, 1988) Fodor Jerry: A THEORY OF CONTENT (MIT Press, 1990) Hintikka Jaakko: THE GAME OF LANGUAGE (Reidel, 1983) Johnson-Laird Philip: MENTAL MODELS (Harvard Univ Press, 1983) Kirkham Richard: THEORIES OF TRUTH (MIT Press, 1992) Kripke Saul: NAMING AND NECESSITY (Harvard University Press, 1980) Lycan William: LOGICAL FORM IN NATURAL LANGUAGE (MIT Press, 1984) Moore A.W.: MEANING AND REFERENCE (Oxford Univ Press, 1993) Putnam Hilary: MIND, LANGUAGE AND REALITY (Cambridge Univ Press, 1975) Putnam Hilary: REASON, TRUTH AND HISTORY (Cambridge Univ Press, 1981) Putnam Hilary: REPRESENTATION AND REALITY (MIT Press, 1988) Quine Willard: WORD AND OBJECT (MIT Press, 1960) Quine Willard: FROM A LOGICAL POINT OF VIEW (Harper & Row, 1961) Quine Willard: THE WEB OF BELIEF (Random House, 1978) Quine Willard: ONTOLOGICAL RELATIVITY (Columbia Univ Press, 1969)
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Tarski Alfred: LOGIC, SEMANTICS, METAMATHEMATICS (Clarendon, 1956)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Ecological Realism: The embodied mind (Helmholtz, Gibson, Neisser, Dretske, Plotkin, Dennett, Gallistel, Bogdan, Barwise & Perry, Brooks, Breitenberg, Maturana, Varela, Dawkins, Millikan, Lewontin)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Information Flow No living being can live in a vacuum. Life in a vacuum is an oxymoron. Life needs an environment. Life is transformation, and, without an environment, physical laws forbid transformation. Transformation requires energy from an external source. Life is a continuously changing equilibrium between an organism and its environment. Even the most remote organism is connected to the rest of the biosphere via the air, which is the way it is mainly because of the metabolism of living beings (the atmosphere contains far more methane and other gases than chemical reactions alone would create). From a biological perspective, the mind is one of the many organs that help an organism survive in the real world. Ultimately, from a biological perspective, the minds belongs to a body. In the 1960s, the work of American biologist James Jerome Gibson originated "ecological realism", the view that meaning is located in the interaction between living beings and the environment. Gibson started out with a critique of the traditional model of perception (that goes back to Helmholtz) and ended with a new view of what cognition is. The 19th-century German physicist Hermann von Helmholtz thought that perceptions are "unconscious inferences". Mind is isolated from the world and only knows what the senses deliver. The senses deliver signals, and the mind has to figure out how to interpret them. The mind uses whatever knowledge it has accrued. As proven by optical illusions, mind makes assumptions on such signals and "infers" what reality is. Perceptions are "hypotheses" on what reality just might be. But all of this inferring is largely invibile.
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Most of what goes on in the brain does not surface to the mind. Passive cognition According to Gibson, instead, the process of perceiving is a process of "picking up" information that is available in the environment. The "information" that the organism uses originates from the interaction between the organism and its environment. The way this information is acquired is rather passive: the organism is free to move in the world, but it's the environment that feeds it information. The way this information is "processed" is direct: there is no mediation by the mind. Action follows perception, and the two can be viewed as dual aspects of the same process. Cognitive life is passive as in "no active inference, "no effort to understand information". The brain does not organize the sensory input or process the sense data. The brain is simply a tool to seek and extract information about the environment. What the brain truly does is recognize information. Information, for Gibson, is patterns: any pattern of environmental stimuli that repeats itself over time constitutes "information". Our brain is an organ capable of discovering "invariants" in the environmental stimuli. Physically, that pattern of stimuli is a pattern of energy that impinges on the brain. A pattern of energy that flows through the sensory system, and that depends in a reliable way on the structure of the environment, is information. In other words, any pattern of energy that corresponds to the structure of the world carries information about the world. We use this principle, for example, every time we draw a line to represent the edge of an object. Perception is a continuously ongoing process and consists in detecting the invariants of the environment. The function of the brain is to orient the organs of perception for seeking and extracting information from the continuous energy flow of the environment. It follows that perception and action are not separate processes. And perception cannot be separated from the environment in which the perceptive system (the organism) evolved and from the information which is present in that environment. Perception, action and the environment are tightly related. Far from being simply a background for action, the environment is therefore viewed as a source of stimulation. Organisms move in the world using all the information that is available in it. Perceptual organs are not passive: they can orient themselves to pick up information, to "resonate" with the information in the environment. Ultimately, there is much more information in the world and less in the head than was traditionally assumed. And the environment does most of the work that we traditionally ascribe to the mind. David Marr explained "how" we see. Gibson explained "what" we see, and why we see what we see. Directed cognition
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Thinking About Thought: Consciousness, Life and Meaning
Ulric Neisser refined this thesis. He defined cognition as the skill of dealing with knowledge that comes from the environment. The mind developed to cope with that knowledge. Neisser agrees with Gibson that organisms "pick up" information from the environment, but he differs from Gibson in that he argues in favor of directionality of exploration by the organism: the organism is not completely passive in the hands of the environment, but somehow it has a cognitive apparatus that directs its search for information. Schemas account for how the organism can gather the available information from the environment. Between perception and action there exists a direct relation, one that is expressed by schemas. A schema is a blueprint for what information the organism presumes to encounter and what that information entails in the environment. The organism selects information from the environment based on its anticipatory schemas. "We can see only what we know how to look for". At every instant the organism constructs anticipations of information that make it easy to pick it up when it becomes available. Once picked up, information may in turn result in a change of the original schema, to direct further exploration of the environment. Perception is therefore a perennial cycle, from schemas to action (schemas direct action) to information (action picks up information) to schemas (information modifies schemas). The schema accounts for adaptive behavior while conserving the preeminence of cognitive processes. Neisser’s "cyclical" theory of perception also explains how the mind "filters" the huge amount of information that would exceed its capacity. An orienting schema of the nearby environment, or "cognitive map", guides the organism around the environment. A cognitive map contains schemas of the objects in the environment and spatial relations between the objects. Perception is not about classifying objects in categories, creating concepts or any other sophisticated cognitive process. Perception is about using the information available in the surroundings for the purpose of directing action in it. Perception and cognition transform the perceiver: an organism "is" the cognitive acts it engages in. Organisms and environment The American philosopher Fred Dretske also believes that information is in the environment and cognitive agents simply absorb it, thereby creating mental states. As Dretske puts it, information is what we can learn about the environment from a sensory signal. From a biological standpoint, Daniel Dennett's "intentional stance" defines just the relationship between an organism and its environment. The organism continuously reflects its environment, as the organization of its system implicitly contains a representation of the environment. The organism refers to the environment. Intentionality defines an organism as a function of its beliefs and desires, which are products of natural selection. Intentional states are not internal states of the system, but descriptions of the relationship between the system and its environment. The British psychologist Henry Plotkin defines knowledge itself as incorporating the environment. His focus is on the harmony established over the centuries between the organization and structure of a living being and the world it inhabits. Adaptation is the act of incorporating the outside world into the organism's http://www.thymos.com/tat/ecologic.html (3 of 14)25/07/2003 14:34:27
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structure and organization. More properly, this is "biological" knowledge. But human knowledge is simply a subset of biological knowledge. This school of thought has been influential in reversing the traditional role between the living organism and the environment: the organism is no longer a protagonist, its free will unleashed and its creativity unlimited; the organism is a far more passive actor in the overall drama of Nature, one that has to rely upon- and whose behavior is conditioned by- the information that the environment supplies. Ecological realism has also been influential in reshaping the profile of a cognitive system: since a cognitive system is simply an apparatus to pick up information and translate it into appropriate action, it turns out that pretty much any living thing can be considered, to some extent, as a cognitive system. All of a sudden, life and cognition have lost some of their exclusive appeal, as we realized how constrained and passive they are. Situation Theory The conceptual revolution due to biological theories has had profound repercussions beyond Biology. The American mathematicians John Barwise and John Perry have devised a "situational semantics" which reverses Frege's theory of meaning. According to the tradition founded more than a century ago by the great German mathematician and philosopher Gottlob Frege, meaning is located in the world of sense. On the contrary, Barwise and Perry anchor their theory of meaning to a biological fact: the world is full of meaning that living organisms can use. Meaning is not an exclusive of language, it is pervasive in nature (e. g., "smoke means fire"). Meaning involves the informational content of situations and arises from regularities in the world. Reality is made of situations. Meaning arises out of recurring relations between situations. Barwise's unit of reasoning are situations because reality comes in situations. Situations are made of objects and spatio-temporal locations; objects have properties and stand in relations. A living organism (a part of the world capable of perception and action) must be able to cope with the ever new situations of its course of events and to anticipate the future course of events. It must be able to pick up information about one situation from another situation. This can be realized by identifying similarities between situations, and relations between such similarities. Each organism performs this process of breaking down reality in a different way, as each organism "sees" reality in a different way, based on its ecological needs. The type of a situation is determined by the regularities that the situation exhibits. Regularities are acquired by adaptation to the environment and define the behavior of an organism in the environment. The similarities between various situations make it possible for an organism to make sense of the world. At the same time they are understood by all members of the same species, by a whole "linguistic community". Formally, one situation can contain information about another situation only if there is a relation that holds between situations sharing similarities with the former situation and situations sharing similarities with the latter situation. In that case the first situation "means" the second. Meaning is defined as relations that allow one situation to contain information about another situation. http://www.thymos.com/tat/ecologic.html (4 of 14)25/07/2003 14:34:27
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Barwise emphasizes the "relational" nature of perception (e.g., perception is a relation between perceiver and perceived) and the "circumstantial" nature of information (information is information about the world). The mind, which processes that information, is strictly controlled by the environment. Goal-driven Evolution In his "teleo-evolutionary" theory, Radu Bogdan summarizes things this way: organisms are systems that are genetically programmed to maintain and replicate themselves, therefore they must guide themselves to their goals, therefore they need to obtain relevant information about their environment, therefore they need to be cognitive. It makes evolutionary sense that cognition should appear. But what "guides" the organism, and its cognition, is the environment. It could not be anything else. Cognitive systems are guided by the environment in their goal-driven behavior. Cognitive systems are actually the very product of the evolutionary pressure of that guiding behavior. Central to his thinking is the concept of "goal-directedness": natural selection presupposes goaldirectedness. Goal-directedness arises from the genes themselves, which operate goal-directedly. Organisms manage to survive and multiply in a hostile world by organizing themselves to achieve specific, limited goals in an ecological niche. To pursue their goals, organisms evolve ways to identify and track those goals. Such ways determine which knowledge is necessary. To obtain such knowledge, organisms learn to exploit pervasive and recurrent patterns of information in the world. The information tasks necessary to manipulate such information "select" the appropriate type of cognitive faculties that the organism must be capable of. Imagine an organism that cannot recognize recurring situations: in every single moment of its life, it must improvise how to deal with the current situation. An organism that can recognize recurring situations can develop ways to best react to those types of situations. These "ways" make up its cognition. The organisms that survived are those whose cognition matched the situations that recur in their ecological niche. The mind is not only controlled by the environment: it was created (or at least "selected") by the environment. Cognition as Adaptation The American biologist and psychologist Randy Gallistel believes that the nature of intelligence lies in some "organizational" principles. Those are principles on how to organize a system so that the system can adjust rapidly and efficiently. In other words, "something" enables living organisms to make rapid adjustments of patterns of action in response to the environment. That "something" is the way they are internally organized. No movement in nature is random, it always serves the purpose of "adapting" the state of the system to the external conditions. No matter how intelligent the action of a living being appears to be, that action satisfies the same general principle: adaptation.
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At first sight, human action looks too complex to be reduced to such a simple scenario. Nevertheless, Gallistel believes that human behavior can be decomposed down to more and more elementary units, and those units do satisfy the general principle of action for the sake of adaptation only. The point is to explain how an action that looks like a whole can be decomposed in many coordinated lower-level actions. In Gallistel’s hypothesis, the elementary units of behavior (reflex, oscillator, servomechanism, i.e. external stimulus to internal signal to muscle contraction) are "catalyzed" by units at the higher levels of the system. Drawing from Paul Weiss' model of a central program, Gallistel assumes that units are organized in a hierarchy that allows for competition and antagonism. A central program is a unit of behavior that is activated as a whole. A central program "selectively potentiates" subsets of lower-level units according to their relevance to the current goal. The principles that determine the "selective potentiation" of lower-level units are the same that govern the properties of elementary units. Each unit in the hierarchy is apparently independent, but at the same time it is held together in a consistent whole. Situated cognition By applying ecological realism to the programs of Artificial Life and Artificial Intelligence, Rodney Brooks coined the discipline of "situated cognition", which shifts the emphasis to the interaction between an agent and its environment. Situated agents have no knowledge. Their memory is not a locus of representation but simply the place where behavior is generated. In Brooks' "subsumption" architecture, behavior is determined by the structure of the environment. The cognitive system has no need to represent the world, but only for how to operate in the world. There is no centralized function that coordinates the entire cognitive system, but a number of distributed decisional centers that operate in parallel, each of them performing a different task. The system does not have the explicit representation of what it is doing. It does have parallel processes that represent only their very limited goals. The system decomposes in layers of goal-driven behavior, each layer being a network of finite-state automata, and incrementally composes its behavior through the interaction with the world. Brooks can therefore account for the very fast response times required in the real world. In the real world there is no clear-cut difference between perception, reasoning and action. Brooks turns the mind into one of many agents that live in the environment. The environment is the center of action, not the mind. The environment is action, continuous action, continuously changing. Only a system of separate, autonomous control systems could possibly react and adapt to such a context. The world contains all the information that the organism needs. Therefore there is no need to represent it in the mind. The environment acts like a memory external to the organism, from which the organism can http://www.thymos.com/tat/ecologic.html (6 of 14)25/07/2003 14:34:27
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retrieve any kind of information through perception. "Intelligent" behavior can be partitioned into a set of asynchronous tasks (eating, walking, etc.), each endowed with a mechanism of perception and action. An artificial organism can be built incrementally by gradually adding new tasks. Behavior arises from layers of competence. Cognition is rational kinematics. Brooks’ ultimate point is that every intelligent being has a body! Vehicles The Italian neurophysiologist Valentino Breitenberg proposed a thought experiment which consists in mentally building progressively more complex machines, starting from the most elementary ones. At the beginning, there are only vehicles that respond to their environment. The first vehicle is simply made of a motor and a sensor: the speed of the motor is controlled by the sensor, motion is meant to be only forward. But in the real world this vehicle is subject to friction (where friction is the metaphysical sum of all forces of the environment) and therefore the trajectory will tend to deviate from the straight line. In fact, in a pond the movement would be quite complex. That's the whole point: despite the simple internal workings of these machines, they seem to be alive. We can increase little by little their circuitry, and at each step these vehicles seem to acquire not only new skills, but also a stronger personality. The second vehicle is still fairly simple: two motors and two sensors. The sensor is designed to get excited by whatever kind of matter. It turns out that depending on the way they are wired, these vehicles react differently to the exciting matter: one runs towards it, the other one runs away from it. One is "aggressive", one is "afraid". And so forth. As their circuitry increases, the vehicles seem to exhibit more sophisticated feelings. Always adding simple electro-mechanical components, Breitenberg induces the machines to reason logically (via McCulloch-Pitts neurons). As the devices get more complicated, shapes are recognized; regularities are represented; properties of objects are discriminated. Hebbian associations (that get stronger as they are used) allows for concepts to emerge. Soon the machines start exhibiting learning and memory. Causation (as constant succession) and attention (as self-control over associations) finally lead to trains of thoughts. At this point the human mind can be said to be born and all Breitenberg has to do is add circuitry for social and moral skills. The leitmotiv of Breitenberg's research is that it is far easier to create machines that exhibit "cognitive" behaviour than it is to analyze their behavior and try to deduce the internal structure that produces such behavior. Breitenberg's ideas spawned an entire generation of robots, which their constructors appropriately tend to call "creatures".
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Autopoiesis From a different perspective, similar conceptual changes were advanced in the early 1960's by the Chilean neurobiologist Humberto Maturana when he argued that the relation with the environment molds the configuration of a cognitive system. "Autopoiesis" is the process by which an organism can continuously reorganize its own structure. Adaptation consists in regenerating the organism's structure so that its relationship to the environment remains constant. An organism is a structure capable of responding to the environment. The organism perceives the environment via stimuli. The stimulus, therefore, can be viewed as the part of environment that is absorbed by the structure. Autopoiesis is a pattern of organization common to all living systems. Living systems are organized in closed loops. A living system is a network in which the function of each component is to create or transform other components while maintaining the circular organization of the whole. A cell exhibits autopoiesis, as does the Earth as a whole. The product of a living system is a new organization of itself. It continually produces itself. The being and the doing are the same. Autopoiesis is self-maintenance. Organisms use energy (mainly from light) and matter (water, carbon, nitrogen, etc) to continuously remake themselves. Living systems are units of interaction. They only exist in an environment. They cannot be understood independently of their environment. They exhibit "exergonic" metabolism, which provides energy for the "endergonic" synthesis of polymers, i.e. for growth and replication. The circular organization of living organisms constitutes a homeostatic system whose function is to maintain this very same circular organization. It is such circular organization that makes a living system a unit of interaction. At the same time, it is this circular organization that helps maintain the organism's identity through its interactions with the environment. Due to this circular organization, a living system is a self-referential system. At the same time, a living system operates as an inductive system and in a predictive manner: its organization reflects regularities in the environment. Living systems are organized accordin to the principle: "what happened once will happen again". Cognition is biological in the sense that the cognitive domain of an organism is defined by its interactions with the environment. Cognition is the way in which an autopoietic system interacts with the environment (ie, reorganizes itself). It is the result of the structural coupling with the environment which causes the continuous reorganization.
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All living systems are cognitive systems. Cognition is simply the process of maintaining oneself by acting in the environment. Action and cognition cannot be separated: "all doing is knowing and all knowing is doing". Living is a process of cognition. In summary, an autopoietic system is a network of transformation and destruction processes whose components interact to continuously regenerate the network. An autopoietic system holds constant its organization (its identity). Autopoiesis generates a structural coupling with the environment: the structure of the nervous system of an organism generates patterns of activity that are triggered by perturbations from the environment and that contribute to the continuing autopoiesis of the organism. Autopoiesis is necessary and sufficient to characterize a living system. A living organism is defined by the fact that its organization makes it continually self-producing (autopoietic), i.e. not only autonomous but also self-referential ("the being and doing of an autopoietic system are inseparable"). Autopoiesis progressively generates more and more complex organisms and then intelligent organisms. Multi-cellular organisms are born when two or more autopoietic units engage in an interaction that takes place more often than any of the interactions of each unit with the rest of the environment (a "structural coupling"). Inert elements then become macromolecules, and macromolecules become organic cells, and so on towards cellular organisms and intelligent beings. A nervous system enables the living organism to expand the set of possible internal states and to expand the possible ways of structural coupling. But the nervous system is self-referential: perception is not representation of external world. Perception does not represent, it specifies the external world. Nothing exists independent of cognition. Each cognitive act is not about knowing the environment, but about reorganizing oneself in accordance with the environment. The autopoietic system knows only itself. There is no representation of the external world. There is just reorganization of the system based on the external world. Intelligent behavior originates in extremely simple processes: the living cell is nothing special, but many living cells one next to the other become a complex system thanks to autopoiesis. Even life's origin can be easily explained: at some point of its history the Earth presented conditions that made the formation of autopoietic systems almost inevitable. The whole process of life depends not on the components of a living organism, but on its organization. Autopoiesis is about organization, not about the nature of the components. Evolution is a natural drift, a consequence of the conservation of autopoiesis and adaptation. There is no need for an external guiding force to direct evolution. All is needed is conservation of identity and capacity for reproduction. http://www.thymos.com/tat/ecologic.html (9 of 14)25/07/2003 14:34:27
Thinking About Thought: Consciousness, Life and Meaning
For Maturana, information is a pointless concept. Communication is not transmission of information but rather coordination of behavior along living systems. Maturana extends the term "linguistic" to any mutually generated domain of interactions (any "consensual domain"). When two or more living organisms interact recurrently, they generate a social coupling. Language emerges from such social coupling. In this view, language is "connotative" and not "denotative". Its function is to orient the organism within its cognitive domain. The point Maturana reiterates is that cognition is a purely biological phenomenon. Organisms do not use any representational structures: their intelligent behavior is due only to the continuous change in their nervous system as induced by perception. Intelligence is action. Memory is not an abstract entity but simply the ability to recreate the behavior that best couples with a recurring situation within the environment. Gaia and the noosphere The biosphere as a whole is autopoietic as it maintains itself through a careful balance of elements. Life (the sum of all living beings) can counter cosmological forces and make sure that the Earth continues to be a feasible habitat for life. Living beings use the chemicals available in the air and on the surface of the Earth and produce other chemicals that are released in the air and on the surface of the Earth. They do so at the rate that keeps the air and the surface of the Earth in balance with whatever cosmological forces operate on the Earth. To paraphrase the American biologist Lynn Margulis, life "is" the surface of the Earth. It is not surprising that the Russian geologist Vladimir Vernadsky in 1926 ranked living matter as the most powerful of geological forces (he even described how life opposes gravity's vertical pull by growing, running, swimming and even flying). It is not surprising that the British biologist James Lovelock views the entire surface of the Earth, including "inanimate" matter, as a living being (which in 1979 he named "Gaia"). Vernadsky even thought that the Earth is developing its own mind, the "noosphere", the aggregation of the cognitive activity of all its living matter. Enaction Following Maurice Merleau-Ponty's philosophical thought and drawing inspiration from Buddhist meditative practice, Francisco Varela, a close associate of Maturana, has argued in favor of an "enactive" approach to cognition: cognition as embodied action (or "enaction"), evolution not as optimal adaptation but as "natural drift". His stance views the human body both as matter and as experience, both as a biological entity and a phenomenological entity. Varela believes in the emergent formation of direct experience without the need to posit the existence of a self. The mind is selfless. "Self" refers to a set of mental and bodily formations that are linked by causal coherence over time. At the same time the world is not a given, but reflects the actions in which we engage, i.e. it is "enacted" from our actions (or structural http://www.thymos.com/tat/ecologic.html (10 of 14)25/07/2003 14:34:27
Thinking About Thought: Consciousness, Life and Meaning
coupling). Everything that exists is the projection of a brain. Organisms do not adapt to a pre-given world. Organisms and environment mutually specify each other. Organisms drift naturally in the environment. Environmental regularities arise from the interaction between a living organism and its environment. The world of an organism is "enacted" by the history of its structural coupling with the environment. Perception is perceptually guided action (or sensorimotor enactment). Cognitive structures emerge from the recurrent sensorimotor activity that enables such a process. And perceptually guided action is constrained by the need to preserve the integrity of the organism (ontogeny) and its lineage (phylogeny). Varela assigns an almost metaphysical meaning to Maturana’s biological findings. Life is an elegant dance between the organism and the environment. The mind is the tune of that dance. The Extended Phenotype A powerful metaphor to express the dependence of an organism from its environment, and the fact that the organism does not make sense without its environment, has been introduced by the American biologist Richard Dawkins: the "extended phenotype" includes the world an organism interacts with. The organism alone does not have biological relevance. What makes sense is an open system made of the organism and its neighbors. For example, a cobweb is still part of the spider. The control of an organism is never complete inside and null outside: there is rather a continuum of degrees of control, which allows partiality of control inside (e.g., parasites operate on the nervous system of their hosts) and an extension of control outside (as in the cobweb). To some extent the very genome of a cell can be viewed as a representation of the environment inside the cell. Ruth Millikan went further claiming that, when determining the function of a biological "system", the "system" must include more than just the organism, something that extends beyond its skin. Furthermore, the system often needs the cooperation of other systems: the immune system can only operate if it is attacked by viruses. An organism is only a part of a biological system. Tools (whether cobwebs or buckets or cars) are an extension of the organism which serve a specific purpose.Buckets store water. Cars help us move faster. Computers are an extension of the organism which serve the purpose of simulating a person or even an entire world. No matter how simple or how complex, those tools are an extension of our organism. The model of the extended phenotype is consistent with a theory advanced by the biologist Richard Lewontin. Each organism is the subject of continuous development throughout its life and such development is driven by mutually interacting genes and environment. Genes per se cannot determine the phenotype, capacity or tendencies. The organism is both the subject and the object of evolution. Organisms construct environments that are http://www.thymos.com/tat/ecologic.html (11 of 14)25/07/2003 14:34:27
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the conditions for their own further evolution and for the evolutions of nature itself towards new environments. Organism and environment mutually specify each other. The Universe is a Message To Life The picture painted by these biologists is completely opposite to the one painted by the logicians who worked on formalizing Logic: where the logician’s program is based on the assumption that reason is an abstract manipulation of symbols, the biologist’s program is based on the assumption that reason is bodily experience grounded in the environment. The two views could not be farther apart. Implicit in the logician’s project were the assumptions that meaning is based on truth and reference, that the mind is independent of the body, that reasoning is independent of the mind (logic exists in a world of its own, regardless of whether somebody uses it or not), and all minds use the same reasoning system. The biological approach puts the mind back firmly in the body, the body in the environment and meaning in the relationship between them. The reasoning system we use depends on our collective experience as a species and on our individual experience as bodies. We are left to face the vast influence that the environment has on the development and evolution of the mental faculties of an organism, no less so than of its body. The development of an organism, an ecosystem or any other living entity, is due to interaction with the environment. In a different world, the same genomes would generate different beings. The universe is a message to life and to mind. Further Reading Barwise John & Perry John: SITUATIONS AND ATTITUDES (MIT Press, 1983) Bogdan Radu: GROUNDS FOR COGNITION (Lawrence Erlbaum, 1994) Breitenberg Valentino: VEHICLES (MIT Press, 1984) Brooks Rodney & Luc Steels: THE ARTIFICIAL LIFE ROUTE TO ARTIFICIAL INTELLIGENCE (Lawrence Erlbaum, 1995) Clancey William: SITUATED COGNITION (Cambridge Univ Press, 1997) Dennett Daniel: THE INTENTIONAL STANCE (MIT Press, 1987) Dretske Fred: KNOWLEDGE AND THE FLOW OF INFORMATION (MIT Press, 1981) Dretske Fred: EXPLAINING BEHAVIOR (MIT Press, 1988)
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Gallistel C.R.: THE ORGANIZATION OF ACTION (Erlbaum, 1980) Gibson James Jerome: THE SENSES CONSIDERED AS PERCEPTUAL SYSTEMS (Houghton Mifflin, 1966) Gibson James Jerome: THE ECOLOGICAL APPROACH TO VISUAL PERCEPTION (Houghton Mifflin, 1979) Helmholtz Hermann: TREATISE ON PHYSIOLOGICAL OPTICS (1866) Kitchener Robert: PIAGET'S THEORY OF KNOWLEDGE (Yale University Press, 1986) Lewontin Richard: HUMAN DIVERSITY (W.H.Freeman, 1981) Lovelock James: GAIA (Oxford University Press, 1979) Maturana Humberto: AUTOPOIESIS AND COGNITION (Reidel, 1980) Maturana Humberto & Varela Francisco: THE TREE OF KNOWLEDGE (Shambhala, 1992) Millikan Ruth: LANGUAGE, THOUGHT AND OTHER BIOLOGICAL CATEGORIES (MIT Press, 1987) Millikan Ruth: WHAT IS BEHAVIOR? (MIT Press, 1991) Neisser Ulric: COGNITION AND REALITY (Freeman, 1975) Neisser Ulric: THE REMEMBERING SELF (Cambridge University Press, 1994) Neisser Ulric: THE PERCEIVED SELF (Cambridge Univ Press, 1994) Plotkin Henry: DARWIN MACHINES AND THE NATURE OF KNOWLEDGE (Harvard University Press, 1994) Varela Francisco, Thompson Evan & Rosch Eleanor: THE EMBODIED MIND (MIT Press, 1991) Varela Francisco: PRINCIPLES OF BIOLOGICAL AUTONOMY (North Holland, 1979) Vernadsky Vladimir: THE BIOSPHERE (?, 1926)(Synergetics, 1986) Winograd Terry & Flores Fernando: UNDERSTANDING COMPUTERS AND COGNITION (Ablex, 1986)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind The Physics of Life (Schroedinger, Prigogine, Odum, Frautschi, Johnson, Langton, Margalef, Kuppers, Brooks, Dyson, Maynard Smith, Morowitz, Layzer, Oyama, Waddington, Sheldrake, Thom, Ingber, Tipler)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Life has three dimensions. One is the evolutionary dimension: living organisms evolve over time. One is the reproduction dimension: living organisms are capable of reproducing. One is the metabolic dimension: living organisms change shape during their life. Each dimension can be studied with the mathematical tools that Physics has traditionally employed to study matter. But it is apparent that traditional Physics cannot explain life. Life exhibits properties that rewrite Physics. The Origin Of Self-organization: life as negative entropy The paradox underlying natural selection (from the point of view of physicists) is that on one hand it proceeds in a blind and purpose-less way and on the other hand produces the illusion of more and more complex design. This continuous increase in information (i.e., the spontaneous emergence of order) seems to violate the second law of Thermodynamics, the law of entropy. Ludwig von Bertalanffy borrowed the term "anamorphosis" from the biologist Woltereck to describe the natural trend towards emergent forms of increasing complexity. Entropy is a measure of disorder and it can only increase, according to the second law of Thermodynamics. Information moves in the opposite direction. Most things in this universe, if left alone, simply decay and disintegrate. Biological systems, instead, appear from nowhere, then organize themselves, then even grow!
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Thinking About Thought: Consciousness, Life and Meaning
This leads to the "two arrows of time": the behavior of physical systems pointing towards entropy increase and therefore disorder increase, and the behavior of biological systems pointing the other way by building increasingly complex structures of order. When you drop a sugar cube in your coffee, it dissolves: while no physical law forbids the recomposition of the sugar cube, in practice it never occurs, and we intuitively know that it cannot occur. Order is destroyed and cannot be recreated. That's a manifestation of the second law of Thermodynamics. On the other hand, a teenager develops into an adult, and, while no biological law forbids it, and as much as they would like to, adults never regress to youth. This is a manifestation of the opposite arrow of time: order is created and cannot be undone. Since organisms are made of chemicals, there is no reason why living systems should behave differently than physical systems. This is a paradox that puzzled not only biologists, but physicists too. The Austrian physicist Erwin Schroedinger, one of the founders of Quantum Mechanics, first proposed the idea that biological organization is created and maintained at the expense of thermodynamic order. Life displays two fundamental processes: creating order from order (the progeny has the same order as the parent) and creating order from disorder (as every living system does at every metabolic step, eating and growing). Living systems seem to defy the second law of Thermodynamics. In reality, they live in a world of energy flux that does not conform to the closed-world assumptions of Thermodynamics. An organism stays alive in its highly organized state by absorbing energy from the environment and processing it to produce a lower entropy state within itself. "Living organisms feed upon negative entropy": they attract "negative entropy" in order to compensate for the entropy increase they create by living. Life is "negentropic". The existence of a living organism depends on increasing the entropy of the rest of the universe. In 1974 the biologist (and Nobel prize winner) Albert Szent-Gyorgyi proposed to replace "negentropy" by the positive term "syntropy", to represent the "innate drive in living matter to perfect itself". This has a correspondent on the psychological level, "a drive towards synthesis, towards growth, towards wholeness and self-perfection". Life as Non-equilibrium In the 1960’s, the Belgian (but Russian-born) physicist Ilya Prigogine (who will later be awarded the Nobel prize for his work in Thermodynamics) had the fundamental intuition: living organisms function as dissipative structures, structures that form as patterns in the energy flow and that have the capacity for selforganization in the face of environmental fluctuations. In other words, they maintain their structure by continously dissipating energy. Such dissipative structures are permanently in states of non-equilibrium. Life maintains itself far from equilibrium: the form stays pretty much the same, while the material is constantly being replaced by new material, part of which comes from matter (food, air, water) and part of which comes from energy (sun). The flow of matter and energy "through" the body of the living organisms is what makes it possible for the organism to maintain a (relatively) stable form. In order to stay alive, they have to be always in this state far from equilibrium. http://www.thymos.com/tat/biology.html (2 of 9)25/07/2003 14:34:46
Thinking About Thought: Consciousness, Life and Meaning
Equilibrium is death, non-equilibrium is life. And here is the solution of the riddle. Equilibrium is the state of maximum entropy: uniform temperature and maximum disorder. A system that is not in equilibrium exhibits a variation of entropy which is the sum of the variations of entropy due to the internal source of entropy plus the variation of entropy due to the interaction with the external world. The former is positive, but the latter can equally be negative. Therefore total entropy can decrease. An organism "lives" because it absorbs energy from the external world and processes it to generate an internal state of lower entropy. An organism "lives" as long as it can avoid falling in the equilibrium state. (In a sense, organisms die because this process is not perfect: if our bodies could be made to keep their shape exactly the same, they would always remain far from the equilibrium and they would never die). Thanks to the advent of non-equilibrium Thermodynamics, it is now possible to bridge Thermodynamics and evolutionary Biology. By focusing on entropy, structure and information, it is now possible to shed some light on the relationship between cosmological evolution and biological evolution. Biological phenomena can be viewed as governed by laws that are purely physical. This step might prove as powerful as the synthetic theory of evolution. Prigogine’s non-equilibrium approach to evolution, i.e. that biological systems (from bacteria to entire ecological systems) are non-equilibrium systems, has become a powerful paradigm to study life in the context of Physics. Life is finally reduced to a natural phenomenon just like electromagnetism and gravity. Bioenergetics These ideas led to an approach to life, called "bioenergetics", which consists in applying thermodynamic concepts (energy, temperature, entropy and information) and non-equilibrium (or irreversible) Thermodynamics to biological structures. The starting point, in the 1920s, was the biologist Alfred Lotka's assumption that ecosystems are networks of energy flows. Then, decades later, the brothers Howard and Eugene Odum devised a thermodynamic model for the development of the ecosystem. That became the route followed by an entire branch of Biology: looking for the thermodynamic principle that guides the development of ecosystems. The thesis of the American biologist Harold Morowitz is that the flow of energy through a living system acts to organize the system: organization emerges spontaneously whenever energy flows through a system. The contradiction between the second law of Thermodynamics (the universe tends towards increasing disorder) and biological evolution (life tends towards increasing organization) is only apparent, because Thermodynamics applies to systems that are approaching equilibrium (either adiabatic, i.e. isolated, or isothermal), whereas natural systems are usually subject to flows of energy/matter to or from other systems.
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Thinking About Thought: Consciousness, Life and Meaning
First of all, life is the property of an ecological system, not of a single, individual, isolated organism. An isolated living organism is an oxymoron. Life of any organism depends on a flow of energy, and, ultimately, life "is" that flow of energy. Morowitz has proven two theorems that analyze what happens during that flow of energy through the chemical systems that living organisms are made of: 1. those systems store energy in chemical bonds, i.e. their complexity steadily increases; and 2. those systems undergo chemical cycles of the kind that pervade the biosphere (e.g., the carbon cycle). The flux of energy turns out to be the organizing factor in a dissipative system. When energy flows in a system from a higher kinetic temperature, the upper energy levels of the system become occupied and take a finite time to decay into thermal modes. During this period energy is stored at a higher free energy than at equilibrium state. Systems of complex structures can store large amounts of energy and achieve a high amount of internal order. The cyclic nature of dissipative systems allows them to develop stability and structure within themselves. The bottom line is that a dissipative system develops an internal order. The Origin of Biological Information A non-biological approach to life that has also yielded stunning results over the last few years is the one based on information and directly influenced by Cybernetics and Information Theory. Life is viewed as information capable of replicating and modifying itself. The American anthropologist Gregory Bateson always believed that the substance of the biological world is "pattern" (not this or that chemical compost), a position that allowed him to seek a unified view of cognitive and biological (and cybernetic) phenomena. His definition of information stretched beyond mere computation: a bit of information is a difference that makes a difference. Thereby implying that, in order to be information, a pattern must affect something. (Also, information is not a thing, it is a relation). The pioneering work of the ecologist Ramon Margalef in the 1960's set the stage. He viewed an ecosystem as a cybernetic system driven by the second law of Thermodynamics. Succession (the process of replacing old species with new species in an ecosystem) is then a self-organizing process, one whereby an element of the system is replaced with a new element so as to store more information at less energetic cost. For example, Kuppers found an elegant way to reconcile the paradox of increasing information. Life is biological information, and the origin of life is the origin of biological information. Information has different aspects: syntactic (as in information theory), semantic (function and meaning of information for an organism's survival), and pragmatic (following Von Weiszacker, "information is only that which produces information"). Since evolution depends on the semantic aspect of information, there is no contradiction with the second law of Thermodynamics, which only deals with the structural aspect of matter (i.e., the syntactic aspect of information). The origin of syntactic information relates to the prebiotic synthesis of biological macromolecules. The origin of semantic information relates to the self-organization http://www.thymos.com/tat/biology.html (4 of 9)25/07/2003 14:34:46
Thinking About Thought: Consciousness, Life and Meaning
of macromolecules. The American biologist Christopher Langton has emphasized that living organisms use information, besides matter and energy, in order to grow and reproduce. In living systems the manipulation of information prevails over the manipulation of energy. Life depends on a balance of information: too little information is not enough to produce life, too much can actually be too difficult to deal with. Life is due to a reasonable amount of information that can move and be stored. Life happens at the edge of chaos. Ultimately, life is a property of the organization of matter. As the Canadian biologist Lionel Johnson put it, the biosystem can be compared to an information processor, whose job is to continuously extract, store and transmit information. Two fundamental and opposed forces compete, one leading towards increased uniformity (and lower information) over "ecological" time and one leading towards increased diversity (and greater information) over "evolutionary" time. This results in a hierarchy of living organisms, which has at the top the one species that developed the best strategy of energy extraction and storage, the highest resource utilization and the least dissipation (this is a reworking of a principle due to Alfred Lotka in the Twenties). Extracting information requires an energy flow, which in turns causes production of entropy. This can also be viewed from the point of view of communication: dissipative structures can exist only if there is communication among their components, whether in the form of genetic code (communication over stime) or societies (communication over space). The biosystem is, ultimately, an information processor and a communication network. At the same time, the Hungarian chemist Tibor Ganti views life as the combination of of two systems: metabolism and information control. The simplest form of life, in practice, is the "chemoton": an autocatalytic cycle coupled with an information molecule. Tibor's living organism, therefore, looks more like a computer than a program, because it includes the "hardware". Life without the hardware is not life, it is just the process that generates life. It also takes that "information molecule" to have life. Lives The distinguished British biologist John Maynard Smith defined progress in evolution as an increase in information transmitted from one generation to another. The key to evolution is heredity: the way information is stored, transmitted and translated. Evolution of life as we know it relies on information transmission. And information transmission depends on replication of structures. The authors believe that evolution was somewhat accelerated, and changed in character, by and because of dramatic changes in the nature of biological replicators, or in the way information is transmitted by biological replicators. New kinds of coding methods made possible new kinds of organisms. Today, replication is achieved via genes, that utilize the genetic code. The authors argue that this is only the latest step in a story that started with the earliest, rudimentary replicators, the first genes.
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Thinking About Thought: Consciousness, Life and Meaning
The first major breakthrough in evolution, the first major change in the technique of replication, was the appearance of chromosomes: when one gene is replicated, all are. A second major change came with the transition from the solitary work of RNA to the dual cooperation of DNA and proteins: it meant the shift from a unitary source of replication to a division of labour. Metabolism was born out of that division of labour and was facilitated by the chemical phenomenon of autocatalysis. Autocatalysis allows for selfmaintenance, growth and reproduction. Growth is autocatalysis. Early, monocellular organisms (prokaryotes) evolved into multicellular organisms (eukaryotes). The new mechanism that arose was gene regulation: the code didn't simply specify instructions to build the organism, but also how cells contributed to the organism. Asexual cloning was eventually was made obsolete by sex, and sex again changed the rules of the game by shuffling the genetic information before transmitting it. Protists split into animals, plants, fungi, that have different information-transmission techniques. Individuals formed colonies, that developed other means of transmitting information, namely "culture; and finally socail behavior led to language, and language is a form of information transmission itself. Each of these steps "invented" a new way of coding, storing and transmitting information. The primacy of energy flows In the beginning was energy, matter came later. The American physicist Ronald Fox showed how, from the beginning, it was energy flows (lightning, volcanic heat) that allowed for the manufacture of unlikely molecules like aminoacids that are the foundations of life. The emphasis shifts to polymers: organisms use energy to excite monomers until they start creating polymers spontaneously. The organism reaches a state in which polymers help produce (synthesize) polymers. Fox speculates that organisms used an abundant natural source of energy (phosphate bond energy), that was created during the "iron catastrophe". That new flow of energy created a new kind of matter. Phosphate is still a key component of energy transactions in living molecules. Biological evolution was subsequently driven by energy regulation and storage. Fox uses nonlinear thermodynamics and therefore chaos theory to show how complex structures can then spontaneously emerge. The nervous system makes sense in this scenario because it provides a biological advantage: it allows the organism to rapidly simulate the outcome of nonlinear events, that are, by their own nature, very hard to predict. Rapid simulation is the only way that the organism can predict what will happen and therefore essential to survival. http://www.thymos.com/tat/biology.html (6 of 9)25/07/2003 14:34:46
Thinking About Thought: Consciousness, Life and Meaning
All based on the simple idea that whatever happened was driven by flows of energy. The Irreversibility of Life Not everybody agrees with Prigogine’s view of living systems as dissipative structures and with Schroedinger's view of life as "negentropic". A law known as "Dollo's law" states the irreversibility of biological evolution: evolution never repeats itself. Darwin's natural selection does not necessarily prescribe progress or regression, does not imply a direction of evolution in time, it only states an environmental constraint. Indirectly, Dollo's law does: it prescribes a trend towards more and more complex, and more and more ordered, living structures. Dollo's law expresses the visible fact that reproduction, ontogeny and phylogeny are biological organizations whose behavior is irreversible: both during growth and during evolution, entropy of biological information constantly increases. We evolved from bacteria to humans, we grew from children to adults. The goal of the unified theory of evolution put forth in the Eighties by the biologist Daniel Brooks and the philosopher E.O. Wiley is to integrate this law with natural selection. Unlike Prigogine, Wiley and Brooks believe that biological systems are inherently different from dissipative structures. Biological systems, unlike physical systems, owe their order and organization to their genetic information, which is peculiar in that it is encoded and hereditary. Dissipation in biological systems is not limited to energy but also involves information, because of the genetic code, which is transmitted to subsequent generations. Organisms simply live and die, they don’t evolve. What evolves is the historic sequence of organisms, which depends on genetic code. The genetic code must therefore be put at the center of any theory of evolution. Unlike most theories of information, that use information to denote the degree to which external forces create structure within a system, Brooks-Wiley's information resides within the system and is material, it has a physical interpretation. It resides in molecular structure as potential for specifying homeostatic and ontogenetic processes. As the organism absorbs energy from the environment, this potential is actualized and is "converted" into structure. What they set out to prove (following Lotka's original intuition and exploiting Layzer's ideas) is that evolution is a particular case of the second law of Thermodynamics, that Dollo's law is the biological manifestation of that second law. Biological order is simply a direct consequence of that law. The creation of new species is made necessary by the second law and is a "sudden" phenomenon similar to phase changes in Physics. Phylogenetic branching is an inevitable increase in informational entropy. In this scenario, the interaction between species and the environment is not as important in molding evolution: natural selection mainly acts as a pruning factor. Over short time intervals, biological systems do behave like dissipative structures. But over longer time intervals, they behave like expanding phase space systems (as proved by Layzer). Their relevant phase http://www.thymos.com/tat/biology.html (7 of 9)25/07/2003 14:34:46
Thinking About Thought: Consciousness, Life and Meaning
space is genetic, an ever increasing genetic phase space. The Brooks-Wiley theory is darwinian in nature, as it subscribes to the basic tenet that evolution is due to variation and selection, but, in addition, it also allows the possibility for evolution to occur without any environmental pressure. A Hierarchy of Lives
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Abraham Ralph: ON MORPHODYNAMICS (Aerial Press, 1985) Driesch Hans: SCIENCE AND PHILOSOPHY OF THE ORGANISM (Black, 1908) Dyson Freeman: INFINITE IN ALL DIRECTIONS (Harper & Row, 1988) Fox Ronald: ENERGY AND THE EVOLUTION OF LIFE (Freeman, 1988) Ganti Tibor: THE PRINCIPLE OF LIFE (Omikk, 1971) Kauffman Stuart: THE ORIGINS OF ORDER (Oxford University Press, 1993) Layzer David: COSMOGENESIS (Oxford University Press, 1990) Lotka Alfred: ELEMENTS OF MATHEMATICAL BIOLOGY (Dover, 1925) Margalef: PERSPECTIVES IN ECOLOGICAL THEORY (Univ of Chicago Press, 1968) Kuppers Bernd-Olaf: INFORMATION AND THE ORIGIN OF LIFE (MIT Press, 1990) Maynard Smith, John: EVOLUTIONARY GENETICS (Oxford University Press, 1989) Maynard Smith, John: THEORY OF EVOLUTION (Cambridge University Press, 1993) Maynard Smith, John & Szathmary Eors: THE ORIGINS OF LIFE (Oxford University Press, 1999) Maynard Smith, John & Szathmary Eors: THE MAJOR TRANSITIONS IN EVOLUTION (W. H. Freeman, 1995)
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Thinking About Thought: Consciousness, Life and Meaning
Morowitz Harold: ENERGY FLOW IN BIOLOGY (Academic Press, 1968) Morowitz Harold: FOUNDATIONS OF BIOENERGETICS (Academic Press, 1978) Morowitz Harold: ENTROPY AND THE MAGIC FLUTE (Oxford University Press, 1993) Odum Eugene: FUNDAMENTALS OF ECOLOGY (Saunders, 1971) Oyama Susan: ONTOGENY OF INFORMATION (Cambridge University Press, 1985) Plotkin Henry: DARWIN MACHINES AND THE NATURE OF KNOWLEDGE (Harvard University Press, 1994) Plotkin Henry: EVOLUTION IN MIND (Allen Lane, 1997) Prigogine Ilya: FROM BEING TO BECOMING (W.H.Freeman, 1980) Schroedinger Erwin: WHAT IS LIFE (Cambridge Univ Press, 1944) Sheldrake Rupert: A NEW SCIENCE OF LIFE (J.P. Tarcher, 1981) Sheldrake Rupert: THE PRESENCE OF THE PAST (Times Books, 1988) Speman Hans: EMBRYONIC DEVELOPMENT AND INDUCTION (Yale Univ PRess, 1938) Thompson D'Arcy: ON GROWTH AND FORM (Cambridge University Press, 1917) Tipler Frank: THE PHYSICS OF IMMORTALITY (Doubleday, 1995) Ulanowicz Robert: GROWTH AND DEVELOPMENT (Springer-Verlag, 1986) Weber Bruce, Depew David & Smith James: ENTROPY, INFORMATION AND EVOLUTION (MIT Press, 1988) Weiss Paul: PRINCIPLES OF DEVELOPMENT (Holt, 1939) Wicken Jeffrey: EVOLUTION, INFORMATION AND THERMODYNAMICS (Oxford Univ Press, 1987)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Evolution: Of designers and designs (Darwin, Lamarck, Mendel, Baldwin, Monod, Miller, Wachtershauser, Gould, Crick, Cairns-Smith, Eigen, Wallace, Mayr, Wimsatt, Hull, Lewontin, Hamilton, D.S. Wilson, Brandon, Murchie, Margulis, Behe, Butler, Dawkins, Cronin, Wilson, Ridley, Jolly, Wicken)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Origins: What was life? While modern research focuses on how the neural processes of the brain can yield the mind, we often forget that brains are first and foremost alive, and no convincing evidence has been presented so far that dead brains can think. As far as we know, minds are alive. As far as we know, life came first, both from an evolutionary perspective and from a bodily perspective. If we accept this principle, then we come to recognize that "thinking life" may just be a particular case of "life", that the same type of processes which are responsible for life may be responsible also for the mind. And the mystery of the mind, or at least the mystery of the principle that underlies the mind, may have been solved a century ago by the most unlikely sleuth: Charles Darwin. Darwin never really explained what he wanted to explain, but he probably discovered the "type of process" that is responsible for life. He called it "evolution", today we call it "design without a designer", "emergence", "self-organization" and so forth. What it means is that properties may appear when a system reorganizes itself due to external constraints, due to the fact that it has to live and survive in this world. This very simple principle may underlie as well the secret of thought. Darwin's theory of evolution is not about "survival of the fittest", Darwin's theory is about "design". Life is defined by properties that occur in species as different as lions and bacteria. Mind would appear to be a property that differentiates life in a crucial way, but at closer inspection… animals do communicate, although they don't use our language; and animals do reason, although they don't use our logic; and animals do show emotions. What is truly unique about humans, other than the fact that we have developed more effective weapons to kill as many animals as we like?
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Thinking About Thought: Consciousness, Life and Meaning
The Dynamics of Life As far as we can tell, there is no mind without life. In order to be thinking, you have to be alive first. What "being alive" means is easily characterized, as we have plenty of specimen to study: life is about growing and reproducing. A living organism is capable of using the environment (sun, water, minerals, other living organisms) in order to change its own shape and size, and it is capable of creating offspring of a similar kind. In technical terms, life has two aspects: metabolism and replication. Metabolism is the interaction with the environment that results in growth. Replication is the copying of information that results in reproduction. Metabolism affects proteins, replication affects nucleid acids. The statement that "life is growing and reproducing" is convenient for studying life on this planet, life as we know it. But certainly it would be confusing if we met aliens who speak and feel emotions but do not need to eat or go to the restrooms and never change shape. They are born adults and they die adults. They do not even reproduce: they are born out of a mineral. Their cells do not contain genetic material. They do not make children. Would that still be life? Also, that definition is not what folk psychology uses to recognize a living thing. What is an animal? Very few people would reply "something that grows and reproduce". Most people would answer "something that moves spontaneously". The "folk" definition is interesting, because it already implies a mind. At the same time, the folk definition does not discriminate in a crisp manner between animate and inanimate matter. A rock can also move. True, it requires a "force" to move it. But so is the case with animals: they also require a force, although it is a chemical rather than a mechanical force. Animals eat and process their food to produce the chemical force that make them move. The difference is the kind of force. The laws of nature revised How that relates to the rest of the universe is less clear. This universe exhibits an impressive spectrum of natural phenomena, some of which undergo spectacular mutations over macro or micro-time (long periods of time, or short periods of time). Life deserves a special status among them for the sheer quantity and quality of physical and chemical transformations that are involved. Nonetheless, ultimately life has to be just one of them. Indirectly, it was Charles Darwin who started this train of thought, when he identified simple rules that Nature follows in determining how life proceeds over macro-time. While those "rules" greatly differ from the laws of Physics that (we think) govern the universe, they are natural laws of equal importance to the laws of electromagnetism or gravitation. Why they differ so much from the others is a matter of debate: maybe Darwin’s laws are gross approximations of laws that, when discovered, will bear striking resemblance to the laws of Physics; or, conversely, maybe the laws of Physics are gross approximations of laws that, when discovered, will bear striking resemblance to the laws of evolution; or maybe they are just two different levels of explanation, http://www.thymos.com/tat/life.html (2 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
one set of laws applying only to the microworld, the other set applying to the macroworld. The mystery of life is that all living systems are made of the same fundamental constituents, molecules that are capable of catalyzing (speeding up) chemical reactions. But these molecules cannot move and cannot grow. Still, when they are combined in systems, they grow and move. New properties emerge. The first new property is the ability to self-assemble, to join other molecules and form new structures which are in turn able to self-assemble, triggering a cycle that leads to cells, tissues, organs, bodies, and possibly to societies and ecosystems. In order to approach the subject of "life" in a scientific way, we first need to discriminate among the various meanings of that term. What we normally call "life" is actually three separate phenomena. Precisely, in nature we observe three levels of organization: the phylogenetic level, which concerns the evolution over time of the genetic programs within individuals and species (and therefore the evolution of species); the ontogenetic level, which concerns the developmental process (or "growth") of a single multicellular organism; and the epigenetic level, which concerns the learning processes during an individual organism's lifetime (in particular, the nervous system, but also the immune system). In other words, life occurs at three levels: organisms evolve into other organisms, each organism changes (or grows) from birth till death, and finally the behavior of each organism changes during its lifetime (the organism "learns"). There are therefore two aspects to the word "life". Because of the way life evolved and came to be what it is today, life is both reproduction and metabolism: it is both information that survives from one individual to another ("genotype"), and information about the individual ("phenotype"). When we say that "ants are alive" and "I am alive" we mean two different things, even if we use the same word. To unify those two meanings it takes a theory that explains both life as reproduction and life as growth. Design Without a Designer The mystery of life was solved through exactly a century of discoveries. In 1859 Darwin published "The Origin Of Species". His claim was that: all existing organisms are the descendants of simpler ancestors that lived in the distant past, and the main force driving this evolution is natural selection by the environment. This is possible because living organisms reproduce and vary (make children that are slightly different than the parents). Through this process of evolution, organisms acquire characteristics that make them more "fit" to survive in their environment (or better "adapted" to their environment). Darwin based his theory of evolution on some hard facts. The population of every species can potentially grow exponentially in size. Most populations don't. Resources are limited. Individuals of all species are unique, each one slightly different from the other. Such individual differences are passed on to offspring. His conclusion was that variation (the random production of different individuals) and selection ("survival of the fittest") are two fundamental features of life on this planet and that, together, they can account for the evolution of species.
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Thinking About Thought: Consciousness, Life and Meaning
To visualize what is so special to Darwin's idea, imagine that you are in a quandary and the situation is very complex. You have two options: 1. You can spend days analyzing the situation and trying to find the best strategy to cope with it. Or 2. you can spend only a few minutes listing ten strategies, which are more or less random and all different one from the other. In the former case, you are still thinking. In the latter case, you start applying each of the strategies at the same time. As you do so, some strategies turn out to be silly, others look promising. You pursue the ones that are promising. For example, you try ten different (random) variations on each of the promising ones. Again, some will prove themselves just plain silly, but others will look even more promising. And so forth. By trial and error (case 2.), you will always be working with a few promising strategies and possibly with a few excellent ones. After a few days you may have found one or more strategies that cope perfectly well with the situation. In case 1., you will be without a strategy for as long as you are thinking. When you finally find the best strategy (assuming that you have enough experience and intelligence to find it at all), it may be too late. In many situations, "design by trial and error" (case 2.) tends to be more efficient than "design by a designer" (case 1.). So Darwin opted for "design without a designer": nature builds species which are better and better adapted and the strategy it employs is one of trial and error. The idea of evolution established a new scientific paradigm that has probably been more influential than even Newton's Mechanics or Einstein's Relativity. Basically, evolution takes advantage of the uncertainty left in the transmission of genes from one generation to another: the offspring is never an exact copy of the parents, there is room for variation. The environment (e.g., natural selection) indirectly "selects" which variations (and therefore which individuals) survive. And the cycle resumes. After enough generations have elapsed, the traits may have varied to the point that a new species has been created. Nobody programs the changes in the genetic information. Changes occur all the time. There may be algorithms to determine how change is fostered. But there is no algorithm to determine which variation has to survive: the environment will make the selection. Living organisms are so complex that it seems highly improbable that natural selection alone could produce them. But Darwin's theory of variation and natural selection, spread over millions of years, yields a sequence of infinitesimally graded steps of evolution that eventually produce complexity. Each step embodies information about the environment and how to survive in it. The genetic information of an organism is a massive database of wisdom accrued over the millennia. It contains a detailed description of the ancient world and a list of instructions for surviving in it. The gorgeous and majestic logical systems of physical sciences are replaced by a completely different, and rather primitive, system of randomness, of chance, of trial and error. Of course, one could object that natural selection has (short-term) tactics, but no (long-term) strategy: that is why natural selection has never produced a clock or even a wheel. Tactics, on the other hand, can get to eyes and brains. Humans can build clocks, but not eyes. Nature can build eyes, but not clocks. Whatever http://www.thymos.com/tat/life.html (4 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
humans build, it has to be built within a lifetime through a carefully planned design. Nature builds its artifacts through millions of years of short-term tactics. "Design" refers to two different phenomena when applied to nature or humans. The difference is that human design has a designer. Darwinism solved the problem of "design without a designer": variation and selection alone can shape the animal world as it is, although variation is undirected and there is no selector for selection. Darwin's greatest intuition was that design can emerge spontaneously via an algorithmic process. The logic of replication In 1865 the Austrian botanist Gregor Mendel, while studying pea plants, proposed a mechanism for inheritance, that was to be rediscovered in 1901. Contrary to the common sense belief of the time, he realized that traits are inherited as units, not as "blends". The daughter of a blue-eyed father and a browneyed mother will not have eyes of a color in between blue and brown, she will most likely have either blue or brown eyes. Mendel came to believe that each trait is represented by a "unit" of transmission, by a "gene". Furthermore, traits are passed on to the offspring in a completely random manner: any offspring can have any combination of the traits of the parents. The model of genes provided for a practical basis to express some of Darwin's ideas. For example, Darwinian variation within a phenotype can be explained in terms of genetic "mutations" within a genotype: when copying genes, nature is prone to making typographical errors that yield variation in a population. In the 1920's, population genetics (as formulated by Sewall Wright and Ronald Fisher) turned Darwinism into a stochastic theory (i.e., it introduced probabilities). Fisher, in particular, proved that natural selection requires Mendelian inheritance in order to work the way it works. In the 1940's, the two theories were merged in the so called "modern synthesis". In practice, the synthetic theory of evolution merged a theory of inheritance (Mendel’s genetics) and a theory of species (evolutionary biology). Since those days, the idea of natural selection has undergone three stages of development, parallel to developments in the physical sciences: the deterministic dynamics of Isaac Newton, the stochastic dynamics of Clerk Maxwell and Ludwig Boltzmann, and now the dynamics of self-organizing systems. If initially Darwin's theory could be related to Newton's Physics in that it assumed an external force (natural selection) causing change in living organisms (just like Newton posited an external force, gravity, causing change in the motion of astronomical objects), with the invention of population genetics, by Ronald Fisher and others, Darwinism became stochastic (the thermodynamic model of genetic natural selection, in which fitness is maximized like entropy), just what Physics had become with Boltzmann's theory of gases. Today, biologists such as David Depew and Bruce Weber point to the idea of self-organization as the next step in the study of evolution. In 1944, Oswald Avery identified the vehicle of iheritance, the substance that genes are made of, the bearer of genetic information: the deoxyribonucleic acid (DNA for short). In 1953, the British biologist Francis Crick and the American biologist James Watson figured out the double-helix structure of the DNA molecule. It appeared that genetic information is encoded in a rather mathematical form, which was http://www.thymos.com/tat/life.html (5 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
christened "genetic code" because that’s what it is: a code. The "genome" is the repertory of genes of an organism. In 1957 Crick, by using only logical reasoning, reached the conclusion that information must flow only from the nucleid acids to proteins, never the other way around. In the 1960's biologists cracked the "genetic code", the code used by DNA to generate proteins, i.e. they found out how the four-letter language of DNA is translated into the twenty-letter language of proteins (the DNA is made of four kinds of nucleotides, proteins are made of twenty types of aminoacids). And, finally, in the 1980s biologists discovered ribonucleic acid (RNA), a single-strand molecule that partners with DNA to manufacture proteins. Recently, we started deciphering the genome of different animals, including our own. Origins From what we know today, we can say that life evolved through momentous leaps forward. First, reproduction occurred: an organism became capable of generating another organism of the same type. Then sexual reproduction occurred, in which it took two organisms to generate an organism of the same type. Then multicell organisms appeared, and organisms became complex assemblies of cells. Fourth, some of those cells developed into specialized organs, so that the organism became an entity structured in a multitude of more or less independent parts. Fifth, a central nervous system developed to direct the organs. And, finally, mind and consciousness appeared, probably originating from the same locus that controls the nervous system. (If life evolved from reproductive minerals to multicellular organisms and to conscious beings, it is intriguing to try to predict what is going to be the next leap forward...) The structure of living things An organism is a set of cells. Every cell of an individual (or, better, the nucleus of each cell) contains the DNA molecule for that individual, or its "genome". A DNA molecule is made of two strings, or "strands", each one the mirror image of the other (in the shape of a "double helix"). Each string is a sequence of "nucleotides" or "bases", which come in four kinds (adenine, guanine, cytosine, thymine). These four bases are paired together (adenine is paired with thymine and cytosine is paired with guanine). Each nucleotide in a string is "mirrored" in a nucleotide of the other string. Each strand of the helix acts therefore as a template to create the other template. Nucleotides are the elementary unit of the "genetic code". In other words, the genetic code is written in an alphabet of these four chemical units. Cells split all the time, and each new cell gets one of the two strings of DNA of the original cell, but each string will quickly rebuild its mirror image out of protoplasm. This process is known as "mitosis". Each cell in an individual has almost exactly the same DNA, which means that it carries the same genome. The genome is made of genes. A gene is a section of the DNA molecule which instructs the cell to manufacture proteins (indirectly, by doing that a gene determines a specific trait of the individual). Genes vary in size, from 500 bases long to more than two million (long genes tend to have just a very long waste). The genome is not a sequential program that is executed mechanically, one gene after the other. It is more like a network of genes that "regulate" each other. The genetic "program" behaves more like a network of http://www.thymos.com/tat/life.html (6 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
switches. More precisely, the DNA is organized into chromosomes (13 pairs in the case of the human race) which are in turn organized into genes. The human genome has 3 billion base pairs of DNA. This means that each cell contains three billion bases of DNA, which is a string of genes about 2 meters long. If we multiply for all the cells in the human body, we get a total length of genetic material which is about 16,000 times the distance between the Earth and the Moon. All living organisms use DNA to store hereditary information and they use the exact same code (the "genetic" code) to write such information in DNA The genome of an individual is written in the genetic code. It is inappropriate (although common) to refer to the "genetic code" of an individual, as all living things on this planet share the same genetic code. The genetic code is a code, just like the Morse code. It specifies how nucleotides (through a "transcription" of the four nucleotides into RNA and a translation of RNA into the twenty aminoacids) are mapped into aminoacids, which in turn make up proteins, which in turn make up bodies. Different genomes yield different bodies. But they always employ the same genetic code to carry out this transformation. The genetic code represents a set of instructions for the growth and behavior of the organism. Each individual is the product of a "genome", a specific repertory of genes written in the genetic code. The genetic code defines the "genotype" of an organism. Genotype is the "genetic makeup" of the organism. The organism itself is the "phenotype". Phenotype refers to how the genetic makeup is expressed in the body (the physical expression of a gene). "Sequencing" the genome refers to the process of identifying the genes. It is estimated that humans have between 25,000 and 150,000 genes. A single gene can often be responsible for important traits. For example, chimpanzees share 98.5% of the human genome, but there is hardly a single trait in common between the two species. 98% of the human genome contains the same DNA found in most other vertebrates. Very similar genetic programs can differ wildly in phenotypic effects. Some of those genes, incidentally, have been around for millions of years, and humans share them with bacteria. As the British biologist Steven Jones wrote, "everyone is a living fossil". The smallest genome that is known is the genome of the Mycoplasma Genitalium: 470 genes. One could wonder what is the smallest amount of genes that is required to have life… Genomes have confirmed the theory of evolution: genomes share common parts and different species are determined by the branching out of the other parts. The genealogical tree of living beings is carefully reflected in the structure of their genomes. The genome of a species is almost a "memory" of that species' evolutionary journey. Most human genes, for example, date back to primitive organisms, and they are shared by all modern animals that descend from those organisms. Only a few can be said to be truly http://www.thymos.com/tat/life.html (7 of 20)25/07/2003 14:35:10
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"human". Every single cell in the body contains roughly the same genetic information (barred copying mistakes) but each cell ends up specializing in a task, depending on where it is located: a heart cell will specialize in heart issues and not, say, liver issues, even if the genetic information describes both sets of issues. A muscle cell is a muscle cell, even if it is identical to a liver cell. This is the phenomenon of "cell differentiation", by which each cell "expresses" only some of the genes in the genome, i.e. only some of the possible proteins are manufactured ("synthesized"). Differentiation seems to be regulated by topology: depending on where a cell is, it exchanges energy (which is information) with some cells rather than others. Neighboring cells "self-organize". The process of "epigenesis" is the process by which the genotype is turned into the phenotype: DNA is transcribed into messenger RNA, which is in turn transcribed into chains of aminoacids (i.e., in proteins). In other words, the DNA is the sequence of instructions for building molecules called proteins, and proteins are manufactured of amino acids, whose order is determined by the DNA. Note that our genome has only 100,000 genes, but our body has 100 trillion cells. As far as the individual goes, we know that her genome is a synthesis of the genome of the parents plus some random shuffling. But it is not clear yet how much of the final individual is due to the genetic code and how much to the interaction with the environment. For example, the genetic code may specify that a muscle must grow between the arm and the trunk, but exercise can make that muscle bigger or smaller. For example, genetic code may determine some psychological characteristics of the individual, but study, meditation and peer pressure can alter some of them. The British biologist William Bateson thought that only the genetic code mattered: we are machines programmed from birth. John Watson, at the other extreme, thought that conditioning could alter at will the personality of an individual: it all depends on experience, the instruction contained in the genetic code is negligible. A puzzling features of genomes is that they contain far more useless junk than useful genes. The human genome, in particular, contains about 95% junk, in between genes. Recently, a certain attention has been drawn to the internals of the cell. Cells contain a structure called cytoskeleton, which is made of aprotein called "tibulin", which forms cylinders called "microtubules". Mutation as destiny In reality, the process of copying DNA is not so smooth. When a cell splits, its DNA is copied to the new cells but the copying process (for whatever whim of nature) is prone to "error" (or, at least, to loss of information). In other words, genes mutate all the time inside our bodies. These mutations may cause fatal diseases (such as cancer) and they are responsible for death. Mutation is what causes aging and death. Millions of cells divide each second and a copy of DNA is likely to carry some mistake, which means that the older we are the more chances that serious mistakes have been made and that our genetic instructions are no longer rational.
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Mutation is also the whole point of sex, and this turns out to be the mirror story of death. Sex is the antidote to the genetic deterioration due to the imperfect copying process. The human race would rapidly degenerate without sex: each individual would pass on genes that have already lost part of their information through so many million internal copies. Sex is what makes the paradox possible, and almost inevitable: individuals decay, but the race progresses. Because sex recombines the genes of the parents, it can produce both better and worse (genetically speaking) individuals, and natural selection will reward the better ones. The long-term outcome of sex is that it is more likely that better future individuals are produced from the deterioration of present individuals. Last but not least, mutation is what drives evolution (evolution is variation and natural selection). Mutation sounds like the god of genetics. The problem is that mutation is random. Evolution occurs by accident, by "genetic drift": by chance and time. Mutation is not everything, though. Mutation requires natural selection in order to yield evolution. Inheritance involves genes and environment working together. Diseases which are dormant in our genes, for example, may be sparked off by environmental conditions. Diet is as important as genes in the development or the prevention of a disease. And pollution is as important as genes to the development of cancer. And so forth. Chance and the environment determine how we evolve. The only party that does not have a saying in this process is… us. The Origin of Life Hypotheses abound on how life originated. Most theories analyze the ingredients of life and speculate how they may have been generated by the Earth’s early activity. It was in 1952 that a young American physicist, Stanley Miller, advanced the idea that the first molecules of life (including aminoacids, the building blocks of proteins) were formed accidentally by the Earth’s early volcanism and then triggered into reproducing systems by the energy of the sun and lightning strikes. His calculations of how lightning may have affected the Earth's primitive atmosphere gave rise to the quest for the experiment that would reproduce the birth of life in a laboratory (with hints of Frankenstein and all the rest). One catch remained, though: the product of Miller’s prebiotic chemistry would still be inactive chemicals. Miller simply revised a theory of chemical formation of life that dates back to the Russian chemist Alexander Oparin, who in 1929 first proposed that life could have been induced in the primeval soup. Autocatalysis
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Thinking About Thought: Consciousness, Life and Meaning
Since the pioneering work conducted in the 1960s by the German physicist Manfred Eigen, autocatalysis has been a prime candidate to explain how life could originate from random chemical reaction. Autocatalysis occurs when a substance A catalyzes the formation of a substance B that catalyzes the formation of a substance C that… eventually catalyzes the formation of A again. At the end of the loop there is still enough A to restart it. All the substances in this loop tend to grow, i.e. the loop as a whole tends to grow. Life could originate precisely from such a loop, in which case the chances that the right combination of chemical reactions occurred at the right time is much higher. The power of this hypothesis is that "autocatalyctic cycles" exhibit properties usually associated with life: metabolism and reproduction. If two such cycles occur in the same "pond", they will compete for resources and natural selection will reward the "best" one. The German patent lawyer Gunter Waechtershauser has improved on that model by explaining how the first forms of life could have synthesized their own vital chemicals rather than absorbing them from the environment, i.e. how a metabolic cycle could have started. Unlike Miller, Waechtershauser speculates that prebiotic reactions occurred not in water but on the ground. At high temperatures, chemicals bound to a metallic surface are much more likely to mix and form the complex molecules which are needed for life. Particularly, iron sulfide (a very common mineral on the Earth) could have been a catalyst of chemical reactions that created the biochemistry of living cells. He proved that peptides (short protein chains) could be creatd out of a few given aminoacids. The next step in the chain would be the emergence of RNA (ribonucleic acid), that he considers a predecessor to DNA. Waechtershauser's emphasis is on "autocatalysis" (in general, as a process that is fast enough for yielding dramatic consequences) and on the ability of minerals in particular to catalyse the right reactions. Life would be but the natural evolution of a primitive chemical cycle that originally arose on an iron-sulfur surface. Complexity The American biologist Stuart Kauffman also advanced a theory of how life may have originated. He refutes the theory that life started simple and became complex in favor of a scenario in which life started complex and whole due to a property of some complex chemical systems, the self-sustaining process of autocatalytic metabolism: when a system of simple chemicals reaches a certain level of complexity, it undergoes a phase transition, the molecules spontaneously combine in an autocatalytic chemical process to yield larger molecules of increasing complexity and catalytic capability. Life is but a phase transition that occurs when the system becomes complex enough. Life is therefore vastly more probable than traditionally assumed. And life began complex, not simple, with a metabolic web which was capable of capturing energy sources. Self-organizing principles are inherent in our universe and life is a direct consequence of self-organization. Therefore, both the origin of life and its subsequent evolution were inevitable. Panspermia Comets are slowly revealing another option. Today's theories are not all that much different from the http://www.thymos.com/tat/life.html (10 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
theory of the Greek philosopher Anaxagoras (fifth century BC): life was dispersed as seeds in the universe and eventually landed on Earth ("panspermia"). The Belgian astrophysicist Armand Delsemme hypothesized that all building blocks of life were brought to Earth by comets. Since then, organic material (from water to methyl alcohol, and even forerunners of DNA’s aminoacids) has been found in the galactic clouds that float among the stars of our galaxy. Interstellar matter seems to be rich in molecules that are needed to create life. Trillions of comets wander through the solar system and occasionally approach the Earth. They are soaked with the organic dust picked up from the interstellar void. In other words, comets may have their own role in the vast drama of life, sowing the seeds of life on all the planets they intersect. Comets have been found to contain many if not all the ingredients necessary for life to originate. (Incidentally, comets have found to carry ice, and no theory of the development of the Earth can account for the enormous quantity of water contained in the oceans, unless the water came from somewhere else). Also, left-handed aminoacids (the kind that life uses) were found in the meteorite fragments that showered Australia in 1969 (including some aminoacids unknown on Earth). If aminoacids are of extraterrestrial origin and Wachtershauser’s mineral-based chemistry can produce biological compounds, the chain that leads from dead matter to living matter would be completed. But life is also capable of reproduction and inheritance. And, unfortunately, Wachtershauser’s model requires high temperatures, whereas four of the five main components of DNA are unstable at those temperatures. Thermosynthesis In 1995 the Dutch chemist Anthonie Muller has shown that "thermosynthesis" is a viable alternative to explain the origin of life. Muller points out that life probably originated in conditions where photosynthesis and chemosynthesis (getting energy from light and food) were unfeasible, simply because there were not enough life and food. If life originated in an underwater volcano covered with ice, neither light nor food were abundant. What was abundant was a temperature difference. This "gradient" of temperature would cause convection currents, that would drag the early forms of life up and down in thermal cycles, from hot to cold and back to hot. The larger the temperature difference, the stronger the convection currents, the faster the thermal cycles, the more efficient the energy production. Heat was therefore the main source of energy, and heat was coming from the environment. Photosynthesis and chemosynthesis do yield much more power, but thermosynthesis was simply the only feasible form of energy production. The early living cells were basically built around "heat engines". Some of their enzymes or membranes worked essentially as heat engines. In a steam engine, for example, water is thermally cycled: water is heated until it turns into steam; the steam expands and performs work; the steam loses its energy and returns to liquid form; and the cycle resumes. In a thermosynthetic cell, a protein is thermally cycled in a similar manner: it is heated until it turns into a more fluid state; this generates work in the form of ATP (the chemical which is the energy source for http://www.thymos.com/tat/life.html (11 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
almost all physiological processes) while the protein returns in its original state; and the cycle resumes. Life before life Other theories focus on the replication mechanism, which doesn’t necessarily require organic matter to occur. For example, the British chemist Graham Cairns-Smith has argued that the first living beings were not carbon composts but clay crystals, i.e. minerals. Life's ancestors were self-replicating patterns of defects in clay crystals. One day those patterns started replicating in a different substance, carbon molecules. (But these are still purely self-replicating entities: it remains a mystery how they started growing bodies...) Synthetic self-replicating molecules that behave like living organisms have been crafted in the laboratory. Julius Rebek has recreated artificially the principles of life postulated by the biologist Richard Dawkins: "complementary" molecules (ones that fit into each other by way of spatial structure and chemical bonds) and even self-complementary molecules. Jeffrey Wicken has shown that the thermodynamic forces underlying the principles of variation and selection begin their operation in prebiotic evolution and lead to the emergence and development of individual, ecological and socioeconomic life. The prebiosphere (i.e., the Earth before life emerged) is treated as a non-isolated closed system in which energy sources create steady thermodynamic cycles. Some of this energy is captured and dissipated through the formation of ever more complex chemical structures. Soon, autocatalytic systems capable of reproduction appears. Living systems, according to his theory, are but "informed autocatalytic systems". Life and heat Whatever the mechanism that created it, the progenitor of all terrestrial life, four billion yeas ago, was able to tolerate the extreme heat conditions of the time (a few hundred degrees or even a thousand). As a matter of fact, if we walk backwards up the phylogenetic tree (the tree of species), we find that genetically older organisms can survive at higher and higher temperatures. Thermophiles (the microbes that live at temperatures of 70-80 degrees) are living relics of the beginnings of life on Earth. Based on such a phylogenetic tree, the American biologist Carl Woese has proposed a classification of living creatures in which thermophiles (or "archaea", first discovered in 1964 by Thomas Brock) are different both from eukaryotes (in which DNA is held by a nucleus) and prokaryotes (in which DNA floats free in the cells of bacteria): in thermophiles, DNA floats free (like in prokaryotes) but resembles the DNA of eukaryotes. Thermophiles can be found underground: some have been retrieved from 3 km beneath earth. An archaea has about two million base pairs of DNA (a human cell has about three billion). Surprisingly, very little has been made so far of a discovery due to Louis Pasteur: that living systems prefer molecules with a certain handedness (all proteins are made of L-amicoacids and genetic material is made of D-sugars). Actually this molecular asymmetry is the only difference between the chemistry of the living and of the dead matter. http://www.thymos.com/tat/life.html (12 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
The Origin of Reproduction The mystery of the origin of genes is particularly challenging because a gene is such a complicated structure, unlikely to evolve spontaneously. Walter Gilbert has noted that most of a person's DNA does not code genes but what appears to be gibberish, and even the part that is code is distributed in fragments (or "exons") separated by useless pauses (or "introns"). In his opinion the first genetic material was made of exons, who symbiotically got together and formed new, more complex genetic material. Introns are not random leftovers, but sort of gluing elements from the original material. In a sense, his theory points to the possibility that the gene is not the ultimate unit, but exons are. Attention has been focusing on RNA since RNA has been shown to be a self-replicating molecule that can act as its own catalyst. DNA cannot make copies of itself, and proteins cannot create themselves. They both depend on each other. But (some kind of) RNA can act as its own enzymes (i.e., its own catalyst). Therefore, RNA is capable of replicating itself without any need of proteins. Stanley Miller proposed that the first living creatures may have been able to synthesize protein and reproduce without the help of the DNA, depending solely on RNA to catalyze their growth and reproduction. Thomas Cech had already proved (in 1982) that RNA molecules alone can induce themselves to split up and splice themselves together in new arrangements. It is also chemically plausible that all four RNA nucleotide bases could have been created in nature by ordinary atmospheric, oceanic and geological processes. Miller's theory, though, requires that life was born in lukewarm water, not the very high temperatures of thermophiles. The American Nobel laureate Melvin Calvin was perhaps the first one to suggest that "autocatalytic" processes can make life more likely by speeding up the manufacturing of the basic ingredients. The German physicist Manfred Eigen induced RNA molecules to replicate by themselves, thereby lending credibility to the hypothesis that RNA came before DNA and that the first forms of life employed only RNA. Eigen's experiments with "autocalytic cycles" involving RNA showed that, under suitable conditions, a solution of nucleotides gives rise spontaneously to a molecule that replicates, mutates and competes with its progeny for survival. The replication of RNA could then be the fundamental event around which the rest of biology developed. Eigen speculates that the genetic code was created when lengths of RNA interacted with proteins in the "primordial soup". First genes were created, then proteins, then cells. Cells simply provide physical cohesion. Cells first learned to self-replicate and then to surround themselves with protective membranes. Bernd-Olaf Kuppers thinks that there is nothing special about life: all living phenomena, such as metabolism and inheritance, can be reduced to the interaction of biological macromolecules, i.e. to the laws of Physics and Chemistry. In particular, the living cell originated from the iterative application of the same fundamental rules that preside to all physical and chemical processes. In opposition to Monod, Kuppers favors the hypothesis that the origin of life from inorganic matter is due to emergent processes of self-
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Thinking About Thought: Consciousness, Life and Meaning
organization and evolution of macromolecules. But, in the balance between law and chance, only the general direction of evolution is determined by natural law: the detailed path is mainly determined by chance. Natural law entails biological structures, but does not specify which biological structures. The American physicist Freeman Dyson believes that one cannot consider life only as metabolism or only as replication. Both aspects must be present. Therefore, we must look not for the origin of life, but for the origin of replication and the origin of metabolism. Since it is unlikely that both metabolism and replication occurred at the same time in one of the primitive organic molecules, life must have had a double origin. It is more reasonable to assume that life "began" twice, with organisms capable of reproduction but not of metabolism and with (separate) organisms capable of metabolism but not of reproduction, and only later there arose a mixture of the two: organisms capable of both reproduction and metabolism. Dyson's idea is that first came organisms that could reproduce but not replicate. Reproduction is simply a cell division: two cells are created by dividing a cell in two. Replication implies that molecules are copied. Reproduction with replication implies that the new cells "inherit" the molecules of the mother cell. Replication became a parasite over metabolism, meaning that organisms capable of replication needed to use organisms capable of metabolism in order to replicate. First proteins were born and somehow began to metabolize. Then nucleic acids were born and somehow began to replicate using proteins as hosts. The two organisms became one thanks to a form of symbiosis between host and parasite. Dyson borrows ideas taken from Manfred Eigen (who claims that RNA can appear spontaneously) and Lynn Margulis (who claims that cellular evolution was due to parasites). Basically, his theory is that RNA was the primeval parasite. Genetic code is just a code that relates mRNA triples and protein's aminoacids. The genetic code is the same for every being. It is just a code. It translates the instructions in the genotype into a phenotype. Did the code itself evolve from a more primitive code? It is unlikely that the first self-replicating organisms were already using today's genetic code. How did the genetic code arise? And why don't we have any evidence of a pre-existing system of replication. Why today there is only one code, rather than a few competing codes (just like there are a few competing genomes)? Chance The ultimate meaning of the modern synthesis for the role of humans in nature is open to interpretation. One particular, devastatingly pessimistic, interpretation came from the French biologist and Nobel Prize winner Jacques Monod: humans are a mere accident of nature. To Monod, living beings are characterized by three properties: teleonomy (organisms are endowed with a purpose which is inherent in their structure and determines their behavior); autonomous morphogenesis (the structure of a living organism is due to intercations within the organism itself); and reproductive invariance (the source of information expressed in a living organism is another structurally identical object - it is the information corresponding to their own structure). A species' teleonomic level is the quantity of information that must be transferred to to the next generation http://www.thymos.com/tat/life.html (14 of 20)25/07/2003 14:35:10
Thinking About Thought: Consciousness, Life and Meaning
to assure transmission of the content of reproductive invariance. Invariance precedes teleonomy, teleonomy is a secondary property stemming from invariance. All three pose, according to Monod, insourmantable problems. The birth of teleonomic systems is improbable. The development of the metabolic system is a superlative feat. And the origin of the genetic code and its translation mechanism is an even greater riddle. From his analysis of how DNA and proteins work, Monod concludes that humans are the product of chance, an accident in the universe. The paradox of DNA is that a mono-dimensional structure like the genome could specify the function of a three-dimensional structure like the body: the function of a protein is underspecified in the code, it is the environment that determines a unique interpretation. There is no causal connection between the syntactic (genetic) information and the semantic (phenotypic) information that results from it. Then the growth of our body, the spontaneous and autonomous morphogenesis, rests upon the properties of proteins. Monod concludes that life was born by accident; then Darwin's natural selection made it evolve, and that also relies on chance. Biological information is inherently determined by chance. Life is not the consequence of a plan embodied in the laws of nature, it is a mere accident of chance. It can only be understood existentially. "Necessity", i.e. the laws of nature, is reduced to natural selection. In the 19th century, the French physicist Pierre Laplace suggested that, known the position and motion of all the particles in the universe, Physics could predict the evolution of the universe into the future. Laplace formulated the ultimate version of classical determinism: that the behavior of a system depends on the behavior of its parts, and its parts obey deterministic law of Physics. Once the initial conditions are known, the whole story of a particle if known. Once all the stories of all the particles are known, the story of the whole system is known. For Laplace, necessity ruled and there was no room for chance. Monod shatters this vision of reality and makes it even worse for humans: we are not robots, deterministic products of universal laws, but mere luck, product of chance. In Monod's world, chance plays the role of rationality: chance is the best strategy to play the game of life, it is necessary for life to exist and evolve. Chance alone is the source of all innovation and creation in the biosphere. The biosphere is a unique occurrence non reducible from first principles. DNA is a registry of chance. The universe has no purpose and no meaning. Monod commented: "Man knows at last that he is alone in the universe's unfeeling immensity out of which he emerged only by chance". In reality, what Monod highlighted is that the structures and processes on the lower level of an organism do not place any restrictions on higher level structures and processes. Reality is stratified into many levels, http://www.thymos.com/tat/life.html (15 of 20)25/07/2003 14:35:11
Thinking About Thought: Consciousness, Life and Meaning
and the higher levels are free from determinism from the lower levels. What this means is that high-level processes can be influenced as much from "above" as they are from "below". Monod's "chance" could simply mean "environment" (which even leaves open the possibility of the superenvironment of a god influencing all systems). A professional physicist, Freeman Dyson, on the other hand wrote: "The more I examine the universe and study the details of its architecture, the more evidence I find that the universe in some sense must have known that we were coming." Necessity At the opposite extreme, the American biologist Harold Morowitz believes that life occurred so early in the history of the planet because it was highly probable. Based on the chemistry of living matter, Morowitz argued that the simplest living cell that can exhibit growth and replication must be a "bilayer vesicle" made of "amphiphiles" (a class of molecules, that includes, for example, fatty acids). Such a vesicle, thermodynamically speaking, represents a "local minimum" of free energy, and that means that it is a structure that emerges spontaneously. The bilayers spontaneously form closed vesicles. The closure (the membrane) led to the physical and chemical separation of the organism from the environment. This, in Morowitz's mind, is the crucial event in the early evolution of life. Later, these vesicles may have incorporated enzymes as catalysts and all the other machinery of life. These vesicles are the "protocells" from which modern cells evolved. I other words, Morowitz believes that first came membranes: first membranes arose, then RNA, DNA or proteins or something else originated life. First of all an organism has a border that differentiates it from the environment, that isolates it thermodynamically, that bestows it an identity, that enables metabolism. The second step is to survive: the membrane's content (the cell) must be able to interact with the environment in such a way that it persists. Then the cell can acquire RNA or DNA or whatever else and reproduce and evolve and so forth. All of this happened not by chance, but because it was very likely to happen, it was written in the laws of Physics and Chemistry. Furthermore, Martin Eigen refuted Monod's thesis by showing that natural selection is not blind. Eigen agrees with Monod that information emerges from random fluctuations (from chance), but he thinks that evolution does not act blindly. Evolution is driven by an internal feedack mechanism that searches for the best route to optimal performance. Eigen found that the distribution of variants is asymmetric, and tends to favor the "best" variants (from a survival point of view). Life seems to know where to look for best variants. As a matter of fact, Eigen discovered a feedback mechanism, inherent in natural selection, that favors (or accelerates the search for) superior variants. Selection is not blind because it is driven by this internal feedback mechanism. Evolution is inherently biased towards the "best" possible solution to the survival problem, and this gives the appearance of goal-directedness of evolution. http://www.thymos.com/tat/life.html (16 of 20)25/07/2003 14:35:11
Thinking About Thought: Consciousness, Life and Meaning
Evolution is "directed" towards optimization of functional efficiency. Where Monod thinks that (biological) information arises from non-information by sheer luck, Eigen thinks that a fundamental law drives non-information towards information.
A History Of Life
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Bateson Gregory: MIND AND NATURE (Dutton, 1979) Behe Michael: DARWIN'S BLACK BOX (Free Press, 1996) Blackmore Susan: THE MEME MACHINE (Oxford Univ Press, 1999) Brandon Robert: GENES ORGANISMS POPULATION (MIT Press, 1984) Brandon Robert: ADAPTATION AND ENVIRONMENT (Princeton Univ Press, 1990) Brooks Daniel & Wiley E.O.: EVOLUTION AS ENTROPY (Univ of Chicago Press, 1986) Buss David: THE EVOLUTION OF DESIRE (Basic, 1994) Butler Samuel: EVOLUTION (?, 1879) Cairns-Smith Graham: GENETIC TAKEOVER (Cambridge University Press, 1982) Calvin Melvin: CHEMICAL EVOLUTION (Clarendon, 1969) Calvin William: THE ASCENT OF MIND (Bantam, 1991) Carvalo Marc: NATURE, COGNITION AND SYSTEM (Kluwer Academic, 1988)
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Capra Fritjof: THE WEB OF LIFE (Anchor Books, 1996) Crick Francis: LIFE ITSELF (Simon & Schuster, 1981) Crick Francis: ASTONISHING HYPOTHESIS (MacMillan, 1993) Cronin Helena: THE ANT AND THE PEACOCK (Cambridge University Press,1992) Darwin Charles: ON THE ORIGIN OF SPECIES BY MEANS OF NATURAL SELECTION (1859) Davies Paul: THE FIFTH MIRACLE (Simon & Schuster, 1998) Dawkins Richard: THE SELFISH GENE (Oxford Univ Press, 1976) Dawkins Richard: THE EXTENDED PHENOTYPE (OUP, 1982) Dawkins Richard: THE BLIND WATCHMAKER (Norton, 1987) Dawkins Richard: RIVER OUT OF EDEN (Basic, 1995) Dawkins Richard: CLIMBING MOUNT IMPROBABLE (Norton, 1996) De Waal Frans: GOOD NATURED : THE ORIGINS OF RIGHT AND WRONG IN HUMANS AND OTHER ANIMALS (Harvard University Press, 1996) Dennett Daniel: DARWIN'S DANGEROUS IDEA (Simon & Schuster, 1995) DeDuve Christian: VITAL DUST (Basic, 1995) Depew David & Weber Bruce: DARWINISM EVOLVING (MIT Press, 1994) Deutsch David: THE FABRIC OF REALITY (Penguin, 1997) Dyson Freeman: ORIGINS OF LIFE (Cambridge Univ Press, 1999) Edelman Gerald: TOPOBIOLOGY (Basic, 1988) Eigen Manfred: STEPS TOWARDS LIFE (Oxford University Press, 1992) Fisher Ronald Aylmer: THE GENETICAL THEORY OF NATURAL SELECTION (Dover, 1929) Goodwin Brian: HOW THE LEOPARD CHANGED ITS SPOTS (Charles Scribner, 1994)
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Gordon Deborah: ANTS AT WORK (Free Press, 1999) Gould Stephen Jay: ONTOGENY AND PHYLOGENY (harvard University Press, 1977) Gould Stephen Jay: EVER SINCE DARWIN (Deutsch, 1978) Gould Stephen Jay: WONDERFUL LIFE (Norton, 1989) Gould Stephen Jay: FULL HOUSE (Random House, 1996) Hamilton William Donald: NARROW ROADS OF GENE LAND (W.H. Freeman, 1996) Hamilton Terrell: PROCESS AND PATTERN IN EVOLUTION (MacMillan, 1967) Jolly Alison: LUCY's LEGACY (Harvard University Press, 1998) Jones Steven: LANGUAGE OF GENES (Harper Collins, 1993) Kauffman Stuart: THE ORIGINS OF ORDER (Oxford University Press, 1993) Kropotkin Petr: MUTUAL AID (1902) Lamarck Jean-Baptiste: PHILOSOPHIE ZOOLOGIQUE (1809) Lewontin Richard: THE GENETIC BASIS OF EVOLUTIONARY CHANGE (Columbia University Press, 1974) Lieberman Philip: UNIQUELY HUMAN (Harvard Univ Press, 1992) Lovelock James: GAIA (Oxford University Press, 1979) Margulis Lynn: WHAT IS LIFE? ( Simon & Schuster, 1995) Mason Stephen: CHEMICAL EVOLUTION (Clarendon Press, 1991) Mayr Ernst: POPULATION, SPECIES AND EVOLUTION (Harvard Univ Press, 1970) Mayr Ernst: THE GROWTH OF BIOLOGICAL THOUGHT (Harvard Univ Press, 1982) Mayr Ernst: TOWARDS A NEW PHILOSOPHY OF BIOLOGY (Harvard Univ Press, 1988) Monod Jacques: LE HASARD ET LA NECESSITE' (1971)
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Thinking About Thought: Consciousness, Life and Meaning
Morowitz Harold: BEGINNINGS OF CELLULAR LIFE (Yale University Press, 1992) Murchie Guy: SEVEN MYSTERIES OF LIFE (Houghton Mifflin, 1978) Murray James Dickson: MATHEMATICAL BIOLOGY (Springer-Verlag, 1993) Nesse Randolph and Williams George: WHY WE GET SICK (Times Books, 1994) Alexander Oparin: THE ORIGIN OF LIFE (?, 1929) Ridley Matt: THE RED QUEEN (MacMillan, 1994) Ridley Matt: THE ORIGINS OF VIRTUE (Viking, 1997) Sober, Elliot and Wilson, David Sloan: UNTO OTHERS (THE EVOLUTION AND PSYCHOLOGY OF UNSELFISH BEHAVIOR) (Harvard Univ Press, 1998) Trivers, Roberts: SOCIAL EVOLUTION (Benjamin/Cummings, 1985) Wallin Ivan: SYMBIOTICISM AND THE ORIGIN OF SPECIES (?,1927) Williams George: ADAPTATION AND NATURAL SELECTION (Princeton University Press, 1966) Wilson Edward Osborne: SOCIOBIOLOGY (Belknap, 1975) Wilson Edward Osborne: CONSILIENCE (Knopf, 1998) Wilson Edward Osborne: THE DIVERSITY OF LIFE (Harvard University Press, 1992) Wilson Edward & Lumsden Charles: GENES, MIND AND CULTURE (Harvard Univ Press, 1981) Wright Robert: THE MORAL ANIMAL (Random House, 1994)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Evolution: Of designers and designs (Darwin, Lamarck, Mendel, Baldwin, Monod, Miller, Wachtershauser, Gould, Crick, Cairns-Smith, Eigen, Wallace, Mayr, Wimsatt, Hull, Lewontin, Hamilton, D.S. Wilson, Brandon, Murchie, Margulis, Behe, Butler, Dawkins, Cronin, Wilson, Ridley, Jolly, Wicken)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Origins: What was life? While modern research focuses on how the neural processes of the brain can yield the mind, we often forget that brains are first and foremost alive, and no convincing evidence has been presented so far that dead brains can think. As far as we know, minds are alive. As far as we know, life came first, both from an evolutionary perspective and from a bodily perspective. If we accept this principle, then we come to recognize that "thinking life" may just be a particular case of "life", that the same type of processes which are responsible for life may be responsible also for the mind. And the mystery of the mind, or at least the mystery of the principle that underlies the mind, may have been solved a century ago by the most unlikely sleuth: Charles Darwin. Darwin never really explained what he wanted to explain, but he probably discovered the "type of process" that is responsible for life. He called it "evolution", today we call it "design without a designer", "emergence", "self-organization" and so forth. What it means is that properties may appear when a system reorganizes itself due to external constraints, due to the fact that it has to live and survive in this world. This very simple principle may underlie as well the secret of thought. Darwin's theory of evolution is not about "survival of the fittest", Darwin's theory is about "design". Life is defined by properties that occur in species as different as lions and bacteria. Mind would appear to be a property that differentiates life in a crucial way, but at closer inspection… animals do communicate, although they don't use our language; and animals do reason, although they don't use our logic; and animals do show emotions. What is truly unique about humans, other than the fact that we have developed more effective weapons to kill as many animals as we like?
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The Dynamics of Life As far as we can tell, there is no mind without life. In order to be thinking, you have to be alive first. What "being alive" means is easily characterized, as we have plenty of specimen to study: life is about growing and reproducing. A living organism is capable of using the environment (sun, water, minerals, other living organisms) in order to change its own shape and size, and it is capable of creating offspring of a similar kind. In technical terms, life has two aspects: metabolism and replication. Metabolism is the interaction with the environment that results in growth. Replication is the copying of information that results in reproduction. Metabolism affects proteins, replication affects nucleid acids. The statement that "life is growing and reproducing" is convenient for studying life on this planet, life as we know it. But certainly it would be confusing if we met aliens who speak and feel emotions but do not need to eat or go to the restrooms and never change shape. They are born adults and they die adults. They do not even reproduce: they are born out of a mineral. Their cells do not contain genetic material. They do not make children. Would that still be life? Also, that definition is not what folk psychology uses to recognize a living thing. What is an animal? Very few people would reply "something that grows and reproduce". Most people would answer "something that moves spontaneously". The "folk" definition is interesting, because it already implies a mind. At the same time, the folk definition does not discriminate in a crisp manner between animate and inanimate matter. A rock can also move. True, it requires a "force" to move it. But so is the case with animals: they also require a force, although it is a chemical rather than a mechanical force. Animals eat and process their food to produce the chemical force that make them move. The difference is the kind of force. The laws of nature revised How that relates to the rest of the universe is less clear. This universe exhibits an impressive spectrum of natural phenomena, some of which undergo spectacular mutations over macro or micro-time (long periods of time, or short periods of time). Life deserves a special status among them for the sheer quantity and quality of physical and chemical transformations that are involved. Nonetheless, ultimately life has to be just one of them. Indirectly, it was Charles Darwin who started this train of thought, when he identified simple rules that Nature follows in determining how life proceeds over macro-time. While those "rules" greatly differ from the laws of Physics that (we think) govern the universe, they are natural laws of equal importance to the laws of electromagnetism or gravitation. Why they differ so much from the others is a matter of debate: maybe Darwin’s laws are gross approximations of laws that, when discovered, will bear striking resemblance to the laws of Physics; or, conversely, maybe the laws of Physics are gross approximations of laws that, when discovered, will bear striking resemblance to the laws of evolution; or maybe they are just two different levels of explanation, http://www.thymos.com/tat/life.html (2 of 20)25/07/2003 14:36:23
Thinking About Thought: Consciousness, Life and Meaning
one set of laws applying only to the microworld, the other set applying to the macroworld. The mystery of life is that all living systems are made of the same fundamental constituents, molecules that are capable of catalyzing (speeding up) chemical reactions. But these molecules cannot move and cannot grow. Still, when they are combined in systems, they grow and move. New properties emerge. The first new property is the ability to self-assemble, to join other molecules and form new structures which are in turn able to self-assemble, triggering a cycle that leads to cells, tissues, organs, bodies, and possibly to societies and ecosystems. In order to approach the subject of "life" in a scientific way, we first need to discriminate among the various meanings of that term. What we normally call "life" is actually three separate phenomena. Precisely, in nature we observe three levels of organization: the phylogenetic level, which concerns the evolution over time of the genetic programs within individuals and species (and therefore the evolution of species); the ontogenetic level, which concerns the developmental process (or "growth") of a single multicellular organism; and the epigenetic level, which concerns the learning processes during an individual organism's lifetime (in particular, the nervous system, but also the immune system). In other words, life occurs at three levels: organisms evolve into other organisms, each organism changes (or grows) from birth till death, and finally the behavior of each organism changes during its lifetime (the organism "learns"). There are therefore two aspects to the word "life". Because of the way life evolved and came to be what it is today, life is both reproduction and metabolism: it is both information that survives from one individual to another ("genotype"), and information about the individual ("phenotype"). When we say that "ants are alive" and "I am alive" we mean two different things, even if we use the same word. To unify those two meanings it takes a theory that explains both life as reproduction and life as growth. Design Without a Designer The mystery of life was solved through exactly a century of discoveries. In 1859 Darwin published "The Origin Of Species". His claim was that: all existing organisms are the descendants of simpler ancestors that lived in the distant past, and the main force driving this evolution is natural selection by the environment. This is possible because living organisms reproduce and vary (make children that are slightly different than the parents). Through this process of evolution, organisms acquire characteristics that make them more "fit" to survive in their environment (or better "adapted" to their environment). Darwin based his theory of evolution on some hard facts. The population of every species can potentially grow exponentially in size. Most populations don't. Resources are limited. Individuals of all species are unique, each one slightly different from the other. Such individual differences are passed on to offspring. His conclusion was that variation (the random production of different individuals) and selection ("survival of the fittest") are two fundamental features of life on this planet and that, together, they can account for the evolution of species.
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To visualize what is so special to Darwin's idea, imagine that you are in a quandary and the situation is very complex. You have two options: 1. You can spend days analyzing the situation and trying to find the best strategy to cope with it. Or 2. you can spend only a few minutes listing ten strategies, which are more or less random and all different one from the other. In the former case, you are still thinking. In the latter case, you start applying each of the strategies at the same time. As you do so, some strategies turn out to be silly, others look promising. You pursue the ones that are promising. For example, you try ten different (random) variations on each of the promising ones. Again, some will prove themselves just plain silly, but others will look even more promising. And so forth. By trial and error (case 2.), you will always be working with a few promising strategies and possibly with a few excellent ones. After a few days you may have found one or more strategies that cope perfectly well with the situation. In case 1., you will be without a strategy for as long as you are thinking. When you finally find the best strategy (assuming that you have enough experience and intelligence to find it at all), it may be too late. In many situations, "design by trial and error" (case 2.) tends to be more efficient than "design by a designer" (case 1.). So Darwin opted for "design without a designer": nature builds species which are better and better adapted and the strategy it employs is one of trial and error. The idea of evolution established a new scientific paradigm that has probably been more influential than even Newton's Mechanics or Einstein's Relativity. Basically, evolution takes advantage of the uncertainty left in the transmission of genes from one generation to another: the offspring is never an exact copy of the parents, there is room for variation. The environment (e.g., natural selection) indirectly "selects" which variations (and therefore which individuals) survive. And the cycle resumes. After enough generations have elapsed, the traits may have varied to the point that a new species has been created. Nobody programs the changes in the genetic information. Changes occur all the time. There may be algorithms to determine how change is fostered. But there is no algorithm to determine which variation has to survive: the environment will make the selection. Living organisms are so complex that it seems highly improbable that natural selection alone could produce them. But Darwin's theory of variation and natural selection, spread over millions of years, yields a sequence of infinitesimally graded steps of evolution that eventually produce complexity. Each step embodies information about the environment and how to survive in it. The genetic information of an organism is a massive database of wisdom accrued over the millennia. It contains a detailed description of the ancient world and a list of instructions for surviving in it. The gorgeous and majestic logical systems of physical sciences are replaced by a completely different, and rather primitive, system of randomness, of chance, of trial and error. Of course, one could object that natural selection has (short-term) tactics, but no (long-term) strategy: that is why natural selection has never produced a clock or even a wheel. Tactics, on the other hand, can get to eyes and brains. Humans can build clocks, but not eyes. Nature can build eyes, but not clocks. Whatever http://www.thymos.com/tat/life.html (4 of 20)25/07/2003 14:36:23
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humans build, it has to be built within a lifetime through a carefully planned design. Nature builds its artifacts through millions of years of short-term tactics. "Design" refers to two different phenomena when applied to nature or humans. The difference is that human design has a designer. Darwinism solved the problem of "design without a designer": variation and selection alone can shape the animal world as it is, although variation is undirected and there is no selector for selection. Darwin's greatest intuition was that design can emerge spontaneously via an algorithmic process. The logic of replication In 1865 the Austrian botanist Gregor Mendel, while studying pea plants, proposed a mechanism for inheritance, that was to be rediscovered in 1901. Contrary to the common sense belief of the time, he realized that traits are inherited as units, not as "blends". The daughter of a blue-eyed father and a browneyed mother will not have eyes of a color in between blue and brown, she will most likely have either blue or brown eyes. Mendel came to believe that each trait is represented by a "unit" of transmission, by a "gene". Furthermore, traits are passed on to the offspring in a completely random manner: any offspring can have any combination of the traits of the parents. The model of genes provided for a practical basis to express some of Darwin's ideas. For example, Darwinian variation within a phenotype can be explained in terms of genetic "mutations" within a genotype: when copying genes, nature is prone to making typographical errors that yield variation in a population. In the 1920's, population genetics (as formulated by Sewall Wright and Ronald Fisher) turned Darwinism into a stochastic theory (i.e., it introduced probabilities). Fisher, in particular, proved that natural selection requires Mendelian inheritance in order to work the way it works. In the 1940's, the two theories were merged in the so called "modern synthesis". In practice, the synthetic theory of evolution merged a theory of inheritance (Mendel’s genetics) and a theory of species (evolutionary biology). Since those days, the idea of natural selection has undergone three stages of development, parallel to developments in the physical sciences: the deterministic dynamics of Isaac Newton, the stochastic dynamics of Clerk Maxwell and Ludwig Boltzmann, and now the dynamics of self-organizing systems. If initially Darwin's theory could be related to Newton's Physics in that it assumed an external force (natural selection) causing change in living organisms (just like Newton posited an external force, gravity, causing change in the motion of astronomical objects), with the invention of population genetics, by Ronald Fisher and others, Darwinism became stochastic (the thermodynamic model of genetic natural selection, in which fitness is maximized like entropy), just what Physics had become with Boltzmann's theory of gases. Today, biologists such as David Depew and Bruce Weber point to the idea of self-organization as the next step in the study of evolution. In 1944, Oswald Avery identified the vehicle of iheritance, the substance that genes are made of, the bearer of genetic information: the deoxyribonucleic acid (DNA for short). In 1953, the British biologist Francis Crick and the American biologist James Watson figured out the double-helix structure of the DNA molecule. It appeared that genetic information is encoded in a rather mathematical form, which was http://www.thymos.com/tat/life.html (5 of 20)25/07/2003 14:36:23
Thinking About Thought: Consciousness, Life and Meaning
christened "genetic code" because that’s what it is: a code. The "genome" is the repertory of genes of an organism. In 1957 Crick, by using only logical reasoning, reached the conclusion that information must flow only from the nucleid acids to proteins, never the other way around. In the 1960's biologists cracked the "genetic code", the code used by DNA to generate proteins, i.e. they found out how the four-letter language of DNA is translated into the twenty-letter language of proteins (the DNA is made of four kinds of nucleotides, proteins are made of twenty types of aminoacids). And, finally, in the 1980s biologists discovered ribonucleic acid (RNA), a single-strand molecule that partners with DNA to manufacture proteins. Recently, we started deciphering the genome of different animals, including our own. Origins From what we know today, we can say that life evolved through momentous leaps forward. First, reproduction occurred: an organism became capable of generating another organism of the same type. Then sexual reproduction occurred, in which it took two organisms to generate an organism of the same type. Then multicell organisms appeared, and organisms became complex assemblies of cells. Fourth, some of those cells developed into specialized organs, so that the organism became an entity structured in a multitude of more or less independent parts. Fifth, a central nervous system developed to direct the organs. And, finally, mind and consciousness appeared, probably originating from the same locus that controls the nervous system. (If life evolved from reproductive minerals to multicellular organisms and to conscious beings, it is intriguing to try to predict what is going to be the next leap forward...) The structure of living things An organism is a set of cells. Every cell of an individual (or, better, the nucleus of each cell) contains the DNA molecule for that individual, or its "genome". A DNA molecule is made of two strings, or "strands", each one the mirror image of the other (in the shape of a "double helix"). Each string is a sequence of "nucleotides" or "bases", which come in four kinds (adenine, guanine, cytosine, thymine). These four bases are paired together (adenine is paired with thymine and cytosine is paired with guanine). Each nucleotide in a string is "mirrored" in a nucleotide of the other string. Each strand of the helix acts therefore as a template to create the other template. Nucleotides are the elementary unit of the "genetic code". In other words, the genetic code is written in an alphabet of these four chemical units. Cells split all the time, and each new cell gets one of the two strings of DNA of the original cell, but each string will quickly rebuild its mirror image out of protoplasm. This process is known as "mitosis". Each cell in an individual has almost exactly the same DNA, which means that it carries the same genome. The genome is made of genes. A gene is a section of the DNA molecule which instructs the cell to manufacture proteins (indirectly, by doing that a gene determines a specific trait of the individual). Genes vary in size, from 500 bases long to more than two million (long genes tend to have just a very long waste). The genome is not a sequential program that is executed mechanically, one gene after the other. It is more like a network of genes that "regulate" each other. The genetic "program" behaves more like a network of http://www.thymos.com/tat/life.html (6 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
switches. More precisely, the DNA is organized into chromosomes (13 pairs in the case of the human race) which are in turn organized into genes. The human genome has 3 billion base pairs of DNA. This means that each cell contains three billion bases of DNA, which is a string of genes about 2 meters long. If we multiply for all the cells in the human body, we get a total length of genetic material which is about 16,000 times the distance between the Earth and the Moon. All living organisms use DNA to store hereditary information and they use the exact same code (the "genetic" code) to write such information in DNA The genome of an individual is written in the genetic code. It is inappropriate (although common) to refer to the "genetic code" of an individual, as all living things on this planet share the same genetic code. The genetic code is a code, just like the Morse code. It specifies how nucleotides (through a "transcription" of the four nucleotides into RNA and a translation of RNA into the twenty aminoacids) are mapped into aminoacids, which in turn make up proteins, which in turn make up bodies. Different genomes yield different bodies. But they always employ the same genetic code to carry out this transformation. The genetic code represents a set of instructions for the growth and behavior of the organism. Each individual is the product of a "genome", a specific repertory of genes written in the genetic code. The genetic code defines the "genotype" of an organism. Genotype is the "genetic makeup" of the organism. The organism itself is the "phenotype". Phenotype refers to how the genetic makeup is expressed in the body (the physical expression of a gene). "Sequencing" the genome refers to the process of identifying the genes. It is estimated that humans have between 25,000 and 150,000 genes. A single gene can often be responsible for important traits. For example, chimpanzees share 98.5% of the human genome, but there is hardly a single trait in common between the two species. 98% of the human genome contains the same DNA found in most other vertebrates. Very similar genetic programs can differ wildly in phenotypic effects. Some of those genes, incidentally, have been around for millions of years, and humans share them with bacteria. As the British biologist Steven Jones wrote, "everyone is a living fossil". The smallest genome that is known is the genome of the Mycoplasma Genitalium: 470 genes. One could wonder what is the smallest amount of genes that is required to have life… Genomes have confirmed the theory of evolution: genomes share common parts and different species are determined by the branching out of the other parts. The genealogical tree of living beings is carefully reflected in the structure of their genomes. The genome of a species is almost a "memory" of that species' evolutionary journey. Most human genes, for example, date back to primitive organisms, and they are shared by all modern animals that descend from those organisms. Only a few can be said to be truly http://www.thymos.com/tat/life.html (7 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
"human". Every single cell in the body contains roughly the same genetic information (barred copying mistakes) but each cell ends up specializing in a task, depending on where it is located: a heart cell will specialize in heart issues and not, say, liver issues, even if the genetic information describes both sets of issues. A muscle cell is a muscle cell, even if it is identical to a liver cell. This is the phenomenon of "cell differentiation", by which each cell "expresses" only some of the genes in the genome, i.e. only some of the possible proteins are manufactured ("synthesized"). Differentiation seems to be regulated by topology: depending on where a cell is, it exchanges energy (which is information) with some cells rather than others. Neighboring cells "self-organize". The process of "epigenesis" is the process by which the genotype is turned into the phenotype: DNA is transcribed into messenger RNA, which is in turn transcribed into chains of aminoacids (i.e., in proteins). In other words, the DNA is the sequence of instructions for building molecules called proteins, and proteins are manufactured of amino acids, whose order is determined by the DNA. Note that our genome has only 100,000 genes, but our body has 100 trillion cells. As far as the individual goes, we know that her genome is a synthesis of the genome of the parents plus some random shuffling. But it is not clear yet how much of the final individual is due to the genetic code and how much to the interaction with the environment. For example, the genetic code may specify that a muscle must grow between the arm and the trunk, but exercise can make that muscle bigger or smaller. For example, genetic code may determine some psychological characteristics of the individual, but study, meditation and peer pressure can alter some of them. The British biologist William Bateson thought that only the genetic code mattered: we are machines programmed from birth. John Watson, at the other extreme, thought that conditioning could alter at will the personality of an individual: it all depends on experience, the instruction contained in the genetic code is negligible. A puzzling features of genomes is that they contain far more useless junk than useful genes. The human genome, in particular, contains about 95% junk, in between genes. Recently, a certain attention has been drawn to the internals of the cell. Cells contain a structure called cytoskeleton, which is made of aprotein called "tibulin", which forms cylinders called "microtubules". Mutation as destiny In reality, the process of copying DNA is not so smooth. When a cell splits, its DNA is copied to the new cells but the copying process (for whatever whim of nature) is prone to "error" (or, at least, to loss of information). In other words, genes mutate all the time inside our bodies. These mutations may cause fatal diseases (such as cancer) and they are responsible for death. Mutation is what causes aging and death. Millions of cells divide each second and a copy of DNA is likely to carry some mistake, which means that the older we are the more chances that serious mistakes have been made and that our genetic instructions are no longer rational.
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Mutation is also the whole point of sex, and this turns out to be the mirror story of death. Sex is the antidote to the genetic deterioration due to the imperfect copying process. The human race would rapidly degenerate without sex: each individual would pass on genes that have already lost part of their information through so many million internal copies. Sex is what makes the paradox possible, and almost inevitable: individuals decay, but the race progresses. Because sex recombines the genes of the parents, it can produce both better and worse (genetically speaking) individuals, and natural selection will reward the better ones. The long-term outcome of sex is that it is more likely that better future individuals are produced from the deterioration of present individuals. Last but not least, mutation is what drives evolution (evolution is variation and natural selection). Mutation sounds like the god of genetics. The problem is that mutation is random. Evolution occurs by accident, by "genetic drift": by chance and time. Mutation is not everything, though. Mutation requires natural selection in order to yield evolution. Inheritance involves genes and environment working together. Diseases which are dormant in our genes, for example, may be sparked off by environmental conditions. Diet is as important as genes in the development or the prevention of a disease. And pollution is as important as genes to the development of cancer. And so forth. Chance and the environment determine how we evolve. The only party that does not have a saying in this process is… us. The Origin of Life Hypotheses abound on how life originated. Most theories analyze the ingredients of life and speculate how they may have been generated by the Earth’s early activity. It was in 1952 that a young American physicist, Stanley Miller, advanced the idea that the first molecules of life (including aminoacids, the building blocks of proteins) were formed accidentally by the Earth’s early volcanism and then triggered into reproducing systems by the energy of the sun and lightning strikes. His calculations of how lightning may have affected the Earth's primitive atmosphere gave rise to the quest for the experiment that would reproduce the birth of life in a laboratory (with hints of Frankenstein and all the rest). One catch remained, though: the product of Miller’s prebiotic chemistry would still be inactive chemicals. Miller simply revised a theory of chemical formation of life that dates back to the Russian chemist Alexander Oparin, who in 1929 first proposed that life could have been induced in the primeval soup. Autocatalysis
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Thinking About Thought: Consciousness, Life and Meaning
Since the pioneering work conducted in the 1960s by the German physicist Manfred Eigen, autocatalysis has been a prime candidate to explain how life could originate from random chemical reaction. Autocatalysis occurs when a substance A catalyzes the formation of a substance B that catalyzes the formation of a substance C that… eventually catalyzes the formation of A again. At the end of the loop there is still enough A to restart it. All the substances in this loop tend to grow, i.e. the loop as a whole tends to grow. Life could originate precisely from such a loop, in which case the chances that the right combination of chemical reactions occurred at the right time is much higher. The power of this hypothesis is that "autocatalyctic cycles" exhibit properties usually associated with life: metabolism and reproduction. If two such cycles occur in the same "pond", they will compete for resources and natural selection will reward the "best" one. The German patent lawyer Gunter Waechtershauser has improved on that model by explaining how the first forms of life could have synthesized their own vital chemicals rather than absorbing them from the environment, i.e. how a metabolic cycle could have started. Unlike Miller, Waechtershauser speculates that prebiotic reactions occurred not in water but on the ground. At high temperatures, chemicals bound to a metallic surface are much more likely to mix and form the complex molecules which are needed for life. Particularly, iron sulfide (a very common mineral on the Earth) could have been a catalyst of chemical reactions that created the biochemistry of living cells. He proved that peptides (short protein chains) could be creatd out of a few given aminoacids. The next step in the chain would be the emergence of RNA (ribonucleic acid), that he considers a predecessor to DNA. Waechtershauser's emphasis is on "autocatalysis" (in general, as a process that is fast enough for yielding dramatic consequences) and on the ability of minerals in particular to catalyse the right reactions. Life would be but the natural evolution of a primitive chemical cycle that originally arose on an iron-sulfur surface. Complexity The American biologist Stuart Kauffman also advanced a theory of how life may have originated. He refutes the theory that life started simple and became complex in favor of a scenario in which life started complex and whole due to a property of some complex chemical systems, the self-sustaining process of autocatalytic metabolism: when a system of simple chemicals reaches a certain level of complexity, it undergoes a phase transition, the molecules spontaneously combine in an autocatalytic chemical process to yield larger molecules of increasing complexity and catalytic capability. Life is but a phase transition that occurs when the system becomes complex enough. Life is therefore vastly more probable than traditionally assumed. And life began complex, not simple, with a metabolic web which was capable of capturing energy sources. Self-organizing principles are inherent in our universe and life is a direct consequence of self-organization. Therefore, both the origin of life and its subsequent evolution were inevitable. Panspermia Comets are slowly revealing another option. Today's theories are not all that much different from the http://www.thymos.com/tat/life.html (10 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
theory of the Greek philosopher Anaxagoras (fifth century BC): life was dispersed as seeds in the universe and eventually landed on Earth ("panspermia"). The Belgian astrophysicist Armand Delsemme hypothesized that all building blocks of life were brought to Earth by comets. Since then, organic material (from water to methyl alcohol, and even forerunners of DNA’s aminoacids) has been found in the galactic clouds that float among the stars of our galaxy. Interstellar matter seems to be rich in molecules that are needed to create life. Trillions of comets wander through the solar system and occasionally approach the Earth. They are soaked with the organic dust picked up from the interstellar void. In other words, comets may have their own role in the vast drama of life, sowing the seeds of life on all the planets they intersect. Comets have been found to contain many if not all the ingredients necessary for life to originate. (Incidentally, comets have found to carry ice, and no theory of the development of the Earth can account for the enormous quantity of water contained in the oceans, unless the water came from somewhere else). Also, left-handed aminoacids (the kind that life uses) were found in the meteorite fragments that showered Australia in 1969 (including some aminoacids unknown on Earth). If aminoacids are of extraterrestrial origin and Wachtershauser’s mineral-based chemistry can produce biological compounds, the chain that leads from dead matter to living matter would be completed. But life is also capable of reproduction and inheritance. And, unfortunately, Wachtershauser’s model requires high temperatures, whereas four of the five main components of DNA are unstable at those temperatures. Thermosynthesis In 1995 the Dutch chemist Anthonie Muller has shown that "thermosynthesis" is a viable alternative to explain the origin of life. Muller points out that life probably originated in conditions where photosynthesis and chemosynthesis (getting energy from light and food) were unfeasible, simply because there were not enough life and food. If life originated in an underwater volcano covered with ice, neither light nor food were abundant. What was abundant was a temperature difference. This "gradient" of temperature would cause convection currents, that would drag the early forms of life up and down in thermal cycles, from hot to cold and back to hot. The larger the temperature difference, the stronger the convection currents, the faster the thermal cycles, the more efficient the energy production. Heat was therefore the main source of energy, and heat was coming from the environment. Photosynthesis and chemosynthesis do yield much more power, but thermosynthesis was simply the only feasible form of energy production. The early living cells were basically built around "heat engines". Some of their enzymes or membranes worked essentially as heat engines. In a steam engine, for example, water is thermally cycled: water is heated until it turns into steam; the steam expands and performs work; the steam loses its energy and returns to liquid form; and the cycle resumes. In a thermosynthetic cell, a protein is thermally cycled in a similar manner: it is heated until it turns into a more fluid state; this generates work in the form of ATP (the chemical which is the energy source for http://www.thymos.com/tat/life.html (11 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
almost all physiological processes) while the protein returns in its original state; and the cycle resumes. Life before life Other theories focus on the replication mechanism, which doesn’t necessarily require organic matter to occur. For example, the British chemist Graham Cairns-Smith has argued that the first living beings were not carbon composts but clay crystals, i.e. minerals. Life's ancestors were self-replicating patterns of defects in clay crystals. One day those patterns started replicating in a different substance, carbon molecules. (But these are still purely self-replicating entities: it remains a mystery how they started growing bodies...) Synthetic self-replicating molecules that behave like living organisms have been crafted in the laboratory. Julius Rebek has recreated artificially the principles of life postulated by the biologist Richard Dawkins: "complementary" molecules (ones that fit into each other by way of spatial structure and chemical bonds) and even self-complementary molecules. Jeffrey Wicken has shown that the thermodynamic forces underlying the principles of variation and selection begin their operation in prebiotic evolution and lead to the emergence and development of individual, ecological and socioeconomic life. The prebiosphere (i.e., the Earth before life emerged) is treated as a non-isolated closed system in which energy sources create steady thermodynamic cycles. Some of this energy is captured and dissipated through the formation of ever more complex chemical structures. Soon, autocatalytic systems capable of reproduction appears. Living systems, according to his theory, are but "informed autocatalytic systems". Life and heat Whatever the mechanism that created it, the progenitor of all terrestrial life, four billion yeas ago, was able to tolerate the extreme heat conditions of the time (a few hundred degrees or even a thousand). As a matter of fact, if we walk backwards up the phylogenetic tree (the tree of species), we find that genetically older organisms can survive at higher and higher temperatures. Thermophiles (the microbes that live at temperatures of 70-80 degrees) are living relics of the beginnings of life on Earth. Based on such a phylogenetic tree, the American biologist Carl Woese has proposed a classification of living creatures in which thermophiles (or "archaea", first discovered in 1964 by Thomas Brock) are different both from eukaryotes (in which DNA is held by a nucleus) and prokaryotes (in which DNA floats free in the cells of bacteria): in thermophiles, DNA floats free (like in prokaryotes) but resembles the DNA of eukaryotes. Thermophiles can be found underground: some have been retrieved from 3 km beneath earth. An archaea has about two million base pairs of DNA (a human cell has about three billion). Surprisingly, very little has been made so far of a discovery due to Louis Pasteur: that living systems prefer molecules with a certain handedness (all proteins are made of L-amicoacids and genetic material is made of D-sugars). Actually this molecular asymmetry is the only difference between the chemistry of the living and of the dead matter. http://www.thymos.com/tat/life.html (12 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
The Origin of Reproduction The mystery of the origin of genes is particularly challenging because a gene is such a complicated structure, unlikely to evolve spontaneously. Walter Gilbert has noted that most of a person's DNA does not code genes but what appears to be gibberish, and even the part that is code is distributed in fragments (or "exons") separated by useless pauses (or "introns"). In his opinion the first genetic material was made of exons, who symbiotically got together and formed new, more complex genetic material. Introns are not random leftovers, but sort of gluing elements from the original material. In a sense, his theory points to the possibility that the gene is not the ultimate unit, but exons are. Attention has been focusing on RNA since RNA has been shown to be a self-replicating molecule that can act as its own catalyst. DNA cannot make copies of itself, and proteins cannot create themselves. They both depend on each other. But (some kind of) RNA can act as its own enzymes (i.e., its own catalyst). Therefore, RNA is capable of replicating itself without any need of proteins. Stanley Miller proposed that the first living creatures may have been able to synthesize protein and reproduce without the help of the DNA, depending solely on RNA to catalyze their growth and reproduction. Thomas Cech had already proved (in 1982) that RNA molecules alone can induce themselves to split up and splice themselves together in new arrangements. It is also chemically plausible that all four RNA nucleotide bases could have been created in nature by ordinary atmospheric, oceanic and geological processes. Miller's theory, though, requires that life was born in lukewarm water, not the very high temperatures of thermophiles. The American Nobel laureate Melvin Calvin was perhaps the first one to suggest that "autocatalytic" processes can make life more likely by speeding up the manufacturing of the basic ingredients. The German physicist Manfred Eigen induced RNA molecules to replicate by themselves, thereby lending credibility to the hypothesis that RNA came before DNA and that the first forms of life employed only RNA. Eigen's experiments with "autocalytic cycles" involving RNA showed that, under suitable conditions, a solution of nucleotides gives rise spontaneously to a molecule that replicates, mutates and competes with its progeny for survival. The replication of RNA could then be the fundamental event around which the rest of biology developed. Eigen speculates that the genetic code was created when lengths of RNA interacted with proteins in the "primordial soup". First genes were created, then proteins, then cells. Cells simply provide physical cohesion. Cells first learned to self-replicate and then to surround themselves with protective membranes. Bernd-Olaf Kuppers thinks that there is nothing special about life: all living phenomena, such as metabolism and inheritance, can be reduced to the interaction of biological macromolecules, i.e. to the laws of Physics and Chemistry. In particular, the living cell originated from the iterative application of the same fundamental rules that preside to all physical and chemical processes. In opposition to Monod, Kuppers favors the hypothesis that the origin of life from inorganic matter is due to emergent processes of self-
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Thinking About Thought: Consciousness, Life and Meaning
organization and evolution of macromolecules. But, in the balance between law and chance, only the general direction of evolution is determined by natural law: the detailed path is mainly determined by chance. Natural law entails biological structures, but does not specify which biological structures. The American physicist Freeman Dyson believes that one cannot consider life only as metabolism or only as replication. Both aspects must be present. Therefore, we must look not for the origin of life, but for the origin of replication and the origin of metabolism. Since it is unlikely that both metabolism and replication occurred at the same time in one of the primitive organic molecules, life must have had a double origin. It is more reasonable to assume that life "began" twice, with organisms capable of reproduction but not of metabolism and with (separate) organisms capable of metabolism but not of reproduction, and only later there arose a mixture of the two: organisms capable of both reproduction and metabolism. Dyson's idea is that first came organisms that could reproduce but not replicate. Reproduction is simply a cell division: two cells are created by dividing a cell in two. Replication implies that molecules are copied. Reproduction with replication implies that the new cells "inherit" the molecules of the mother cell. Replication became a parasite over metabolism, meaning that organisms capable of replication needed to use organisms capable of metabolism in order to replicate. First proteins were born and somehow began to metabolize. Then nucleic acids were born and somehow began to replicate using proteins as hosts. The two organisms became one thanks to a form of symbiosis between host and parasite. Dyson borrows ideas taken from Manfred Eigen (who claims that RNA can appear spontaneously) and Lynn Margulis (who claims that cellular evolution was due to parasites). Basically, his theory is that RNA was the primeval parasite. Genetic code is just a code that relates mRNA triples and protein's aminoacids. The genetic code is the same for every being. It is just a code. It translates the instructions in the genotype into a phenotype. Did the code itself evolve from a more primitive code? It is unlikely that the first self-replicating organisms were already using today's genetic code. How did the genetic code arise? And why don't we have any evidence of a pre-existing system of replication. Why today there is only one code, rather than a few competing codes (just like there are a few competing genomes)? Chance The ultimate meaning of the modern synthesis for the role of humans in nature is open to interpretation. One particular, devastatingly pessimistic, interpretation came from the French biologist and Nobel Prize winner Jacques Monod: humans are a mere accident of nature. To Monod, living beings are characterized by three properties: teleonomy (organisms are endowed with a purpose which is inherent in their structure and determines their behavior); autonomous morphogenesis (the structure of a living organism is due to intercations within the organism itself); and reproductive invariance (the source of information expressed in a living organism is another structurally identical object - it is the information corresponding to their own structure). A species' teleonomic level is the quantity of information that must be transferred to to the next generation http://www.thymos.com/tat/life.html (14 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
to assure transmission of the content of reproductive invariance. Invariance precedes teleonomy, teleonomy is a secondary property stemming from invariance. All three pose, according to Monod, insourmantable problems. The birth of teleonomic systems is improbable. The development of the metabolic system is a superlative feat. And the origin of the genetic code and its translation mechanism is an even greater riddle. From his analysis of how DNA and proteins work, Monod concludes that humans are the product of chance, an accident in the universe. The paradox of DNA is that a mono-dimensional structure like the genome could specify the function of a three-dimensional structure like the body: the function of a protein is underspecified in the code, it is the environment that determines a unique interpretation. There is no causal connection between the syntactic (genetic) information and the semantic (phenotypic) information that results from it. Then the growth of our body, the spontaneous and autonomous morphogenesis, rests upon the properties of proteins. Monod concludes that life was born by accident; then Darwin's natural selection made it evolve, and that also relies on chance. Biological information is inherently determined by chance. Life is not the consequence of a plan embodied in the laws of nature, it is a mere accident of chance. It can only be understood existentially. "Necessity", i.e. the laws of nature, is reduced to natural selection. In the 19th century, the French physicist Pierre Laplace suggested that, known the position and motion of all the particles in the universe, Physics could predict the evolution of the universe into the future. Laplace formulated the ultimate version of classical determinism: that the behavior of a system depends on the behavior of its parts, and its parts obey deterministic law of Physics. Once the initial conditions are known, the whole story of a particle if known. Once all the stories of all the particles are known, the story of the whole system is known. For Laplace, necessity ruled and there was no room for chance. Monod shatters this vision of reality and makes it even worse for humans: we are not robots, deterministic products of universal laws, but mere luck, product of chance. In Monod's world, chance plays the role of rationality: chance is the best strategy to play the game of life, it is necessary for life to exist and evolve. Chance alone is the source of all innovation and creation in the biosphere. The biosphere is a unique occurrence non reducible from first principles. DNA is a registry of chance. The universe has no purpose and no meaning. Monod commented: "Man knows at last that he is alone in the universe's unfeeling immensity out of which he emerged only by chance". In reality, what Monod highlighted is that the structures and processes on the lower level of an organism do not place any restrictions on higher level structures and processes. Reality is stratified into many levels, http://www.thymos.com/tat/life.html (15 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
and the higher levels are free from determinism from the lower levels. What this means is that high-level processes can be influenced as much from "above" as they are from "below". Monod's "chance" could simply mean "environment" (which even leaves open the possibility of the superenvironment of a god influencing all systems). A professional physicist, Freeman Dyson, on the other hand wrote: "The more I examine the universe and study the details of its architecture, the more evidence I find that the universe in some sense must have known that we were coming." Necessity At the opposite extreme, the American biologist Harold Morowitz believes that life occurred so early in the history of the planet because it was highly probable. Based on the chemistry of living matter, Morowitz argued that the simplest living cell that can exhibit growth and replication must be a "bilayer vesicle" made of "amphiphiles" (a class of molecules, that includes, for example, fatty acids). Such a vesicle, thermodynamically speaking, represents a "local minimum" of free energy, and that means that it is a structure that emerges spontaneously. The bilayers spontaneously form closed vesicles. The closure (the membrane) led to the physical and chemical separation of the organism from the environment. This, in Morowitz's mind, is the crucial event in the early evolution of life. Later, these vesicles may have incorporated enzymes as catalysts and all the other machinery of life. These vesicles are the "protocells" from which modern cells evolved. I other words, Morowitz believes that first came membranes: first membranes arose, then RNA, DNA or proteins or something else originated life. First of all an organism has a border that differentiates it from the environment, that isolates it thermodynamically, that bestows it an identity, that enables metabolism. The second step is to survive: the membrane's content (the cell) must be able to interact with the environment in such a way that it persists. Then the cell can acquire RNA or DNA or whatever else and reproduce and evolve and so forth. All of this happened not by chance, but because it was very likely to happen, it was written in the laws of Physics and Chemistry. Furthermore, Martin Eigen refuted Monod's thesis by showing that natural selection is not blind. Eigen agrees with Monod that information emerges from random fluctuations (from chance), but he thinks that evolution does not act blindly. Evolution is driven by an internal feedack mechanism that searches for the best route to optimal performance. Eigen found that the distribution of variants is asymmetric, and tends to favor the "best" variants (from a survival point of view). Life seems to know where to look for best variants. As a matter of fact, Eigen discovered a feedback mechanism, inherent in natural selection, that favors (or accelerates the search for) superior variants. Selection is not blind because it is driven by this internal feedback mechanism. Evolution is inherently biased towards the "best" possible solution to the survival problem, and this gives the appearance of goal-directedness of evolution. http://www.thymos.com/tat/life.html (16 of 20)25/07/2003 14:36:24
Thinking About Thought: Consciousness, Life and Meaning
Evolution is "directed" towards optimization of functional efficiency. Where Monod thinks that (biological) information arises from non-information by sheer luck, Eigen thinks that a fundamental law drives non-information towards information.
A History Of Life
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
Further Reading Bateson Gregory: MIND AND NATURE (Dutton, 1979) Behe Michael: DARWIN'S BLACK BOX (Free Press, 1996) Blackmore Susan: THE MEME MACHINE (Oxford Univ Press, 1999) Brandon Robert: GENES ORGANISMS POPULATION (MIT Press, 1984) Brandon Robert: ADAPTATION AND ENVIRONMENT (Princeton Univ Press, 1990) Brooks Daniel & Wiley E.O.: EVOLUTION AS ENTROPY (Univ of Chicago Press, 1986) Buss David: THE EVOLUTION OF DESIRE (Basic, 1994) Butler Samuel: EVOLUTION (?, 1879) Cairns-Smith Graham: GENETIC TAKEOVER (Cambridge University Press, 1982) Calvin Melvin: CHEMICAL EVOLUTION (Clarendon, 1969) Calvin William: THE ASCENT OF MIND (Bantam, 1991) Carvalo Marc: NATURE, COGNITION AND SYSTEM (Kluwer Academic, 1988)
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Thinking About Thought: Consciousness, Life and Meaning
Capra Fritjof: THE WEB OF LIFE (Anchor Books, 1996) Crick Francis: LIFE ITSELF (Simon & Schuster, 1981) Crick Francis: ASTONISHING HYPOTHESIS (MacMillan, 1993) Cronin Helena: THE ANT AND THE PEACOCK (Cambridge University Press,1992) Darwin Charles: ON THE ORIGIN OF SPECIES BY MEANS OF NATURAL SELECTION (1859) Davies Paul: THE FIFTH MIRACLE (Simon & Schuster, 1998) Dawkins Richard: THE SELFISH GENE (Oxford Univ Press, 1976) Dawkins Richard: THE EXTENDED PHENOTYPE (OUP, 1982) Dawkins Richard: THE BLIND WATCHMAKER (Norton, 1987) Dawkins Richard: RIVER OUT OF EDEN (Basic, 1995) Dawkins Richard: CLIMBING MOUNT IMPROBABLE (Norton, 1996) De Waal Frans: GOOD NATURED : THE ORIGINS OF RIGHT AND WRONG IN HUMANS AND OTHER ANIMALS (Harvard University Press, 1996) Dennett Daniel: DARWIN'S DANGEROUS IDEA (Simon & Schuster, 1995) DeDuve Christian: VITAL DUST (Basic, 1995) Depew David & Weber Bruce: DARWINISM EVOLVING (MIT Press, 1994) Deutsch David: THE FABRIC OF REALITY (Penguin, 1997) Dyson Freeman: ORIGINS OF LIFE (Cambridge Univ Press, 1999) Edelman Gerald: TOPOBIOLOGY (Basic, 1988) Eigen Manfred: STEPS TOWARDS LIFE (Oxford University Press, 1992) Fisher Ronald Aylmer: THE GENETICAL THEORY OF NATURAL SELECTION (Dover, 1929) Goodwin Brian: HOW THE LEOPARD CHANGED ITS SPOTS (Charles Scribner, 1994)
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Thinking About Thought: Consciousness, Life and Meaning
Gordon Deborah: ANTS AT WORK (Free Press, 1999) Gould Stephen Jay: ONTOGENY AND PHYLOGENY (harvard University Press, 1977) Gould Stephen Jay: EVER SINCE DARWIN (Deutsch, 1978) Gould Stephen Jay: WONDERFUL LIFE (Norton, 1989) Gould Stephen Jay: FULL HOUSE (Random House, 1996) Hamilton William Donald: NARROW ROADS OF GENE LAND (W.H. Freeman, 1996) Hamilton Terrell: PROCESS AND PATTERN IN EVOLUTION (MacMillan, 1967) Jolly Alison: LUCY's LEGACY (Harvard University Press, 1998) Jones Steven: LANGUAGE OF GENES (Harper Collins, 1993) Kauffman Stuart: THE ORIGINS OF ORDER (Oxford University Press, 1993) Kropotkin Petr: MUTUAL AID (1902) Lamarck Jean-Baptiste: PHILOSOPHIE ZOOLOGIQUE (1809) Lewontin Richard: THE GENETIC BASIS OF EVOLUTIONARY CHANGE (Columbia University Press, 1974) Lieberman Philip: UNIQUELY HUMAN (Harvard Univ Press, 1992) Lovelock James: GAIA (Oxford University Press, 1979) Margulis Lynn: WHAT IS LIFE? ( Simon & Schuster, 1995) Mason Stephen: CHEMICAL EVOLUTION (Clarendon Press, 1991) Mayr Ernst: POPULATION, SPECIES AND EVOLUTION (Harvard Univ Press, 1970) Mayr Ernst: THE GROWTH OF BIOLOGICAL THOUGHT (Harvard Univ Press, 1982) Mayr Ernst: TOWARDS A NEW PHILOSOPHY OF BIOLOGY (Harvard Univ Press, 1988) Monod Jacques: LE HASARD ET LA NECESSITE' (1971)
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Thinking About Thought: Consciousness, Life and Meaning
Morowitz Harold: BEGINNINGS OF CELLULAR LIFE (Yale University Press, 1992) Murchie Guy: SEVEN MYSTERIES OF LIFE (Houghton Mifflin, 1978) Murray James Dickson: MATHEMATICAL BIOLOGY (Springer-Verlag, 1993) Nesse Randolph and Williams George: WHY WE GET SICK (Times Books, 1994) Alexander Oparin: THE ORIGIN OF LIFE (?, 1929) Ridley Matt: THE RED QUEEN (MacMillan, 1994) Ridley Matt: THE ORIGINS OF VIRTUE (Viking, 1997) Sober, Elliot and Wilson, David Sloan: UNTO OTHERS (THE EVOLUTION AND PSYCHOLOGY OF UNSELFISH BEHAVIOR) (Harvard Univ Press, 1998) Trivers, Roberts: SOCIAL EVOLUTION (Benjamin/Cummings, 1985) Wallin Ivan: SYMBIOTICISM AND THE ORIGIN OF SPECIES (?,1927) Williams George: ADAPTATION AND NATURAL SELECTION (Princeton University Press, 1966) Wilson Edward Osborne: SOCIOBIOLOGY (Belknap, 1975) Wilson Edward Osborne: CONSILIENCE (Knopf, 1998) Wilson Edward Osborne: THE DIVERSITY OF LIFE (Harvard University Press, 1992) Wilson Edward & Lumsden Charles: GENES, MIND AND CULTURE (Harvard Univ Press, 1981) Wright Robert: THE MORAL ANIMAL (Random House, 1994)
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Thinking About Thought: Consciousness, Life and Meaning
Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Self-organization and the Science of Emergence (Koestler, Salthe, Von Bertalanffy, Laszlo, Haken, Eigen, Prigogine, Cohen, Turing, Von Neumann, Conway, Holland, Goldberg, Langton, Kauffman, Thom, Gell-Man, Varela, Fuller)
These are excerpts from my book "Thinking About Thought". Click here for information on how to purchase the book.
The Origin of Order When Darwin discovered evolution, he also indirectly created the premises for a momentous shift in the scientific paradigm. Over the centuries, Science had always held that order can be built only rationally, by application of a set of fundamental laws of Physics. Scientists like Newton and Einstein simply refined that model by using more and more sophisticated mathematics. Throughout the theoretical developments of Physics, the fundamental idea remained that in nature order needs to be somehow created by external forces. Darwin showed that order can build itself spontaneously, without any help from the outside. Evolution is such a process: it is capable of building higher and higher degrees of order starting from almost nothing. As far as Darwin was concerned, this paradigm only applied to Biology, but the idea has been so powerful that recently more and more natural phenomena have been reduced to some kind of spontaneous "emergence" of order. Indirectly Darwin is causing a dramatic change in the idea of Physics itself: are splitting the atom and observing distant galaxies the right ways to explain the universe? or should we focus instead on the evolutionary process that gradually built the universe the way it is now? Should we study how things are modified when a force is applied (the vast majority of what Physics does today) or should we deal with how things modify themselves spontaneously? Can Physics ever explain how a tree grows or how a cloud moves by bombarding particles with radiations? The macroscopic phenomena we observe are more likely to be explained by laws about systems than by laws about particles. Science’s ultimate theme is still the origin of order, but the perspective may be changing. Furthermore, order is directly related to information, and Darwin’s theory has to do with the creation of information. From its new perspective, Science may be as much a study of information as it is a study of gravitation or electricity. And the creation f order is inevitably related to the destruction of entropy (or the creation of negative entropy): entropy is therefore elevated to a higher rank among physical quantities. http://www.thymos.com/tat/emergenc.html (1 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
As a matter of fact, Darwin’s laws, unlike the laws of nature claimed by physical sciences, cannot be written down in the form of differential equations. They can only be stated in a generic manner, and any attempt to formalize them resorts to algorithms rather than equations. Algorithms are fundamentally different from equations in that they are discrete, rather than continuous, they occur in steps rather than istantaneously, and they can refer to themselves. A Science based on algorithms would be inherently different from a Science based on equations. Finally, Darwin’s paradigm is one that is rooted in the concept of organization and that ultimately aims at explaining organization. Indirectly, Darwin brought to the surface the elementary fact that the concept of organization is deeply rooted in the physical universe. Darwin’s treatise on the origin of species was indeed a treatise on the origin of order. There lies its monumental importance. Design Without a Designer Why do children grow up? Why aren't we born adults? Why do all living things (from organs to ecosystems) have to grow, rather than being born directly in their final configuration? Darwin's principle was that given a population and fairly elementary rules of how the population can evolve (mainly, natural selection), the population will evolve, and get better and better (adapted) over time. Whether natural selection is really the correct rule is secondary. The powerful idea was that the target object can be reached not by designing it and then building it, but by taking a primitive object and letting it evolve. The target object will not be built: it will emerge. Trees are not built, they grow. Societies are not built, they form over centuries. Most of the interesting things we observe in the world are not built, they developed slowly over time. How they happen to be the way they are depends to some extent on the advantages of being the way they are and to some extent on mere chance. When engineers build a bridge, they don't let chance play with the design and they don't assume that the bridge will grow by itself. They know exactly what the bridge is going to look like and they decide which day construction will be completed. They know the bridge is going to work because they can use mathematical formulas. Nature seems to use a different system, where things use chance to vary and variation leads to evolution because of the need for adaptation. By using this system, Nature seems to be able to obtain far bigger and more complex structures than humans can ever dream of building. It is ironic that, in the process, Nature uses much simpler mathematics. Engineers need to deal with derivatives and cosines. Nature's mathematics (i.e., the mathematics involved in genetic variation) is limited to arithmetics. Humans have developed a system that is much more complex than anything Nature has ever dreamed of using! It is stunning that such simple algorithms as used by Nature can produce the complexity of living organisms. Each algorithm can be reduced to even simpler steps. And still the repeated application of those steps eventually yields the complex order of life. http://www.thymos.com/tat/emergenc.html (2 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
The same theme occurs inside the brain. Neurons exchange simple messages, but the network of those messages over time can produce the very complex behavior of the human mind. Another simple algorithm that creates complexity. In both cases the algorithm is simple, but there is a catch. The algorithm is such that every time it ends it somehow remembers the result of its computation and will use it as the starting point for the next run. Species are selected out of the most recently selected species. Neural connections are modified out of the connections already established. Chaos and Complexity One of the themes straddling both biological and physical sciences is the quest for a mathematical model of phenomena of emergence (spontaneous creation of order), and in particular adaptation, and a physical justification of their dynamics (which seems to violate physical laws). The physicist Sadi Carnot, one of the founding fathers of Thermodynamics, realized that the statistical behavior of a complex system can be predicted if its parts were all identical and their interactions weak. At the beginning of the century, another French physicist, Henri Poincare`, realizing that the behavior of a complex system can become unpredictable if it consists of few parts that interact strongly, invented "chaos" theory. A system is said to exhibit the property of chaos if a slight change in the initial conditions results in large-scale differences in the result. Later, Bernard Derrida will show that a system goes through a transition from order to chaos if the strength of the interactions among its parts is gradually increased. But then very "disordered" systems spontaneously "crystallize" into a higher degree of order. First of all, the subject is "complexity", because a system must be complex enough for any property to "emerge" out of it. Complexity can be formally defined as nonlinearity. The world is mostly nonlinear. The science of nonlinear dynamics was originally christened "chaos theory" because from nonlinear equations unpredictable solutions emerge. A very useful abstraction to describe the evolution of a system in time is that of a "phase space". Our ordinary space has only three dimensions (width, height, depth) but in theory we can think of spaces with any number of dimensions. A useful abstraction is that of a space with six dimensions, three of which are the usual spatial dimentions. The other three are the components of velocity along those spatial dimensions. In ordinary 3-dimensional space, a "point" can only represent the position of a system. In 6dimensional phase space, a point represents both the position and the motion of the system. The evolution of a system is represented by some sort of shape in phase space. The shapes that chaotic systems produce in phase space are called "strange attractors" because the system will tend towards the kinds of state described by the points in the phase space that lie within them. The program then becomes that of applying the theory of nonlinear dynamic systems to Biology.
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Inevitably, this implies that the processes that govern human development are the same that act on the simplest organisms (and even some nonliving systems). They are processes of emergent order and complexity, of how structure arises from the interaction of many independent units. The same processes recurr at every level, from morphology to behavior. Darwin's vision of natural selection as a creator of order is probably not sufficient to explain all the spontaneous order exhibited by both living and dead matter. At every level of science (including the brain and life) the spontaneous emergence of order, or self-organization of complex systems, is a common theme. Koestler and Salthe have shown how complexity entails hierarchical organization. Von Bertalanffi's general systems theory, Haken's synergetics, and Prigogine's non-equilibrium Thermodynamics belong to the class of mathematical disciplines that are trying to extend Physics to dynamic systems. These theories have in common the fact that they deal with self-organization (how collections of parts can produce structures) and attempt at providing a unifying view of the universe at different levels of organization (from living organisms to physical systems to societies). Holarchies The Hungarian writer and philosopher Arthur Koestler first brought together a wealth of biological, physical, anthropological and philosophical notions to construct a unified theory of open hierarchical systems. Language has to do with a hierarchical process of spelling out implicit ideas in explicit terms by means of rules and feedbacks. Organisms and societies also exhibit the same hierarchical structure. In these hierarchies, each intermediary entity ("holon") functions as a self-contained whole relative to its subordinates and as one of the dependent parts of its superordinates. Each holon tends to persist and assert its pattern of activity. Wherever there is life, it must be hierarchically organized. Life exhibits an integrative property (that manifests itself as symbiosis) that enables the gradual construction of complex hierarchies out of simple holons. In nature there are no separated, indivisible, self-contained units. An "individual" is an oxymoron. An organism is a hierarchy of self-regulating holons (a "holarchy") that work in coordination with their environment. Holons at the higher levels of the hierarchy enjoy progressively more degrees of freedom and holons at the lower levels of the hierarchy have progressively less degrees of freedom. Moving up the hierarchy, we encounter more and more complex, flexible and creative patterns of activity. Moving down the hierarchy behavior becomes more and more mechanized. A hierarchical process is also involved in perception and memorization: it gradually reduces the percept to its fundamental elements. A dual hierarchical processis involved in recalling: it gradually reconstructs the percept. Hierarchical processes of the same nature can be found in the development of the embryo, in the evolution http://www.thymos.com/tat/emergenc.html (4 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
of species and in consciousness itself (which should be analyzed not in the context of the mind/body dichotomy but in the context of a multi-levelled hierarchy and of degrees of consciousness). They all share common themes: a tendency towards integration (a force that is inherent in the concept of hierarchic order, even if it seems to challenge the second law of Thermodynamics as it increases order), an openess at the top of the hierarchy (towards higher and higher levels of complexity) and the possibility of infinite regression. Hierarchies from Complexity Stanley Salthe, by combining the metaphysics of Justus Buchler and Michael Conrad's "statistical state model" of the evolutionary process, has developed what amounts to a theory of everything: an ontology of the world, a formal theory of hierarchies and a model of the evolution of the world. The world is viewed as a determinate machine of unlimited complexity. Within complexity, discontinuities arise. The basic structure of this world must allow for complexity that is spontaneously stable and that can be broken down in things divided by boundaries. The most natural way for the world to satisfy this requirement is to employ a hierarchical structure, which is also implied by Buchler's principle of ordinality: Nature (i.e., our representation of the world) is a hierarchy of entities existing at different levels of organization. Hierarchical structure turns out to be a consequence of complexity. Entities are defined by four criteria: boundaries, scale, integration, continuity. An entity has size, is limited by boundaries, and consists of an integrated system which varies continuously in time. Entities at different levels interact through mutual constraints, each constraint carrying information for the level it operates upon. A process can be described by a triad of contiguous levels: the one it occurs at, its context (what the philosopher Mario Bunge calls "environment") and its causes (Bunge's "structure"). In general, a lower level provides initiating conditions for a process and an upper level provides boundary conditions. Representing a dynamic system hierarchically requires a triadic structure. Aggregation occurs upon differentiation. Differentiation interpolates levels between the original two and the new entities aggregate in such a way that affects the structure of the upper levels: every time a new level emerges, the entire hierarchy must reorganize itself. Salthe also recalls a view of complexity due to the physicist Howard Hunt Pattee: complexity as the result of interactions between physical and symbolic systems. A physical system is dependent on the rates at which processes occur, whereas a symbolic system is not. Symbolic systems frequently serve as constraints applied to the operation of physical systems, and frequently appear as products of the activity of physical systems (e.g., the genome in a cell). A physical system can be said to be "complex" when a part of it functions as a symbolic system (as a representation, and therefore as an observer) for another part of it. These abstract principles can then be applied to organic evolution. Over time, Nature generates entities of gradually more limited scope and more precise form and behavior. This process populates the hierarchy of intermediate levels of organization as the hierarchy spontaneously reorganizes itself. The same model http://www.thymos.com/tat/emergenc.html (5 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
applies to all open systems, whether organisms or ecosystems or planets. By applying principles of complex systems to biological and social phenomena, Salthe attempts to reformulate Biology on development rather than on evolution. His approach is non-Darwinian to the extent that development, and not evolution, is the fundamental process in self-organization. Evolution is merely the result of a margin of error. His theory rests on a bold fusion of hierarchy theory, Information Theory and Semiotics. Salthe is looking for a grand theory of nature, which turns out to be essentially a theory of change, which turns out to be essentially a theory of emergence. General Systems Theory "General Systems Theory" was born before Cybernetics, and cybernetic systems are merely a special case of self-organizing systems; but General System Theory took longer to establish itself. It was conceived in the 1930s by the Austrian biologist Ludwig Von Bertalanffy. His ambition was to create a "universal science of organization". His legacy is to have started "system thinking", thinking about systems as systems and not as mere aggregates of parts. The classical approach to the scientific description of a system's behavior (whether in Physics or in Economics) can be summarized as the search for "isolable causal trains" and the reduction to atomic units. This approach is feasible under two conditions: 1. that the interaction among the parts of the system be negligible and 2. that the behavior of the parts be linear. Von Bertalanffy's "systems", on the other hand, are those entities (oe "organized complexities") that consist of interacting parts, usually described by a set of nonlinear differential equations. Systems Theory studies principles which apply to all systems, properties that apply to any entity qua system. Basic concepts of Systems Theory are, for example, the following: every whole is based upon the competition among its parts; individuality is the result of a never-ending process of progressive centralization whereby certain parts gain a dominant role over the others. General Systems Theory looks for laws that can be applied to a variety of fields (i.e., for an isomorphism of law in different fields), particularly in the biological, social and economic sciences (but even in history and politics). General Systems Theory mainly studies "wholes", which are characterized by such holistic properties as hierarchy, stability, teleology. "Open Systems Theory" is a subset of General Systems Theory. Because of the second law of Thermodynamics, a change in entropy in closed systems is always positive: order is continually destroyed. In open systems, on the other hand, entropy production due to irreversible processes is balanced by import of negative entropy (as in all living organisms). If an organism is viewed as an open system in a steady state, a theory of organismic processes can be worked out.
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Thinking About Thought: Consciousness, Life and Meaning
Furthermore, a living organism can be viewed as a hierarchical order of open systems, where each level maintains its structure thanks to continuous change of components at the next lower level. Living organisms maintain themselves in spite of continuous irreversible processes and even proceed towards higher and higher degrees of order. Ervin Laszlo's take at a "theory of natural systems" (i.e., a theory of the invariants of organized complexity) is centered around the concept of "ordered whole", whose structure is defined by a set of constraints. Laszlo adopts a variant of Ashby's principle of self-organization, according to which any isolated natural system subject to constant forces is inevitably inhabited by "organisms" that tend towards stationary or quasi-stationary non-equilibrium states. In Laszlo's view, the combination of internal constraints and external forces yields adaptive self-organization. Natural systems evolve towards increasingly adapted states, corresponding to increasing complexity (or negative entropy). Natural systems sharing an environment tend to organize in hierarchies. The set of such systems tends to become itself a system, its subsystems providing the constraints for the new system. Laszlo offered rigorous foundations to deal with the emergence of order at the atomic ("microcybernetics"), organismic ("bio-cybernetics") and social levels ("socio-cybernetics"). A systemic view also permits a formal analysis of a particular class of natural systems: cognitive systems. The mind, just like any other natural system, exhibits an holistic character, adaptive self-organization, and hierarchies, and can be studied with the same tools ("psycho-cybernetics"). Synergetics "Synergetics", as developed in Germany by the physicist Hermann Haken, is a theory of pattern formation in complex systems. It tries to explain structures that develop spontaneously in nature. Synergetics studies cooperative processes of the parts of a system far from equilibrium that lead to an ordered structure and behavior for the system. Haken's favorite example was the laser: how do the atoms of the laser agree to produce a single coherent wave flow? The answer is that the laser is a self-organizing system far from the equilibrium (what Prigogine would call a dissipative structure). A "synergetic" process in a physical system is one in which, when energy is pumped into the system, some macroscopic structure emerges from the disorderly behavior of the large number of microscopic particles that make up the physical system. As energy is pumped into the system, initially nothing seems to happen, other than additional excitation of the particles, but then the system reaches a threshold beyond which structure suddenly emerges. The laser is such a synergetic process: a beam of coherent light is created out of the chaotic movement of particles. What happens is that energy pushes the system of particles beyond a http://www.thymos.com/tat/emergenc.html (7 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
threshold, and suddenly the particles start behaving harmoniously.. Since order emerges out of chaos, and chaos is not well defined, synergetics employs probabilities (to describe uncertainty) and information (to describe approximation). Entropy becomes a central concept, relating Physics to Information Theory. Synergetics revolves around a number of technical concepts: compression of the degrees of freedom of a complex system into dynamic patterns that can be expressed as a collective variable; behavioral attractors of changing stabilities; and the appearance of new forms as non-equilibrium phase transitions. Synergetics applies to systems driven far from equilibrium, where the classic concepts of Thermodynamics are no longer adequate. It expresses the fact that order can arise from chaos and can be maintained by flows of energy/matter. Systems at instability points (at the "threshold") are driven by a "slaving principle": long-lasting quantities (the macroscopic pattern) can enslave short-lasting quantities (the chaotic particles), and they can force order on them (thereby becoming "order parameters"). The system exhibits a stable "mode", which is the chaotic motion of its particles, and an unstable "mode", which is its macroscopic structure and behavior of the whole system. Close to instability, stable modes are "enslaved" by unstable modes and can be ignored. Instead of having to deal with millions of chaotic particles, one can focus on the macroscopic quantities. De facto, the degrees of freedom of the system are reduced. Haken shows how one can write the dynamic equations for the system, and how such mathematical equations reflect the interplay between stochastic forces ("chance") and deterministic forces ("necessity"). Hypercycles The German chemist Manfred Eigen was awarded the Nobel Prize in 1967 for discovering that very short pulses of energy could trigger extremely fast chemical reactions. In the following years, he started looking for how very fast reactions could be used to create and sustain life. Indirectly, he ended up studying the behavior of biochemical systems far from equilibrium. Eventually, Eigen came up with the concept of an "hypercycle". A hypercycle is a cyclic reaction network, i.e. a cycle of cycles of cycles (of chemical reactions). Then he proved that life can be viewed as the product of a hierarchy of such hypercycles. A catalist is a substance that favors a chemical reaction. When enough energy is provided, some catalytic reactions tend to combine to form networks, and such networks may contain closed loops, called catalytic cycles.
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Thinking About Thought: Consciousness, Life and Meaning
If even more energy is pumped in, the system moves even farther from equilibrium, and then catalytic cycles tend ot combine to form closed loops of a higher level, or hypercycles, in which the enzymes produced by a cycle act as catalysts for the next cycle in the loop. Each link of the loop is now a catalytic cycle itself. Eigen showed that hypercycles are capable of self-replication, which may therefore have been a property of nature even before the invention of living organisms. Hypercycles are capable of evolution through more and more complex stages. Hypercycles compete for natural resources and are therefore subject to natural selection. The hypercycle falls short of being a living system because it defines no "boundary": the boundary is the container where the chemical reaction is occurring. A living system, on the other hand, has a boundary that is part of the living system (eg, the skin). Catalysis is the phenomenon by which a chemical reaction is sped up: without catalysis, all processes that give rise to life would take a lot longer, and probably would not be fast enough for life to happen. Then Eigen shows that they can be organized into an autocatalytic cycle, i.e. a cycle that is capable of selfreproducing: this is the fundamental requirement of life. A set of autocatalytic cycles gets, in turn, organized into a catalytic hypercycle. This catalytic hypercycle represents the basic form of life. Formally: "hypercycles" are a class of nonlinear reaction networks. They can originate spontaneously within the population of a species through natural selection and then evolve to higher complexity by allowing for the coherent evolution of a set of functionally coupled self-replicating entities. A hypercycle is based on nonlinear autocatalysis, which is a chain of reproduction cycles which are linked by cyclic catalysis, i.e. by another autocatalysis. A hypercycle is a cycle of cycles of cycles. A hypercycle can be viewed as the next higher level in the hierarchy of autocatalytic systems. Systems can be classified in four groups according to their stability with respect to fluctuations: stable systems (the fluctuations are self-regulating), indifferent systems (the fluctuations have no effect), unstable systems (self-amplification of the fluctuations) and variable systems (which can be in any of the previous states). Only the last type is suitable for generation of biological information because it can play all best tactics: indifference towards a broad mutant spectrum, stability towards selective advantages and instability towards unfavorable configurations. In other words, it can take the most efficient stance in the face of both favorable and adverse situations. Eigen’s model explains the simultaneous unity (due to the use of a universal genetic code) and diversity (due to the "trial and error" approach of natural selection) in evolution. This dual process started even before life was created. Evolution of species was preceded by an analogous stepwise process of molecular evolution. Whatever the mathematics, the bottom line is that natural selection itself turns out to be inevitable: given a set of self-reproducing entities that feed on a common and limited source of energetic/material supply, natural selection will spontaneously appear. Natural selection is a mathematical consequence of the http://www.thymos.com/tat/emergenc.html (9 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
dynamics of self-reproducing systems of this kind. Dissipative Systems By far, though, the most influential school of thought has been the one related to Ilya Prigogine's nonequilibrium Thermodynamics, which redefined the way scientists approach natural phenomena and brought self-organizing processes to the forefront of the study of complex systems. His theory found a stunning number and variety of fields of application, from Chemistry to Sociology. In his framework, the most difficult problems of Biology, from morphogenesis to evolution, found a natural model. Classical Physics describes the world as a static and reversible system that undergoes no evolution, whose information is constant in time. Classical Physics is the science of being. Thermodynamics, instead, describes an evolving world in which irreversible processes occurs. Thermodynamics is the science of becoming. The second law of Thermodynamics, in particular, describes the world as evolving from order to disorder, while biological evolution is about the complex emerging from the simple (i.e. order arising from disorder). While apparently contradictory, these two views show that irreversible processes are an essential part of the universe. Furthermore, conditions far from equilibrium foster phenomena such as life that classical Physics does not cover at all. Irreversible processes and non-equilibrium states turn out to be fundamental features of the real world. Prigogine distinguishes between "conservative" systems (which are governed by the three conservation laws for energy, translational momentum and angular momentum, and which give rise to reversible processes) and "dissipative" systems (subject to fluxes of energy and/or matter). The latter give rise to irreversible processes. The theme of science is order. Order can come either from equilibrium systems or from non-equilibrium systems that are sustained by a constant source (or, dually, by a persistent dissipation) of matter/energy. In the latter systems, order is generated by the flux of matter/energy. All living organisms (as well as systems such as the biosphere) are non-equilibrium systems. Prigogine proved that, under special circumstances, the distance from equilibrium and the nonlinearity of a system drive the system to ordered configurations, i.e. create order. The science of being and the science of becoming describe dual aspects of Nature. What is needed is a combination of factors that are exactly the ones found in living matter: a system made of a large collection of independent units which are interacting with each other, a flow of energy through the system that drives the system away from equilibrium, and nonlinearity. Nonlinearity expresses the fact that a perturbation of the system may reverberate and have disproportionate effects.
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Thinking About Thought: Consciousness, Life and Meaning
Non-equilibrium and nonlinearity favor the spontaneous development of self-organizing systems, which maintain their internal organization, regardless of the general increase in entropy, by expelling matter and energy in the environment. When such a system is driven away from equilibrium, local fluctuations appear. This means that in places the system gets very unstable. Localized tendencies to deviate from equilibrium are amplified. When a threshold of instability is reached, one of these runaway fluctuations is so amplified that it takes over as a macroscopic pattern. Order appears from disorder through what are initially small fluctuations within the system. Most fluctuations die along the way, but some survive the instability and carry the system beyond the threshold: those fluctuations "create" new form for the system. Fluctuations become sources of innovation and diversification. The potentialities of nonlinearity are dormant at equilibrium but are revelead by non-equilibrium: multiple solutions appear and therefore diversification of behavior becomes possible. Technically speaking, nonlinear systems driven away from equilibrium can generate instabilities that lead to bifurcations (and symmetry breaking beyond bifurcation). When the system reaches the bifurcation point, it is impossible to determine which path it will take next. Chance rules. Once the path is chosen, determinism resumes. The multiplicity of solutions in nonlinear systems can even be interpreted as a process of gradual "emancipation" from the environment. Most of Nature is made of such "dissipative" systems, of systems subject to fluxes of energy and/or matter. Dissipative systems conserve their identity thanks to the interaction with the external world. In dissipative structures, non-equilibrium becomes a source of order. These considerations apply very much to living organisms, which are prime examples of dissipative structures in non-equilibrium. Prigogine's theory explains how life can exist and evolution work towards higher and higher forms of life. A "minimum entropy principle" characterizes living organisms: stable nearequilibrium dissipative systems minimize their rate of entropy production. From non-equilibrium Thermodynamics a wealth of concepts has originated: invariant manifolds, attractors, fractals, stability, bifurcation analysis, normal forms, chaos, Lyapunov exponents, entropies. Catastrophe and chaos theories turn out to be merely special cases of nonlinear non-equilibrium systems. In concluding, self-organization is the spontaneous emergence of ordered structure and behavior in open systems that are in a state far from equilibrium described mathematically by nonlinear equations. Catastrophe Theory Rene' Thom's catastrophe theory, originally formulated in 1967 and popularized ten years later by the work of the British mathematician Erich Zeeman, became a widely used tool for classifying the solutions of nonlinear systems in the neighborhood of stability breakdown. http://www.thymos.com/tat/emergenc.html (11 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
In the beginning, Thom, a French mathematician, was interested in structural stability in topology (stability of topological form) and was convinced of the possibility of finding general laws of form evolution regardless of the underlying substance of form, as already stated at the beginning of the century by D'Arcy Thompson. Thom's goal was to explain the "succession of form". Our universe presents us with forms (that we can perceive and name). A form is defined, first and foremost, by its stability: a form lasts in space and time. Forms change. The history of the universe, insofar as we are concerned, is a ceaseless creation, destruction and transformation of form. Life itself is, ultimately, creation, growth and decaying of form. Every physical form is represented by a mathematical quantity called "attractor" in a space of internal variables. If the attractor satisfies the mathematical property of being "structurally stable", then the physical form is the stable form of an object. Changes in form, or morphogenesis, are due to the capture of the attractors of the old form by the attractors of the new form. All morphogenesis is due to the conflict between attractors. What catastrophe theory does is to "geometrize" the concept of "conflict". The universe of objects can be divided into domains of different attractors. Such domains are separated by shock waves. Shock wave surfaces are singularities called "catastrophes". A catastrophe is a state beyond which the system is detroyed in an irreversible manner. Technically speaking, the "ensembles de catastrophes" are hypersurfaces that divide the parameter space in regions of completely different dynamics. The bottom line is that dynamics and form become dual properties of nonlinear systems. This is a purely geometric theory of morphogenesis, His laws are independent of the substance, structure and internal forces of the system. Thom proves that in a 4-dimensional space there exist only 7 types of elementary catastrophes. Elementary catastrophes include: "fold", destruction of an attractor which is captured by a lesser potential; "cusp", bufurcation of an attractor into two attractors; etc. From these singularities, more and more complex catastrophes unfold, until the final catastrophe. Elementary catastrophes are "local accidents". The form of an object is due to the accumulation of many of these "accidents". The Origin of Regularity Prigogine's "bifurcation theory" is a descendent of the theory of stability initiated by the Russian mathematician Aleksander Lyapounov. Rene' Thom's catastrophe theory is particular case of bifurcation theory, so they all belong to the same family. They all elaborate on the same theorem, Lyapounov's theorem: for isolated systems, thermodynamic equilibrium is an attractor of nonequilibrium states. Then the story unfolds, leading to dissipative systems and eventually to the reversing of Thermodynamics' fundamental assumption, the destruction of structure. Order emerges from the very premises that seem to deny it. http://www.thymos.com/tat/emergenc.html (12 of 23)25/07/2003 14:36:48
Thinking About Thought: Consciousness, Life and Meaning
Jack Cohen and Ian Steward are among those who study how the regularities of nature (from Cosmology to Quantum Theory, from Biology to Cognitive Psychology) emerge from the underlying chaos and complexity of nature: "emergent simplicities collapse chaos". They proved that external constraints are fundamental in shaping biological systems (DNA does not uniquely determine an organism) and defined new concepts: "simplexity" (the tendency of simple rules to emerge from underlying disorder and complexity) and "complicity" (the tendency of interacting systems to coevolve leading to a growth of complexity). Simplexity is a "weak" form of emergence, and is ubiquitous. Complicity is a stronger form of emergence, and is responsible for consciousness and evolution. Emergence is the rule, not the exception, and it is shaped by simplexity and complicity. Emergent Computation Emergent computation is to standard computation what nonlinear systems are to linear systems: it deals with systems whose parts interact in a nontrivial way. Both Turing and Von Neumann, the two mathematicians who inspired the creation of the computer, were precursors in emergent computation: Turing formulated a theory of self-catalytic systems and Von Neumann studied self-replicating automata. Alan Turing (in the 1950's) advanced the reaction-diffusion theory of pattern formation, based on the bifurcation properties of the solutions of differential equations. Turing devised a model to generate stable patterns: ❍
X catalyzes itself: X diffuses slowly
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X catalyzes Y: Y diffuses quickly
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Y inhibits X
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Y may or may not catalyze or inhibit itself
Some reactions might be able to create ordered spatial schemes from disordered schemes. The function of genes is purely catalytic: they catalyze the production of new morphogenes, which will catalyze more morphogenes until eventually form emerges. Von Neumann saw life as a particular class of automata (of programmable machines). Life's main property is the ability to reproduce. Von Neumann proved that a machine can be programmed to make a copy of itself. Von Neumann's automaton was conceived to absorb matter from the environment and process it to build another automaton, including a description of itself. Von Neumann realized (years before the genetic code was discovered) that the machine needed a description of itself in order to reproduce. The description itself would be copied to make a new machine, so that the new machine too could copy itself. http://www.thymos.com/tat/emergenc.html (13 of 23)25/07/2003 14:36:48
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In Von Neumann's simulated world, a large checkerboard was a simplified version of the world, in which both space and time were discrete. Time, in particular, was made to advance in discrete steps, which meant that change could occur only at each step, and simultaneously for everything that had to change. Von Neumann's studies of the 1940s led to an entire new field of Mathematics, called "cellular automata". Technically speaking, cellular automata are discrete dynamical systems whose behavior is completely specified in terms of a local relation. In practice, cellular automata are the computer scientist's equivalent of the physicist's concept of field. Space is represented by a uniform grid and time advances in discrete steps. Each cell of space contains bits of information. Laws of nature express what operation must be performed on each cell's bits of information, based on its neighbor's bits of information. Laws of nature are local and uniform. The amazing thing is that such simple "organisms" can give rise to very complex structures, and those structures recur periodically, which means that they achieve some kind of stability. Von Neumann's idea of the dual genetics of self-reproducing automata (that the genetic code must act as instructions on how to build and organism and as data to be passed on to the offspring) was basically the idea behind what will be called DNA: DNA encodes the instructions for making all the enzymes and the protein that a cell needs to function and DNA makes a copy of itself every time the cell divides in two. Von Neumann indirectly understood other properties of life: the ability to increase its complexity (an organism can generate organisms that are more complex than itself) and the ability to self-organize. When a machine (e.g., an assembly line) builds another machine (e.g., an appliance), there occurs a degradation of complexity, whereas the offsprings of living organisms are at least as complex as their parents and their complexity increases in evolutionary times. A self-reproducing machine would be a machine that produces another machine of equal of higher complexity. By representing an organism as a group of contigous multi-state cells (either empty or containing a component) in a 2-dimensional matrix, Von Neumann proved that a Turing-type machine that can reproduce itself could be simulated by using a 29-state cell component. John Conway is the inventor of a game "Life", that is staged in Von Neumann’s checkerboard world (in which the state of a square changes depending on the adjacent squares). Conway proved that, given enough resources and time, self-reproducing patterns will occur. Turing proved that there exists a universal computing machine. Von Neumann proved that there exists a universal computing machine which, given a description of an automaton, will construct a copy of it, and, by extension, that there exists a universal computing machine which, given a description of a universal computing machine, will construct a copy of it, and, by extension, that there exists a universal computing machine which, given a description of itself, will construct a copy of itself. The two most futuristic topics addressed by Cybernetics were self-reproducing machines and selforganizing systems. They are pervasive in nature, and modern technologies make it possible to dream of building them artificially as well. Still, they remained merely speculative. The step that made emergent computation matter to the real world came from the computational application of the two pillars of the
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synthetic theory of evolution, namely the genetic code and adaptation. Genetic Algorithms The momentum for the computational study of genetic algorithms and adaptive systems was created in large part by John Holland's work. In the 1970s, the American computer scientist John Holland had the intuition that the best way to solve a problem is to mimick what biological organisms do to solve their problem of survival: to evolve (through natural selection) and to reproduce (through genetic recombination). Genetic algorithms apply recursively a series of biologically-inspired operators to a population of potential solutions of a given problem. Each application of operators generates new populations of solutions which should better and better approximate the best solution. What evolves is not the single individual but the population as a whole. Genetic algorithms are actually a further refinement of search methods within problem spaces. Genetic algorithms improve the search by incorporating the criterion of "competition". Recalling Newell and Simon's definition of problem solving as "searching in a problem space", David Goldberg defines genetic algorithms as "search algorithms based on the mechanics of natural selection and natural genetics". Unlike most optimization methods, that work from a single point in the decision space and employ a transition method to determine the next point, genetic algorithms work from an entire "population" of points simultaneously, trying many directions in parallel and employing a combination of several genetically-inspired methods to determine the next population of points. One can employ simple algorithms such as "reproduction" (that copies chromosomes according to a fitness function), "crossover" (that switches segments of two chromosomes) and "mutation", as well as more complex algorithms such as "dominance" (a genotype-to-phenotype mapping), "diploidy" (pairs of chromosomes), "abeyance" (shielded against overselection), "inversion" (the primary natural mechanism for recoding a problem, by switching two points of a chromosome); and so forth. Holland's classifier (which learns new rules to optimize its performance) was the first practical application of genetic algorithms. A classifier system is a machine learning system that learns syntactically rules (or "classifiers") to guide its performance in the environment. A classifier system consists of three main components: a production system, a credit system (such as the "bucket brigade") and a genetic algorithm to generate new rules. Its emphasis on competition and coopertation, on feedback and reinforcement, rather than on pre-programmed rules, set it apart from knowledge-based models of Artificial Intelligence. A measure function computes how "fit" an individual is. The selection process starts from a random population of individual. For each individual of the population the fitness function provides a numeric value for how much the solution is far from the ideal solution. The probability of selection for that individual is made proportional to its "fitness". On the basis of such fitness values a subset of the population is selected. This subset is allowed to reproduce itself through biologically-inspired operators of crossover, mutation and inversion. Each individual (each point in the space of solutions) is represented as a string of symbols. Each genetic http://www.thymos.com/tat/emergenc.html (15 of 23)25/07/2003 14:36:48
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operators perform an operation on the sequence or content of the symbols. When a message from the environment matches the antecedent of a rule, the message specified in the consequent of the rule is produced. Some messages produced by the rules cycle back into the classifier system, some generate action on the environment. A message is a string of characters from a specified alphabet. The rules are not written in the first-order predicate logic of expert systems, but in a language that lacks descriptive power and is limited to simple conjunctive expressions. Credit assignment is the process whereby the system evaluates the effectiveness of its rules. The "bucket brigade" algorithm assigns a strength (a maesure of its past usefulness) to each rule. Each rule then makes a bid (proportional to its strength and to its relevance to the current situation) and only the highest bidding rules are allowed to pass their messages on. The strengths of the rules are modified according to an economic analogy: every time a rule bids, its strength is reduced of the value of the bid while the strength of its "suppliers" (the rules that sent the messages matched by this bidder) are increased. The bidder strength will in turn increase if its consumers (the rules that receive its message) will become bidders. This leads to a chain of suppliers/consumers whose success ultimately depends on the success of the rules that act directly on the environment. Then the system replaces the least useful (weak) rules with newly generated rules that are based on the system's accumulated experience, i.e. by combining selected "building blocks" ("strong" rules) according to some genetic algorithms. Holland then went on to focus on "complex adaptive systems". Such systems are governed by principles of anticipation and feedback. Based on a model of the world, an adaptive system anticipates what is going to happen. Models are improved based on feedback from the environment. Complex adaptive system are ubiquitous in nature. They include brains, ecosystems and even economies. They share a number of features: each of these systems is a network of agents acting in parallel and interacting; behavior of the system arises from cooperation and competitiong among its agents; each of these systems has many levels of organization, with agents at each level serving as building blocks for agents at a higher level; such systems are capable of rearranging their structure based on their experience; they are capable of anticipating the future by means of innate models of the world; new opportunities for new types of agents are continously beeing created within the system. All complex adaptive systems share four properties (aggregation, nonlinearity, flowing, diversity) and three mechanisms (categorization by tagging, anticipation through internal models, decomposition in building blocks). Each adaptive agent can be represented by a framework consisting of a performance system (to describe the system's skills), a credit-assignment algorithm (to reward the fittest rules) and a rule-discovery algorithm (to generate plausible hypotheses). The Edge of Chaos
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A new theoretical breakthrough occurred when Chris Langton demonstrated that physical systems achieve the prerequisites for the emergence of computation (i.e., transmission, storage, modification) in the vicinity of a phase transition ("at the edge of chaos"). Specifically, information becomes an important factor in the dynamics of cellular automata in the vicinity of the phase transition between periodic and chaotic behavior, i.e. between order and chaos. The idea is that systems undergo transformations, and while they transform they constantly move from order to chaos and back. This transition is similar to the "phase transitions" undergone by a substance when it turns liquid or solid or fluid. When ice turns into water, the atoms have not changed, but the system as a whole has undergone a phase transition. Microscopically, this means that atoms are behaving in a different way. The transition of a system from chaos to order and back is similar in that the system is still made of the same parts, but they behave in a different way. The state between order and chaos (the "edge of chaos") is sometimes a very "informative" state, because the parts are not as rigidly assembled as in the case of order and, at the same time, they are not as loose as in the case of chaos. The system is stable enough to keep information and unstable enough to dissipate it. The system at the edge of chaos is both a storage and a broadcaster of information. At the edge of chaos, information can propagate over long distances without decaying appreciably, thereby allowing for long-range correlation in behavior: ordered configurations do not allow for information to propagate at all, and disordered configurations cause information to quickly decay into random noise. This conclusion is consistent with Von Neumann's findings. A fundamental connection therefore exists between computation and phase transition. The edge of chaos is where the system can perform computation, can metabolize, can adapt, can evolve. In a word: these systems can be alive. Basically, Langton proved that Physics can support life only in a very narrow boundary between chaos and order. In that locus it is possible to build artificial organisms that will settle into recurring patterns conductive to an orderly transmission of information. Langton also related phase transitions, computation and life, which means that he built a bridge between Thermodynamics, Information Theory and Biology. The edge of chaos is also the locus of Murray Gell-Man's speculations. Gell-Man, a physicist who was awarded the Nobel prize for theorizing about the quarks, thinks that biological evolution is a complex adaptive system that complies with the second law of Thermodynamics once the entire environment, and not only the single organism, is taken into account. Living organisms dwell "on the edge of chaos", as they exhibit order and chaos at the same time, and they must exhibit both in order to survive. Living organisms are complex adaptive systems that retrieve information from the world, find regularities, compress them into a schema to represent the world, predict the evolution of the world and prescribe behavior for themselves. The schema may undergo variants that http://www.thymos.com/tat/emergenc.html (17 of 23)25/07/2003 14:36:48
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compete with one another. Their competition is regulated by feedback from the real world under the form of selection pressure. Disorder is useful for the development of new behavior patterns that enable the organism to cope with a changing environment. Technically speaking, once complex adaptive systems establish themselves, they operate through a cycle that involves variable schemata, randomness, phenotypic consequences and feedback of selection pressures to the competition among schemata. Complex Systems The American biologist Stuart Kauffman is the prophet of "complex" systems. Kauffman's quest is for the fundamental force that counteracts the universal drift towards disorder required by the second law of Thermodynamics. His idea is that Darwin was only half right: systems do evolve under the pressure of natural selection, but their quest for order is helped by a property of our universe, the property that "complex" systems just tend to organize themselves. Darwin's story is about the power of chance: by chance life developed and then evolved. Kauffman's story is about destiny: life is the almost inevitable result of a process inherent in nature. Kauffman's first discovery was that cells behave like mathematical networks. In the early 1960s, Monod and others discovered that genes are assembled not in a long string of instructions but in "genetic circuits". Within the cell, there are regulatory genes whose job is to turn on or off other genes. Therefore genes are not simply instructions to be carried out one after the other, they realize a complex network of messages. A regulatory gene may trigger another regulatory gene that may trigger another gene… etc. Each gene is typically controlled by two to ten other genes. Turning on just one gene may trigger an avalanche of effects. The genetic program is not a sequence of instructions but rather a regulatory network that behaves like a self-organizing system. By using a computer simulation of a cell-like network, Kauffman proved that, in any organism, the number of cell types must be approximately the square root of the number of genes. He starts where Langton ended. His "candidate principle" states that organisms change their interactions in such a way to reach the boundary between order and chaos. For example, the Danish physicist Per Bak studied the pile of sand, whose collapse under the weight of a new grain is unpredictable: the pile self-organizes. No external force is shaping the pile of sand, it is the pile of sand that organizes itself. Further examples include any ecosystem (in which organisms live at the border between extinction and overpopulation), the price of a product (which is defined by supply and demand at the border of where nobody wants to buy it and where everybody wants to buy it). Evolution proceeds towards the edge of chaos. Systems on the boundary between order and chaos have the flexibility to adapt rapidly and http://www.thymos.com/tat/emergenc.html (18 of 23)25/07/2003 14:36:48
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successfully. Living organisms are a particular type of complex adaptive systems. Natural selection and selforganization complement each other: they create complex systems poised at the edge between order and chaos, which are fit to evolve in a complex environment. At all levels of organization, whether of living organisms or ecosystems, the target of selection is a type of adaptive system at the edge between chaos and order. Kauffman's mathematical model is based on the concept of "fitness landscapes" (originally introduced by Sewall Wright). A fitness landscape is a distribution of fitness values over the space of genotypes. Evolution is the traversing of a fitness landscape. Peaks represent optimal fitness. Populations wander driven by mutation, selection and drift across the landscape in their search for peaks. It turns out that the best strategy for reaching the peaks occurs at the phase transition between order and disorder, or, again, at the edge of chaos. The same model applies to other biological phenomena and even nonbiological phenomena, and may therefore represent a universal law of nature. Adaptive evolution can be represented as a local hill climbing search converging via fitter mutants toward some local or global optimum. Adaptive evolution occurs on rugged (multipeaked) fitness landscapes. The very structure of these landscapes implies that radiation and stasis are inherent features of adaptation. The Cambrian explosion and the Permian extinction (famous paradoxes of the fossil record) may be the natural consequences of inherent properties of rugged landscapes. Kauffman also noted how complex (nonlinear dynamic) systems which interact with the external world classify and know their world through their attractors. Kauffman's view of life can be summarized as follows: autocatalytic networks (networks that feed themselves) arise spontaneously; natural selection brings them to the edge of chaos; a genetic regulatory mechanism accounts for metabolism and growth; attractors lay the foundations for cognition. The requirements for order to emerge are far easier than traditionally assumed. The main theme of Kauffman's research is the ubiquitous trend towards self-organization. This trend causes the appearance of "emergent properties" in complex systems. One such property is life. There is order for free. Far from equilibrium, systems organize themselves. The way they organize themselves is such that it creates systems at higher levels, which in turn tend to organize themselves. Atoms organize in molecules that organize in autocatalytic sets that organize in living organisms that organize in ecosystems. The whole universe may be driven by a principle similar to autocatalysis. The universe may be nothing but a hierarchy of autocatalytic sets. Autonomous Systems http://www.thymos.com/tat/emergenc.html (19 of 23)25/07/2003 14:36:48
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The Chilean neurologist Francisco Varela has adapted Maturana's thought to the theory of autonomous systems, by merging the themes of autonomy of natural systems (i.e. internal regulation, as opposed to control) and their informational abilities (i.e., cognition) into the theme of a system possessing an identity and interacting with the rest of the world. The organization of a system is the set of relations that define it as a unity. The structure of a system is the set of relations among its components. The organization of a system is independent of the properties of its components. A machine can be realized by many sets of components and relations among them. Homeostatic systems are systems that keep the values of their variables within a small range of values, i.e. whose organization makes all feedback internal to them. An autopoietic system is a homeostatic system that continously generates its own organization (by continously producing components that are capable of reproducing the organization that created them). Autopoietic systems turn out to be autonomous, to have an identity, to be unities, and to compensate external perturbations with internal structural changes. Living systems are autopoietic systems in the physical space. The two main features of living systems follow from this: self-reproduction can only occur in autopoietic systems, and evolution is a direct consequence of self-reproduction. Every autonomous system is organizationally closed (they are defined as a unity by their organization). The structure constitutes the system and determines its behavior in the environment; therefore, information is a structural aspect, not a semantic one. There is no need for a representation of information. Information is "codependent". Mechanisms of information and mechanisms of identity are dual. The cognitive domain of an autonomous system is the domain of interaction that it can enter without loss of closure. An autonomous unit always exhibits two aspects: it specifies the distinction between self and notself, and deals with its environment in a cognitive fashion. The momentous conclusion that Varela reaches is that every autonomous system (ecosystems, societies, brains, conversations) is a "mind" (in the sense of cognitive processes). A Science of Prisms Alternatives to traditional science now abound. One is interesting because it starts with a completely different approach towards reality and it encompasses more than just matter. In the 1970's the American physicist Buckminster Fuller developed a visionary theory, also called "synergetics", that attacked traditional science at its very roots. "Synergy" is the behavior of a whole that cannot be explained by the parts taken separately. Synergetics, http://www.thymos.com/tat/emergenc.html (20 of 23)25/07/2003 14:36:48
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therefore, studies system in a holistic (rather than reductionistic) way. The way it does this, is by focusing on form rather than internal structure. Because of its emphasis on shape, Synergetics becomes a branch of Geometrics, the discipline of configurations (or patterns). Synergetics employs 60-degree coordination instead of the usual 90-degree coordination. The triangle (and tetrahedron) instead of the square (and the cube) is the fundamental geometric unit. Fuller's thought is inspired by one of his own inventions, the "geodesic" dome (1954), a structure that exploits a very efficient way of enclosing space and that gets stronger as it gets larger. The bottom line is that reality is not made of "things", but of angle and frequency events. All experience can be reduced to only angles and frequencies. Fuller finds "prisms" to be ubiquitous in nature and in culture. All systems contained in the universe are polyhedra, "universe" being the collection of all experiences of all individuals. Synergetics rediscovers, in an almost mystical way, most of traditional science, but mainly through topological considerations (with traditional topology extended to "omnitopology"). For example, Synergetics proves that the universe is finite and expanding, and that Planck's constant is a "cosmic relationship". The Emergence of a Science of Emergence Prigogine's non-equilibrium Thermodynamics, Haken's synergetics, Von Bertalanffi's general systems theory and Kauffman's complex adaptive systems all point to the same scenario: the origin of life from inorganic matter is due to emergent processes of self-organization. The same processes account for phenomena at different levels in the organization of the universe, and, in particular, for cognition. Cognition appears to be a general property of systems, not an exclusive of the human mind. A science of emergence, as an alternative to traditional, reductionist, science, could possibly explain all systems (living and not). Further Reading Buchler Justus: METAPHYSICS OF NATURAL COMPLEXES (Columbia University Press, 1966) Bunge Mario: TREATISE ON BASIC PHILOSOPHY (Reidel, 1974-83) Cohen Jack & Steward Ian: THE COLLAPSE OF CHAOS (Viking, 1994) Coveney Peter: FRONTIERS OF COMPLEXITY (Fawcett, 1995) Dalenoort G.J.: THE PARADIGM OF SELF-ORGANIZATION (Gordon & Breach, 1989)
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Dalenoort G.J.: THE PARADIGM OF SELF-ORGANIZATION II (Gordon & Breach, 1994) Davies Paul: GOD AND THE NEW PHYSICS (Penguin, 1982) Eigen Manfred & Schuster Peter: THE HYPERCYCLE (Springer Verlag, 1979) Forrest Stephanie: EMERGENT COMPUTATION (MIT Press, 1991) Fuller Richard Buckminster: SYNERGETICS: EXPLORATIONS IN THE GEOMETRY OF THINKING (Macmillan, 1975) Fuller Buckminster: COSMOGRAPHY ( Macmillan, 1992) Gell-Mann Murray: THE QUARK AND THE JAGUAR (W.H.Freeman, 1994) Gleick James: CHAOS (Viking, 1987) Goldberg David: GENETIC ALGORITHMS (Addison Wesley, 1989) Haken Hermann: SYNERGETICS (Springer-Verlag, 1977) Holland John: ADAPTATION IN NATURAL AND ARTIFICIAL SYSTEMS (Univ of Michigan Press, 1975) Holland John: HIDDEN ORDER (Addison Wesley, 1995) Kauffman Stuart: THE ORIGINS OF ORDER (Oxford University Press, 1993) Kauffman Stuart: AT HOME IN THE UNIVERSE (Oxford Univ Press, 1995) Koestler Arthur: THE GHOST IN THE MACHINE (Henry Regnery, 1967) Langton Christopher: ARTIFICIAL LIFE (Addison-Wesley, 1989) Laszlo Ervin: INTRODUCTION TO SYSTEMS PHILOSOPHY (Gordon & Breach, 1972) Lewin Roger: COMPLEXITY (Macmillan, 1992) Mandelbrot Benoit: THE FRACTAL GEOMETRY OF NATURE (W.H.Freeman, 1982) Nicolis Gregoire & Prigogine Ilya: SELF-ORGANIZATION IN NON-EQUILIBRIUM SYSTEMS (Wiley, 1977) Nicolis Gregoire & Prigogine Ilya: EXPLORING COMPLEXITY (W.H.Freeman, 1989)
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Nicolis Gregoire: INTRODUCTION TO NONLINEAR SCIENCE (Cambridge University Press, 1995) Pattee Howard Hunt: HIERARCHY THEORY (Braziller, 1973) Prigogine Ilya: INTRODUCTION TO THERMODYNAMICS OF IRREVERSIBLE PROCESSES (Interscience Publishers, 1961) Prigogine Ilya: NON-EQUILIBRIUM STATISTICAL MECHANICS (Interscience Publishers, 1962) Prigogine Ilya & Stengers Isabelle: ORDER OUT OF CHAOS (Bantham, 1984) Salthe Stanley: EVOLVING HIERARCHICAL SYSTEMS (Columbia University Press, 1985) Salthe Stanley: DEVELOPMENT AND EVOLUTION (MIT Press, 1993) Thom Rene': MATHEMATICAL MODELS OF MORPHOGENESIS (Horwood, 1983) Thom Rene': STRUCTURAL STABILITY AND MORPHOGENESIS (Benjamin, 1975) Toffoli Tommaso & Margolus Norman: CELLULAR AUTOMATA MACHINES (MIT Press, 1987) Turing Alan Mathison: MORPHOGENESIS (North-Holland, 1992) Varela Francisco: PRINCIPLES OF BIOLOGICAL AUTONOMY (North Holland, 1979) Von Bertalanffy Ludwig: GENERAL SYSTEMS THEORY (Braziller, 1968) Von Neumann John: THEORY OF SELF-REPRODUCING AUTOMATA (Princeton Univ Press, 1947) Waldrop Mitchell: COMPLEXITY (Simon & Schuster, 1992) Zeeman Erich Christian: CATASTROPHE THEORY (Addison-Wesley, 1977)
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Thinking About Thought Piero Scaruffi (Copyright © 1998-2001 Piero Scaruffi | Legal restrictions - Termini d'uso ) Inquire about purchasing the book | Annotated Bibliography | Class on Nature of Mind Traduzione in Italiano
The New Physics: The Ubiquitous Asymmetry (Galileo, Newton, Hamilton, Maxwell, Clausius, Carnot, Boltzmann, Poincare', Murray Gell-man, Prigogine, Einstein, Lorentz, Minkowski, Riemann, Planck, Broglie, Heisenberg, Schroedinger, Born, Casimir, Bohr, Bell, Bohm, Price, Von Neumann, Penrose, Lockwood, Deutsch, Hawking, Zurek, Anglin, Dirac, Wigner, Pauli, Weinberg, Kaluza, Schwarz, Gross, Witten, Montonen, Hooft, Freund, Kaku, Bondi, Davies, Milne, Feynman, Wheeler, Zeilinger, Schwarzschild, Godel, Kerr, Tipler, Thorne, Gold, Ricci, Weyl, Strominger, Bekenstein, Guth, Linde, Smolin, Mach) Physics and the Mind Today’s science, in particular Relativity and Quantum theories, present us with a world that is hardly the one we intuitively know. The reason is simply: Quantum and Relativity theories deal with the problems of the immensely large or the immensely small. Our brains were built to solve a different class of problems. They were built to deal with midsize, colored objects that move slowly in a three-dimensional space over a span of less than a century. The vast majority of theories of mind still assume that the world is a Newtonian world of objects, of continuous time, of absolute reality and of force-mediated causality. What that means is very simple: most theories of mind are based on a Physics that has been proven wrong. Newton's Physics does work in many cases, but today we know that it does not work in other cases. We don't know whether mind belongs to the set of cases for which Newton's Physics is a valid approximation of reality, or whether mind belongs to the set of cases for which Newton's Physics yields wrong predictions. Any theory of mind that is based on Newton's Physics is a gamble. For example, psychologists often like to separate the senses and feelings based on the intuitive fact that the senses gives us a photograph of the world, whereas pleasure and pain are the outcome of an interpretation of the world. When I see an object, I am transferring a piece of reality as it is inside my mind. When I feel pleasure, I am interpreting something and generating a feeling. This separation makes sense only if one assumes that objects do exist. Unfortunately, modern Physics has changed our perception of reality. What exists is a chaos of elementary particles, that our eyes "interpret" as object. A chair is no more real than a feeling of pain. They are both created by my http://www.thymos.com/tat/physics.html (1 of 68)25/07/2003 14:37:26
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mind. Actually, what exists is truly waves of probabilities, that somehow our brain reduces to objects. Modern Physics is not necessarily right (although Newton is necessarily wrong on several issues, otherwise Hiroshima would still be standing). But many theories of mind rely on a Physics that, de facto, is either Newton's or is a Physics that has not been invented yet. The Classical World: Utopia Since we started with the assumption that our Physics is inadequate to explain at least one natural phenomenon, consciousness, and therefore cannot be "right" (or, at least, complete), it is worth taking a quick look at what Physics has to say about the universe that our consciousness inhabits. Our view of the world we live in has undergone a dramatic change over the course of this century. Quantum Theory and Relativity Theory have changed the very essence of Physics, painting in front of us a completely different picture of how things happen and why they happen. Let’s first recapitulate the key concepts of classical Physics. Galileo laid them down in the Sixteenth century. First of all, a body in free motion does not need any force to continue moving. Second, if a force is applied, then what will change is the acceleration, not the velocity (velocity will change as a consequence of acceleration changing). Third, all bodies fall with the same acceleration. A century later, Newton expressed these findings in the elegant form of differential calculus and immersed them in the elegant setting of Euclid's geometry. Three fundamental laws explain all of nature (at least, all that was known of nature at the time). The first one states that the acceleration of a body due to a force is inversely proportional to the body’s "inertial" mass. The second one states that the gravitational attraction that a body is subject to is proportional to its "gravitational" mass. The third one indirectly states the conservation of energy: to every action there is always an equal reaction. They are mostly rehashing of Galileo’s ideas, but they state the exact mathematical relationships and assign numerical values to constants. They lent themselves to formal calculations because they were based on calculus and on geometry, both formal systems that allowed for exact deduction. By applying Newton’s laws, one can derive the dynamic equation that mathematically describes the motion of a system: given the position and velocity at one time, the equations can determine the position and velocity at any later time. Newton’s world was a deterministic machine, whose state at any time was a direct consequence of its state at a previous time. Two conservation laws were particularly effective in constraining the motion of systems: the conservation of momentum (momentum being velocity times mass) and the conservation of energy. No physical event can alter the overall value of, say, the energy: energy can change form, but ultimately it will always be there in the same amount. In the Nineteenth century, the Irish mathematician William Hamilton realized what Newton had only implied: that velocity, as well as position, determines the state of a system. He also realized that the key quantity is the overall energy of the system. By combining these intuitions, Hamilton redefined Newton’s dynamic equation with two equations that derived from just one quantity (the http://www.thymos.com/tat/physics.html (2 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
Hamiltonian function, a measure of the total energy of the system), that replaced acceleration (a second-order derivative) with the first-order derivative of velocity, and that were symmetrical (once velocity was replaced by momentum). The bottom line was that position and velocity played the same role and therefore the state of the system could be viewed as described by six coordinates, the three coordinates of position plus the three coordinates of momentum. At every point in time one could compute the set of six coordinates and the sequence of such sets would be the history of the system in the world. One could then visualize the evolution of the system in a six-dimensional space, the "phase" space. In the Ninetieth century two phenomena posed increasing problems for the Newtonian picture: gases and electromagnetism. Gases had been studied as collections of particles, but, a gas being made of many minuscule particles in very fast motion and in continuous interaction, this model soon revealed to be a gross approximation. The classical approach was quickly abandoned in favor of a stochastic approach, whereby what matters is the average behavior of a particle and all quantities that matter (from temperature to heat) are statistical quantities. In the meantime, growing evidence was accumulating that electric bodies radiated invisible waves of energy through space, thereby creating electromagnetic fields that could interact with each other, and that light itself was but a particular case of an electromagnetic field. In the 1860s the British physicist James Maxwell expressed the properties of electromagnetic fields in a set of equations. These equations resemble the Hamiltonian equations in that they deal with first-order derivatives of the electric and magnetic intensities. Given the distribution of electric and magnetic charges at a time, Maxwell’s equation can determine the distribution at any later time. The difference is that electric and magnetic intensities refer to waves, whereas position and momentum refer to particles. The number of coordinates needed to determine a wave is infinite, not six... By then, it was already clear that Science was faced with a dilemma, one which was bound to become the theme of the rest of the century: there are electromagnetic forces that hold together particles in objects and there are gravitational forces that hold together objects in the universe, and these two forces are both inverse square forces (the intensity of the force is inversely proportional to the square of the distance), but the two quantities they act upon (electric charge and mass) behave in a completely different way, thereby leading to two completely different descriptions of the universe. Another catch hidden in all of these equations was that the beautiful and imposing architecture of Physics could not distinguish the past from the future, something that is obvious to all of us. All of Physics' equations were symmetrical in time. There is nothing in Newton's laws, in Hamilton's laws, in Maxwell's laws or even in Einstein's laws that can discriminate past from future. Physics was reversible in time, something that goes against our perception of the absolute and (alas) irrevocable flow of time. The removal of consciousness In the process, something else had also happened, something of momentous importance, even if its consequences would not be appreciated for a few centuries. Rene` Descartes had introduced the
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"experimental method": science has to be based on experiments and proofs. Descartes started out by defining the domain of science. He distinguished between matter and mind, and decided that science had to occupy itself with matter. Therefore the scism was born that would influence the development of human knowledge for the next three centuries: science is the study of nature, and our consciousness does not belong to nature. Galileo improved Descartes' method by fostering the mathematical study of nature. Newton built on Galileo's foundations. Physics, in other words, had been forced to renounce consciousness and developed a sophisticated system of knowledge construction and verification which did not care about, and therefore did not apply to, consciousness. Scientists spoke of "nature" as if it included only inanimate, unconscious objects. No wonder that they ended up building a science that explains all known inanimate, unconscious phenomena, but not consciousness. Entropy: The Curse of Irreversibility The single biggest change in scientific thinking may have nothing to do with Relativity and Quantum theories: it may well be the discovery that some processes are not symmetric in time. Before the discovery of the second law of Thermodynamics, all laws were symmetric in time, and change could always be bi-directional. Any formula had an equal sign that meant one can switch the two sides at will. We could always replay the history of the universe backwards. Entropy changed all that. Entropy was "discovered" around 1850 by the German physicist Rudolf Clausius in the process of revising the laws proposed by the French engineer Sadi Carnot, that would become the foundations of Thermodynamics. The first law of Thermodynamics is basically the law of conservation of energy: energy can never be created or destroyed, it can only be transformed. The second law states that any transformation has an energetic cost: this "cost" of transforming energy Clausius called "entropy". Natural processes generate entropy. Entropy explains why heat flows spontaneously from hot to cold bodies, but the opposite never occurs: energy can be lost in entropy, not viceversa. Clausius summarized the situation like this: the energy of the universe is constant, the entropy of the universe is increasing. In the 1870s, the German physicist Ludwig von Boltzmann tried to deduce entropy from the motion of gas particles, i.e. from dynamic laws which are reversible in nature. Basically, Boltzman tried to prove that entropy (and therefore irreversibility) is an illusion, that matter at microscopic level is fundamentally reversible. Boltzmann ended up with a statistical definition of entropy to characterize the fact that many different microscopic states of a system result in the same macroscopic state: the entropy of a macrostate is the logarithm of the number of its microstates. It is not very intuitive how this definition of entropy relates to the original one, but it does. Basically, entropy's usefulness is that it turns out to be a measure of disorder in a system. The second law of Thermodynamics is an inequality: it states that entropy can never decrease. Indirectly, this law states that transformation processes cannot be run backward, cannot be "undone". Young people can age, but old people cannot rejuvenate. Buildings don't improve over the years, they decay. Scrambled eggs cannot be unscrambled and dissolved sugar cubes cannot be
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recomposed. The universe must evolve in the direction of higher and higher entropy. Some things are irreversible. The universe as a whole is proceeding towards its unavoidable fate: the "heat death", i.e. the state of maximum entropy, in which no heat flow is possible, which means that temperature is constant everywhere, which means that there is no energy available to produce more heat, which means that all energy in the universe is in the form of heat. (The only escape from the heat death would be if the energy in the universe were infinite). Scientists were (and still are) puzzled by the fact that irreversibility (the law of entropy) had been deduced from reversibility (basically, Newton's laws). Mechanical phenomena tend to be reversible in time, whereas thermodynamic phenomena tend to be irreversible in time. Since a thermodynamic phenomenon is made of many mechanical phenomena, the paradox is how can an irreversible process arise from many reversible processes? It is weird that irreversibility should arise from the behavior of molecules which, if taken individually, obey physical laws that are reversible. We can keep track of the motion of each single particle in a gas, and then undo it. But we cannot undo the macroscopic consequence of the motion of thousands of such particles in a gas. If one films the behavior of each particle of a gas as the gas moves from non-equilibrium to equilibrium, and then plays back the film backwards, the film is perfectly consistent with the laws of Mechanics. In practice, though, systems never spontaneously move from equilibrium to nonequilibrium: the film is perfectly feasible, but in practice it is never made. The only reason one could find was probabilistic, not mechanical: the probability of low-entropy macrostates is smaller, by definition, than the probability of high-entropy macrostates, so the universe tends to proceed towards higher entropy. And one can rephrase the same idea in terms of equilibrium: since equilibrium states are states that correspond to the maximum number of microstates, it is unlikely that a system moves to a state of non-equilibrium, likely that it moves to a state of equilibrium. The trick is that Boltzmann assumed that a gas (a discrete set of interacting molecules) can be considered as a continuum of points and, on top of that, that the particles can be considered independent of each other: if these arbitrary assumptions are dropped, no rigorous proof for the irreversibility of natural processes exists. The French mathematician Jules Henri Poincare', for example, proved just about the opposite: that every closed system must eventually revert in time to its initial state. Poincare' proved eternal recurrence where Thermodynamics had just proved eternal doom. Entropy is a measure of disorder, and information is found in disorder (the more microstates the more information, ergo the more disorder the more information), so ultimately entropy is also a measure of information. Later, several scientists interpreted entropy as a measure of ignorance about the microscopic state of http://www.thymos.com/tat/physics.html (5 of 68)25/07/2003 14:37:26
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a system, for example as a measure of the amount of information needed to specify it. Murray Gellman recently summarized these arguments when he gave his explanation for the drift of the universe towards disorder. The reason that nature prefers disorder over order is that there are many more states of disorder than of order, therefore it is more probable that the system ends up in a state of disorder. In other words, the probability of disorder is much higher than the probability of spontaneous order, and that's why disorder happens more often than disorder. It took the Belgian (but Russian-born) physicist and Nobel-prize winner Ilya Prigogine, in the 1970s, to provide a more credible explanation for the origin of irreversibility. He observed some inherent time asymmetry in chaotic processes at the microscopic level, which would cause entropy at the macroscopic level. He reached the intriguing conclusion that irreversibility originates from randomness which is inherent in nature. Equilibrium states are also states of minimum information (a few parameters are enough to identify the state, e.g. one temperature value for the whole gas at a uniform temperature). Information is negative entropy and this equivalence would play a key role in applying entropy beyond Physics. An Accelerated World Science has been long obsessed with acceleration. Galileo and Newton went down into history for managing to express that simple concept of acceleration. After them Physics assumed that an object is defined by its position, its velocity (i.e., the rate at which its position changes) and its acceleration (i.e., the rate at which its velocity changes). The question is: why stop there? Why we don't need the "ratio and object changes its acceleration" and so forth? Position is a space coordinate. Velocity is the first derivative with respect to time of a space coordinate. Acceleration is the second derivative with respect to time of a space coordinate. Why we only need two orders of derivative to identify an object, and not three or four or twenty-one? Because the main force we have to deal with is gravity, and it only causes acceleration. We don't know any force that causes a change of acceleration, therefore we are not interested in higher orders of derivatives. To be precise, forces are defined as things that cause acceleration, and only acceleration (as in Newton's famous equation "F=ma"). We don't even have a word for things that would cause a third derivative with respect to time of a space coordinate. As a matter of fact, Newton explained acceleration by introducing gravity. In a sense Newton found more than just a law of Physics, he explained a millenary obsession: the reason mankind had been so interested in acceleration is that there is a force called gravity that drives the whole world. If gravity did not exist, we would probably never have bothered to study it. Car manufacturers would just tell customers how long it takes for their car to reach such and such a speed. Acceleration would not even have a name. Relativity: The Primacy of Light The Special Theory of Relativity was born (in 1905) out of Albert Einstein’s belief that the laws of http://www.thymos.com/tat/physics.html (6 of 68)25/07/2003 14:37:26
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nature must be uniform, whether they describe the motion of bodies or the motion of electrons. Therefore, Newton’s equations for the dynamics of bodies and Maxwell’s equations for the dynamics of electromagnetic waves had to be unified in one set of equations. In addition, they must be the same in all frames of reference that are "inertial", i.e. whose relative speed is constant. Galileo had shown this to be true for Newton's mechanics, and Einstein wanted it to be true for Maxwell's electromagnetism as well. In order to do that, one must modify Newton’s equations, as the Dutch physicist Hendrik Lorentz had already pointed out in 1892. The implications of this unification are momentous. Relativity conceives all motions as "relative" to something. Newton's absolute motion, as the Moravian physicist Ernst Mach had pointed out over and over, is an oxymoron. Motion is always measured relative to something. Best case, one can single out a privileged frame of reference by using the stars as a meta-frame of reference. But even this privileged frame of reference (the "inertial" one) is still measured relative to something, i.e. to the stars. There is no frame of reference which is at rest, there is no "absolute" frame of reference. While this is what gave Relativity its name, much more "relativity" was hidden in the theory. In Relativity, space and time are simply different dimensions of the same space-time continuum (as stated in 1908 by the Russian mathematician Hermann Minkowski). Einstein had shown that the length of an object and the duration of an event are relative to the observer. This is equivalent to calculating a trajectory in a four-dimensional spacetime which is absolute. The spacetime is the same for all reference frames and what changes is the component of time and space that is visible from your perspective. All quantities are redefined in space-time and must have four dimensions. For example, energy is no longer a simple (mono-dimensional) value, and momentum is no longer a three-dimensional quantity: energy and momentum are one space-time quantity which has four dimensions. Which part of this quantity is energy and which part is momentum depends on the observer: different observers see different things depending on their state of motion, because, based on their state of motion, a four-dimensional quantity gets divided in different ways into an energy component and a momentum component. All quantities are decomposed into a time component and a space component, but how that occur depends on the observer’s state of motion. This phenomenon is similar to looking at a building from one perspective or another: what we perceive as depth, width or height, depends on where we are looking from. An observer situated somewhere else will have a different perspective and measure different depth, width and height. The same idea holds in space-time, except that now time is also one of the quantities that change with "perspective" and the motion of the observer (rather than her position) determines what the "perspective" is. This accounts for bizarre distortions of space and time: as speed increases, lengths contract and time slows down (the first to propose that lengths must contract was, in 1889, the Irish physicist George Fitzgerald, but he was thinking of a physical contraction of the object, and Lorentz endorsed it because it gave Maxwell's equations a particularly elegant form, whether the observer was at rest or in motion). This phenomenon is negligible at slow speeds, but becomes very visible at speeds close to the speed of light.
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A further implication is that "now" becomes a meaningless concept: one observer's "now" is not another observer's "now". Two events may be simultaneous for one observer, while they may occur at different times for another observer: again, their perspective in space-time determines what they see. Even the very concept of the flow of time is questionable. There appears to be a fixed space-time, and the past determines the future. Actually, there seems to be no difference between past and future: again, it is just a matter of perspective. Mass and energy are not exempted from "relativity". The mass and the energy of an object increase as the object speeds up. This principle violates the traditional principle of conservation, which held that nothing can be destroyed or created, but Einstein proved that mass and energy can transform into each other according to his famous formula (a particle at rest has an energy equal to its mass times the speed of light squared), and a very tiny piece of matter can release huge amounts of energy. Scientists were already familiar with a phenomenon in which mass seemed to disappear and correspondingly energy seemed to appear: radioactivity, discovered in 1896. But Einstein's conclusion that all matter is energy was far more reaching. Light has a privileged status in Relativity Theory. The reason is that the speed of light is always the same, no matter what. If one runs at the same speed of a train, one sees the train as standing still. On the contrary, if one could run at the speed of light, one would still see light moving at the speed of light. Most of Relativity's bizarre properties are actually consequences of this postulate. Einstein had to adopt Lorentz's transformations of coordinates, which leave the speed of light constant in all frames of reference, regardless of the speed it is moving at, but in order to achieve this result must postulate that moving bodies contract and moving clocks slow down by an amount that depends on their speed. If all this sounds unrealistic, remember that according to traditional Physics the bomb dropped on Hiroshima should have simply bounced, whereas according to Einstein’s Relativity it had to explode and generate a lot of energy. That bomb remains the most remarkable proof of Einstein’s Relativity. Nothing in Quantum Theory can match this kind of proof. Life On A World Line The speed of light is finite and one of Relativity’s fundamental principles is that nothing can travel faster than light. As a consequence, an object located in a specific point at a specific time will never be able to reach space-time areas of the universe that would require traveling faster than the light. The "light cone" of a space-time point is the set of all points that can be reached by all possible light rays passing through that point. Because the speed of light is finite, that four-dimensional region has the shape of a cone (if the axis for time is perpendicular to the axes for the three spatial dimensions). The light cone represents the potential future of the point: these are all the points that can be reached in the future traveling at the speed of light or slower. By projecting the cone backwards, one gets the light cone for the past. The actual past of the point is contained in the past light cone and the http://www.thymos.com/tat/physics.html (8 of 68)25/07/2003 14:37:26
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actual future of the point is contained in the future light cone. What is outside the two cones is unreachable to that point. And, viceversa, no event located outside the light cone can influence the future of that point. The "event horizon" of an observer is a space-time surface that divides spacetime into regions which can communicate with the observer and regions which cannot. The "world line" is the spatio-temporal path that an object is actually traveling through space-time. That line is always contained inside the light cone. Besides the traditional quantity of time, Relativity Theory introduces another type of time. "Proper" time is the space-time distance between two points on a world line, because that distance turns out to be the time experienced by an observer traveling along that world line. Relativity erased the concept of an absolute Time, but in doing so it established an even stronger type of determinism. It feels like our lives are rigidly determined and our task in this universe is simply to cruise on our world line. There is no provision in Relativity for free will. General Relativity: Gravity Talks Newton explained how gravity works, but not what it is. Einstein’s Relativity Theory is ultimately about the nature of gravitation, which is the force holding together the universe. Relativity explains gravitation in terms of curved space-time, i.e. in terms of geometry. The fundamental principle of this theory (the "principle of equivalence") is actually quite simple: any referential frame in free fall is equivalent to an inertial reference frame. That is because if you are in a free fall, you cannot perceive your own weight, i.e. gravity (gravity is canceled in a frame of reference which is free falling, just like the speed of an object is canceled in a frame of reference which is moving at the same speed). The laws of Special Relativity still apply. Einstein's principle of equivalence simply expresses the fact that gravitation and acceleration are equivalent. If you can't see what is going on, and all you can measure is the 9.8 m/sec2 acceleration of an object that you let fall, you can't decide whether you are standing still, and subject to Earth’s gravity, or you are accelerating in empty space. Al you observe is an acceleration of 9.8. If you are still, that's the acceleration you expect for any falling object. If you are in a rocket that is accelerating upwards at 9.8, that's the acceleration you expect for any falling object. Unless you can see, you cannot know which one it is. The effect is the same. Therefore, Einstein concluded, you can treat them as one: gravity and acceleration are equivalent. Since gravitation is natural motion, Einstein’s idea was to regard free falls as natural motions, as straight lines in space time. The only way to achieve this was to assume that the effect of a gravitational field is to produce a curvature of space-time: the straight line becomes a "geodesic", the shortest route between two points on a warped surface (if the surface is flat, then the geodesic is a straight line). Bodies not subject to forces other than a gravitational field move along geodesics of http://www.thymos.com/tat/physics.html (9 of 68)25/07/2003 14:37:26
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space-time. The curvature of space-time is measured by a "curvature tensor" originally introduced in 1854 by the German mathematician Bernhardt Riemann. The Riemann geometry comprises the classical Euclidean geometry as a special case, but it is much more general. Minkowsky's four-dimensional spacetime is characterized by a "metrics". A metrics is a 4x4 matrix, each row and column representing one of the dimensions. The metrics for Newton's spacetime has zeros everywhere except in the diagonal of the matrix. The diagonal has values 1,1,1 and -1. This means that Pitagora's theorem still works, and time is an added dimension. The zeros in the other positions of the matrix specify that the space is flat. When the ones and the zeros change, their values specify a curvature for spacetime. Euclidean geometry works only with the flat-space metrics. Riemann's geometry works with any combination of values, i.e. with any degree and type of curvature. A specific consequence of Riemann's geometry is that "force" becomes an effect of the geometry of space. A "force" is simply the manifestation of a distortion in the geometry of space. Wherever there is a distortion, a moving object feels a "force" affecting its motion. Riemann's geometry is based on the notion of a "metric (or curvature) tensor", that expresses the curvature of space. On a twodimensional surface each point is described by three numbers. In a four-dimensional world, it takes ten numbers at each point. This is the metric tensor. Euclid's geometry corresponds to one of the infinite possible metric tensors (the one that represents zero curvature). Not only space and time are relative, but space-time is warped. With his 1915 field equations, Einstein made the connection with the physical world: he related the curvature of space-time caused by an object to the energy and momentum of the object (precisely, the curvature tensor to the "energy-momentum tensor"). Einstein therefore introduced two innovative ideas: the first is that we should consider space and time together (three spatial dimensions and one time dimension), not as separate; the second is that what causes the warps in this space-time (i.e., what alters the metric from Euclid's geometry) is mass. A mass does not voluntarily cause gravitational effects: a mass first deforms space-time and that warping will affect the motion of other objects that will therefore be indirectly feeling the "gravitational force" of that mass. Summarizing: the dynamics of matter is determined by the geometry of space-time, and that geometry is in turn determined by the distribution of matter. Space-time acts like an intermediary device that relays the existence of matter to other matter. Incidentally, this implies that mass-less things are also affected by gravitation. This includes light itself: a light beam is bent by a gravitational field. Light beams follow geodesics, which may be bent by a space-time warp. Special Relativity asked the laws of nature be the same in all inertial frames; which implied that they had to be invariant with respect to the Lorentz transformations. As a consequence, Einstein had to http://www.thymos.com/tat/physics.html (10 of 68)25/07/2003 14:37:26
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accept that clocks slow down and bodies contract. With General Relativity he wanted laws of nature to be the same in all frames, inertial or not (his field equations basically removed the need for inertial frames). This implies that the laws of nature must be "covariant" (basically must have the same form) with respect to a generic transformation of coordinates. That turned out to imply a further erosion of the concept of Time: it turned out that clocks slow down just for being in the wrong place, i.e. in a gravitational field. While apparent paradoxes (such as the twins paradox) have been widely publicized, Relativity Theory has been amazingly accurate in its predictions and so far no serious blow has been dealt to its foundations. While ordinary people may be reluctant to think of curved spaces and time dilatations, all these phenomena have been corroborated over and over by countless experiments. Quantum Theory: The Wave Quantum Theory was the logical consequence of two discoveries. In 1900 the German physicist Max Planck solved the mystery of radiation emitted by heated objects: he realized that atoms can emit energy only in discrete amounts. Nature seemed to forbid exchanges of energy in between those discreet values. In 1913 the Danish physicist Niels Bohr solved another mystery, the structure of the atom: electrons turn around the nucleus and are permitted to occupy only some orbits. Again, Nature seemed to forbid existence in between orbits. The fundamental assumption of Quantum Theory is that any field of force manifests itself in the form of discrete particles (or "quanta"). Forces are manifestations of exchanges of discrete amounts of energy. For example, electromagnetic waves carry an energy which is an integer multiple of a fundamental constant, the "Planck constant". An implication, as outlined by the French physicist Louis de Broglie in 1923 (after Einstein had made the same assumption regarding light), is that waves and particles are dual aspects of the same phenomena: every particle behaves like a wave, and every wave can be associated to a particle. One can talk of energy and mass, or one can talk of frequency and wavelength. The two descriptions are equivalent, or, better, one complements the other. The character of this relationship was defined in 1925 by Werner Heisenberg in Germany and Erwin Schroedinger in Austria. Both devised equations that replaced the equations of Newton's physics, but both equations had unpleasant consequences: Heisenberg's equations implied that the result of a physical experiment depends on the order in which the calculations were performed, and Schroedinger's equations implied that each particle could only really be considered a wave. In 1926 Max Born realized the implications of the wave-particle duality: the wave associated to a particle turns out to be a wave of probabilities, in order to account for the alternative possibilities that open up for the future of a particle. The state of a particle is described by a "wave function" which summarizes (and superposes) all the alternatives and their probabilities. The wave function contains all the information there is about the particle (or, in general, about a system). It contains the answers to all the questions that can be asked about the particle.
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The reason this is a "wave" of probabilities and not just a set of probabilities is that the equation devised by Schroedinger to describe it is the equation of an electromagnetic wave. Schroedinger's equation describes how this wave function evolves in time, and is therefore the quantum equivalent of Hamilton's equations. The Schroedinger equation fixes, deterministically, the temporal development of the state of the universe. But at every point in time the wave function describes a set of possibilities, not just one actuality. The particle’s current state is actually to be thought of as a "superposition" of all those alternatives that are made possible by its wavelike behavior. A particle's current state is, therefore, a number of states: one can view the particle as being in all of those states at the same time. This is a direct consequence of a particle not being just a particle but being also a wave. As Born phrased it, the motion of particles follows the law of probabilities, but the probability itself follows the law of causality. In 1927 Bohr stated the ultimate paradox of the wave-particle duality: everything is both particle and wave, but one must choose whether to measure one or the other aspect of nature, and then stick to it. If you try to mix the two, you run into contradictions. Enter Uncertainty In classical Physics, a quantity (such as the position or the mass) is both an attribute of the state of the system and an observable (a quantity that can be measured by an observer). Quantum Theory makes a sharp distinction between states and observables. If the system is in a given state, an observable can assume a range of values (so called "eigenvalues"), each one with a given probability. The evolution over time of a system can be viewed as due (according to Heisenberg) to time evolution of the observables or (according to Schroedinger) to time evolution of the states An observer can measure at the same time only observables which are compatible. If the observables are not compatible, they stand in a relation of mutual indeterminacy: the more accurate a measurement of the one, the less accurate the measurement of the other. Position and momentum are, for example, incompatible. This is a direct consequence of the wave-particle dualism: only one of the two natures is "visible" at each time. One can choose which one to observe (whether the particle, that has a position, or the wave, that has a momentum), but cannot observe both aspects at the same time. Precisely, Heisenberg’s famous "uncertainty principle" states that there is a limit to the precision with which we can measure, at the same time, the momentum and the position of a particle. If one measures the momentum, then it cannot measure the position, and viceversa. This is actually a direct consequence of Einstein's equation that related the wavelength and the momentum (or the frequency and the energy) of a light wave: if coordinates (wavelength) and momentum are related, they are no longer independent quantities. Einstein never believed in this principle, but he was indirectly the one who discovered it.
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Thinking About Thought: Consciousness, Life and Meaning
The wave function contains the answers to all the questions that can be asked about a system, but not all those questions can be asked simultaneously. If they are asked simultaneously, the replies will not be precise. The degree of uncertainty is proportional to the Planck constant. This implies that there is a limit to how small a physical system can be, because, below a quantity proportional to the Planck constant and called "Planck length", the physical laws of Quantum Theory stop working altogether. The Planck scale (10^-33 cm, i.e. the shortest possible length, and 10^-43 sec, i.e. the time it takes for a light beam to cross the Planck length, i.e. the shortest possible time tick) is the scale at which spacetime is no longer a continuum but becomes a grid of events separated by the Planck distance. What happens within a single cell of the grid, is beyond the comprehension of Physics. As the American physicist John Wheeler suggested in the 1950s, even the very notions of space and time stop making sense in this "quantum foam". Planck and Heisenberg proved that at that scale, the vacuum of empty space is actually "full" of all sorts of subtle events, and in 1948 the Dutch physicist Hendrick Casimir even showed how this allpervading zero-point energy could be measured (so it is now known as "Casimir force"). This was the culmination of the eccentricities of Quantum Theory: that the vacuum was not empty. The world and the mind Realtivity Theory and Quantum Theory said something important about the mind. They were as much about mind as they were about matter, only in a more subtle way. Relativity Theory was not only about reality being "relative" to something. It was (first and foremost) about reality being beyond the reach of our senses. Einstein's underlying principle is that we don't always see the universe as it is. Newton's underlying principle was that we see the universe as it is. Newton's Physics is a description of how our mind perceives the universe. There are bodies, there is absolute time, etc. Einstein's Physics is a "guess" about what the universe really is, even if our mind cannot perceive it. Einstein's Physics implied that there may be aspects of the universe that our mind cannot perceive, and that we can guess only by analyzing the aspects that we can perceive. Quantum Theory was not only about reality being "quantisized". It was also about reality being beyond the reach of our mind. The single most distressing finding of Quantum Theory is that reality as we know it only occurs when somebody observes it. The electron is in a certain place only when somebody actually looks at it, otherwise the electron is, simultaneously, in several different places. We can analyze this finding with either of two stances. 1. Our mind has no limitations. It can perfectly perceive nature as it is. It observes only one value because that is what nature does: the multiple choices for a quantity's value http://www.thymos.com/tat/physics.html (13 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
collapse to just one value when that quantity is observed by an observer. 2. Our mind has limitations. The quantum collapse from many values to just one value is due to a limitation of our mind. Our mind cannot perceive nature as it is. It can only perceive one value for each quantity. The electron is in many places, but our mind cannot perceive a thing being in many places at the same time, so it "collapses" the electron into only one specific place at a time. This is just an effect due to the limitation of our mind. We are forced to "sample" reality because we can't handle all of it. After all, that's what all our senses do. They are bombarded all the time with data from the environment, and they only pick up some of those data. We don't perceive every single detail of what is going on around us, we are forced to be selective. The mind turns out to be a sense that also has limited capacity, although the limitation is of a different kind. Each item of reality (a position, a speed, etc) "has" many values. The reason we observe only one value is that our mind can't handle a universe in which quantities have more than one value. The conceptual revolution caused by Quantum Theory was somewhat deeper than the one caused by Relativity Theory. Reconciling Newton and Einstein is relatively easy: Newton's theory was not false, it was just a special case of Einstein's theory, the one in which the spacetime is Euclidean. Reconciling Newton and Quantum Theory is, on the other hand, impossible: Newton's theory is just false. It seems to work because insist to assume that such things as big objects truly exist. A theory of mind that does not take into account Relativity is a legitimate approximation, just like a theory of the Earth that does not take into account Relativity is a legitimate approximation. But no theory of mind can ignore Quantum Theory. The Power of Constants At this point we can note that all the revolutionary and controversial results of these new theories arose from the values of two constants. Quantum Mechanics was a direct consequence of Planck's constant: were that constact zero, there would be no uncertainty. Relativity Theory was a direct consequence of the speed of light being constant in all frames of reference: were the speed of light infinite, there would be no time dilatation and contraction of length. These two constants were determined, indirectly, by studying two minor phenomena that were still unsolved at the end of the century: the ether and the black body radiation. The presence of the ether could not be detected by measuring the speed of light through it; so Einstein assumed that the speed of light is always the same.
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Thinking About Thought: Consciousness, Life and Meaning
The black body does not radiate light with all possible values of energy but only with some values of energy, those that are integer multiples of a certain unit of energy; so Planck assumed that energy exchanges must only occur in discrete packets. These two universal constants alone revealed a whole new picture of our universe. Quantum Reality: Fuzzy or Incomplete? Many conflicting interpretations of Quantum Theory were offered from the beginning. Niels Bohr claimed that only phenomena (what appears to our senses, whether an object or the measurement of an instrument) are real, in the human sense of the word: particles that cannot be seen belong to a different kind of reality, which, circularly, cannot be perceived by humans; and the wave function is therefore not a real thing. Reality is unknowable because it is inherently indeterminate, and we humans do not live in a world of indeterminate things, we live in a world of phenomena (where "phenomena" presumably includes also houses and trees, the effect of those elementary processes). Werner Heisenberg, the man who discovered in 1925 the first complete theory of the quantum, believed that the world "is" made of possibility waves and not particles: particles are not real, they are merely "potentialities", something in between ideas and actualities. Our world, what we call "reality", is a sequence of collapses of wave of possibilities. The quantum world and our world are bridged by the "measurement". Reality arises from quantum discontinuities (or "quantum jumps"): classical evolution of the Schroedinger equation builds up "propensities", then quantum discontinuities (the collapse of the wave function) select one of those propensities. Every time this happens, reality changes. Therefore reality "is" the sequence of such quantum discontinuities. What turns the unknowable world of particles into human-perceivable "phenomena" is the observation: the moment we observe something, we create a phenomenon. As John Wheeler put it, "no phenomenon is a real phenomenon until it is an observed phenomenon". Furthermore, Heisenberg interpreted this reality as "knowledge'': the quantum state is a mathematical description of the state of the observer's knowledge rather than a description of the objective state of the physical system observed. The British physicist Paul Dirac, the man who in 1928 merged Quantum Physics and Special Relativity in Quantum Field Theory, pointed out that Quantum Physics is about our knowledge of a system. It does not describe reality but our knowledge of reality. A wave function represents our knowledge of a system before and experiment and the reduced wave function our more precise knowledge after the measurement. The indivisible universe
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Thinking About Thought: Consciousness, Life and Meaning
Albert Einstein was so unhappy with the uncertainty principle that he accepted Quantum Mechanics only as an incomplete description of the universe. He thought that Quantum Mechanics had neglected some "hidden variables". Once those hidden variables were found, we would have a complete theory without Quantum Theory’s oddities but with all of Quantum Theory’s results. Quantum Theory is a practical tool to calculate probabilities for sets of particles, but no prescription is provided for calculating quantities of individual particles. Einstein thought that there is an underlying reality where determinism rules and the behavior of the individual particle can be predicted. It is just that Quantum Mechanics is incomplete and has not found out that underlying reality yet. Einstein was particularly unhappy about the "nonlocality" of Quantum Physics, which he thought constituted a paradox. "Nonlocality" means "action at a distance". In Quantum Physics one can prove that, if they were once part of the same state, two particles will be always connected: once we measure the position of the first one, we istantaneously determine the position of the other one, even if, in the meantime, it has traveled to the other end of the universe. Since no information can travel faster than light, it is impossible for the second particle to react instantaneously to a measurement that occurs so far from it. The only possible explanation for this "paradox" was, to Einstein, that the second particle must have properties which are not described by Quantum Mechanics. Einstein thought that Quantum Physics provides a fuzzy picture of a sharp reality, whereas for Bohr it provides a compete picture of a fuzzy reality. Einstein was proven wrong in 1964 by the Irish physicist John u, whose theorem basically ruled out "local hidden variables", precisely the type that Einstein invoked. Bell's conclusion is that, on the contrary, there are objective, non-local connections in the universe. In other words, two particles, once they have interacted, will keep interacting forever (their wave functions get entangled forever). Einstein believed in the law of locality, i.e. that two objects can interact only if they touch each other or if their interaction is mediated by some other object; but Bell proved that the "wave" is enough to provide interaction. Two measurements can be related instantaneously even if they are located in regions too far apart for a light signal to travel between them. Non-locality, or inseparability, is a fact of nature. Since then, experiments have provided concrete examples of non-locality. This shattered another belief of classical Physics. Newton believed that objects interact through forces that somehow have to travel from one to the other. A cannonball has to travel from the cannon to the walls before the walls explode; and nothing else in the universe is affected. The sun attracts the earth into an orbit, but it doesn't have any effect on the other stars. These are "local" interactions. Einstein added that forces can only travel as fast as light. Therefore, the impact of a force o an object is delayed by the time it takes for the force to reach that object at a speed which cannot exceed the speed http://www.thymos.com/tat/physics.html (16 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
of light. "Locality" became a distance: there is only so much in the universe that can exert a force on me, because only so much of the universe can send its force to me during my lifetime. If I live 80 years, an event that occurs more than 80 light-years away from here will never cause any disturbance on my life. Bell proved that this is not the case, because Quantum Theory prescribes the existence of a non-local "force": once two waves have interacted, they are forever entangled. Note that Heiseinberg's "knowledge interpretation" never had a problem with nonlocality: obviously, a change in the observer's knowledge does change the observer's knowledge about the entire system, regardless of how "extended" in space the system is. For example, if I observed the two particles at the beginning, when they were in the same place, and noticed that one is black and the other one is white, and later I observe the white one, I will "know" that the other one is black even if the other one is lightyears away from me. Ontological interpretation The American physicist David Bohm believed in an "undivided whole" even before Bell's experiment. His idea was that the whole universe is entangled in one gigantic wave. One of Quantum Theory's most direct consequences is indeterminism: one cannot know at the same time the value of both the position and the momentum of a particle. One only knows a probability for each of the possible values, and the whole set of probabilities constitute the "wave" associated with the particle. Only when one does observe the particle, does one particular value occur; only then does the wave of probabilities "collapse" to one specific value. In 1952 Bohm presented his "ontological" interpretation of Quantum Theory, that almost resurrected determinism at the quantum level. Bohm’s bold assumption was that the quantum "wave" is a real wave, due to a real potential. Bohm assumed that the wave function does not represent just a set of probabilities: it represents an actual field. A particle is always accompanied by such a field. This field is a real field and acts upon particles the same way a classical potential does. (Bohm resurrected an interpretation of Quantum Theory that de Broglie had abandoned, the theory of an ordinary wave guiding an ordinary particle). The beauty of this assumption is that, with the introduction of this additional potential, something momentous happens to the equations of Quantum Mechanics: position and momentum of a particle are no longer incompatible, they can be measured precisely at the same time, and Heisenberg’s principle is defeated. The behavior of the particle in Bohm’s theory is determined by the particle's position http://www.thymos.com/tat/physics.html (17 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
and momentum, by whatever force is acting on it, and by the quantum potential. For Bohm, particles do exist and are always accompanied by a field. An electron is neither a particle nor a wave (field), it is a particle plus a wave (that cannot be separated). But Bohm's wave is not Born's wave: Born's wave is only a function of probabilities that helps compute the particle's position, whereas Bohm's wave is a real wave that guides the particle (therefore also referred to as the "pilot-wave"). Everything is both a particle and a wave, and is acted upon by both a classical potential and a quantum potential (the "pilot wave"). Basically, the wave-function provides an additional potential that, once inserted in the traditional Hamiltonian of classical Physics, yields a welldetermined trajectory for each particle (but since the initial position cannot be known, we still can't predict the path of a particle, only notice that there exists a well-determined path prescribed by nature). Bohm had found an interpretation of Quantum Theory in terms of particles with well-defined position and momentum. What Bohm had done with his assumption was, basically, to add some "hidden variables" (the quantum potential) to the equations, precisely what Einstein had suggested to restore determinism in Physics. The pilot-wave To explain the function of the quantum potential, Bohm introduced the notion of "active in-formation" (as in "give form", for example to a particle's movement). A particle is moved by whatever energy it has (for example, because a force is acting on it) but its movement is guided by the "in-formation" in the quantum field (in the "pilot-wave"). In Physics, a potential describes a field in terms of how, at each point in space, the particle located at that point will be affected by that field. In Newton's physics the effect of the classical potential on a particle is proportional to the magnitude of the field. Bohm thought that his quantum field, in particular, had to reflect whatever is going on in the environment, including the measuring apparatus. Therefore, the quantum potential depends only on the form, and not on the magnitude, of the quantum field. The "strength" of the quantum potential does not depend on the intensity of the wave but only on the form of the wave. Even a very weak quantum potential can affect the particle. Even a very distant event can affect the particle.
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Thinking About Thought: Consciousness, Life and Meaning
The previous interpretations of Quantum Theory were trying to reconcile the traditional, classical concept of "measurement" (somebody who watches a particle through a microscope) with a quantum concept of "system". Bohm dispensed with the classical notion of "measurement": one cannot separate the measuring instrument from the measured quantity, as they interact all the time. It is misleading to call this act "measurement". It is an interaction, just like any other interaction, and, as Heisenberg's principle states, the consequence of this interaction is not a measurement at all. Implicate order The field that Bohm introduced in the equations to fix Heisenberg’s indeterminism represents a "sub-quantum" reality. Bohm's quantum potential does not act within the 4-dimensional geometry of spacetime; it acts beyond it. In a sense, it defines a common pool of information, a way to connect everything together, just like dancers can use the music to move together in harmony. Bohm thought that this field must be fluctuating rapidly and what Quantum Theory observes is merely an average over time (just like Newton's physics reads a value for quantities that are actually due to the Brownian motion of many particles). Quantum physics deals with mean values of an underlying reality just like Newton's physics deals with mean values of thermodynamic quantities. At this "sub-quantum" level, quantum effects all but disappear: a particle’s position and momentum are well-determined. The mystery of the collapse of the wave function, of the discontinuity in the transition from the quantum world to the classical world, occurs only at the quantum level, whereas Bohm believes there is a deeper level at which the apparent discontinuity of the collapse disappears. After all, the study of "elementary" particles has shown that even elementary particles can be destroyed and created, which means that they are not the ultimate components of the universe, that there must be un underlying reality, or, in Bohm's terms, an underlying "flux". Bohm thought that the basic problem lied in an obsolete notion of "order". Thus, Bohm distinguished between the "explicate" order (the world of isolated spacetime thing-events that our senses experience) and the "implicate" order (all thing-events are part of a whole, the "holomovement"). The explicate order emerges from the
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Thinking About Thought: Consciousness, Life and Meaning
holomovement. The holomovement contains all instances of explicate order as potentialities. Cartesian order (the "grid" of space-time events) is appropriate for Newtonian physics in which the universe is divided in separate objects, but inadequate for Quantum and Relativity theories to reflect their idiosyncrasie and in particular the undivided wholeness of the universe that Bohm has been focusing on. Bohm's solution was to contrast the "explicate order" that we perceive and that Physics describes (the Cartesian order of isolated space-time thing-events) with the "implicate order", which is an underlying, hidden layer of relationships. The explicate order is but a manifestation of the implicate order. Space and time, for example, are "forms" of the explicate order that are derived from the implicate order. The implicate order is similar to the order within a hologram: the implicate order of a hologram gives rise to the explicate order of an image, but the implicate order is not simply a one-to-one representation of the image. In fact, each region of the hologram contains a representation of the entire image. The implicate order and the explicate order are fundamentally different. The main difference is that in the explicate order each point is separate from the others. In the intricate order, the whole universe is "enfolded" in everything, and everything is enfolded in the whole. In the explicate order "things" become (relatively) independent. In the implicate order, all thing-events are part of a whole, the "holomovement". The explicate order emerges from the holomovement. The holomovement contains all instances of explicate order as potentialities. Bohm suggested that the implicate order could be defined by the quantum potential, the field consisting of an infinite number of pilot waves. The overlapping of the waves generates the explicate order of particles and forces, and ultimately space and time. Since Bohm’s quantum field is affected by all particles (the pilotwave that guides all particles is affected by all particles), nonlocality is a feature of reality: a particle can depend strongly on distant features of the environment. Bohm's universe is one indivisible whole. Everything in the universe is entangled in everything else, and ultimately in the whole. It does not make sense to analyze
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particles of subsets of the world as independent and separate parts. Beyond locality Einstein's objection did not die there and is still very much alive, if nothing else because, ultimately, it can be read as an objection to the role that the observer plays in Quantum Theory. The American physicist Alwyn Scott has recently resuscitated Einstein's hypothesis. Scott argues in favor of an interpretation of Quantum Theory as an approximation to a not yet discovered nonlinear theory. The new theory must be nonlinear because it is the only way to remove Heisenberg's uncertainty principle, which descends from the linearity of Schroedinger's equation. Again inspired by Einstein, the Australian philosopher Huw Price thinks that backward causation (that future can influence the past), or advanced action, is a legitimate option. Price believes that our theories are time-asymmetric because we are conditioned by folk concepts of causality. Physical theories are built starting with the assumption that the future cannot influence the past, and therefore it is no surprise that they prescribe that the future cannot influence the past. If we remove our preconceptions about causality, then we can redraw Quantum Physics. Then it turns out that Einstein was right with his hypothesis of hidden variables, and that Quantum Physics provides an incomplete description of the universe. A complete Quantum Physics will not assign any critical role to the observer. In the 1980s the American physicist John Cramer has traveled the opposite route with his "transactional interpretation" of Quantum Theory, which aims at sending back the observer to the laboratory and removing her from the formalism. Cramer builds on "absorber theory" developed in the 1940s by John Wheeler and Richard Feynman. They described a radiative process as a "transaction" in which the emitter of the radiation and the absorber of the radiation exchange waves: the emitter sends a "retarded" wave to the absorber, and simultaneously the absorber sends an "advanced" wave to the emitter. Advanced waves are canceled and therefore cannot be detected. An observer perceives only that a retarded wave has traveled from the emitter to the absorber. "Advanced" waves are solutions of a wave equation which contain only the second time derivative. Advanced waves have "eigenvalues" of negative energy and frequency, and they propagate in the negative time direction. Advanced waves are basically the timereversed counterparts of normal (or retarded) waves. Both http://www.thymos.com/tat/physics.html (21 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
"advanced" and "retarded" waves are valid orthogonal solutions of the electromagnetic wave equation, but in conventional electrodynamics the advanced solutions are usually ignored as unnatural, because they violate the law of causality, and only "retarded" solutions are retained. Wheeler and Feynman proposed that the time symmetry in the wave equation reflects a property a nature, that both types of waves actually occur. In the Wheeler-Feynman absorber theory, any emission process makes advanced waves on an equal basis with ordinary "retarded" waves. Cramer has extended the idea and claims that any quantum event is a "handshake" executed through an exchange of advanced and retarded waves. The exchange of a quantum of energy between a present emitter and a future absorber occurs through a WheelerFeynman exchange of advanced and retarded waves. The emitter sends an "offer" wave to the absorber (forward in time). The absorber then returns a "confirmation" wave to the emitter (backwards in time). The transaction is then completed with an "handshake" across space-time, which leads to the transfer of energy from emitter to absorber. The transaction is explicitly non-local because the future is affecting the past. Einstein's paradox is solved without resorting to a knowledge-based interpretation. The discountinuity of time One of Newton's postulates was that "time flows equably". The biggest problem with Quantum Theory is how the observed world (the world we know, made of well-defined objects) emerges from the quantum world (a world of mere possibilities and uncertainties, thanks to Heisenberg’s principle). The Hungarian mathematician John Von Neumann (the same one who invented the computer) distinguished between processes of the first and second kinds that occur when one is analyzing the evolution of a system with Quantum Theory. First-kind processes occur in isolated systems, on which no measurements can be carried out, and they closely resemble classical, deterministic evolution of a physical system. Second-kind processes occur when a measurement is carried out and they are indeterministic (or at least probabilistic): when an observable is measured, the state of the system suddenly jumps to an unpredictable state (or "eigenstate") associated with the measured eigenvalue of the observable. Unlike classical Physics, in which the new state can
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Thinking About Thought: Consciousness, Life and Meaning
be determined from the prior state of the system, Quantum Theory can only specify the probabilities of moving into any of the observable’s eigenstates. In quantum lingo, a measurement causes a "collapse of the wave function", after which the observable assumes a specific value. A continuous process of the first kind gives rise to a discontinuous process of the second kind. Isolated systems obey to the Schroedinger equation, observed systems obey to Heisenberg's quantum jumps. Quantum Theory therefore implies that something turns a process of the first kind into a process of the second kind when it is observed. The problem is that Quantum Theory does not prescribe or describe when and how this happens. The flow of time is mysteriously altered by measurements: a system evolves in a smooth and deterministic fashion until a measurement is performed, then it jumps more or less randomly into an eigenstate of the measured observable, from where it resumes its smooth evolution until the next measurement. Time seems to behave in an awkwardly capricious way. As Bohr pointed out, a measurement also introduces irreversibility in nature: collapse cannot be undone. Once we measured a quantity, at that point in time a discontinuity is introduced in the evolution of the wave function. If, after a while, we proceeded backwards in time, we would reach the same point from the future with a wave function which could collapse in any of the legal ways, only one of which is the one that originated the future we are coming from. It is very unlikely that we would retrace the same past. The Measurement Problem According to Quantum Theory, our universe needs both kinds of processes. Von Neumann tried to figure out how they interact and realized that the answer lies in the "measurement" of the system. Reality seems to proceed on two parallel tracks. The Schroedinger equation determines (in a deterministic manner) the evolution of the state of the system, but that state is a set of possible states each with its own probability of happening. So long as nobody observes the system, the Schroedinger equation predicts future probabilities of the system. Then Heisenber's principle causes that wave function to "collapse" whenever the system is observed. The collapse causes the system to choose only one of the possible states. Once the observer has observed the system, only a part of the wave survives and evolves according to the Schroedinger equation. At this point the Schroedinger equation can http://www.thymos.com/tat/physics.html (23 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
calculate a new set of possible states. And so forth. The two views are both necessary to explain the evolution of the universe. They are not alternative views of the universe. One complements the other. Note that the observer does more than just observe something: the observer also decides "what" to observer. That decision has an effect on the state of the system, because it forces the system to choose among all the possible states. Nature's role is really only to choose one of those possible states, and Quantum Theory can only presume that this is done randomly. Von Neumann pointed out that measurement of a system consists in a process of interactions between the instrument and the system, whereby the states of the instrument become dependent on the states of the system. There is a chain of interactions that leads from the system to the observer’s consciousness. For example, a part of the instrument is linked to the system, another part of the instrument is linked to the previous part, and so forth until the interaction reaches the observer’s eye, then an interaction occurs between the eye and the brain and finally the chain arrives to the observer’s consciousness. Eventually, states of the observer’s consciousness are made dependent on states of the system, and the observer "knows" what the value of the observable is. Somewhere along this process the collapse has occurred, otherwise the end result of the chain would be that the observer’s consciousness would exhibit the same probabilistic behavior of the observable: if the observer reads one specific value on the instrument, it means that the wave of possibilities has collapsed (has chosen just that one specific value) somewhere between the system and the observer’s consciousness. At which point? What exactly causes the "collapse"? The instrument? The lense? The electrons inside the instrument? The observer's retina? The observer's nervous system? The observer's consciousness? What constitutes a valid observer? Does it have to be big? Does it have to be in the brain? Does it have to be conscious? Does it have to be human? Von Neumann showed mathematically that Quantum Theory is indifferent: it makes no difference to the statistical predictions of Quantum Theory where exactly this happens and what causes it. But humans are curious and would like to find out. In a sense, Von Neumann was trying to reconcile "objective being" and "subjective knowing". In classical Physics they are one and the same, but in Quantum Physics they are different, and it is not completely clear how subjective knowing relates to objective being. http://www.thymos.com/tat/physics.html (24 of 68)25/07/2003 14:37:26
Thinking About Thought: Consciousness, Life and Meaning
The Brain as a Measurement Device Quantum Theory is really about waves of possibilities. A particle is described by a wave function as being in many possible places at the same time. When the particle is observed, its wave function "collapses" with definite attributes, including the location it occupies, but such attributes cannot be foreseen until they actually collapse. In other words, the observer can only observe a quantum system after having interfered with it Von Neumann highlighted an inconsistence in the standard interpretation of Quantum Theory: the objects to be observed are treated as quantum objects (or waves), while the objects that observe (the instruments) are classical objects, with a shape, a position and no wave. The "measurer" is a natural object as much as the "measured", but we grant it immunity from Quantum Theory. Von Neumann objected to dividing the world into two parts that behaved differently. Quantum Theory inequivocally states that everything is a quantum system, no matter how small or big it is. On the other hand, if everything is a quantum system regulated by a wave of possibilities, what makes it collapse? Von Neumann was led again to postulate that something "different" from a quantum system has the power to cause such a collapse, and that something had to be human consciousness. Nothing in the world is real unless perceived by a mind, as the British philosopher Berkeley had argued centuries before Von Neumann. What if we built an instrument which is smaller than the system to be observed? What would be a quantum system: the smaller or the bigger, the measurer or the measured? The range of uncertainty of a particle is measured by Max Planck's constant. Because Planck's constant is so small, big objects have a well-defined position and shape and everything. The features of small objects such as particles are instead highly uncertain. Therefore, large objects are granted an immunity from quantum laws that is based only on their size. Consciousness creates reality John Wheeler believes that the collapse can be caused by anything that (aware or unaware) makes a "record" of the observation. An observer is anything in Nature that causes the observation to become public and irreversible. An observer could be a crystal. Recently, Roger Penrose, inspired by work done initiated by
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Thinking About Thought: Consciousness, Life and Meaning
Frenkel Karolyhazy in the 1960's, has invoked gravity to justify that special immunity: in the case of large objects, the spacetime curvature affects the system's wave function, causing it to collapse spontaneously into one of the possibilities. Precisely, Penrose believes that different space-time curvatures cannot overlap, because each curvature implies a metric and only one metric can be the metric of the universe at a certain point at a certain time. If two systems engage in some interaction, Nature must choose which metrics prevails. Therefore, he concludes, the coupling of a field with a gravitational field of some strength must cause the wave function of the system to collapse. This kind of self-collapse is called "objective" reduction to distinguish it from the traditional reductioin of Quantum Theory which is caused by environmental interaction (such as a measurement). Selfcollapse occurs to everything, but the mass of the system determines how quickly it occurs: large bodies self-collapse very quickly, elementary particles would not for millions or even billions of years. That is why the collapse of wavefunctions for elementary particles in practice occurs only when caused by environmental interaction. In practice, the collapse of the wave, which is the fundamental way in which Quantum Theory can relate to our perceptions, is still a puzzle, a mathematical accident that still has no definite explanation. It is not clear to anybody whether this "collapse" corresponds to an actual change in the state of the particle, or whether it just represents a change in the observer's amount of knowledge or what. It is not even clear if "observation" is the only operation that can cause the collapse. And whether it has to be "human" (as in "conscious") observation: does a cat collapse the wave of a particle? Does a rock? What attributes must an object possess to collapse a wave? Is it something that only humans have? If not, what is the smallest object that can collapse a wave? Can another particle collapse the wave of a particle? (In which case the problem wouldn't exist because each particle's wave would be collapsed by the surrounding particles). What is the measuring apparatus in Quantum Physics? Is it the platform that supports the experiment? Is it the pushing of a button? Is it a lens in the microscope? Is it the light beam that reaches the eye of the observer? Is it the eye of the observer? Is it the visual process in the mind? It is also a mystery how Nature knows which of the two systems is http://www.thymos.com/tat/physics.html (26 of 68)25/07/2003 14:37:26
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the measurement system and which one is the measured system: the one that collapses is the measured one, but the two systems are just systems, and it is not clear how Nature can discriminate the measuring one from the measured one and let only the latter collapse. If a wave collapses (i.e., a particle assumes well-defined attributes) only when observed by a conscious being, then Quantum Theory seems to specify a privileged role for the mind: the mind enters the world through the gap in Heisenberg's uncertainty principle. Indeed, the mind "must" exist for the universe to exist, otherwise nobody would be there to observe it and therefore the world would only be possibilities that never turn into actualities. Reality is just the content of consciousness, as the Hungarian physicist Eugene Wigner pointed out in 1961. Of course, mind must therefore be an entity that lies outside the realm of Quantum Theory and of Physics in general. The mind must be something special, that does not truly belong to "this" world. Wigner observed that Schroedinger’s equation is linear, but would stop being linear if its object were the very consciousness that collapses the wave. Therefore, Schroedinger’s equation would result in a non-linear algorithm that may justify the mind’s privileged status. If the collapse occurs only when observed by a conscious being, if the collapse occurs at the border between mind and matter, as Wigner believes, then the evolution of the universe changed after the appearance of human beings (there was no collapse anywhere before mind appeared). Undeterred by this objection, the American physicist John Archibald Wheeler believes that ours is a "participatory" universe, one in which consciousness participates in creating reality. The observer and the phenomenon are engaged in a creative act that yields reality. Consciousness does not create reality. Consciousness' role is extremely limited: it can't even choose which of the possibilities contained in the wave function will become reality. It can only "precipitate" reality out of many possibilities. Which possibility becomes reality is up to nature. Nonetheless, Wigner and Wheeler believe that consciousness is crucial to creating reality: as limited as its contribution is, without it there would be no reality, only possibilities. Wheeler even speculated that the rise of consciousness retroactively determined the history of the universe because it collapsed the mother of all waves that had never been collapsed before, thereby fixing every single event in the previous life of the universe.
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Quantum theoretical effects could be considered negligible if they only affected particles. Unfortunately, Erwin Schroedinger, with his famous cat experiment, established that Heisenberg's uncertainty affects big objects too. Basically, Schroedinger devised a situation in which a quantum phenomenon causes the cat to die or stay alive, but since any quantum phenomenon is uncertain the cat's life is also uncertain: until we look at the cat, the cat is neither alive nor dead, but simply a wave of possibilities itself. Since no Quantum Theory scientist has volunteered to take the cat's place in Schroedinger's experiment, we don't know for sure what would happen. (One can accuse quantum theorists of being charlatans, but not of being stupid). The Multiverse: The Quest for Certainty The traditional (or "Copenhagen") interpretation of Quantum Mechanics seems to be trapped in its unwavering faith in uncertainty. Others have looked for ways out of uncertainty. One possibility is to deny that the wave function collapses at all. Instead of admitting a random choice of one of many possibilities for the future, one can subscribe to all of the possibilities at the same time. In other words, the probabilistic nature of Quantum Mechanics allows the universe to unfold in an infinite number of ways. Hugh Everett's "many-universes" interpretation of Quantum Mechanics, originally put forward in 1957, states, basically, that if something physically can happen, it does: in some universe. Everett interpreted quantum "possibilities" as actualities. A particle "is" in many places at the same time: those places are in different universes. Physical reality consists of a collection of universes: the "multiverse". We exist in one copy for each universe and observe all possible outcomes of a situation. It is not only the universe that splits in many universes, it is also the observer that splits in many observers. For a particle there is no wave of possibilities: each possibility is an actuality in one universe. (Alternatively, one can say that there is one observer for each possible outcome of a measurement). Each measurement splits the universe in many universes (or, as Michael Lockwood puts it, each measurement splits the observer). Biographies form a branching structure, and one which depends on how often they are observed. No reduction/collapse occurs. The wave function evolves in a deterministic way, just like in Newton's physics.
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Naturally, the observer perceives exactly what I am perceiving: a flow of smooth changes. There is an alternative way to present Everett's ideas. Everett basically accepts that the Scroedinger equation is all there is. The world is described by that equation. We have to take it literally. The particle is in all the states that the equation prescribes. The trick is that the state of the observer is as superposed as that of the observed system. Therefore the observer sees all of the possible states of the observed system. This way the world does not split, but the mind of the observer does. Each mind observes only one state of the many that are possible according to the Schroedinger equation. Therefore each mind perceives a separate world, that is a subset of the world described by the Schroedinger equation. In a sense, each mind views the world from a subjective perspective. The objective state of the world is the one described by the equation, and it corresponds to the superposition of all the states observed by all the minds of the observer. The British physicist Stephen Hawking is even trying to write down the wave function of the universe, which will actually describe an infinite set of possible universes. Basically, he looks at the universe as if it were one big particle. Just like the wave function of a particle describes an infinite set of possible particles, the wave function of the universe actually describes an infinite set of possible universes. In Everett's multiverse, Quantum Theory is deterministic and the role of the observer is vastly reduced (we really don't need an observer anymore, since the wave collapses in every single universe, albeit in different ways). Quantum Theory looks more like classical theory, except for the multiplication of universes. The immanent manyverse Because of the apparent approximation of any quantum theory description of a phenomenon, the Israeli physicist David Deutsch also thinks that our universe cannot possibly constitute the whole of reality, it can only be part of a "multiverse" of parallel universes. But Deutsch's multiverse is not a mere collection of parallel universes, with a single flow of time. He highlights the contradiction of assuming an external, superior time in which all spacetimes flow. This is still a classical view of the world. Deutsch's manyverse is instead a collection of moments. There is no such a thing as the "flow of time". Each "moment" is a universe of the manyverse. Each moment exists forever, it does not flow from a previous moment to a following one. Time does not flow http://www.thymos.com/tat/physics.html (29 of 68)25/07/2003 14:37:26
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because time is simply a collection of universes. We exist in multiple versions, in universes called "moments". Each version of us is indirectly aware of the others because the various universes are linked together by the same physical laws, and causality provides a convenient ordering. But causality is not deterministic in the classical way: it is more like predicting than like causing. If we analyze the pieces of a jigsaw puzzle, we can predict where some of the missing pieces fall. But it would be misleading to say that our analysis of the puzzle "caused" those pieces to be where they are, although it is true that they position is "determined" by the other pieces being where they are. Furthermore, Deutsch claims that Quantum Theory is not enough to understand reality. He does not adhere to the dominant philosophical stance, that to understand a system is to understand its parts and to have a theory of that system is to have a set of predictions of its future behavior. Deutsch things that the predictions are merely the tools to verify if the theory is correct, but what really matters is the "explanation" that the theory provides. Scientific knowledge consists of explanations, not of facts or of predictions of facts. And, contrary to the dominant "reductionist" approach, an explanation that reduces large-scale events to the movement of the smallest possible constituents of matter is not an explanation. As he puts it, why is a specific atom of copper on the nose of the statue of Churchill? Not because the dynamic equations of the universe predict this and that, and not because of the story of that particle, but because Churchill was a famous person, and famous people are rewarded with statues, and statues are built of bronze, and bronze is made of copper. Scientists who adhere to the reductionist stance believe that the rules governing elementary particles (the base of the reductionist hierarchy) explain everything but they do not provide the kind of answer that we would call "explanation". So we need four strands of science to undestand reality: a theory of matter (quantum theory), a theory of evolution, a theory of knowledge (epistemology), and a theory of computation. The combined theory provides the "explanations" that Deutsch is interested in. Einselection: Darwinian Collapse One man who has been studying the problem of how classical Physics emerges from Quantum Physics (how objects that behave deterministically emerge from particles that behave http://www.thymos.com/tat/physics.html (30 of 68)25/07/2003 14:37:26
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probabilistically, how coherent states of Quantum Mechanics become classical ones) is the Polish-born Wojciech Zurek. He does not believe that consciousness has anything to do with it: it is rather the environment which determines the emergence of reality. Since 1991, experiments have been performed to show the progressive evolution of a system from quantum to classical behavior. The goal is to observe the progressive collapse of the wave function, the progressive disappearance of quantum weirdness, and the progressive emergence of reality from probability. Zucker (1984) has proposed a different twist to the debate on the "collapse of the wave". It doesn't necessarily take an observer. Zucker thinks that the environment destroys quantum "coherence" (superposition). The environment includes anything that may interact with the quantum system, from a single photon to a microscope. The environment causes "decoherence" (the choice of one or some of the possible outcomes) and decoherence causes selection (or "einselection") of which possibilities will become reality. The "best fit" states turn out to be the classical states. Systems collapse to classical states because classical states are the ones that best "fit" the environment. The environment causes the collapse of the wave just like an observer. Decoherence occurs to any system that interacts with other systems. Large objects are classical and not quantum objects because they are inherently "decohered" by being a collection of interacting parts. Small objects are isolated to some extent and therefore exhibit quantum behavior. In America, James Anglin, a close associate of Zurek, is studying the evolution of "open quantum systems" far from equilibrium, which resemble Prigogine's studies on open classical systems. This line of research is, indirectly, establishing intriguing similarities between the emergence of classical systems from quantum systems and the emergence of living systems from nonliving systems. Qubits In the 1990s another interpretation of quantum mechanics has been put forth by the Austrian physicist Anton Zeilinger. He set out to find a fundamental principle that would explain the three odd features of the quantum world:
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quantization (all fundamental physical quantities come in discrete amounts),
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randomness (we can only know the probability of an event) and
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entanglement (everything is connected, no matter how far objects are). He proposed a very simple principle: each elementary system, called "qubit" (e.g., the spin of the electron), carries one and only one bit of information; two systems carry two and only two bits of information; and so forth. After all, our physical description of the world is represented by propositions, and each proposition can be true or false, i.e. each elementary system carries one and only one bit of information. The consequences of this principle are simple to derive:
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I can't know two things about an electron, but only one at the time (uncertainty), everything has to be quantized because the unit of information is the bit (yes/no, or one/zero);
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Two systems carry exactly two bits of information, which means that they are entangled forever (if one changes, the other one has to change too in order to still yield two bits of information).
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Schroedinger's equation can be derived as the description of motion in a three-dimensional information space. Zeilinger's interpretation is therefore that only information truly exists and that quantum mechanics is simply a theory of how information behaves in this world. The Physics of Elementary Particles: Close Encounters with Matter Quantum Theory redrew the picture of nature and started a race to discover the ultimate constituents of matter. This program culminated in formulation of the theories of Quantum Electrodynamics (virtually invented by the British physicist Paul Dirac in 1928 when he published his equation for the electron in an electromagnetic field, which combined Quantum Mechanics and Special Relativity) and Quantum Chromodynamics (virtually invented by the America physicist Murray Gell-Man in 1963 when he hypothesized the breakdown of the nucleus into quarks).
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It follows from Dirac’s equation that for every particle there is a corresponding anti-particle which has the same mass and opposite electric charge, and, generally speaking, behaves like the particle moving backwards in space and time. Forces are mediated by discrete packets of energy, commonly represented as virtual particles or "quanta". The quantum of the electromagnetic field (e.g., of light) is the photon: any electromagnetic phenomenon involves the exchange of a number of photons between the particles taking part in it. Photons exchange energy in units of the Planck constant, a very small value, but nonetheless a discrete value. Other forces are defined by other quanta: the weak force by the W particle, gravitation by the graviton and the nuclear force by gluons. Particles can, first of all, be divided according to a principle first formulated (in 1925) by the Austrian physicist Wolfgang Pauli: some particles (the "fermions", named after the Italian physicist Enrico Fermi) never occupy the same state at the same time, whereas other particles (the "bosons", named after the Indian physicist Satyendra Bose) do. The wave functions of two fermions can never completely overlap, whereas the wave fuctions of two bosons can completely overlap (the bosons basically lose their identity and become one). (Technically, "boson" is the general name for any particle with an angular momentum, or spin, of an integer number, whereas "fermion" is the general name for any particle with a odd half quantum unit of spin). It turns out (not too surprisingly) that fermions (such as electrons, protons, neutrons) make up the matter of the universe, while bosons (photons, gravitons, gluons) are the virtual particles that glue the fermions together. Bosons therefore represent the forces that act on fermions. They are the quanta of interaction. An interaction is always implemented via the exchange of bosons between fermions. (There exist particles that are bosons but do not represent interactions, the so called "mesons". Mesons decay very rapidly. No stable meson is known). Three forces that act on elementary particles have been identified: the electromagnetic, the "weak" and the "strong" forces. Correspondingly, there are bosons that are weak (W and Z
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particles), strong (the gluons) and electromagnetic (the photon). Fermions can be classified in several ways. First of all, the neutron and the proton (the particles that made up the nuclei of atoms) are not elementary: they are made of 18 quarks (6 quarks, each of one comes in three "colors"). Then there are twelve leptons: the electron, the muon, the tau, their three neutrinos and their six anti-particles. A better way to organize Fermions is to divide them in six families, each led by two leptons: the electron goes with the electron's neutrino, the down quark and the up quark. This family makes up most of the matter we know. Another family of Fermions is led by the muon and contains its neutrino and contains two more quarks. The third family contains the tau particle, its neutrino and two more quarks (bottom and top). Particles made of quarks are called "hadrons" and comprise "baryons" (made of three quarks, and therefore fermions, such as the proton and the neutron) and "mesons" (made of one quark and one antiquark, and therefore bosons). The electromagnetic force between leptons is generated by the virtual exchange of massless particles called "photons". The weak force is due to the W and Z particles (there are two W particles). The "strong" force between quarks (the one that creates protons and neutrons) is generated by the virtual exchange of "gluons". Quarks come in "six" flavors and three "colors". Gluons are sensitive to color, not to flavor. The strong force between protons and neutrons is a direct consequence of the color force. Leptons do not have color, but have flavor (for example, the electron and its neutrino have different flavors). The "weak" force is actually the flavor force between leptons. W+ and W- are the quanta of this flavor force. This model explains what we know of matter. It does not explain why there are 4 forces, 18 quarks, six leptons, etc. The numbers seem to be arbitrary. In particular, it does not explain why particles have the masses they have. A field (called the Higgs field) is supposed to permeate the universe and the mass of a particle is supposed to be a measure of the intensity of its interaction with the Higgs field. Unification: In Search of Symmetry Since the electric charge also varies with flavor, it can be considered a flavor force as well. Along these lines, in 1967
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Steven Weinberg and Abdus Salam unified the weak and the electromagnetic forces into one flavor force (incidentally founding "Quantum Flavor Dynamics", the analogous of "Quantum Chromodynamics"), and discovered a third flavor force, mediated by the Z quanta. The unified flavor force therefore admits four quanta: the photon, the W- boson, the W+ boson and the Z boson. These quanta behave like the duals of gluons: they are sensitive to flavor, not to color. All quanta are described by the so called "Yang-Mills field", which is a generalization of the Maxwell field (Maxwell's theory becomes a particular case of Quantum Flavor Dynamics: "Quantum Electrodynamics"). Therefore, the world is made of six leptons, six quarks, four bosons for leptons and eight gluons for quarks. Alternatively, leptons and quarks can also be combined in three families of fermions: one comprising the electron, its neutrino and two flavors of quarks ("up" and "down"); one comprising the muon, its neutrino and two flavors of quarks ("strange" and "charmed"); and one comprising the tauon, its neutrino and two flavors of quarks ("bottom" and "top"). Plus the three corresponding families of anti-particles. Eight particles per family (each flavor of quark counts as three particles). The grand total is 48 fermions. The bosons are twelve: eight gluons, the photon and the three bosons for the weak interaction. Sixty particles overall. The profusion of particles is simply comic. Quantum Mechanics has always led to this consequence: in order to explain matter, a multitude of hitherto unknown entities is first postulated and then "observed" (actually, verified consistent with the theory). More and more entities are necessary to explain all phenomena that occur in the laboratory. When the theory becomes a self-parody, a new scheme is proposed whereby those entities can be decomposed in smaller units. So physicists are already, silently, seeking evidence that leptons and quarks are not really elementary, but made of a smaller number of particles. It is easy to predict that they will eventually break the quark and the electron, and start all over again. Several other characteristics look bizarre. For example, the three families of fermions are very similar: what need did Nature have to create three almost identical families of particles? The spins of these particles is totally arbitrary. Fermions have spin 1/2 and bosons have integral spin. Why? The whole set of equations for these particles has 19 arbitrary http://www.thymos.com/tat/physics.html (35 of 68)25/07/2003 14:37:26
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constants. Why? Gluons are fundamentally different from photons: photons are intermediaries of the electromagnetic force but do not themselves carry an electric charge, whereas gluons are intermediaries of the color force that do carry themselves a color (and therefore interact among themselves). Why? Also, because color comes in three varieties, there are many gluons, while there is only one photon. As a result, the color force behaves in a fundamentally different way from the electromagnetic force. In particular, it extends to infinite. That confines quarks inside protons and neutrons. Why? Also, the symmetry of the electroweak force (whereby the photon and the bosons get transformed among themselves) is not exact as in the case of Relativity (where time and space coordinates transform among themselves): the photon is massless, whereas bosons have masses. Only at extremely high temperatures the symmetry is exact. At lower temperatures a spontaneous breakdown of symmetry occurs. This seems to be a general caprice of nature. At different temperatures symmetry breaks down: ferromagnetism, isotropic liquids, the electroweak force... A change in temperature can create new properties for matter: it creates magnetism for metals, it creates orientation for a crystal, it creates masses for bosons. The fundamental forces exhibit striking similarities when their bosons are massless. The three families of particles, in particular, acquire identical properties. This leads scientists to believe that the "natural" way of being for bosons in a remote past was massless. How did they acquire the mass we observe today in our world? And why they all have different masses? The Higgs mechanism gives fermions and bosons a mass. Naturally it requires bosons of its own, the Higgs bosons (particles of spin 0). Each interaction exhibits a form of symmetry, but unfortunately they are all different, as exemplified by the fact that quarks cannot turn into leptons. In the case of the weak force, particles (e.g., the electron and its neutrino) can be interchanged, while leaving the overall equations unchanged, according to a transformation called SU(2), meaning that one particle can be exchanged for another one. For the strong force (i.e., the quarks) the symmetrical transformation is SU(3), meaning that three particles can be shuffled around. For the electromagnetic force, it is U(1), meaning that only the electrical and magnetic http://www.thymos.com/tat/physics.html (36 of 68)25/07/2003 14:37:26
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component of the field can be exchanged for each other. Any attempt to find a symmetry of a higher order results into the creation of new particles. SU(5), for example, entails the existence of 24 bosons... but it does allow quarks and leptons to mutate into each other (five at the time), albeit at terribly high temperatures. Finally, Quantum Theory does not incorporate gravity. Since gravity is an interaction (albeit only visible among large bodies), it does require its own quantum of interaction, the so called "graviton" (a boson of spin 2). Once gravity is "quantisized", one can compute the probability of a particle interacting with the gravitational field: the result is... infinite. The difficulty of quantisizing gravity is due to its selfreferential (i.e., nonlinear) nature: gravity alters the geometry of space and time, and that alteration in turns affects the behavior of gravity. The fundamental differences between Quantum Theory and General Relativity can also be seen topologically: the universe of Relativity is curved and continuous; the universe of Quantum Theory is flat and granular. Relativity prescribes that matter warps the continuum of spacetime, which in turns affects the motion of matter. Quantum Theory prescribes that matter interacts via quanta of energy in a flat spacetime. (Even finding a common vocabulary is difficult!) The bridge between the two views would be to "quantize" spacetime, the relativistic intermediary between matter and matter: then the two formulations would be identical. If spacetime warping could be expressed in terms of quanta of energy, then the two prescriptions would be the same. Recently, Abhay Ashtekar has proposed the "loop-space model", based on the 1985 theory of Amitabha Sen, that splits time and space into two distinct entities subject to quantum uncertainty (analogous to momentum and position). The solutions of Einstein's equations would then be quantum states that resemble "loops". The truth is that Quantum Theory had reached an impasse. There seems to be no way that (General) Relativity can be modified to fit Quantum Mechanics. Superstring Theory: Higher Dimensions Countless approaches have been proposed to integrate the quantum and the (general) relativistic views of the world.
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The two theories are obviously very different and the excuse that they operate at different "granularity" levels of nature (Quantum Theory being for the very small and Relativity Theory being for the very big) is not very credible. Physicists have been looking for a theory that explains both, a theory of which both would be special cases. Unfortunately, applying Quantum Theory to Relativity Theory has proved unrealistic. The problem is that they are founded on different "metaphors" of the world. Relativity Theory binds together space-time and matter. Quantum Theory binds together matter and the observer (an observer who is supposed to verify the consequences of binding together matter and the observer who is supposed to...). Relativity focuses on how the gravity of massive bodies bends the structure of time and space and are in turn influenced in their motion by the curvature of space-time. Quantum Theory focuses on the fuzziness in the life of elementary particles. If one simply feeds Schroedinger's equation (how the world evolves according to Quantum Theory) into Einstein's equation (how the world evolves according to Relativity Theory) the resulting equation appears to be meaningless. Basically, we don’t have a Physics that holds in places where both gravity and quantum effects are crucial, like at the centers of black holes or during the first moments of the Big Bang. General Relativity explains motion. Einstein’s equations are precise. Quantum Theory explains that motion is undefined. Heisenberg’s principle is fuzzy. General Relativity shows that time is relative. Quantum Theory assumes a universal watch setting the pace for the universe. "Time" looks completely different in one theory and in the other, almost as if the two theories used the term "time" to refer to two different things. Ditto for the "observer": Einstein’s observer is part of the universe and in fact is affected by the universe, whereas Quantum Theory’s observer has a special status that exempts her from quantum laws (the quantum universe is divided into particles that are measured and "observers" who make measurements).
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Superstrings A route to merging Quantum Theory and Relativity Theory is to start with Relativity and see if Quantum Theory can be found as a special case of Einstein's equations. In 1919, the German physicist Theodr Kaluza discovered that electromagnetism would follow if a fifth dimension was added to Einstein's four-dimensional spacetime continuum: by re-writing Einstein's field equations in five dimensions, Kaluza obtained a theory that contained both Einstein's General Relativity (i.e., the theory of gravitation) and Maxwell's theory of electromagnetism. Kaluza thought that light's privileged status came from the fact that light is a curling of the fourth spatial dimension. Later, the mathematician Oskar Klein explained how the fifth dimension could be curled up in a loop the size of the Planck length (the shortest length that Quantum Physics can deal with). The universe could have five dimensions, except that one is not infinite but closed in on itself. In the 1960s, the American physicist Bryce DeWitt and others proved that a Kaluza theory in higher dimensions is even more intriguing: when the fifth and higher dimensions are curled up, the theory yields the Yang-Mills fields required by Quantum Mechanics. It was this approach that in 1974 led the American physicist John Schwarz to formulate Superstring Theory. His early studies had been triggered by a formula discovered in 1968 by the Italian physicist Gabriel Veneziano and its interpretation as a vibrating string by the Japanese physicist Yoichiro Nambu. Schwarz quickly realized that both the standard model for elementary particles and General Relativity’s theory of gravitation were implied by Superstring Theory. Superstring Theory views particles as one-dimensional entities (or "strings") rather than points: tiny loops of the magnitude of the Planck length. Particles are simply resonances (or modes of vibrations) of tiny strings. In other words, all there is vibrating strings and each particle is due to a particular mode of vibration of the string. Each vibrational mode has a fixed energy, which means a mass, charge and so forth. Thus the illusion of a particle. All matter consists of these tiny vibrating strings. The key point is that one of these vibrational modes is the "graviton", the particle that accounts for gravitation: Superstring theory is a Quantum Theory that predicts the existence of General Relativity’s gravitation.
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The behavior of our universe is largely defined by three universal constants: the speed of light, the Planck constant and the gravitational constant. The "Planck mass" is a combination of those three magic numbers and is the mass (or energy) at which the superstring effects would be visible. Unfortunately, this is much higher than the mass of any of the known particles. Such energies were available only in the early stages of the universe and for a fraction of a second. The particles that have been observed in the laboratory are only those that require small energies. A full appreciation of Superstring Theory would require enormous energies. Basically, Superstring Theory is the first scientific theory that states the practical impossibility of being verified experimentally (at least during the lifetime of its inventors). Furthermore, the superstring equations yield many approximate solutions, each one providing a list of massless particles. This can be interpreted as allowing a number of different universes: our is one particular solution, and that solution will yield the particles we are accustomed with. Even the number of dimensions would be an effect of that particular solution. There is, potentially, an infinite number of particles. Before the symmetry breaks down, each fermion has its own boson, which has exactly the same mass. So a "photino" is postulated for a "photon" and a "s-electron" for the electron. Space-time must have ten dimensions. Six of them are curved in minuscule tubes that are negligible for most uses. Matter originated when those six dimensions of space collapsed into superstrings. Ultimately, elementary particles are compactified hyper-dimensional space. Einstein's dream was to explain matter-energy the same way he explained gravity: as fluctuations in the geometry of space-time. The "heterotic" variation of Superstring Theory, advanced by the American physicist David Gross and others in the 1980s, does just that: particles emerge from geometry, just like gravity and the other forces of nature. The heterotic string is a closed string that vibrates (at the same time) clockwise in a ten-dimensional space and counterclockwise in a 26-dimensional space (16 dimensions of which are compactified). Einstein's General Theory of Relativity is implied by Superstring Theory, to the point that another American physicist, Edward Witten, has written that Relativity Theory was discovered first by mere accident. Incidentally, the same Witten, in 1985, has provided the most complete "field string theory".
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In the meantime Superstring Theory has progressed towards a peculiar form of duality. In 1977 a Finnish and a British physicists, Claus Montonen and David Olive, proposed that there may exist a dual Physics which deals with "solitons" instead of "particles". In that Physics, magnetic monopoles are the elementary units, and particles emerge as solitons, knots in fields that cannot be smoothed out (in our conventional Physics, magnetic monopoles are solitons of particles). Each particle corresponds to a soliton, and viceversa. They proved that it would not matter which Physics one chooses to follow: all results would automatically apply to the dual one. In particular, one could think of solitons are aggregates of quarks (as originally done in 1974 by the Dutch physicist Gerard 't Hooft). Then a theory of solitons can be built on top of a theory of quarks, or a theory of quarks can be built on top of a theory of solitons. In 1996 the American physicist Andrew Strominger has even found a connection between black holes and strings: if the original mass of the black hole was made of strings, the Hawking radiation would ultimately drain the black hole and leave a thing of zero size, i. e. a particle. Since a particle is ultimately a string, the cycle could theoretically resume: black holes decaying into strings and strings decaying into black holes. Superstring Theory is the only scientific theory of all times that requires the universe to have a specific number of dimensions: but why ten? Physicists like Peter Freund, a Romanian native, and Michio Kaku have observed that the laws of nature become simpler in higher dimensions. The perceptual system of humans can only grasp three dimensions, but at that level the world looks terribly complicated. The moment we move to a fourth dimension, we can unify phenomena that looked very different. As we keep moving up to higher and higher dimensions, we can unify more and more theories. This is precisely how Einstein unified Mechanics and Electromagnetism (by introducing a fourth dimension), how quantum scientists unified electromagnetism with the weak and strong nuclear forces and how particle physicists are now trying to unify these forces with gravity. Still: why ten? Are there more phenomena around that we still have to discover and that, once unified with the existing scientific theories, will yield even more dimensions? Are these dimensions just artifices of http://www.thymos.com/tat/physics.html (41 of 68)25/07/2003 14:37:26
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the Mathematics that has been employed in the calculations, or are they real dimensions that may have been accessible in older times? And why mono-dimensional strings, and not poli-dimensional objects? Paul Dirac, way back in 1962, had thought that the electron could be a bubble, which is a membrane closed in on itself. Quantum Gravity Penrose also agrees that the right approach to the integration of Quantum Theory and Relativity Theory is not to be concerned about the effects of the former on the latter but viceversa. Penrose (like everyone else) is puzzled by the two different, and incompatible, quantum interpretations of the world. One is due to Schroedinger's equation, which describes how a wave function evolves in time. This interpretation is deterministic and provides a continuous history of the world. The other is due to the collapse of the wave function in the face of a measurement, which entails determining probabilities of possible outcomes from the squared moduli of amplitudes in the wave function ("state-vector reduction"). This interpretation is probabilistic and provides a discontinuous history of the world, because the system suddenly jumps into a new state. We can use Schroedinger's equation to determine what is happening at any point in time; but, the moment we try to actually measure a quantity, we must resort to statevector reduction in order to know what has happened. Penrose postulates that these two incompatible views must be reconciled at a higher level if abstraction by a new theory, and such a theory must be based on Relativity Theory. Such a theory, which he calls "quantum gravity", would also rid Physics of the numerous infinites that plague it today. It should also be timeasymmetrical, predicting a privileged direction in time, just like the second law of Thermodynamics does. Finally, in order to preserve free will, it would contain a non-algorithmic element, which means that the future would not be computable from the present. Penrose even believes that Quantum Gravity will explain consciousness. The Trail of Asymmetry Somehow asymmetry seems to play a protagonist role in the history of our universe and our life. Current cosmological models speculate that the four fundamental forces of nature arose when symmetry broke down after the very high temperatures of the early
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universe began to the child of that there would be no universe would be
cool down. Today, we live in a universe that is momentous split. Without that "broken symmetry" electrical force and no nuclear force, and our vastly impoverished in natural phenomena.
Scientists have also speculated at length about the asymmetry between matter and antimatter: if one is the mirror image of the other and no known physical process shows a preference for either, why is it that in our universe protons and electrons (matter) overwhelmingly prevails over positrons and antiprotons (antimatter)? Most physical laws can be reversed in time, at least on paper. But most will not. Time presents another asymmetry, the "arrow of time" which points always in the same direction, no matter what is allowed by Mathematics. The universe, history and life all proceed forward and never backwards. Possibly related to it is the other great asymmetry: entropy. One can't unscramble an egg. A lump of sugar which is dissolved in a cup of coffee cannot become a lump of sugar again. Left to themselves, buildings collapse, they do not improve. Most artifacts require periodic maintenance, otherwise they would decay. Disorder is continuously accumulated. Some processes are irreversible. It turns out that entropy is a key factor in enabling life (and, of course, in ending it). Living organisms maintain themselves far from equilibrium and entropy plays a role in it. Moreover, in 1848 the French biologist Louis Pasteur discovered that aminoacids (which make up proteins which make up living organisms) exhibit another singular asymmetry: for every aminoacid there exist in nature its mirror image, but life on Earth uses only one form of the aminoacids (left-handed ones). Pasteur’s mystery is still unexplained (Pasteur thought that somehow that "was" the definition of life). Later, biologists would discover that bodies only use right-handed sugars, thereby confirming that homochirality (the property of being single-handed) is an essential property of life. Finally, an asymmetry presents itself even in the site of thinking itself, in the human brain. The two cerebral emispheres are rather symmetric in all species except ours. Other mammals do not show preferences for grasping food with one or the other paw. We do. Most of us are right-handed and those who are not are left-handed. Asymmetry seems to be a fundamental feature of our brain. The left hemisphere is primarily used for language and the interplay http://www.thymos.com/tat/physics.html (43 of 68)25/07/2003 14:37:26
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between the two hemispheres seems to be important for consciousness. It may turn out to be a mere coincidence, but the most conscious creatures of our planet have also the most asymmetric brains. Was there also a unified brain at the origin of thinking, whose symmetry broke down later on in the evolutionary path? A Fuzzy World Modern physics relies heavily on Quantum Mechanics. Quantum Mechanics relies heavily on the theory of probabilities. At the time, probabilities just happened to fit well in the model. Quantum Mechanics was built on probabilities because the theory of probabilities is what was available in those times. Quantum Mechanics was built that way not because Nature is that way, but because the mathematical tools available at the time were that way; just like Newton used Euclid's' geometry because that is what Geometry could provide at the time. Boltzmann's stochastic theories had showed that the behavior of gases (which are large aggregates of molecules) could be predicted by a dynamics which ignored the precise behavior of individuals, and took into account only the average behavior. In retrospect Boltzmann's influence was enormous on Quantum Mechanics. His simplification was tempting: forget about the individual, focus on the population. Quantum Mechanics therefore prescribed a "population" approach to Nature: take so many electrons, and some will do something and some will do something else. No prescription is possible about a single electron. Quantum phenomena specify not what a single particle does, but what a set of particles do. Out of so many particles that hit a target, a few will pass through, a few will bounce back. And this can be expressed probabilistically. Today, alternatives to probabilities do exist. In particular, Fuzzy Logic can represent uncertainty in a more natural way (things are not black or white, but both black and white, to some extent). Fuzzy Logic is largely equivalent to Probability Theory, but it differs in that it describes single individuals, not populations. On paper, Quantum Mechanics could thus be rewritten with Fuzzy Logic (instead of probabilities) without altering any of its http://www.thymos.com/tat/physics.html (44 of 68)25/07/2003 14:37:26
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conclusions. What would change is the interpretation: instead of a theory about "set of individuals" (or populations) it would become a theory about "fuzzy individuals". In a Fuzzy Logic scenario, a specific particle hitting a potential barrier would both go through and bounce back. To some extent. It is not that out of a population some individuals do this and some individuals do that; a specific individual is both doing this and doing that. The world would still behave in a rather bizarre way, but somehow we would be able to make statements about individuals. However, this approach would allow Physics to return to a science of individual objects, not of populations of objects. The uncertainty principle could change quite dramatically: instead of stating that we can never observe all the parameters of a particle with absolute certainty, it could state that we can observe all the parameters of a particle with absolute certainty, but certainty not being exact. When I say that mine is a good book, I am being very certain. I am not being exact (what does "good" mean? How good is good? Etc). The fact that a single particle can be in different, mutually exclusive states at the same time has broad implications on the way our mind categorizes "mutually exclusive" states; not on what Nature actually does. Nature never constrained things to be either small or big. Our mind did. Any scientific theory we develop is first and foremost a "discourse" on Nature; i.e., a representation in our mind of what Nature is and does. Some of the limits we see in Nature (i.e., the fact that something is either big or small) are limits of our mind; and conversely some of the perfections that we see in Nature are perfections of our mind (i.e., the fact that there is a color white or something is cold or a stone is round, while in Nature no object is fully white, cold or round). Fuzzy Logic is probably a better compromise between our mind and Nature, because it allows to express the fact that things are not just zero or one, white or black, cold or warm, round or square; they are "in between", both white and black, both cold and warm, both... Time: When? To closer inspection, the main subject of Relativity and Quantum theories may well be Time. Most of the bizarre implications of those theories are things that either happen "in time" or are caused by Time. Relativity turned Time into one of several dimensions, mildly different from the others but basically very similar to the http://www.thymos.com/tat/physics.html (45 of 68)25/07/2003 14:37:26
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others. This clearly contrasts with our perception of Time as being utterly distinct from space. Hawking, for example, thinks that originally Time was just a fourth spatial dimension, then gradually turned into a different type of dimension and, at the Big Bang, it became Time as we know it today. The mathematician Hermann Bondi has argued that the roles of Time are utterly different in a deterministic and in a indeterministic universe. Whereas in a deterministic universe, Time is a mere coordinate, in a universe characterized by indeterminacy, such as one governed by Quantum Theory, the passage of time transforms probabilities into actualities, possibility into reality. If Time did not flow, nothing would ever be. Things would be trapped in the limbo of wave functions. The Australian physicist Paul Davies claims exactly the opposite: Time is rather meaningless in the context of a quantum model of the universe, because a general quantum state of the universe has no well-defined time. With Hawking, Time may not have existed before the Big Bang, and may have originated afterwards by mere accident. Time: What? The subject of Time has puzzled and fascinated philosophers since the dawn of consciousness. What is Time made of? What is the matter of Time? Is Time a human invention? There are no doubts that physical Time does not reflect psychological Time. Time, as we know it, is subjective and relative. There is a feeling to the flow of time that no equation of Physics can reproduce. Somehow, the riddle of Time reminds us of the riddle of consciousness: we know what it is, we can feel it very clearly, but we cannot express it, and we don't know where it comes from. If you think that there is absolute time, think again. Yes, all clocks display the same time. But what makes you think that what they display is Time? As an example, let's go back to the age when clocks had not been invented yet. Time was defined by the motion of the sun. People knew that a day is a day because the sun takes a day to turn around the Earth (that's what they thought). And a day was a day everywhere on the Earth, even among people who had never communicated to each other. Is that absolute Time? What would happen if the Sun all of a sudden slowed down? People all over the planet would still think that a day is a day. Their
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unit of measurement would be different. They would be measuring something else, without knowing it. What would happen today if a galactic wave made all clocks slow down? We would still think that ten seconds are ten seconds. But the "new" ten seconds would not be what ten seconds used to be. So clocks do not measure Time, they just measure themselves. We take a motion that is the same all over the planet and use that to define something that we never really found in nature: Time. At the least, we can say that measurement of Time is not innate: we need a clock to tell "how long it took". Unfortunately, human civilization is founded on Time. Science, the Arts and technology are based on the concept of Time. What we have is two flavors of Time: psychological time, which is a concrete quantity that the brain creates and associates to each memory; and physical time, an abstract quantity that is used in scientific formulas for the purpose of describing properties of matter. The latter was largely an invention of Isaac Newton, who built his laws of nature on the assumption of an absolute, universal, linear, continuous Time. Past is past for everybody, and future is future for everybody. Einstein explained that somebody's past may be somebody else's present or even future, and thereby proved that time is not absolute and not universal. Any partitioning of space-time into space and time is perfectly legal. The only requirement on the time component is that evens can be ordered in time. Time is pretty much reduced to a convention to order events, and one way of ordering is as good as any other way. In the meantime, the second law of Thermodynamics had for the first time established formally the arrow of time that we are very familiar with, the flowing from past to future and not viceversa. Time: Where? Once the very essence of Time had been doubted, scientists began to doubt even its existence. The British physicists Arthur Milne and Paul Dirac are two of the scientists who have wondered if the shaky character of modern Physics may be due to the fact that there are two different types of time and that we tend to confuse them. Both maintained that atomic time and astronomical time may be out of sync. In other words, the speeds of planets slowly change all the time in terms
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of atomic time, although they remain the same in terms of astronomical time. A day on Earth is a day regardless of the speed of the Earth, but it may be lasting less and less according to an atomic clock. In particular, the age of the universe may have been vastly exaggerated because it is measured in astronomical time and astronomical processes were greatly speeded up in the early stages of the universe. Not to leave anything untried, the American physicist Richard Feynman even argued in favor of matter traveling backwards in time: an electron that turns into a positron (its anti-particle) is simply an electron that turns back in time. His teacher John Wheeler even argued that maybe all electrons are just one electron, bouncing back and forth in time; and so all other particles. There is only one instance of each particle. That would also explain why all electrons are identical: they are all the same particle. Einstein proved that Time is not absolute and said something about how we experience time in different ways depending on how we are moving. But he hardly explained what Time is. And nobody else ever has. The British physicist Julian Barbour believes that Time does not exist, and that most of Physics' troubles arise from assuming that it does exist. We have no evidence of the past other than our memory of it. We have no evidence of the future other than our belief in it. Barbour believes that it is all an illusion: there is no motion and no change. Instants and periods do not exist. What exists is only "time capsules", which are static containers of "records". Those records fool us into believing that things change and events happen. There exists a "configuration space" that contains all possible instants, all possible "nows". This is "Platonia." We experience a set of these instants, i.e. a subset of Platonia. Barbour is inspired by Leibniz' theory that the universe is not a container of objects, but a collection of entities that are both space and matter. The universe does not contain things, it "is" things. Barbour does not answer the best part of the puzzle: who is deciding which "path" we follow in Platonia? Who is ordering the instants of Platonia? Barbour simply points to quantum mechanics, that prescribes we should always be in the "instant" that is most likely. We experience an ordered flow of events because that is what we were designed for: to interpret the sequence of most likely instants as an ordered flow of events. Barbour also offers a solution to integrating relativity and http://www.thymos.com/tat/physics.html (48 of 68)25/07/2003 14:37:26
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quantum mechanics: remove time from a quantum description of gravity. Remove time from the equations. In his opinion, time is precisely the reason why it has proved so difficult to integrate relativity and quantum theories. Time: Why? In classical and quantum Physics, equations are invariant with respect to time inversion. Future and past are equivalent. Time is only slightly different from space. Time is therefore a mere geometrical parameter. Because of this, Physics offers a static view of the universe. The second law of Thermodynamics made official what was already obvious: that many phenomena are not reversible, that time is not merely a coordinate in space-time. In the 1970's Prigogine showed, using Boltzmann's theorem and thermodynamic concepts, that irreversibility is the manifestation at macroscopic level of randomness at microscopic level. Prigogine then attempted a microscopic formulation of the irreversibility of laws of nature. He associates macroscopic entropy with a microscopic entropy operator. Time too becomes an operator, no longer a mere parameter. Once both time and entropy have become operators, Physics has been turned upside down: instead of having a basic theory expressed in terms of wave functions (i.e., of individual trajectories), he obtains a basic theory in terms of distribution functions (i.e., bundles of trajectories). Time itself depends on the distribution and therefore becomes itself a stochastic quantity, just like entropy, an average over individual times. As a consequence, just like entropy cannot be reversed, time cannot: the future cannot predicted from the past anymore. Traditionally, physical space is geometrical, biological space (the space in which biological form develops) is functional (for example, physical time is invariant with respect to rotations and translations, biological space is not). Prigogine's Time aims at unifying physical and biological phenomena. Black Holes and Wormholes: Gateways to Other Universes and Time Travel Shortly after Einstein published his gravitational field equation, the German physicist Karl Schwarzschild found a solution that determines the gravitational field for any object, given its mass and its size. That solution goes to infinity for a specific ratio between mass and size: basically, if the object is dense enough
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(lots of mass in a tiny size), the gravitational attraction it generates is infinite. Nothing, not even light, can escape this object, which was therefore named "black hole" (by John Wheeler). And everything that gets near it is doomed to fall into it, and be trapped in it forever. All information about the matter that fell into it is also lost forever: a black hole may have been generated by any initial configuration of matter, but there is no record of which one it was. Even worse, in the 1970's Stephen Hawking proved that black holes evaporate, therefore information is not only trapped inside the black hole, it truly disappears forever. The disappearance of matter, energy and information in a black hole has puzzled physicists since the beginning, as it obviously violates the strongest principle of conservation that our Physics is built upon. It also highlights the contradictions between Quantum Theory and Relativity Theory: the former guarantees that information is never lost, the latter predicts that it will be lost in a black hole. Einstein himself realized that black holes implied the existence of a "bridge" between our universe and a mirror universe which is hidden inside the black hole, and in which Time runs backwards. It was the Austrian mathematician Kurt Godel, the same individual who had just single-handedly shattered the edifice of Mathematics, who, in 1949, pointed out how Einstein's equations applied to a rotating universe implied that space-time can curve to the point that a particle will return to a previous point in time; in other words, "wormholes" exist connecting two different points in time of the same universe. In the 1950s, John Wheeler speculated that two points in space can be connected through several different routes, because of the existence of spatial wormholes. Such wormholes could act like shortcuts, so that travel between the two points can occur even faster than the speed of light. The New Zealand mathematician Roy Kerr in 1963 and the American physicist Frank Tipler in 1974 found other situations in which wormholes were admissible. In the U.S., Kip Thorne even designed a time machine capable of exploiting such time wormholes. In the U. K., Stephen Hawking came up with the idea of wormholes connecting different universes altogether. Hawking's wave function allows the existence of an infinite set of universes, some more likely than others, and wormholes the size of the Planck length connect all these parallel universes with each other. The History of the Universe One of the consequences of General Relativity is that it prescribes the evolution of the universe. A few possible futures http://www.thymos.com/tat/physics.html (50 of 68)25/07/2003 14:37:26
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are possible, depending on how some parameters are chosen. These cosmological models regard the universe as one system with macroscopic quantities. Since the discovery that the universe is expanding, the most popular models have been the ones that predict expansion of space-time from an initial singularity. Since a singularity is infinitely small, any cosmological model that wants to start from the very beginning must combine Relativity and Quantum Physics. The story usually starts with an infinitely small universe (Roger Penrose and Stephen Hawking have proved that Relativity implies this), in which quantum fluctuations of the type predicted by Heisenberg's principle are not negligible, especially when the universe was a size smaller than the Planck length. The fluctuations actually "created" the universe (space, time and matter) in a "Big Bang". Time slowly turned into space-time, giving rise to spatial dimensions. Space-time started expanding, the expansion that we still observe today. In a sense, there was no beginning of the universe: the "birth" of the universe is an illusion. There is no need to create the universe, because its creation is part of the universe itself. There is no real origin. The universe is self-contained, it does not require anything external to start it. Then the universe expanded. If the mass of the universe is big enough (and this is still being debated, but most cosmologists seem to believe so), then at some point the expansion will peak and it will reverse: the universe will contract all the way back into another singularity (the "Big Crunch"). At that point the same initial argument holds, which is likely to start another universe. For example, John Wheeler claims that the universe oscillates back and forth between a Big Bang and a Big Crunch. Each time the universe re-starts with randomly assigned values of the physical constants and laws. Both the beginning and the end are singularities, which means that the laws of Physics break down. The new universe can have no memory of the old universe, except for a higher entropy (assuming that at least that law is conserved through all these singularities), which implies a longer cycle of expansion and contraction (according to Richard Tolman's calculations). Some scientists believe that they can remove the singularities. In particular, Hawking has proposed a model in which Time is unbounded but finite, and therefore it is not created in the Big Bang even if the universe today has a finite age. (According to Einstein, space is also finite yet unbounded). In his model, Time http://www.thymos.com/tat/physics.html (51 of 68)25/07/2003 14:37:26
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emerges gradually from space and there is no first moment. The real conundrum for cosmologists, however, is to find the missing matter: about 80% of the matter required for the universe to be the way it is (to account for the gravity that holds together the galaxies the way they are held together) has never been observed. Physicists are searching for "dark matter" that does not interact with ordinary matter, does not emit and does not reflect light. Whatever the reason, 80% of the mass of the universe has not been found. The End of Entropy Very few people are willing to take the second law of Thermodynamics as a primitive law of the universe. Explicitly or implicitly, we don't seem happy with this law that states an inequality. Somehow it must be a side effect of some other phenomenon. Thomas Gold (among others) believes that the second law follows the direction of the universe: entropy increases when the universe expands, it decreases when the universe contracts (or, equivalently, when Time flows backwards). The second law would simply be an effect of the expansion or contraction. In that case the universe might be cyclic. Roger Penrose has also investigated the mystery of entropy. A gravitational effect results in two dual phenomena: a change in shape and a change in volume of space-time. Consequently, Penrose separates the curvature tensor in two components: the Ricci tensor (named after the Italian mathematician Gregorio Ricci who founded the theory of tensors) and the Weyl tensor (named after the German mathematician Hermann Weyl, a close associate of Einstein's). The Weyl tensor measures the change in shape, and, in a sense, the gravitational field, whereas the Ricci tensor measures the change in volume, and, in a sense, the density of matter. The Weyl tensor measures a "tidal" effect and the Ricci tensor measures an effect of volume reduction. The Ricci tensor is zero in empty space, it is infinite in a singularity. The Weyl tensor is zero in the initial singularity of the Big Bang, but infinite at the final singularity of the Big Crunch. Penrose has showed that entropy follows the Weyl tensor and the Weyl tensor may hide the puzzling origin of the second law of Thermodynamics. The Resurrection of Information The curvature in proximity of a black hole is infinite: all
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objects are doomed. There is a distance from the black hole which is the last point where an object can still escape the fall: the set of those points defines the horizon of the black hole. In 1974 Stephen Hawking discovered that black holes may evaporate and eventually vanish. The "Hawking radiation" that remains has lost all information about the black hole. This violates the assumption of determinism in the evolution of the universe, i.e. that, if we know the present, we can always derive the past, because the present universe contains all information about how the past universe was. Only two options have been found to allow for the conservation of information. The first one is to allow for information to travel faster than light. That would allow it to escape the black hole. But it would violate the law of causality (that nothing can travel faster than light). The second option is that a vanishing black hole may leave behind a remnant the size of the Planck length. Andrew Strominger has argued for the latter option. This option calls for an infinite number of new particles, as each black hole is different and would decay into a different particle. Strominger believes that such particles are extreme warps of space-time, "cornucopions", that can store huge amount of information even if they appear very small to an outside observer and their information would not be accessible. After all, Stephen Hawking and Jacob Bekenstein have proved that the entropy of a black hole is proportional to its surface, which means that entropy should decrease constantly during the collapse of the black hole, which means that information must somehow increase, and not disappear... Inflation: Before Time What was there before the Big Bang created our universe? A widely held "cosmological principle" requires that the universe has no center, no special place. That means that the Big Bang did not occur in a specific point of the universe: it occurred everywhere in the universe, it was the universe. The universe was a point and the Big Bang is merely the moment when it began to expand. By cosmological standards, the Big Bang is still occurring now, in every single point of the universe. Space is being created as the universe expands. There was "nothing" before the Big Bang and there is "nothing" beyond the universe. The Big Bang creates the universe which is everything that exists.
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This "inflationary" model (proposed by Alan Guth in 1981 and expanding on the work of George Gamow who, in turn, developed an idea by the Belgian physicist Georges Lemaitre) assumes that the universe began its life in a vacuum-like state containing some homogeneous classical fields but no particles (no matter as we know it). Then it expanded exponentially (that’s the "inflation") and the vacuum-like state decayed into particles. Guth's model is based on the existence of scalar fields. A scalar field is one caused by a quantity which is purely numerical, such as temperature or household income. Gravitational and electromagnetic fields, in contrast, also point in a specific direction, and are therefore "vector" fields. Vector fields are perceived because they exert some force on the things they touch, but scalar fields are virtually invisible. Nonetheless, scalar fields play, for example, a fundamental role in unified theories of the weak, strong and electromagnetic interactions. Like all fields, scalar fields carry energy. Guth assumed that in the early stage of the universe a scalar field provided a lot of energy to empty space. This energy produced the expansion, which for a while occurred at a constant rate, thereby causing an exponential growth. Guth's model solves a few historical problems of cosmology: the "primordial monopole" problem (grand unified theories predict the existence of magnetic monopoles); the "flatness" problem (why the universe is so flat, i.e. why the curvature of space is so small); and the "horizon" problem (how casually disconnected regions of the universe can have started their expansion simultaneously). It does not account for dark matter and energy. While everybody agrees that the universe is expanding, not everybody agrees on what that means. In the quest for an explanation of dark matter and dark energy, the British physicist Geoffrey Burbidge, the American physicist Fred Hoyle and the Indian physicist Jayant Narlikar have developed the "Quasi Steady State Cosmology" (reprised in the "Cyclic Universe Theory" by the American physicist Paul Steinhardt and the British physicist Neil Turok), according to which there is no "big bang" to begin with, and there will be no "big crunch" to end with. Space and time existed ever since and will exist forever. There is no beginning nor end. The evolution of the universe is due to a series of "bangs" (explosive expansions) and "crunches" (contractions). The big bang that we observe today with the most powerful detectors of microwave radiation is simply one of the many expansions following one of the many contractions. Each phase may last a trillion years, and therefore be undetected by human instruments. Burbidge doubts black holes, quasars and the cosmic radiation.
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Natural Selection for Universes Refining Guth’s vision, in the 1980s the Russian physicist Andrei Linde came up with a "chaotic inflationary" model. Linde realized that Guth's inflation must litter the universe with bubbles, each one expanding like an independent universe, with its own Big Bang and its own Big Crunch. Linde's model is "chaotic" because it assumes a chaotic initial distribution of the scalar field: instead of being uniform, the original scalar field was fluctuating wildly from point to point. Inflation therefore began in different points at different times and at different rates. Regions of the universe that are isolated by a length greater than the inverse of the Hubble constant cannot be in any relation with the rest of the universe. They expand independently. Any such region is a separate mini-universe. In any such region the scalar field can give rise to new mini-universes. One mini-universe produces many others. It is no longer necessary to assume that there is a "first" universe. Each mini-universe is very homogeneous, but on a much larger scale the universe is extremely inhomogeneous. It is not necessary to assume that the universe was initially homogeneous or that all its casually disconnected parts started their expansion simultaneously. One region of the inflationary universe gives rise to a multitude of new inflationary regions. In different regions, the properties of space-time and elementary particles may be utterly different. Natural laws may be different in each mini-universe. The evolution of the universe as a whole has no end, and may have no beginning. The "evolution" of mini-universes resembles that of any animal species. Each mini-universe leads to a number of mini-universes that are mutated versions of it, as their scalar fields is not necessarily the same. Each mini-universe is different, and miniuniverses could be classified in a strict hierarchy based on a parent-child relationship. This mechanism sort of "reproduces" mini-universes in a fashion similar to how life reproduces itself through a selection process.
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The combinatorial explosion of mini-universes can be viewed as meant to create mini-universes that are ever better at "surviving". Each mini-universe "inherits" the laws of its parent mini-universe to an extent, just like living beings inherit behavior to an extent through genetic code. A "genome" is passed from parent universe to child universe, and that "genome" contains instructions about which laws should apply. Each genome only prescribes a piece of the set of laws governing the behavior of a universe. Some are random. Some are generated by "adaptation" to the environment of many coexisting universes. At the same time, expansion means that information is being propagated like in a neural network through the hierarchy of expanding universes. It may also be that a universe is not born just out of a parent universe, but of many parent universes. A region of the universe expands because of the effect of many other regions. This is similar to what happens with neural networks. With a little imagination, the view of the chaotic inflationary theory can be interpreted in this way: ❍
The expansion of a new region may be determined by many regions, not just one.
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Each region somehow inherits its laws from those regions.
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The laws in a region may change all the time, especially at the beginning.
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The laws determine how successful a region is in its expansion.
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Different expansion regions with different laws can communicate. They are likely to compete for survival.
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Adaptation takes a toll on expansion regions. Regions die. Branches of regions become extinct. Obviously, this scenario bears strong similarities with biological scenarios. Another theory that presupposes evolving universes is the one advanced in 1992 by the American astrophysicist Lee Smolin. He
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thinks that black holes are the birthplaces of offspring universes. The constants and laws of Physics are randomly changed in the new universes, just like the genome of offspring is randomly mutated. Black holes guarantee reproduction and inheritance. Universes that do not give rise to black holes cannot reproduce: there is therefore also a kind of "natural selection" among Smolin's universes. Our universe's delicate balance of constants and forces is the result of evolution. Loop Quantum Gravity The ultimate goal of Loop Quantum Gravity (LQG) is still the "quantization" of general relativity, but the way it approaches the problem is very different: it is purely geometric. In 1971, Roger Penrose introduced the notion of a "spin network" (derived from Louis Kauffman's "knot theory") in an attempt to explain the structure of 3-dimensional space. Lee Smolin then discovered something that is built into any theory of "quantum gravity" (into any quantization of relativity): the volumes of regions in space must come in discrete units, like energy comes in discrete units. If energy comes in discrete units, then space must come in discrete units. Just like matter is made of discrete particles, space itself must be made of discrete units. A volume cannot be divided forever: there is an elementary unit of volume. This conclusion had been reached independently by Jacob Bekenstein (in his studies on the thermodynamics of black holes). The space that we experience is continuous. Spin networks, instead, are discrete. They are graphs with edges labelled by "spins" (that come in multiples of 0.5) and with three edges meeting at each vertex. As these spin networks become larger and more complex, they "yield" our ordinary, continuous, smooth 3dimensional space. A spin network, therefore, "creates" geometry. It is not that a spin network yields a metrics (the metrics being what defines the geometry of a region of space) but that each vertex of a spin network creates the volume of a region of space. The way spin networks combine to form space is not clear, as there seems to be no "natural law" (no equivalent of gravitation or of electromagnetism) at work. Spin networks "spontaneously" combine to form space. The formation of space resembles the Darwinian process that creates order via natural selection of selforganizing systems. Space appears to be the result of spontaneous
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processes of self-organization a` la Stuart Kauffman. Spin networks thus solve "quantum gravity" in three dimensions. The problem is that the fourth dimension ("time") is not accounted for, i.e. the "dynamics" of the universe is not accounted for. In 2001 the Greek physicist Fotini Markopoulou has shown that spin networks evolve in time in discrete steps: at every step, the change of each vertex of the spin network only depends on its immediate neighbors. This is reminescent of Von Neumann's cellular automata and of algorithm-based thinking, as opposed to the traditional formula-oriented thinking of Physics. Brains, Lives, Universes Let's take a closer look at Life. We have organisms. Each organism is defined by its genome. An organism's genome does not vary during its lifetime. The genome of its offspring varies. The variation is the result of random processes. Each organism interacts with the environment and may or may not survive such interactions. Indirectly, interactions with the environment determine how genomes evolve over many generations. Then we have neural networks. The behavior of each thinking organism is controlled by a neural network. The principle of a neural network is that of interacting with the environment, propagating the information received from the environment through its neurons and thereby generating behavior. Each neuron has influence over many neurons and what determines the behavior is the connections between neurons. A neural network changes continuously during the life of an organism, especially at the very beginning. Within neural networks a selection process also applies. Connections survive or die depending on how useful they are. Connections are stronger or weaker depending on how useful they are. Usefulness is defined by interaction with the environment. Genomes and neural networks are systems that have in common the principle of propagating information about the environment within itself through a process of a) interaction with the environment, b) feedback from the environment, c) selection. Neural networks, genetic algorithms and chaotic inflationary universes seem to obey very similar principles. They "expand" in order to
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Propagate information within the individual, so as to determine behavior
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Propagate information within the population, so as to determine evolution The Nature of the Laws of Nature Even with the sophistication of Relativity Theory, our universe presents us with an uncomfortable degree of arbitrariness. What is still not clear is why laws (e.g. Einstein's field equations) and constants (e.g., the Planck distance) are the way they are. Why is the universe the way it is? Furthermore: why do properties of matter such as electrical charge and mass exert forces on other matter? Why do things interact at all? The cosmological models presume that the physical laws we know today were already in effect at the very beginning, i.e. were born with the universe, and actually pre-existed it. The laws of Physics are simply regularities that we observe in nature. They allow us to explain why what happened, and why it happened the way it happened. They also allow us to make predictions. Science is all about predictions. If we couldn't make predictions, any study of Nature would be pretty much useless. We can build bridges and radios because we can make predictions on how things will work. Three aspects of the fundamental laws are especially puzzling. The first has to do with the nature of the laws of Nature. How absolute are they? Some laws can be reduced to other laws. Newton's law of gravitation is but a special case of Einstein's. It was not properly a law of Nature, it was an effect of a law of nature that Newton did not know. These days, we are witnessing a quest for a unification theory, a theory that will explain all four known forces (weak, nuclear, electric and gravitational) in one megaforce: if the program succeeds, we will have proved that those four forces were effects, not causes. Is the second law of Thermodynamics a law indeed, or just the effect of something else? After all, the laws as we study them today in textbooks are the product of a historical process of scientific discovery. Had history been different (had progress followed a different route) we may have come up with a description of the universe based on different laws, that would equally well fit (individually) all the
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phenomena we are aware of. The second question is why are they mathematical formulas. Mathematics is a human invention, but it is amazing how well it describes the universe. True, Mathematics is more a discovery process than an invention process. But, even so, it is a discovery of facts that occur in the realm of mathematical ideas (theorems and the likes). It is amazing that facts occurring in that abstract realm reflect so well facts that occur in the physical realm. Most Mathematics that is employed today so effectively for describing physical phenomena was worked out decades and even centuries before by mathematicians interested only in abstract mathematical problems. The rule almost never fails: sooner or later a physical phenomenon will be discovered that perfectly matches a mathematical theory. It feels like the universe is a foreign movie, subtitled in mathematical language. Even more intriguing is the fact that the world of Mathematics is accessible by the human mind. Our bodies have privileged access to physical space, our minds have privileged access to the notes that describe it. We get both treats. The body perceives physical reality through the senses, the mind perceives mathematical reality through reasoning. The third question is whether they are truly eternal. Were they always the same? Will they always be the same? Naturally, if the answer is negative, then we don't know anything It would seem more likely that they are part of the universe and therefore came to be precisely when the universe came to be. In that case it would therefore be impossible to compute a model of how the universe was born, because we don't know which laws (if any) were in place before the universe was born! (We don't even know for sure whether the laws of Nature are the same in the whole universe. We don't even know if they have been the same all the time or if they have been changing over time). Similar arguments hold for the "constants" of Physics, for the dimensionless parameters that shape the laws of nature, in particular for the speed of light, the Planck constant, and the charge of the electron. Why do they have the value they have? Einstein asked: did God have a choice when he created the universe? Could those numbers be different, or are they the only
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combination that yields a stable universe? A famous formula has been puzzling scientists: the square of the charge of the electron divided by the speed of light and by the Planck constant is almost exactly 1/137. Why? We don't have a science of natural laws which studies where laws come from. Laws are assumed to transcend the universe, to exist besides and despite the existence of a universe. But that's a rather arbitrary conclusion (or, better, premise). The Prodigy of Stability Chaos is a matter of life in this universe. What is surprising is that we do not live in chaos. We live in almost absolute stability. The computer I am writing on right now is made of a few billion particles of all kinds that interact according to mechanic, gravitational, electric, magnetic, weak and strong forces. The equations to describe just a tiny portion of this computer would take up all my life. Nonetheless, every morning I know exactly how to turn on my computer and every day I know exactly how to operate on it. And the "stability" of my computer will last for a long time, until it completely breaks down. My body exhibits the same kind of stability (for a few decades, at least), so much so that friends recognize me when they see me and every year the IRS can claim my tax returns (no quantum uncertainty there). Stability is what we are built to care for. We care very little about the inner processes that lead to the formation of a tomato plant: we care for the tomatoes. We care very little for the microscopic processes that led a face to be what it is: we care for what "it looks like". At these levels stability is enormous. Shape, size, position are stable for a number of days, weeks, months, maybe years. Variations are minimal and slow. The more we get into the detail of what we were not built to deal with and the more confused (complex and chaotic) matter looks to us, with zillions and zillions of minuscule particles in permanent motion. Science was originally built to explain the world at the "natural" level. Somehow scientists started digging into the structure of matter and reached for lower and lower levels. The laws of Physics got more and more complicated, less and less useful for the everyman. Even more surprising, each level of granularity (and therefore complexity) seems largely independent of the lower and higher
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levels. Sociology doesn't really need Anatomy and Anatomy doesn't really need Chemistry and Chemistry doesn't really need Quantum Theory. The smaller we get the more the universe becomes messy, incomprehensible, continuously changing, very unstable. We have grown used to thinking that this is the real universe, because the ultimate reduction is the ultimate truth. The surprising thing is that at higher levels we only see stability. How does chaos turn into stability? We witness systems that can create stability, order, symmetry out of immense chaos. One answer is that maybe it is only a matter of perception. Our body was built to perceive things at this level, and at that level things appear to be stable just because our senses have been built to perceive them stable. If our senses weren't able to make order out of chaos, we wouldn't be able to operate in our environment. Another answer, of course, could be that all other levels are inherently false... A Self-organizing Universe The main property of neural networks is feedback: they learn by doing things. Memory and learning seem to go hand in hand. Neural networks are "self-organizing" objects: response to a stimulus affects, among other things, the internal state of the object. To understand the behavior of a neural network one does not need to analyze the constituents of a neural network; one only needs to analyze the "organization" of a neural network. Physics assumes that matter has no memory and that the laws of Nature entail no feedback. Physics assumes that all objects in the universe are passive and response to a stimulus does not affect the internal state of the object: objects are non-organizing, the opposite of self-organizing objects. To understand the behavior of a physical object, one needs analyze its constituents: the object is made of molecules, which are made of atoms, which are made of leptons and quarks, which are made of... There is no end to this type of investigation, as history has proved. The behavior of matter still eludes physicists even if they have reached a level of detail that is millions of times finer-grained than the level at which we operate. There is no end to this type of investigation, because everything has constituents: there is no such thing as a fundamental constituent.
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Just like there is no such thing as a fundamental instant of time or point of space. We will always be able to split things apart with more powerful equipment. The equipment itself might be what creates constituents: atoms were "seen" with equipment that was not available before atoms were conceived. In any case it is the essence itself of a "reductionist" (constituent-oriented) science that requires scientists to keep going down in levels of detail. No single particle, no matter how small, will ever explain its own behavior. One needs to look at its constituents to understand why it behaves the way it behaves. But then it will need to do the same thing for each new constituent. And so on forever. Over the last century, Physics has gotten trapped into this endless loop. Could matter in general be analyzed in the same that we analyze neural networks? Could matter be explained in terms of selforganizing systems? Neural networks remember and learn. There is evidence that other objects do so too: a piece of paper, if folded many times, will "remember" that it was folded and will learn to stay folded. Could we represent a piece of paper as a selforganizing system? Nature exhibits a "hierarchy" of sort of self-organizing systems, from the atomic level to the biological level, from the cognitive level to the astronomical level. The "output" of one selforganizing system (e.g. the genome) seems to be a new selforganizing system (e.g. the mind). Can all self-organizing systems be deduced from one such system, the "mother" of all selforganizing systems? We are witnessing a shift in relative dominant roles between Physics and Biology. At first, ideas from physical sciences were applied to Biology, in order to make Biology more "scientific". This led to quantifying and formalizing biological phenomena by introducing discussions on energy, entropy and so forth. Slowly, the debate shifted towards unification of Physics and Biology, rather then unidirectional import of ideas from Physics. Biological phenomena just don't fit in the rigid deterministic model of Physics. Then it became progressively clear that biological phenomena cannot be reduced to Physics the way we know it. And now we are moving steadily towards the idea that Physics has to be changed to cope with biological phenomena, it has to absorb concepts that come from Biology. In order to accommodate biological concepts, such as selection and feedback, in order to be able to encompass neural and living systems, which evolve in a Darwinian fashion and whose behavior is http://www.thymos.com/tat/physics.html (63 of 68)25/07/2003 14:37:26
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described by nonlinear equations, Physics will need to adopt nonlinear equations and possibly an algorithm-oriented (rather than equation-oriented) approach. Almost all of Physics is built on the idea that the solution to a problem is the shortest proof from the known premises. The use and abuse of logic has determined a way of thinking about nature that tends to draw the simplest conclusions given what is known (and what is not known) about the situation. For example, it was "intuitive" for scientists to think that the immune system creates anti-bodies based on the attacking virus. This is the simplest explanation, and the one that stems from logical thinking: a virus attacks the body, a virus is killed by the body; therefore the body must be able to build a "killer" for that virus. The disciplines of life constantly remind us of a different approach to scientific explanation: instead of solving a mathematical theorem through logic, nature always chooses to let things solve themselves. In a sense, solutions are found by natural systems not via the shortest proof but thanks to redundancy. The immune systems creates all sorts of antibodies. An invading virus will be tricked into "selecting" the one that kills it. There is no processor in the immune system that can analyze the invading virus, determine its chemical structure and build a counter-virus, as a mathematician would "intuitively" guess. The immune system has no ability to "reason" about the attacking virus. It doesn't even know whether some virus is attacking or not. It simply keeps producing antibodies all the time. If a virus attacks the body, the redundancy of antibodies will take care of it. This represents a fundamental shift of paradigm in thinking about Nature. For many centuries, humans have implicitly assumed that the universe must be behaving like a machine: actions follow logically from situations, the history of the universe is but one gigantic mathematical proof. It is possible that the larger-scale laws of nature resemble very little a mathematical proof. They might have more to do with randomness than with determinism. The distinction between instruction and selection is fundamental. Physics has evolved around the concept of instruction: mathematical laws instruct matter how to behave. Selection entails a different set of mind: things happen, more or less by accident, and some are "selected" to survive. The universe as it is may be the product of such selection, not of a logical chain of instructions. Physics is meandering after the unified theory that would explain all forces. What seems more interesting is a unification of physical and biological laws. We are now looking for the ultimate
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theory of nature from whose principles the behavior of all (animate and inanimate) systems can be explained. Particles, waves and forces seem less and less interesting objects to study. Physics has been built on recurring "themes": planets revolve around the sun, electrons revolve around the nucleus; masses attract each other, charged particles attract each other. Still, Physics has not explained these recurring patterns of Nature. Biology is explaining its recurring patterns of evolution. A new scenario may be emerging, one in which the world is mostly nonlinear. And somehow that implies that the world self-organizes. Self-organizing systems are ones in which very complex structures emerge from very simple rules. Self-organizing systems are about where regularity comes from. And self-organizing systems cannot be explained by simply analyzing their constituents, because the organization prevails: the whole is more than its parts. The Universe as the Messenger One pervasive property of the universe and everything that exists is communication. Things communicate all the time. The Austrian physicist and philosopher Ernst Mach, held in great consideration by Einstein, had a vision of the universe that proved influential on all Twentieth century Physics. Newton defined inertial systems as systems which are not subject to any force. They move at constant or null speed. Systems that are accelerated are not inertial and, by magic, strange forces ("inertial forces") appear in them. Mach realized that all systems are subject to interactions with the rest of the universe and redefined inertial systems as systems which are not accelerated in the frame of fixed stars (basically, in the frame of the rest of the universe). The inertia of a body is due to its interaction with the rest of the matter in the universe. Mach's principle implies that all things communicate with all other things all the time. This universe appears to be built on messages. The dynamics of the universe is determined to a large extent by the messages that are exchanged between its parts (whether you look at the level of RNA, synapses or gravitation). Things communicate. It is just their nature to communicate. More: their interactions determine what happens next. Things communicate in order to happen. Life happens because of communication. We think because of communications.
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If all is due to messages, a theory of the universe should decouple the message from the messenger. Messages can be studied by defining their "languages". Maybe, just maybe, instead of sciences like Physics and Biology we should focus on the "language" of the universe. The Science of Impossibility: The End of Utopia It is intriguing that the three scientific revolutions of the last century all involved introducing limits to classical Physics. Newton thought that signals could travel at infinite velocities, that position and momentum could be measured simultaneously and that energy could be manipulated at will. Relativity told us that nothing can travel faster than the speed of light. Quantum Mechanics told us that we cannot measure position and momentum simultaneously. Thermodynamics told us that every manipulation of energy implies a loss of order. There are limits in our universe that did not exist in Newton's ideal universe. These limits are as arbitrary as laws and constants. Why these and not others? May they be just clues to a more general limit that constrains our universe? May they be simply illusions, due to the way our universe is evolving? Then Newton's world has been shaken to its foundations by Darwin's revolution. Natural systems look different now. Not monolithic artifacts of logic, but flexible and pragmatic side effects of randomness. By coincidence, while Physics kept introducing limits, Biology has been telling us the opposite. Biological systems can do pretty much anything, at random. Then the environment makes the selection. We have been evangelized to believe that nothing is forbidden in Nature, although a lot will be suppressed. Once all these views are reconciled, Newton's Utopia may be replaced by a new Utopia, with simple laws and no constraints. But it's likely to look quite different from Newton's. Where to, Albert? Further Reading Ashtekar Abbay: CONCEPTUAL PROBLEMS OF QUANTUM GRAVITY (Birkhauser, 1991) Barbour Julian: THE END OF TIME (Oxford Univ Press, 2000)
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Bohm David: THE UNDIVIDED UNIVERSE (Routledge, 1993) Bohm David: QUANTUM THEORY (Constable, 1951) Bohm David: WHOLENESS AND THE IMPLICATE ORDER (Routledge, 1980) Bohr Nils: ATOMIC THEORY AND THE DESCRIPTION OF NATURE (Cambridge University Press, 1934) Bunge Mario: QUANTUM THEORY AND REALITY (Springer, 1967) Davies Paul: ABOUT TIME (Touchstone, 1995) Deutsch David: THE FABRIC OF REALITY (Penguin, 1997) Ferris Timothy: THE WHOLE SHEBANG (Simon And Schuster, 1997) Flood Raymond & Lockwood Michael: NATURE OF TIME (Basil Blackwell, 1986) Gell-Mann Murray: THE QUARK AND THE JAGUAR (W.H.Freeman, 1994) Greene Brian: THE ELEGANT UNIVERSE (WW Norton, 1999) Guth Alan: THE INFLATIONARY UNIVERSE (Helix, 199#) Hawking Stephen: A BRIEF HISTORY OF TIME (Bantam, 1988) Heisenber Werner: THE REPRESENTATION OF NATURE IN CONTEMPORARY PHYSICS (Deadalus, 1958) Hoyle Fred, Burbidge Geoffrey, and Narlikar Jayant: A DIFFERENT APPROACH TO COSMOLOGY (Cambridge Univ Press, 2000) Kaku Michio: HYPERSPACE (Oxford University Press, 1994) Linde Andrei: PARTICLE PHYSICS AND INFLATIONARY COSMOLOGY (Harwood, 1990) Linde Andrei: INFLATION AND QUANTUM COSMOLOGY (Academic Press, 1990) Penrose Roger: THE EMPEROR'S NEW MIND (Oxford Univ Press, 1989)
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Price Huw: TIME'S ARROW AND ARCHIMEDE'S POINT (Oxford University Press, 1996) Prigogine Ilya: FROM BEING TO BECOMING (W. H. Freeman, 1980) Rees Martin: BEFORE THE BEGINNING (Simon And Schuster, 1996) Scott Alwyn: STAIRWAY TO THE MIND (Copernicus, 1995) Smolin, Lee: THREE ROADS TO QUANTUM GRAVITY (Weidenfeld and Nicolson, 2000) Von Neumann John: DIE MATHEMATISCHE GRUNDLAGEN DER QUANTENMECHANIK/ MATHEMATICAL FOUNDATIONS OF QUANTUM MECHANICS (Princeton University Press, 1932) Weinberg Steven: DREAMS OF A FINAL THEORY (Pantheon, 1993) Wigner Eugene: SYMMETRIES AND REFLECTIONS (Indiana Univ Press, 1967)
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Book reviews - Cognitive Science
This Month's Reviews Additions to the Bibliography on Mind and Consciousness) compiled by Piero Scaruffi | Check my essays | Cognitive Science news (Copyright © 2000 Piero Scaruffi | Legal restrictions )
Stenning, Keith : SEEING REASON (Oxford Univ Press, 2002) Dudai, Yadin: MEMORY FROM A TO Z (Oxford Univ Press, 2002) Damasio, Antonio: LOOKING FOR SPINOZA (Harcourt, 2003) Gregersen, Niels: FROM COMPLEXITY TO LIFE (Oxford Univ Press, 2003) O'Shaughnessy, Brian: CONSCIOUSNESS AND THE WORLD (Oxford Univ Press, 2002)
Forthcoming reviews To receive periodic news and updates on cognitive science, philosophy of mind, neurobiology, artificial intelligence, etc, ask to be added to my mailing list.
Previous months:
Armstrong, David Malet: THE MIND-BODY PROBLEM (Westview, 1999) Baker, Mark: : THE ATOMS OF LANGUAGE: THE MIND'S HIDDEN RULES OF GRAMMAR (Basic Books, 2001) Baars Bernard: A COGNITIVE THEORY OF CONSCIOUSNESS (Cambridge Univ Press, 1993) Barbour Julian: THE END OF TIME (Oxford Univ Press, 2000) Barnet Ann: THE YOUNGEST MINDS (SImon & Schuster, 1998) Blackmore, Susan: THE MEME MACHINE (Oxford University Press, 1998) Bohm David: WHOLENESS AND THE IMPLICATE ORDER (Routledge, 1980) Bohm David: THE UNDIVIDED UNIVERSE (Routledge, 1993) Breitenberg Valentino: VEHICLES: EXPERIMENTS IN SYNTHETIC PSYCHOLOGY (MIT Press, 1984) Burnham, Terry & Phelan, Jay: MEAN GENES (Basic, 2000)
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Book reviews - Cognitive Science
Butler Samuel: EVOLUTION (?, 1879) Cairns-Smith, Graham: EVOLVING THE MIND (Cambridge University Press, 1995) Calvin, William: HOW BRAINS THINK (Basic, 1996) Calvin William & Bickerton Derek : LINGUA EX MACHINA (MIT Press, 2000) Campbell Joseph: PRIMITIVE MYTHOLOGY: THE MASKS OF GOD (Viking, 1959) Capra Fritjof: THE WEB OF LIFE (Anchor Books, 1996) Carlson Richard: EXPERIENCED COGNITION (Lawrence Erlbaum, 1997) Cavalli-Sforza Luigi: GENES, PEOPLES AND LANGUAGES (North Point, 2000) Chalmers David: THE CONSCIOUS MIND (Oxford University Press, 1996) Churchland Paul & Churchland Patricia: ON THE CONTRARY (MIT Press, 1998) Clark, Andy: MINDWARE (Oxford Univ Press, 2000) Clark, Andy: ASSOCIATIVE ENGINES (MIT Press, 1993) Cohen Jonathan & Schooler Jonathan: SCIENTIFIC APPROACHES TO CONSCIOUSNESS (Erlbaum, 1997) Cowie, Fiona: WHAT'S WITHIN (Oxford Univ Press, 1998) Culbertson, James: SENSATIONS MEMORIES AND THE FLOW OF TIME (Cromwell Press, 1976) Cziko Gary: THE THINGS WE DO (MIT Press, 2000) Damasio, Antonio: THE FEELING OF WHAT HAPPENS (Harcourt Brace, 1999) Damasio Antonio: DESCARTES' ERROR (G.P. Putnam's Sons, 1995) Dawkins Richard: CLIMBING MOUNT IMPROBABLE (Norton, 1996) Dawkins Richard: Dawkins, Richard: THE BLIND WATCHMAKER (Norton, 1987) Dawkins Richard: THE EXTENDED PHENOTYPE (OUP, 1982) Deacon Terrence: THE SYMBOLIC SPECIES (Norton, 1998) DeDuve Christian: VITAL DUST (Basic, 1995) de Waal Frans: GOOD NATURED (Harvard Univ Press, 1996) Dennett, Daniel: KINDS OF MINDS (Basic, 1998) Dennett Daniel: DARWIN'S DANGEROUS IDEA (Simon & Schuster, 1995) Deutsch David: THE FABRIC OF REALITY (Penguin, 1997) Devlin, Keith J.: GOODBYE, DESCARTES (Wiley, 1998) DeWaal Frans: BONOBO: THE FORGOTTEN APE (University of California Press, 1997) Donald Merlin: ORIGINS OF THE MODERN MIND (Harvard Univ Press, 1991) Douglas, Mary: NATURAL SYMBOLS (Random House, 1970) Dreyfus Hubert: WHAT COMPUTERS CAN'T DO (Harper & Row, 1979) Dyson Freeman: ORIGINS OF LIFE (Cambridge Univ Press, 1999) Edelman Gerald: NEURAL DARWINISM (Basic, 1987) Edelman Gerald: TOPOBIOLOGY (Basic, 1988) Edelman Gerald: THE REMEMBERED PRESENT (Basic, 1989) Edelman Gerald: BRIGHT AIR BRILLIANT FIRE (Basic, 1992) Eichenbaum, Howard : COGNITIVE NEUROSCIENCE OF MEMORY (Oxford Univ Press, 2002) Eigen Manfred: STEPS TOWARDS LIFE (Oxford University Press, 1992)
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Book reviews - Cognitive Science
Flanagan Owen: DREAMING SOULS (Oxford Univ Press, 2000) Fodor, Jerry: THE MIND DOESN'T WORK THAT WAY (MIT Press, 2000) Fox Ronald: ENERGY AND THE EVOLUTION OF LIFE (Freeman, 1988) Freeman Dyson: ORIGINS OF LIFE (Cambridge Univ Press, 1999) Freeman Walter: SOCIETIES OF BRAINS (Erlbaum, 1995) Ganti Tibor: THE PRINCIPLE OF LIFE (Omikk, 1971) Gazzaniga Michael & LeDoux Joseph: INTEGRATED MIND (Plenum Press, 1978) Gazzaniga Michael: NATURE's MIND (Basic, 1992) Gisolfi Carl & Mora Francisco: THE HOT BRAIN (MIT Press, 2000) Goldberg, Elkhonon : THE EXECUTIVE BRAIN (Oxford Univ Press, 2001) Goldstein Kurt: THE ORGANISM: A HOLISTIC APPROACH TO BIOLOGY (American Book, 1939) Gould Stephen Jay: FULL HOUSE (Random House, 1996) Greenfield Susan: THE HUMAN MIND EXPLAINED (Henry Holt & Co, 1996) Greenfield, Susan: THE HUMAN BRAIN (Basic, 1999) Gregory Richard: MIND IN SCIENCE (Cambridge Univ Press, 1981) Hameroff Stuart: ULTIMATE COMPUTING : BIOMOLECULAR CONSCIOUSNESS AND NANOTECHNOLOGY (Elsevier Science, 1987) Heidegger Martin: BEING AND TIME (1962) Herbert, Nick: ELEMENTAL MIND (Dutton, 1993) Herbert, Nick: FASTER THAN LIGHT: SUPERLUMINAL LOOPHOLES IN PHYSICS (Dutton, 1988) Herbert, Nick: QUANTUM REALITY: BEYOND THE NEW PHYSICS (Doubleday, 1985) Hobson, Allan: THE CHEMISTRY OF CONSCIOUS STATES (Little & Brown, 1994) Ingebo-Barth, Denise: THE CONSCIOUS STREAM (Universal Publisher, 2000) Ivry Richard & Robertson Lynn: THE TWO SIDES OF PERCEPTION (MIT Press, 1998) Jibu Mari & Yasue Kunio: QUANTUM BRAIN DYNAMICS AND CONSCIOUSNESS (John Benjamins, 1995) Jones Steven: LANGUAGE OF GENES (Harper Collins, 1993) Jouvet, Michel: THE PARADOX OF sLEEP: THE STORY OF DREAMING (MIT Press, 1999) Karmiloff-Smith Annette: BEYOND MODULARITY (MIT Press, 1992) Kim, Jaegwon: MIND IN A PHYSICAL WORLD (MIT Press, 1998) Lakoff, George: PHILOSOPHY IN THE FLESH (Basic, 1998) Lakoff, George: WOMEN, FIRE AND DANGEROUS THINGS (Univ of Chicago Press, 1987) Lakoff, George: METAPHORS WE LIVE BY (Chicago Univ Press, 1980) Lane, Richard & Nadel, Lynn: COGNITIVE NEUROSCIENCE OF EMOTION (Oxford Univ Press, 2000) Layzer, David : COSMOGENESIS (Oxford University Press, 1990) Levine, Joseph: PURPLE HAZE (Oxford Univ Press, 2000) Lotitz, Donald: HOW THE BRAIN EVOLVED LANGUAGE (Oxford Univ Press, 1999) Lynch, Michael: THE NATURE OF TRUTH (MIT Press, 2001) MacLean Paul: THE TRIUNE BRAIN IN EVOLUTION (Plenum Press, 1990) MacPhail Euan: THE EVOLUTION OF CONSCIOUSNESS (Oxford University Press, 1998) http://www.thymos.com/mind/index.html (3 of 5)25/07/2003 22:46:51
Book reviews - Cognitive Science
Margulis, Lynn: WHAT IS LIFE (MIT Press, 1995) Marshall, I.N. & Zohar Danah: QUANTUM SOCIETY (William Morrow, 1994) Maturana Humberto: AUTOPOIESIS AND COGNITION (Reidel, 1980) Maynard Smith, John & Szathmary Eors: THE ORIGINS OF LIFE (Oxford University Press, 1999) Maynard Smith, John & Szathmary Eors: THE MAJOR TRANSITIONS IN EVOLUTION (W. H. Freeman, 1995) McGinn Colin: THE PROBLEM OF CONSCIOUSNESS (Oxford Univ Press, 1991) McGinn, Colin: THE MYSTERIOUS FLAME (Basic, 1999) Mead, George Herbert: THE PHILOSOPHY OF THE ACT (Univ of Chicago Press, 1938) Milner Peter: THE AUTONOMOUS BRAIN (Lawrence Erlbaum, 1999) Mithen Steven: THE PREHISTORY OF THE MIND (Thames and Hudson, 1996) Monod Jacques: CHANCE AND NECESSITY (Knopf, 1971) Morowitz Harold: BEGINNINGS OF CELLULAR LIFE (Yale University Press, 1992) Murchie Guy: SEVEN MYSTERIES OF LIFE (Houghton Mifflin, 1978) Norretranders Tor: THE USER ILLUSION (Viking, 1998) Ornstein, Robert: MULTIMIND (Houghton Mifflin, 1986) Penrose Roger: SHADOWS OF THE MIND (Oxford University Press, 1994) Pinker Steven: HOW THE MIND WORKS (Norton, 1997) Pinker, Steven: WORDS AND RULES (Basic, 1999) Plotkin Henry: EVOLUTION IN MIND (Allen Lane, 1997) Putnam, Hilary : THE THREEFOLD CORD: MIND, BODY AND WORLD (Columbia Univ, 1999) Reiser, Morton: MEMORY IN MIND AND BRAIN (Basic, 1990) Ridley Matt: THE RED QUEEN (MacMillan, 1994) Ridley Mark: THE COOPERATIVE GENE (Free Press, 2001) Rolls, Edmund : : THE BRAIN AND EMOTION (Oxford Univ Press, 1999) Rucker Rudy: INFINITY AND THE MIND (Birkhauser, 1982) Searle John: MIND, LANGUAGE AND SOCIETY (Basic, 1998) Sedlmeier, Peter: FREQUENCY PROCESSING AND COGNITION (Oxford, 2002) Sheldrake Rupert: A NEW SCIENCE OF LIFE (J.P. Tarcher, 1981) Sheldrake Rupert: PRESENCE OF THE PAST (Grimes, 1988) Shettleworth, Sara: COGNITION, EVOLUTION AND BEHAVIOR (Oxford Univ Press, 1998) Stapp Henry: MIND, MATTER AND QUANTUM MECHANICS (Springer-Verlag, 1993) Thompson D'Arcy: ON GROWTH AND FORM (Cambridge University Press, 1917) Tipler Frank: THE PHYSICS OF IMMORTALITY (Doubleday, 1995) Todes, Samuel: BODY AND WORLD (MIT Press, 2001) Tulving Endel & Craik Fergus: THE OXFORD HANDBOOK OF MEMORY (Oxford Univ Press, 2000) Turner, Scott: THE EXTENDED ORGANISM (Harvard Univ Press, 2000) Tye, Michael: TEN PROBLEMS OF CONSCIOUSNESS (MIT Press, 1995) Wills, Christopher & Bada, Jeffrey: THE SPARK OF LIFE (Perseus, 2000) Wilson, Edward Osborne: SOCIOBIOLOGY (Belknap, 1975)
http://www.thymos.com/mind/index.html (4 of 5)25/07/2003 22:46:51
Book reviews - Cognitive Science
Winson Jonathan: BRAIN AND PSYCHE (Anchor Press, 1985) Wolf, Fred Alan: MIND INTO MATTER (Moment Point, 2001) Wolf, Fred Alan: STAR WAVE: MIND, CONSCIOUSNESS AND QUANTUM PHYSICS (Macmillan, 1984) Wright, Robert: THE MORAL ANIMAL (Vintage Books, 1995) Young John: THE MEMORY SYSTEM OF THE BRAIN (University of California Press, 1966) Zohar Danah: QUANTUM SELF (William Morrow, 1990) Cognitive Ethology: A reader The whole bibliography
(Copyright © 2000 Piero Scaruffi | Legal restrictions - Termini d'uso )
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