New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach

New Thinking in Complexity for the Social Sciences and Humanities

Ton Jörg

New Thinking in Complexity for the Social Sciences and Humanities A Generative, Transdisciplinary Approach

Ton Jörg Centre for Education and Learning (former IVLOS) University of Utrecht Utrecht The Netherlands [email protected]

ISBN 978-94-007-1302-4 e-ISBN 978-94-007-1303-1 DOI 10.1007/978-94-007-1303-1 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2011928083 © Springer Science+Business Media B.V. 2011 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

To Werner, original source of inspiration

Acknowledgements

This book is about the problem of complexity and how this can be tackled from a scientific perspective. The inspiration for this book has a long history, of almost forty years, and the path of creation was a tortuous path indeed. Many traps, such as blind spots, blinding paradigms and learned ignorance had to be circumvented before finally arriving to the writing of this book. Many others were involved, but Werner Holländer was the unexpected, generating source of inspiration for this book, which was as much a surprise for him as it was for me myself. Since my membership of the special interest group “Chaos and Complexity Theory” of the yearly educational conference AERA in 1998, I have been inspired by the conversations in this particular group of educational thinkers about complexity. These people and conversations made me more and more aware that the concept of complexity in use could be considered as a deeply contested concept. The study of complexity showed to be a hardy perennial for thinking about complexity; not only for education but for all of our sciences. To deal with this problem of complexity new thinking in complexity seemed very much needed. I am very grateful to all people which have supported the proposal for this book, i.e. Klaus Mainzer, who is author of a book on thinking in complexity about complexity by Springer, and Dorothy Robbins, both of whom gave such a wonderful recommendation for the publisher, thereby enabling this book in Springer’s interdisciplinary program of “Springer: Complexity”. Some people showed the value of critical and generous colleagues for writing this book, like Weichao Chen, in her critical comments on difficult parts about causal complexity modeled within the (extended) causal framework, and René van de Kraats, in his joyful comments on some of my complex texts. Other readers of parts of the texts in this book, like Theo Niessen, Robert Ulanowicz and Jayne Fleener, gave me the strong feeling to be on the right track in dealing with the problem of complexity. My deep thanks go to Deborah Osberg, Bill Doll and Donna Trueit, the editors of the international (on-line) journal Complicity. They have stimulated my confidence on the contested topic of complexity for education, by choosing my contribution on the topic of complexity and education for a special issue of this journal, with critical but supportive comments of different specialists in the field of education.

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Acknowledgements

Special thanks go to Professor Rongbin Lee who made me aware of both the necessity and the promise to go beyond the field of learning and education, and to overcome the learned incapacities in this and in other fields of science, to become explanatory of the complexities involved in these new fields. If this book may show to have didactic characteristics and to be of value for educational purposes, it may have found its inspiration from my background as educational researcher in a department of teacher education at the University of Utrecht in the Netherlands. Finally, and in especial, I would like to thank Rob Houwen who was very helpful during so many years, patiently making all the drawings in this book. During all of the time of writing of this book, Harmen van Paradijs, as contact with the publisher of this book, gave me the wonderful feeling of creativity in writing this book by offering the time and space needed to be really creative during the whole period of writing, thereby avoiding the bad connotations linked to the rather awkward word ‘deadline’. The Netherlands

Houten

Contents

  1 Mission of the Book..................................................................................

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  2 Introduction..............................................................................................

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  3 The Crisis in the Social Sciences............................................................. Introduction................................................................................................ The Crisis in Science and Society.............................................................. Reflecting on the Crisis.............................................................................. What’s the Use of Crisis?........................................................................... Crisis: Danger or Opportunity?.................................................................. Theory of the Crisis................................................................................... The Crisis................................................................................................... Mission of the Book................................................................................... ‘Solving’ the Crisis.................................................................................... Steps to Be Taken.......................................................................................

17 17 20 22 25 26 28 33 34 35 39

  4 Giving Birth to a New Science – Setting the Agenda............................ Introduction................................................................................................ Thinking About Complexity...................................................................... Giving Birth to a New Science?................................................................. An Agenda for a New Science................................................................... Understanding Complexity Anew – A Note for the Reader...................... Starting New Thinking in Complexity.......................................................

43 43 44 45 46 47 48

  5 A New Agenda for the Social Sciences................................................... Introduction................................................................................................ New Thinking for a New Science.............................................................. On Becoming Reflective About Our Viewing and Doing Science....... Escaping Old Thinking About the Complexity of Reality.................... On Becoming Aware of Potential New Ways of Knowing................... New Thinking About Interaction.......................................................... New Thinking About Causality............................................................ New Thinking About the Unit of Study................................................

53 53 54 55 58 59 60 61 61 ix

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Contents

Linking of All New Thinking – A Programmatic View........................ New Framework.................................................................................... What Is the Use of a Programmatic View?...........................................

62 63 64

  6 On Becoming Reflective About Our Viewing and Doing Science........ Introduction................................................................................................ Why Should We Become Reflective?................................................... What Is the Meaning of Becoming Reflective?.................................... What Is the Meaning of Becoming Reflective About Science?............ What to Reflect About?......................................................................... How to Reflect?.....................................................................................

69 69 71 72 77 78 82

  7 The Reality of Reality.............................................................................. Introduction................................................................................................ New Thinking About Reality..................................................................... A Transdisciplinary Reality?..................................................................... Reality as a Choice?................................................................................... Vygotsky About the Reality of the Real[m].............................................. New Reality for Science?........................................................................... A Realist Version of Reality...................................................................... Reality and New Thinking in Complexity................................................. New Thinking in Complexity About the Complexity of Reality............... A New Science About a New Reality........................................................ Thinking in Complexity............................................................................. Complexity and Science............................................................................ Building a New Science About a Complex Reality................................... A New Reality............................................................................................

85 85 89 90 92 93 95 97 99 100 102 103 105 109 111

  8 New Ways of Knowing About the Complexity of Reality: The Epistemological Problem................................................................. Introduction................................................................................................ Epistemology, You Never Walk Alone!..................................................... How to Go On?.......................................................................................... A New Foundation..................................................................................... A New Framework of Knowing................................................................. Epistemology and the Real Complexity of Reality.................................... How Complex Are the New Ways of Knowing?....................................... The Struggle of Escape.............................................................................. Finding an Answer to the Methodological Challenge............................... New Language...........................................................................................

115 115 118 123 123 124 126 129 130 134 135

  9 An Introduction to the Chaps. 10–12..................................................... 137 The Art and Practice of Building a New Science – A Transdisciplinary Approach......................................................... 137 The Agenda for a New Science.................................................................. 139

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A Programmatic View for a TD Approach................................................ 141 A Short Preview......................................................................................... 143 A New Methodology with New Tools of Thought.................................... 145 10 Rethinking Interaction............................................................................ Introduction................................................................................................ Interaction.................................................................................................. Reinvention of Interaction.......................................................................... How to Go On?..........................................................................................

147 147 148 150 153

11 Rethinking Causality............................................................................... Introduction................................................................................................ New Thinking About Causality................................................................. Complexity of Causality............................................................................ A Short History of Causality in the Social Sciences.................................. The Introduction of the Causal Framework............................................... How to Go On?.......................................................................................... Bootstrapping Within the Causal Framework............................................ Overcoming the Explanatory Gap............................................................. Extending the Causal Framework.............................................................. Modelling Causal Interaction..................................................................... Causal Effects over Time........................................................................... Non-Linearity of Reciprocal Causal Effects.............................................. Conclusions About Extended Causal Framework (ECF)..........................

155 155 156 159 160 161 162 163 165 168 169 170 174 175

12 Rethinking the Unit of Study.................................................................. Introduction................................................................................................ Unit of Study.............................................................................................. From the Simple to the Complex............................................................... Networks and Generative Systems............................................................ A New Unit for Conceptualizing Complexity........................................... The Complex ‘Work’ of Causal Networks................................................ From Simplicity to Complexity – A Transdisciplinary View.................... Explaining Emergent Dynamic Complexity as a Condition for Effective Complexity.................................................................. Complexifying Modelling..................................................................... From the Simple to the Complex Unit of Networks..................................

179 179 180 181 184 185 187 188

13 The Complexity of Complexity............................................................... Introduction................................................................................................ The Complexity of the Concept of Complexity......................................... A New Approach of the Complexity of Reality........................................ Generative Complexity......................................................................... A Generative Approach of Complexity................................................ New Thinking in Complexity....................................................................

197 197 198 199 200 203 204

189 189 192

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14 The Complexity of Human Interaction.................................................. Introduction................................................................................................ Modelling the Complexity of Human Interaction...................................... The Need for New Tools for the Description and Explanation of Generative Complexity................................................................ What Makes Complexity Generative?....................................................... The Complexity Paradigm......................................................................... Distinctions to Be Made............................................................................. The Enhancement of Complexity.............................................................. Complex Modelling of the Complexity of Complexity............................. Dynamics of Complexity of Interaction.................................................... Landscapes of Effects Within State Hyperspaces...................................... Implications for New Thinking in Complexity.......................................... Steps Towards a New Science of Complexity........................................... Linking the Fundamental with the Practical.............................................. Enlarging the Space of the Possible...................................................... Spaces of Possibility............................................................................. Annex 14.1  Main Possibilities of Combinations of Interaction.............. Annex 14.2  State Hyperspaces for A and B with Composite Function of Effects, Depending on the Variables Affect and Motor Activity of the Brain................................................. Annex 14.3  Information About “Timewriter” by Lonny van Ryswyck, Atelier NL, The Netherlands.......

207 207 208

15 Summary and Conclusions..................................................................... Introduction................................................................................................ Elaborating on the General Aim of the Book............................................ Learning to Think in Complexity.............................................................. Elaborating on All the Steps Made............................................................ The Significance of Generative Complexity.............................................. How Far Have We Come?.......................................................................... Theorizing on Complexity for the Social Sciences and Humanities......... Conclusions................................................................................................ How to Understand the Building of a New Science?................................. The New Science....................................................................................... The Architecture of a New Science of Complexity................................... Causality and Explanation.................................................................... Complexity, Causality, and Novelty...................................................... Annex 15.1  Information About the “Sleeping Beauty” by Nadine Sterk, Atelier NL, The Netherlands...................

237 237 238 239 241 245 248 251 254 256 258 259 260 262

210 211 211 213 215 218 219 222 225 227 228 229 229 234 234 235

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Bibliography..................................................................................................... 267 Index.................................................................................................................. 281

Chapter 1

Mission of the Book

And the world’s complexity means that there is, now and always, more to reality than our science is able to dream of (Rescher 1998, p. 28; emphasis added)

In this book, the aim is to develop the foundation of a new science of complexity (ScoC), with a new focus on what we take as ‘the complexity of real-world complexity’. Inspired by the work of Niklas Luhmann, the aim is to re-describe the foundation of our Social Sciences and Humanities. We argue that this should be the new focus for a new science within the scientific realms of our sciences with their different disciplines, i.e., within the Social Sciences and Humanities. This new science of complexity can be taken as a kind of complementary science, born out of dissatisfaction with the way sciences are ‘normally’ operating in our society, showing their incapacity to deal with real complexity as a serious topic of study. We think it is time to open the social sciences and to go beyond the habitual, limiting views of these sciences (Wallerstein et  al. 1996). These social sciences have become entrapped in a kind of cul-de-sac in their viewing and doing science, as a result of the dominance of linear thinking in these sciences. Some speak about this critical situation in terms of a real crisis (e.g., Morin 2001). We have come to the conclusion that we desperately need innovation in our dealing with the reality of real-world complexity, to put an end to this entrapped situation. With the new science, we may put an end to the common trivialization of complex phenomena in the field of these sciences, such as the unfathomably complex human being. This reduction of complexity is very common within the social sciences, such as in the field of learning and education (cf.

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_1, © Springer Science+Business Media B.V. 2011

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1 Mission of the Book

von Foerster 1993) but also in the field of brain research, with scientists being ‘prisoners of description’ (see, e.g., Edelman and Tononi 2000). In our effort of developing a new science of complexity, based on new thinking in complexity, we express the firm hope that this new science will open a new way of viewing and doing science within the social sciences. It may make an end to the limiting way of viewing and doing science within the traditional scientific realms of the real.1 The opening may lead to the innovation of the social sciences and humanities and may improve their quality by showing the unexpected and hitherto unknown ‘world of the possible’ (Kauffman 1993, p. 375; emphasis added). This world is very much about the enlarged space of the possible (Osberg 2009); that is, about the hitherto unknown realms of possibilities. This world, we argue, is the world of real-world complexity. This complex world, we argue, is still to be explored. With Nicholas Rescher (1998), we fully support the notion that “complexity is self-potentiating”. Of course, this is not selfevident. It demands for explanation, in terms of how complexity may really ‘work’ in the scientific realms of the scientific enterprise. This is what this book is about: to build a new framework of complexity that is based on the reframing of complexity as a new concept and a new tool for use in our sciences. This demands for rethinking of our basic concepts in use in our doing science, like the concepts of ‘causality’ and that of ‘interaction’. It also demands for a different ontology and epistemology, in their fundamental connectedness. By adopting the new science of complexity, we are ready for enlarging our capacity to deal with the complexity of real-world complexity. This may imply the enlarging of the space of the possible, in terms of a more true understanding of the complexity of real-world complexity. We also focus on a better understanding of the forces, structures and mechanisms that drive and sustain the dynamics of complexity of the vast and complex dynamical systems in our complex real world. It is our hope for the future that we can convince the reader that we need a more practical kind of science for being able to deal with the big questions and issues in the real world (cf. Scheffer 2009, p. 8, and p. 327). These are the questions and issues that are still unanswered and are still waiting for an answer. We support the challenging view of Marten Scheffer, that “we need good science to help 1

 cf. mission of European initiative of Institute Para Limes.

1 Mission of the Book

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us shape the future” (Scheffer 2009, p. 8). Although it remains questionable what ‘good’ science will be, we may actually know what ‘bad’ science is. Only by linking the fundamental with the practical we may be able to shape the future of our society and humanity at large. This may result in a generative approach that can be developed into a general transdisciplinary approach, for use in the different scientific realms of our sciences and their disciplines. This generative approach is about the fundamental, generative nature of complexity. This is the reason why the focus is on generative complexity. The new approach involves the acceptance of the (hitherto) unknown, the unexpected and the unforeseeable.2 The new science of complexity has the aim to become explanatory about this generative nature of complexity. Only then we may become explanatory about the generativity of complexity, which we view to be the key to an understanding of complexity as self-potentiating (Rescher 1998, p. 28; emphasis added). In explaining and understanding generativity as the key to a better understanding of real-world complexity, we may find an answer to the question “how we come to see things in new ways” (Schön 1987, p. 138). In our analysis of the crisis in our sciences we come to the conclusion that we are still the captives of old thinking. Although we may know that “nothing in the social world actually happens mechanistically” (Bhaskar 2002, p. 249, fn. 39), we still seem to take “mapping mechanistic models to reality as the core of science” (Scheffer 2009, p. 274). The rejection of this stance, we argue, may be opening for a different view of reality: as a complex, nonlinear reality (cf. Mainzer 2004, p. 407). Although we may know that ‘the problem of causality’ is still an unsolved problem in our sciences, we are still operating on the basis of what Susan Oyama has described as “the Central Dogma of one-way flow of causality”, which is still our guiding metaphor in causal thinking about the real (see Oyama 1989, p. 29). This is why our new science of complexity, in its fundamental critique on viewing and doing science as usual within the social sciences, may open a new window upon reality and possibly even a ‘re-enchantment of reality’ (Bhaskar 2002, p. 242). We are also of the opinion that the new science offers a new opportunity “to humanize determinism”, in the words of the  See ‘Charter of transdisciplinary’, article 14, at http://basarab.nicolescu.perso.sfr.fr/ciret/english/ charten.htm

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Russian psychologist Lev Vygotsky (1997). We fully support Edgar Morin’s statement that complexifying is a way of humanizing the sciences3 (Morin 2002, p. 9). We argue in this book that determinism can be viewed differently: as more dynamic and fluid than has always been done in our history of philosophy and the sciences. We introduce the complex notion of ‘fluid determinism’. This fluid version of determinism is about the processes of causal influencing in interaction within interactive relationships, showing a fluid interplay of forces as a kind of shaping forces over time, with (causal) effects as “reciprocal effects of one on the other” (Follett 1924; emphasis added). These effects may cumulate over time: both in a linear and in a potential non-linear way! The shaping of one another in dyadic human interaction may happen by those impelling causal forces that interpenetrate each other’s systems as complex systems (cf. van der Veer and Valsiner 1994, p. 213; Luhmann 2002, p. 182). The causal dynamics involved in this emergent kind of interaction, evolving over time, can be described as a kind of complex process of dynamic interweaving. This complexity of interweaving can and better should be linked to network thinking for new thinking in complexity in our sciences (cf. Barabási 2003). The complexity involved can be characterized by different individual and interpersonal parameters (see Smith and Stevens 1999, p. 408). From our new complexity perspective, this kind of fluid determinism through complex, dynamic interweaving is taking place within webbed networks with their webbed interactions within relational networks. It is the interweaving of the relationships within these dynamic loop networks that is generating potential nonlinear multiplier effects over time, such as Snowball Phenomenon, Butterfly Effect, as examples of bootstrapping effects. More specifically, we focus on complex, hypercyclic webs, with dynamic, web-like structures; that is, structures of dynamically interconnected loops with nonlinear, hypercyclic couplings and their hypercyclic organization (Kauffman 1993, p. 359, p. 361). These couplings of cycles itself, with their coupled activity as emerging from the causal dynamics of impelling forces and causal effects, exerted within the causal loops of interactive relationships, can be taken as dynamic unities of ensembles. The responses of the activities involved are complex responses to a reciprocal kind of ­relating (see Follett 1924; see also Follett, in Drucker et al. 3

 “complexifier, c’est humaniser les sciences” (Morin 2002, p. 9).

1 Mission of the Book

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1995, pp. 42, 43). For the case of dyadic human interaction, with interaction within a context or environment being part of the functioning of a whole, this implies a kind of triangular model of a fundamental, complex unity, with reciprocal interdependence (cf. Mainzer 2004, pp. 115–117). The human development can be modelled as a kind of spiral development towards higher levels, potentially generating such a spiral of development for both partners. This is how human beings can make one another by shaping each other in their communicative human interaction (see Kauffman 1993, p. 371). This description of the complexity of human interaction is way beyond that of the machine metaphor, linked to the ­mechanistic version of determinism. We may conclude that the kind of new thinking in complexity is what humanizing such ­determinism is really about for the social sciences and humanities. As we argue below, the new approach may also bring with it a humanizing of these sciences and humanities themselves. We believe this is of special importance for the study of the lived realities of human being in these fields of science, in terms of realizing themselves. This is especially of significance for the field of learning and education, by opening and enlarging the space of the possible within a world of the ­possible (Kauffman 1993; italics in original; see also Osberg 2009; Jörg 2009). We are of the opinion that the new science of complexity may deliver the new tools of thinking needed for becoming descriptive and explanatory about the unfathomable complexity of human beings as part and parcel of real-world complexity within our social world. These tools are of relevance for all the disciplines of our social sciences. These tools of thinking include a reframing of complexity and a new framework for dealing with this real complexity. The new science is founded on a different ontology about real-world complexity and on new ways of knowing about this complexity. This epistemology is fundamentally an epistemology of the possible. With this epistemology about real-world complexity, we think we are able to open the world of the possible. This epistemology may offer the opening to address what Niklas Luhmann has described as the fundamental ‘uncertainty of knowledge’ (Luhmann 2002, p. 152). With Luhmann, we must realize that we cannot reach certainty of knowledge about the very complexity of complexity itself. We think, we may address this hitherto unknown complexity of real-world complexity, with this uncertainty included. This epistemology

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1 Mission of the Book

new Science of Complexity (ScoC)

real-world complexity with real-world dynamics

real-world research about real-world problems

Fig.  1.1  Triangular, reciprocal interdependency between the new Science of Complexity (ScoC), real-world complexity and real-world research

of complexity, which is simultaneously an epistemology of the possible, is opening new spaces of the possible, within a new world of the possible. Consequently, the new science of complexity offers an enlarged worldview about a richer sort of reality. The new thinking in complexity of the new science offers a new lens for viewing and doing science within the different disciplines: of viewing systems with new eyes. This can offer a real and realistic opening for a new kind of research. With Robson (2002), this kind of research may be described as ‘real world research’ about real-world problems within the real world, which is commonly related to real-world complexity: see Fig. 1.1, about the triangular, reciprocal interdependency between the new science and the problems at hand, with a ‘natural’ complexity involved. These problems are often about the so-called ‘big questions’ that are still unanswered in our sciences (Morin 2008). To find the answers, we need to become more inventive and creative in our way of thinking. This new real world research, with a focus on big questions and complex phenomena, may bring with it an opening of the social sciences. This can be the very opening as desired by different groups of various kinds of scientists all over the world (cf. Wallerstein et al. 1996; the Santa Fé group in the USA; the corresponding European initiative of Para Limes; the European Committee of Complex Systems; NWO 2008 and more local initiatives by universities). We are deeply convinced that we need a reframing of complexity to be able to generate a better understanding of real-world complexity and to deal with this natural complexity.

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Only by reframing complexity, we are able to understand how we may turn complexity into effective complexity. The ultimate challenge is to become more knowledgeable about how we may turn this effective complexity into a kind of advantageous complexity, for the benefit of humanity and society at large. So, we come to the conclusion that we need a true understanding of complexity to tackle the problems of complexity of real-world complexity. Because of its deep connection with real-world complexity, we think we may present our theorizing about complexity in terms of a so-called ‘grounded theory’: a grounded theory of complexity, which is fundamentally grounded in the causal power of causal forces, exerted in causal interaction within interactive causal relations (cf. Craver 2007, p. 224). These causal relations are reciprocal causal relations in our modelling of the causal processes involved in causal interaction between the fluid entities of the new dynamic unit of the ensemble, as a kind of system. The new science, with its grounded theory of complexity, is opening for a true understanding of the forces operating in the complexity of forces exerted in causal interaction within interactive relationships (cf. Scheffer et al. 2009, p. 8). The new science offers an explanatory framework of nonlinear causality about complex phenomena like those of bootstrapping, the known ‘Matthew effect’ and unknown ‘Jörg effect’ and other nonlinear effects, which may fuel transitions and transformations in the real world. These are complex phenomena that thrive on the shaping forces exerted through causal influences in interaction. The mechanisms at ‘work’ in this, are kind of causal, generative mechanisms within the extended causal framework, which are enabling for the driving forces that may enforce complex, nonlinear phenomena in our complex nonlinear reality. The new science, with the grounded theory of complexity, can be taken as an integrative science, because the same tools of thinking may be of use for the tackling of complexity in the variety of scientific realms and disciplines. What helps for this integration, is the creation of a new language, with new metaphors, like generative mechanisms, generative spaces and generative power as examples of ‘the ­generative metaphor’ (Schön 1993). This new language, with a new vocabulary and new metaphors, is constitutive for how we view reality in our new science of complexity: see Fig. 1.2. We believe this language has the power of inducing a language-effected

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1 Mission of the Book

new Science of Complexity (ScoC)

new reality

new language

Fig.  1.2  Triangular, reciprocal interdependency between the new science of complexity (ScoC), the new reality and the new language

reality, which is very much about the richer sort of reality: that is, the nonlinear complex reality of real-world complexity (cf. Mainzer 2007). Although we may speak about our new science as a shift of mind, we think it is of importance to stress that the new science of complexity should not be taken as a shift of paradigm, in terms of Thomas Kuhn. Our shift of mind, grounded in new thinking in complexity, has not the intention to replace the ‘normal’ science, as Kuhn viewed such a shift of paradigm. Although we do propose a shift of focus on complexity and a new thinking in complexity, resulting in a reframing of complexity, we would like to propose the new science of complexity as a complementary kind of science, which is a fundamental and foundational kind of science. The new science of complexity (ScoC) is fundamental, because of the new method, which is of relevance for all our scientific realms and disciplines and foundational because the new ScoC offers a new tool for deepening our view of doing ­science. It offers the perspective of a kind of retooling of our sciences by new ways of thinking about the complexity of real-world complexity (see Kuhn 1970). We do have the intention to present our new science of complexity as a keystone for the social sciences. We are of the opinion that this is the stone that has been disdained by the builders of these sciences. The new science presents not only complexity as a serious object of study for the different scientific realms of our

1 Mission of the Book

M. C. Escher’s “Metamorphose II” © 2010 The M.C. Escher Company B. V. Baarn - Holland. All rights reserved.

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sciences but also with a complementary method for constructing models of nonlinear complex systems in the natural and social sciences (cf. Mainzer 2004, p. 406). These complex models are the models we need for ‘modelling collective behaviour’ (Mainzer 2004, p. 407; see also Kauffman 1993, 1995a, b, 2008). We think all of this is i.e., of relevance for the social sciences, with their variety of disciplines. The new science of complexity, with its fundamental and foundational generative approach, can therefore be regarded as a transdisciplinary science. It will be a science with a generative, transdisciplinary approach of complexity as generative complexity. We hope the new science of complexity may expand the viewing and doing of science within the various fields and disciplines of our sciences, by taking into account the very complexity of various subjects of study in these scientific realms. Of course, by taking the complexity of real-world complexity as a serious subject of study, it may have consequences for the agenda of our sciences. Although our focus has been very much on the social sciences and humanities, we think it may bring with it unexpected openings to the natural sciences as well. Our modelling of the complexity of complex systems can be of use for the functioning of complex systems as wholes, in their interaction with one another, with the potential of transitory, transactional processes and patterns of development, generated through the (causal) power of bootstrapping (Kauffman 1993, 1995a, b; Scheffer 2009; Scheffer et  al. 2009). Although our modelling diverges from the main roads of modelling in biology, this modelling, based on the modelling of nonlinear causality within the extended causal framework (ECF), shows an unexpected explanatory power. As such, the new science may be the foundation for “good science that is needed to shape the future in the best way” (Scheffer 2009, p. 8). By the use of the generative power of generative complexity, for the use of shaping the future of our social sciences and humanities, it may become ‘a science of hope’. The fact is that complexity ìs self-potentiating (Rescher 1998, p. 28; emphasis added)

Chapter 2

Introduction

There is a new set of metaphors to describe ourselves, our minds, the universe, and all of the things we know in it (Brockman 1995, p. 21)

This book may be viewed as a complex book about the topic of complexity. It is both critical of the present state of art in the social sciences and constructive in its view about the possibility of building a new science for the future. A science that takes the complexity of reality as real. A science that is based on a new framework: a framework that does not yet exist. The new framework, therefore, will be a framework that has to be invented. The underlying idea and motive for the book is that the notion of complexity may humanize the social sciences, by opposing what may be called ‘the common trivialization’ of our worldview and of its inhabitants living in this world. As a consequence we really need to rethink our view, both in theory and in or for ­practice. The focus is on “bringing real people back in”1 in our doing and viewing science: through a new way of thinking in complexity. The new thinking may lead to a new science with a focus on the inherent complexity of human beings: the very complexity that has been denied so often. This perspective entails a broader view of reality as well: not a reality to be taken as a ‘delivered’ reality but a reality that is to be taken as less fixed and more fluid. Thinking about reality, we may turn reality as assumed, as fixed in our doing social science, into a more complex, that is: a richer reality for all. Thinking in complexity may therefore imply a kind of re-enchantment of reality, of a ­re-enchanted world (Bhaskar 2002, pp. 242–243). But not only for the sake of ­reality and how we may experience the world as such! The terrain of new thinking in complexity, as a way of complexifying reality, may also be viewed as a new ­terrain for social theorizing: as a terrain to be discovered for “the discovery of the enchantment of humankind.” (Archer 2000, p. 306) The field of social sciences may be regarded as

See Margaret Archer [2000], p. 306.

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T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_2, © Springer Science+Business Media B.V. 2011

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2 Introduction

an unmined research field. A field that might as well show up to be a terrain that still has to be invented, or re-invented in a certain way (Jörg 2004b). For this purpose, the field of social sciences may be taken as profoundly ‘known’ to be the field of the still unknown. Consequently, for scholars of social sciences, this field of science is the field of learning within the unknowable. This is the field to be entered, the field of a new potential: the potential of creating a new language, with new set of metaphors. These are the very metaphors that have to be invented, for a new kind of “description of ourselves, our minds, the universe, and all of the things we know in it.” (Brockman 2006, p. 21) The main focus of this book is on new thinking in complexity, with complexity to be taken as derived from the Latin word ‘complexus’: ‘that which is interwoven.’ (Morin 2001, p. 31) It may be stated right from the start that the new discourse of thinking in complexity “is not a ready-made discourse.” (Davis and Sumara 2006) This is not only true for education but for the social sciences in general as well. That makes the view presented a programmatic view, delineating a new path to be taken: a path to “learning within the unknowable” (see Flood 1999). The book starts with the notion that the complexity of reality should not be taken for granted but as reflecting the real. The new thinking wants to escape the greatest danger of our time: of linear thinking about a reality that is fundamentally a complex, nonlinear reality (Mainzer 2004). It is for instance the danger of a science fragmented in different disciplines and the danger of thinking in terms of linear causality. The focus will be on a trans-disciplinary approach, with different tools of thinking. Tools that may be valid for all of the different disciplines. So, the new thinking means a kind of rethinking too. It is because of such rethinking that a new framework may be built. It will be one of the main goals of the book to show how such a new framework will look like. So, it keeps a distance to the complexity theories that are around in the field of science such as the chaos theory, catastrophe theory and computational complexity theory, which are all based on mathematics. New thinking in complexity starts from the recognition of the role of the dynamics of complexity in reality. The rethinking may offer the opportunity of building a new science: of a more promising science for the future of the social sciences and humanities. It is the ­linking of science with a more complex, nonlinear notion of reality that offers the perspective of a new science. This may demand quite a bit of rethinking: a rethinking of the basic assumptions of our doing science as usual. The promise is not only a new science about a richer reality but also the promise of a new, richer culture. The new thinking in complexity has the potential of dealing with the apparently unsolvable problems with which human society is beset (see Bohm 1996, p. 77). These are the very problems and questions in our sciences whose best answers may have remained unknowable (Simon 1996). So, the new science will operate within the field of the unknowable. But how can one know what one does not know yet? It may look like an impossible mission. The question, then, is how this mission of solving these problems for our society, may have its course in the near future? Clearly not by ‘simply’ applying complexity sciences to human action. A better idea is to start with the recognition of the ‘real’ complexity, of ‘that which is ­interwoven’ and the dynamics of such complexity. By taking complexity seriously

2 Introduction

13

and not for granted, we may be able to humanize the sciences, i.e., the sciences related to the study of the human being. To do so, the human being should not be taken as an isolated individual, as a closed system, stripped of attributes that may be called ‘social’ but as a human being, being radically interwoven with his/her social environment. Instead of reducing the human being to an isolated individual, to generate predictable citizens, one may complexify the individual into a complex human being. This path of complexifying of the individual as subject of study may seem a paradoxical way of liberating the individual as an inherently limited subject of study in the social sciences. It is this path, which however, may turn out to be the path of cultivating humanity by humanizing the subject of study: the complex nonlinear human being (Stanley 2005, p. 143). To overcome the crisis of our time, by recognizing the lacuna of our thinking, we may ultimately find an opening for new thinking and find ways to realize “the possibility of the cultivation of humility, of real humanity.” (Jardine et al. 2006, p. 135; cf. Biesta 2006; Archer 2000) In this book a link will be made with the so-called ‘deprivation of our culture’: a deprivation fostered by the separation of the two cultures present in our Western ­culture, the so-called first and second culture, the famous distinction made by C. P. Snow (1959). Each one of these cultures seems to ‘deliver’ a reality being not only very different but also without having a connection. For now and in the future of our sciences it may be not only be desirable but even urgent to leave the jargon of each of these cultures behind; of cultures with their characteristic imprisonment of meaning and a separate scientific mentality, with their provincial limitations. The concomitant effects, like the effects on education, may be regarded as disastrous for our culture. Consequently, the question how to overcome the signalled deprivation of our culture will be an important topic in this book. It may be stated that a richer culture will be a culture in which Snow’s two distinct cultures are to be linked, comprising a kind of so-called ‘third culture.’ (Brockman 1995) A third culture that has benefits of the joint ‘production’ from these sources for a better future of both cultures and for society at large. Philosophy may be regarded as the key for both the invention and elaboration of the third culture. It may open our eyes for a new framework of viewing the world: “a conceptual framework that does not yet exist.” (Kauffman 1995b, p. 185) Of course art, with its continual renewal and innovation, maybe and should be part of that third culture as well. Both art and science may be conceived as a kind of rebellion against reality: of reality as usual (see e.g., Schama 2006; Gohr 2000; cf. Gilbert & George, in the Tate Gallery in London). It is this very similarity that makes it possible to draw parallels between the development of art and science, as will be illustrated in the drawings and figures of various artists in this book. The trans-disciplinary approach advocated here will be trans-disciplinary in two ways: firstly, by going beyond the separate disciplines within the fields of both natural sciences and social sciences and, secondly, by going beyond the separate cultures of the natural sciences and of the social sciences and humanities. The book is strongly inspired by the work of the Russian psychologist Lev Vygotsky.2 In his day, at the beginning of the twentieth century, he tried to build

He lived from 1896–1934.

2 

14

2 Introduction

a new science of psychology. He did so by starting from the notion of a scientific crisis in psychology; a crisis that was primarily a methodological crisis to him (see Vygotsky 1987b, p. 54). Building a new science meant for him that you had to invent such a new science (Vygotsky 1987b). He may be regarded as one of the first thinkers in complexity, by taking the very complexity of the subject of his study of psychology very seriously. He made clear that describing the complexity of human development is not enough; you need to become explanatory about the dynamics of complexity involved. The notions of qualitative change and transformation were central in his theorizing. His way of thinking, in terms of recognizing the potential nonlinear complex reality, was clearly a way of humanizing the subject of study of psychology. It is for this very reason that we may celebrate the new thinking in complexity: both for our doing science and for our society in the near future. Vygotsky’s view about building a new science will be linked to the view of Thomas Kuhn on the role of crises in the innovation of sciences, or the so-called “scientific revolutions”. (Kuhn 1970) It may be stated that Vygotsky was one of the first to recognize the role of crisis for a radical innovation of the science of concern: in this case that of psychology. In his writings he made clear that you cannot find a science; you have to invent it. The work of Kuhn convinced me both of the possibility and of the power of inventing a new science, to be based on a different worldview: about a world of being through becoming. Although the world itself may not change with a change in worldview, the scientist afterward may work in a different world, by seeing the world of their research-engagement differently (see Kuhn 1970, Ch. X). Ultimately, it may be shown that an innovated trans-disciplinary form of science can be developed, with a concomitant worldview of scientists. An innovated form that is fully able to deal with a richer reality. That is, a reality that is a more elaborated version of reality as taken for granted. In short: a fluid, potentially nonlinear version of reality. It will be a form that enables the possibility to view the human being as a complex human being, to be understood as a radical social being, with the potential of becoming a nonlinear being. In the end a new science with a new language may be developed for the future of the social sciences and humanities; a new science that is really promising for our society. A science that is liberating the human sciences from their conceptual blindness, i.e., from “the ‘learned incapacities’ and ‘disciplinary pathologies’ that restrict the horizons of modern academic discourse.” (Wertsch 1998, p. 4, p. 11) It may be hoped for that this book may contribute to a science in the twenty-first century that will be really different from that of the twentieth century. In its rebellion against simplicity and the inherent trivialization of the subject of study, the new science may become the building stone for a better society. Recognizing that the core of all the troubles we face today is “our very ignorance of knowing,” (Maturana and Varela 1987; cf. Simon 1996) and a concomitant lack of understanding our

2 Introduction

15

understanding (see von Foerster 1993), the new science may offer some promising answers to questions that have only seemed unknowable for so long. It is time to enter the space of the seemingly unknowable. Die ‘meist einfache’ Sachen sind sehr compliciert – man kann sich darüber nicht genug erwundern! (Nietzsche, in his work “Morgenröte”)3

3

 The ‘most simple’ cases are very complex, – one cannot be surprised enough about that!

Chapter 3

The Crisis in the Social Sciences

There is a new set of metaphors to describe ourselves, our minds, the universe, and all of the things we know in it (Brockman 1995, p. 21)

Introduction In this chapter the basic position of the book will be delineated. This is very much about the crisis of our social sciences and about a concomitant distorted worldview. Actually it is about the wrong foundation of our social sciences. History has shown how these sciences have evolved as a wrong kind of copy of the natural sciences, with a concomitant degeneration of the social sciences; a degeneration which has ultimately led to a contemporary crisis of our sciences and humanities and in society­ at large (cf. Sandywell 1996, p. xv). So, the topic of concern to be dealt with will be nothing less than The Future of the Sciences and Humanities (cf. Tindemans et al. 2002). The basic problem of the contemporary crisis seems to be that the system we are in as participating scientists is not able to reflect on itself (Sandywell 1996, p. xv). The functioning of us as scientists doing our science is comparable with the metaphor of the functioning of the eye which Giambattista Vico (1744/1984) used, in his book about The New Science: of the eye which is not able to see the eye itself (proposition 331). In direct relation to that inability, he described the need for the use of a mirror to see itself. This is also what we, as social scientists, need today for reflection on our doing science (Sandywell 1996, p. xv). As was the case for Vico, this reflection on the man-made construction of our world may be regarded as a turning point for our ‘wo/man-made’ view of the world. We may become aware that reality, as we perceive it, is not a given reality but an invented, ‘man-made’ reality (see e.g. Watzlawick 1984, p. 9; and Sandywell 1999, p. x). Just because it is a kind of invented reality, this reality cannot be the true reality (Watzlawick 1984, p. 9). This moment of reflection, of looking in the mirror, may make us aware that science itself, like reality, is not an independent T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_3, © Springer Science+Business Media B.V. 2011

17

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3 The Crisis in the Social Sciences

variable! Both kinds of invention may be considered to be a kind of choice made in our history of science: a choice which could have been a different choice, made by men (see e.g. Vico 1744/1968; Whitehead 1925/1967, p. 200). The real challenge for our viewing and doing science will be to recognize the crisis we are in, and the need to start reflecting on the crisis. Only then, it may be possible to develop a theory of the very crisis we are in, and how this crisis has led to degeneration of the social sciences and of our system of education. This may be illustrated by the notion of ‘trivialization’: of the trivialization of our children in the field of learning and education (von Foerster1993). In general it seems that science itself has become a closed system: “objective science finds its measure only in itself” (Jardine et al. 2006, p. 133). For this reason the system, not being able to reflect on the crisis it is in, may lose its very foundation of humanity. This may imply a danger of turning the system’s worldview into a dehumanized view of the world. By losing contact with the complexity of reality the system, as a closed system, loses contact with the complexly human of the human subject, and its view of the real may turn into a perverse version of reality (cf. Nock 1931). There is a real danger that we may not be able to escape this ­situation. The French pedagogue and philosopher Edgar Morin has warned us of this possibility in his recent book for UNESCO about Seven Complex Lessons in Education for the Future, by putting it this way: “the crisis worsens as fast as the incapacity to reflect on the crisis increases” (Morin 2001, p. 35). A condition like this can turn the system of education into a perverted system (Morin 2001). So the challenge is to reflect on the crisis for good reasons: to formulate a theory of the crisis we are in, and see how new thinking in complexity may be the foundation stone for the building of a new science. We think it is possible to develop an adequate theory of change which can be derived from the theory of the crisis. The challenge, then, is to formulate a theory of change, based on a new kind of thinking. It is on the shoulders of the psychologist Lev Vygotsky that it will be possible to find the line of thinking and reflection needed for the scientific enterprise of a real innovation in doing science, to escape the more traditional way of doing ­science. We may become aware that, to have a kind of scientific revolution in our sciences, we really need a corresponding kind of rebellion against ‘the system’. Einstein, for instance, has been described as such, in terms of “creator and rebel” (Hoffman and Dukas 1984). This kind of rebellion is similar to what happened in our history of art (see e.g. Gohr 2000, about René Magritte). The basic idea is that it may be possible to start new thinking in the social ­sciences: a new kind of thinking in complexity about a reality which is taken as fundamentally complex. It is this very complexity of reality which is real! We need to escape the very notion of reduction of that complexity. So, the kind of reductionism­, which is so characteristic of the traditional, ‘normal science’ (Kuhn 1970), has to be rejected as a ‘black hole’ in its operation at its centre (Reid 2007, p. 11; cf. Archer 2003, p. 15). It is of importance to see what kind of regularities in our doing and viewing of the social sciences are responsible for the inherent closure of operation of these sciences in our society at large. By looking in the

Introduction

19

mirror it may be possible to enforce a different kind of science for our times. It will be a science based on the notion of complexity, of thinking in complexity about the complexity of reality, with the aim to harness the very complexity of real-world complexity. The new science will involve a new framework about the hidden complexity of reality. Consequently, the new science will be about “a framework that does not yet exist” (Kauffman 1995b). So, it may be concluded that a new kind of thinking in complexity is needed to develop such a framework (see also Archer 1995, p. 5). The new science will be able to describe and explain complexity as self-potentiating; not only as a possibility but as a fact, according to the American philosopher Nicholas Rescher (1998): “The fact is that complexity is self-potentiating” (p. 28). He continues­ (on the same page) that “the world’s complexity means that there is, now and always, more to reality than our science is able to dream of” (Rescher 1998, p. 28). Consequently, we believe that the new science in the twenty-first century may become really different, in many ways, and “not be like science-as-weknow-it” (Rip 2002). The complexifying of reality may not only turn science into a new kind of ­science but also foster the humanizing of the social sciences (see Morin 2002, p. 9). This will be part and parcel of our mission in this book. Ultimately it is the cultivating and enchantment­of humanity that is the ultimate goal of this book. It will be a goal that is made possible by the celebration of complexity as a ‘real’ part of reality, i.e. the thinking in complexity about reality. To be more specific: of new thinking in complexity about a different kind of reality. The focus will be new thinking about the complexity of reality; that is, of the real world we live in. The possibility of enchantment of humanity and of humankind is therefore also based on the re-enchantment of reality (Bhaskar 2002). The new reality may, in the end, be a greater reality (Vico 1744/1968, par. 349). The new thinking in complexity is fundamentally about ­enlarging the spaces of the possible (Osberg 2009), with expanded spaces of ­explosive possibilities and potentialities (see Barab and Kirshner 2002). Reality, then, may be considered as an unexpected outcome, of complex processes of thinking, and not as a given reality (cf. Andreas Roepstorff 20071). The new reality goes beyond what Margaret Archer, for good ­reasons, described as “the provisional nature of known reality” (see Archer 2003, p. 36). In the end, we may think about realities as ­potentially plural: as essentially fluid instead of a single static reality. Even more importantly, we may think about realities as delivered realities: delivered by us as scientists, based on a common framework and a common view of the world we live in. It is along this line of complexifying reality itself, through a more open attitude, and by thinking in complexity, that we may oppose the tendencies of repression of the intrinsically reflexive, temporal, and dialogical dimensions of human experience (Sandywell 1996, p. xv). Tendencies that are contributing to the degeneration and perversion of a deprived culture, as manifestations of the very crisis we are in. A crisis which is both a scientific crisis and a crisis of the society we live in.

1

 In the journal Nexus, nr. 48, pp. 191–192.

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3 The Crisis in the Social Sciences Go, go, go, said the bird: human kind cannot bear very much reality T. S. Eliot, in “Burnt Norton” 1935, No. 1 of Four Quartets 2

The Crisis in Science and Society When speaking about the topic of crisis, we may speak about crises in different areas: of the crises in our society, and of the scientific crisis. For society at large we may refer to what Mary Clark (2002) has described as “the multiple crises that beset us” (p. xviii). These multiple crises may be viewed as responsible for what Mary Midgley has called “the deprivation” of our culture (see Midgley 2001, p. 179). Some describe the crisis in terms of the de-humanizing of the world we live in, the lack of humanity, or of a humanism which is not sufficiently human (Prigogine and Stengers 1984; Jardine et al. 2006; and Biesta 2006). Others speak frankly about The Wreck of our Western Culture, like John Carroll (1993), in his book about the state of art of humanism. Of course, the crises in our society and our dominant culture are not only a result of the scientific crisis, although there may be strong relationships in terms of the dehumanizing effects of scientific reasoning and the related worldviews (Prigogine and Stengers 1984; Sandywell 1996; cf. Vygotsky 1926/1997). The scientific crisis itself seems to be a kind of result of the so-called ‘normal science’ we are operating in as scientists (Kuhn 1970); the ‘normal science’, as described by Thomas Kuhn, with its inherent incapacity to create novelties of fact or theory as a fundamental characteristic (see p. 52). It is this very incapacity which may be taken as a kind of implicit effect of the ‘blinding paradigms’ scholars work with (Morin 2001). We may start thinking of what is fundamentally wrong about the position taken in the science of today, with its ontology and epistemology, leading to a crisis. Above we referred to Barry Sandywell (1996), who, in his recent book Reflexivity and the Crisis of Western Reason, openly states that this is a crisis of both the sciences and humanities, with its concomitant “repression of the intrinsically reflexive, temporal, and dialogical dimensions of human experience” (p. xv; cf. Archer 2003, p. 36). For Sandywell this is constitutive of the “contemporary crisis of the sciences and humanities” (Sandywell 1996, p. xv). It is his aim to develop a transdisciplinary approach “to criticize the ‘world models’ of dominant modes of analysis” (Sandywell 1996, p. xv). It is this rather ambitious aim that is the point of departure in this book too! We may also take a different view of science: not of a science operating as driven by a hidden agenda (Dennett 2003; cf. Tindemans et al. 2002, p. 235). This is actually an agenda that, according to Daniel Dennett, “tends to distort theorizing in all the social 2

 See Tristan Fecit (2000): available online at: http://www.tristan.icom43.net/quartets/norton.html

The Crisis in Science and Society

21

sciences and life sciences” (Dennett 2003, p. xi). All of this may lead to a distorted view of reality itself, with scientists as the normal ‘deliverers’ of such a distorted kind of reality (see Säljö 2002; cf. Sandywell 1999, p. x). These scientists ‘simply’ operate as ‘inventors’ of the very reality conceived of, or of the reality as a constructed reality (see Watzlawick 1984). We should, however, be critical and careful about the invention of a reality because “an invented reality cannot – precisely because it is invented – be the true reality” (Watzlawick 1984, p. 9; italics in original). The descriptions above of a distorted theorizing in the social sciences clearly show some factors which hamper the development of science, in terms of real ­innovation. It seems to be the inability to view the old habits of thinking as being responsible, and actually ‘productive’ for so-called “conceptual deadlocks” (EUROCORE 2004), or of the ‘black hole of reductionism’ (Reid 2007, p. 11). It is this very inability of reflexivity that is hampering real novelty and innovation (cf. Kuhn 1970, p. 52, on the incapacities of ‘normal science’). All of these inabilities and incapacities prevented the kind of rethinking, so much needed in our sciences; a situation that may be viewed as corresponding to a self-imposed kind of immaturity (cf. Sandywell 1999, p. x), comparable with the situation described by Kant, in his famous description of Enlightenment: of the need of man “to release from his self-incurred tutelage through the exercise of his own understanding” (Kant 1992, p. 90). One really needs an understanding of what is going on in science, of what makes science lack potentiality for innovation and novelty, to become more reflective and able to start the rethinking that is so much needed. This will be a rethinking that takes complexity not for granted but as a foundational concept, showing a fundamental power of ‘self-potentiating’: not only in theory but also in practice, that is as a fact (see Rescher 1998, p. 28). This is the key, not only for re-describing complexity as we know it but also for becoming explanatory about this complexity of real-world complexity. It may be stated right away that it is the very generative nature of complexity that is responsible for the self-generative, self-potentiating power of complexity. It is the fact that complexity thrives on indefinite interactions, with their interplay of forces that can turn complexity into generative complexity, with a power of self-potentiating. It is this notion of interaction that goes beyond “the Central Dogma of one-way flow of causality, information and form as our guiding metaphor for development” (Oyama 1989, 29; see also Oyama 2000). Vygotsky, in his day, spoke frankly about the new, neglected building stone for building a new science: “the stone which the builders have disdained must become the foundation stone” (Vygotsky 1987b, p. 91). This means in practice that reality can be a different reality. It can be a reality in which novelty construction is part and parcel of human development (van der Veer and Valsiner 1991, p. 311). It might be a reality which is unexpectedly different from what is commonly assumed by social scientists. It is about a reality as being not homogeneous (cf. Archer 2003, pp. 35–36; emphasis added). It might as well be a greater reality, with unexpected possibilities and potentialities (see Vico 1744/1967, proposition 349, p. 104). In this chapter a so-called ‘theory of the crisis’ will be developed. This theory is strongly inspired by the theorizing of Vygotsky on the crisis of psychology at the beginning of the twentieth century. It may be shown that it is really a complex of

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factors which seem responsible for the crisis at hand: a complex of factors which are strongly interwoven. It is this state that is actually constitutive for the closure of the system. It is for this state of being so strongly interwoven that science desperately needs an analytical disentanglement. It might be the start for a rebuilding of science as we know it. It is our challenge and hope for the future to turn it into a new science of the twenty-first century (cf. Rip 2002). …after all, science has been more wrong than right about the entities it has considered to furnish the world (Archer 2003, p. 36)

Reflecting on the Crisis It is not an easy task to write about the crisis in our sciences, i.e. the crisis in the social sciences. This is the case for the simple reason that the crisis at hand has almost always been the crisis which is denied (cf. Kuhn 1970). Some ‘simply’ declare the social sciences to be the wrong copy of the natural sciences (Schnabel 2002). But why it is a wrong copy, and how it all happened to be or has become such a wrong copy in our history of science, is not very much debated in practice. Lest the question how social sciences may find a possibly different foundation. In general one may view the sciences as a kind of closed system, not really able to change from within. It may be for this very reason that speaking about a crisis is not a popular topic for scientists operating within these sciences. Yet it can be a topic for discussion, which might be very relevant for science, even if it is not the case for the science in operation. One of the main questions to be addressed in this discussion is: “What crisis?” Another question is: “How can we get knowledgeable about the crisis?” And ultimately, the question is: “How do we get out of this very crisis, and start building a new science, based on a new paradigm as a tool for use of new thinking?” (cf. Kuhn 1970) It may seem, already in advance, that taking crisis as a problem for our doing science may be regarded as not fruitful at all! Probably it is for this very reason that the notion of crisis and the role of crisis in the history of the social sciences have in fact hardly been described for such a long time. This situation for the social sciences is in fact quite similar to the role of crisis in the natural sciences, over the last three centuries. It was only through the writings of Thomas Kuhn (1970) that the notion of crisis became truly relevant for thinking about the development of the natural sciences. He tried to show that the crises in our history of sciences were in fact necessary conditions for the scientific revolutions in the natural sciences. In his work he described what he called ‘normal science’ (Kuhn 1970, p. 24). Actually he defined the nature of ‘normal science’ as characteristic of the development of science in a pre-revolutionary period. This is a period before the crisis in science may eventually

Reflecting on the Crisis

23

develop. He described ‘normal science’ as follows: “Normal science does not aim at novelties of fact or theory and, when successful, finds none” (Kuhn 1970, p. 52; emphasis added). So, normal science seems to operate like a closed system, and the scientists, doing their science as ‘normal,’ do not seem able to get out of this closed system at all. The situation can be compared with Kant’s notion about the state of art of thinking as a state of immaturity, as one of ‘self-incurred tutelage’ (Kant 1784/1983). For him, it was this kind of tutelage which demanded the Enlightenment, with its demand for courage to use your own reason, as proposed by Kant himself: Sapere aude! which means “Have the courage to use your own understanding,” and has become known as the famous motto of the Enlightenment (Kant 1784/1983, p. 41; see also Jardine et al. 2006, p. 129, about the Kantian topic of immaturity as selfimposed immaturity and his clarion call to pursue Enlightenment; and Biesta 2006, p. 129, about the relevance of this topic for education). For our time, with our social sciences and society being in a fundamental and foundational crisis, we may need the same courage and the same kind of enlightenment of our thinking to be able to delineate a different future for the social sciences and humanities (cf. Tindemans et al. 2002). It is the very courage for starting a new kind of thinking: of what may be characterized as thinking in complexity. The kind of thinking needed may not only lead to the complexifying of reality, but at the same time of all human beings involved as a subject of study in the social sciences and humanities as we know them. In time, new thinking may show how complex the whole human being may really be, as a kind of fact (see Rescher 1998, p. 28). In the end, this way of new thinking in complexity about real-world complexity as a new kind of fact, that is of complexity as self-potentiating (Rescher 1998, p. 28),

Box 3.1  Text by T. S. Eliott, About the Perverse in Thinking and Writing It is not in his personal emotions, the emotions provoked by particular events in his life, that the poet is in any way remarkable or interesting. His particular emotions may be simple, or crude, or flat. The emotion in his poetry will be a very complex thing, but not with the complexity of the emotions of people who have very complex or unusual emotions in life. One error, in fact, of eccentricity in poetry is to seek for new human emotions to express; and in this search for novelty in the wrong place it discovers the perverse. (Emphasis added.)3

3  T.S. Eliot (1922). “Tradition and the Individual Talent.” In: The Sacred Wood: Essays on Poetry and Criticism.

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may lead to a re-enchantment of reality, of the world (Bhaskar 2002). This kind of new thinking, as a way of rethinking, may bring with it the potential enrichment of humanity and humankind (Archer 2000). The new thinking in complexity may be regarded as the foundation stone for the (our) job of ‘reclaiming Humanity’ (Archer 2000, p. 2), and for the facilitation of the possibility of what David Jardine has called “the cultivation of humility, of real humanity” (Jardine et al. 2006, p. 135), of relevance for the social sciences and humanities in general and for education in particular (see Archer 2000; Clark 2002; Biesta 2006). The contrast involved may make visible that such a thing like the perverse effect of (old) habits of thought may have a strong effect on our view and our doing science. It may be along the lines of new thinking in complexity, as sketched above, that we may be able to recognize and understand how to escape the perverse, of perverted systems like that of ‘normal science’ in general, and of education as a system in particular, both functioning as a kind of closed system (see Morin 2001, p. 72; see also Nock 1931). As a consequence, we may become aware of the perverse of the effects of such a closed system: e.g. the perverse of a humanism, which is insufficiently humanistic (Biesta 2006). It is about a humanism that may end in a humanism manifesting itself as The Wreck of Western Culture (Carroll 1993). How such a kind of the perverse may emerge is shown in Box 3.1 above, in a description by T.S. Eliot (1922), in his Essays on Poetry and Criticism. From this poem, it may not only be understood how the perverse may actually grow over time. It is the not being able to search for novelty in the right place that brings the writing (and the poem itself, of course) into the realm of the perverse. This poem may also elucidate how the perverse may be opposed in our daily doing of science. It does so by showing how the perverse of doing ‘normal science’ corresponds to the perverse of writing a poem: by searching for novelty in the wrong place, with a concomitant lack of understanding of the complexity of emotions related to the expression of what is really of worth in poetry in general. We may link this kind of perverse writing with the perverse of thinking: of learned incapacities and learned inabilities. We may refer here to the inability to go beyond the ‘black hole of reductionism’ (Reid 2007) or the dominance of ‘the Central Dogma’s one-flow causality’ (Oyama 1989, p. 29; cf. Oyama 2000). These inabilities may as well be viewed as characteristic of a perverted system of thinking. According to Sandywell (1996) for instance, “we think, without thinking about thinking” (p. xiv), which can be viewed as resulting from the repression of the reflective dimensions of human experience, mentioned above (see Sandywell 1996, p. xv). In general, it may be stated that there is a lack of a more explanatory mode of thinking in the social sciences and humanities; a mode that takes “the causal dynamic relations that underlie phenomena” fully into account, making use of “new methods of investigation and analysis”, that had to be invented for this purpose (Vygotsky 1978, p. 62, p. 58). We may also refer here to Van der Veer and Valsiner (1991), who in their book Understanding Vygotsky, stress the need “to re-construct the causal system” (p. 311); that is, for the description and explanation of processes of novelty construction, which is part and parcel of Vygotsky’s ambition to invent a new science of psychology.

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What’s the Use of Crisis? It may be stated that only when it is recognised that science itself is in a crisis, and what this crisis looks like, that we might be able to deal with the crisis. The importance of this sort of acknowledgment was also noted by Vygotsky, in his first years as a young scholar (around the age of 29), writing about ‘the crisis in psychology’ in his main work Problems of the Theory and History of Psychology.4 For him the crisis in psychology was what he called “its profound crisis” (Vygotsky 1997b, c, d, d4, p. 97). He saw it as one of the preconditions for a paradigm shift in his field of study to formulate a so-called ‘theory of the crises’. By describing and formulating such a theory, we might be able to perceive a crisis, understand its effects, and start to ‘solve’ it. Of course, this is not an easy job to do. It will never be the case that every scholar in the field will agree about the nature of the crisis. It will even be an illusion to think these scholars will agree about their science being in a crisis at all. In fact, most of them will deny the crisis in the field of concern. They ‘simply’ seem to know what they know and how they came to know it. This situation of scholars, doing their “science as usual” (see Longino and Doell 1983/1987, in Oyama 2000, p. 147), is still the case in our day. With Oyama, we think here is a real danger of science turning into ‘bad science’ (Oyama 2000, p. 147; cf. ‘normal science’ in Kuhn 1970, and its incapacity to create novelty and innovation). Hence, it may be stated that the current situation is related to what Edgar Morin (2001) has called ‘the epistemological problem’. Morin also warns us about the danger of the crisis, in case we are not taking the crisis seriously. Scientists, then, may meet a conceptual deadlock (see e.g. EUROCORE 2005), become the captive of myopia, of blind spots or tunnel vision, or the victims of blinding, or misguided paradigms (Morin 2001). On the danger of crisis, Morin stated clearly that “the crisis worsens as fast as the incapacity to reflect on the crisis increases” (Morin 2001, p. 35). How the epistemological problem relates to the crisis may be illustrated by the writings of James Wertsch (1998), who explained in his book Minds as Action that a situation like this can emerge because of “the ‘learned incapacities’ and ‘disciplinary pathologies’ that restrict the horizons of modern academic discourse” (Wertsch 1998, p. 11). So, it may be derived from this kind of reasoning about the crisis that we, as scientists, desperately need to overcome these very incapacities by becoming more reflective about the very crisis we are involved in as social scientists. It is not only strongly needed to become aware of the blinding paradigms (Morin 2001), the hidden agenda of our doing and viewing the science in which social scientists operate (Dennett 2003; Tindemans et al. 2002), but also of the way we, as scientists, are operating as ‘deliverers of reality’ (Säljö 2002). By becoming more reflective about our viewing and doing science, we may recognize and become more fully aware that we might have become the ‘deliverers’ of a distorted reality in the social sciences (see Dennett 2003).  See Vygotsky (1926/1997) for his contribution on the crisis in psychology, which was not ­published until after his death.

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This is also the moment in our history that we, as social scientists, start a serious reflection on the system we are in, to become aware of the danger of linear thinking, of the fragmented worldview, the learned incapacities and the disciplinary pathologies of our disciplines. All of this for the sake of overcoming the crisis we are in. Then, it might be said, that the crisis is not only a danger for our society but also offers an opportunity for a real change: a change which might turn out to be revolutionary in the end.

Crisis: Danger or Opportunity? It may be of importance to stress here that a crisis is not only a danger in practice, but may also offer an opening, an opportunity for a real change of that very practice. This point has been elucidated by Thomas Kuhn in his work on The Structure of Scientific Revolutions (Kuhn 1970, i.e. in Chapter VII). He describes how the phenomenon of crisis shows to be an emergent crisis in the history of science. It is a crisis which, looking back, shows to be a response to a period of stagnation, a period of problems that are not only left unsolved but which are seemingly unknowable. It is a period in which science operates as a closed system, a period in which real innovation is not only not needed but even viewed as impossible. Yet, somehow science and their scientists doing science seem able to overcome the crisis in the end. This transition has been described by Kuhn (1970) as A Scientific Revolution (pp. 20–21). In his famous book, he gives some nice examples of such revolutions in the history of the natural sciences. Although he does not give examples from the social sciences, he leaves it open that they may well be occurring today in (parts of) the social sciences (Kuhn 1970, p. 21). He describes transitions like those mentioned above as “transitions to maturity”5 (Kuhn 1970, p. 21). We may refer here to scholars like Mary Parker Follett, who described the situation in the social sciences as pre-Newtonian, or Lev Vygotsky, who was fully aware of the crisis of psychology in his day and who tried to invent a new science. The state of crisis is actually a process of growing crisis, as described eloquently by Thomas Kuhn (1970). It implies destruction and major shifts in the problems and techniques of what he describes as so-called ‘normal science’. All of this generates quite a bit of uncertainty and insecurity for scholars working in the discipline of concern. It is therefore no surprise that, as an example, Kuhn describes what kind of metaphor Copernicus used to characterize the state of art in the field of concern: that of astronomy. Copernicus wrote about the fruit of the astronomical tradition as “only a monster” (Kuhn 1970, p. 69). It was his exceptional quality as a scientist that Copernicus could look at his own science in this way. For him it was clearly a state of art which inspired him to rebel against the system. You need a lot of courage to do so, as history has shown. You may ‘simply’ lose your head, as in the famous case of Galileo.  This kind of immaturity may be linked with the state of immaturity, described by Kant, in his famous text on Enlightenment, in which he connects this state of self-incurred immaturity with the courage to think: Sapere aude!

5

Crisis: Danger or Opportunity?

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The rebellion against the system, to be taken as synonymous with a revolt, may simultaneously be the start for opening up new vistas for a science (cf. Whitehead 1925/1967, p. 200). To put it differently, the notion of a growing crisis may imply both a kind of destructive and constructive element of change (see Kuhn 1970, p. 66). Whitehead openly claimed the clash of doctrines as an opportunity (Whitehead 1925/1967, p. 186; see also Prigogine and Stengers 1984, p. 213, referring to Whitehead’s statement). This kind of thinking does not seem restricted to our Western culture. Darren Stanley (2005), for instance, noticed that in China the symbol for the word crisis, which is wei-ji, has both elements in the iconographic composition: “it is a combination of both ‘danger’ and ‘opportunity’” (Stanley 2005, p. 142). He also refers to the relation between crisis and the notion of a ‘turning point’ in society at large in the work of Fritjof Capra (1983). This kind of reflection on the crisis brings us to the point where, speaking about the crisis and turning points in our history of science, we may open up a new process of becoming reflective as scientists, to start reflecting on the mechanisms which play a role in bringing about the turning point and the potential of a revolution: be it scientific or in society at large. Or, to put it differently, it may be questioned how scientists can deal with insecurity and uncertainty in the field of science they participate in. It is very hard indeed “to comprehend the possibility that there might be other ways of thinking” (Lincoln and Guba 1985, p. 9; emphasis added). To believe in this very possibility seems for scientists to enable new ways of thinking about their science and their own ‘doing’ science in their own field of science. Now, being aware of the potential opportunities a crisis may offer (cf. Fig. 3.1), we may put the question: “How can it be fostered and stimulated that the crisis will be a period of opportunities for scientists?” In the next paragraph this question will be addressed, by taking up ‘the problem of crisis’ as a serious subject of study for our science: both for science as a subject to reflect on science itself and as an activity of doing science as a scientist. This stance is not only of relevance for the discipline of concern one is active in, but also for the broader field of various, different but related, disciplines. Along the line of new thinking and reflection, as sketched above, it becomes relevant to speak about a transdisciplinary approach: an approach which focuses on the different disciplines of the social sciences. Questions of interest, then, will be questions like: “What is common to the different disciplines in terms of their problems,

Fig. 3.1  Chinese symbol for crisis associated with danger and opportunity. (According to some experts this is actually a very untrue ‘translation’ of old Chinese symbols)

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their methods in use, and their implicit or explicit view of the world scientists live in?” To reflect along this line of thinking, a so-called ‘theory of the crisis’ may be needed (cf. Vygotsky 1926/1997). It will be a theory which tries to link the unwelcome crisis, and its concomitant insecurity and uncertainty, with the more than welcome opportunities of the very same crisis. These may imply not only a new framework: a framework that does not yet exist, or a new kind of science, but even a kind of scientific revolution. Will it be possible, then, to enlarge the spaces of the possible or even open up new spaces of possibility? Are we able to find the bridge to the unknown: of spaces of the unknowable? To start with this ambitious enterprise, we may start with what Robert Flood, in his book Rethinking the Fifth Discipline, on the topic of so-called ‘Learning Organizations’ has nicely called “learning within the unknowable” (Flood 1999). This parallel, drawn between fostering a Learning Organization and what we may call ‘The Project of (doing) Science’, is itself an example of the necessity and possibility of use of the new transdisciplinary approach. It shows the possibility of dealing with science as a kind of self-organized system, to be dealt with as a self-organizing activity by the scientists involved in the system. Ultimately, it may be shown that it is the very same mechanisms that are responsible for the growth in and of the system at large (see e.g. the relevant work of Peter Senge and his companions, 1990, 2000, 2004, about a new concept of learning and the learning organization). In the next paragraphs, a sketch will be given of how to solve the very crisis we are in as participants in The Project of Science. The basic point to start with is the notion of how science relates to the real. Crisis for enabling society’s finding itself at a turning point See Darren Stanley (2005), p. 143, referring to Fritjof Capra 1983

Theory of the Crisis Writing about the crisis in our sciences is not an easy job. It might be stated that in general the very crisis to deal with is the crisis which has mostly been neglected. This seems to be the case for the ‘simple’ reason of an inability to deal with the crisis. Mostly because the crisis at hand has been the crisis denied, or ‘simply’ not recognized as a crisis at all. This conclusion, beforehand, may be drawn from our history of the sciences. In this section of the book, the aim is to recognize the crisis as a crisis, and to develop a theory of the crisis, in terms of mechanisms and processes which play a role in this specific phenomenon of science. One of the predominant features of science is the drive to be in control as scientists doing and viewing science, and to eliminate uncertainty and insecurity about the domain of knowledge for study (cf. Juarrero 1999, p. 259). The domain of the unknowable is not always the best friend of scientists. To foster learning within the unknowable, to create novelty and innovation, which demands new thinking, is actually one of the most difficult tasks for scientists (see e.g. Bateson 1972, p. 462 and Lincoln and Guba 1985, pp. 8–9, on new ways of thinking; see Kuhn 1970, p. 52, on creating novelty and innovation).

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Ultimately, the aim of unfolding a theory of the crisis is to foster the possibility of innovation and novelty in science, in doing science in a potentially better way, by showing the very possibilities and potentialities of a renewed science. To write about the theory of the crisis, one may focus on the whole history of our sciences, as Kuhn has done for the natural sciences. In this chapter a different view will be taken. To be more specific, the focus is on (the history of) the social sciences. To be even more specific, the focus is on the new thinking by Vygotsky, who addressed in his work the whole of the scientific enterprise of psychology. What is so impressive about Vygotsky is that he, at the age of 29, started his career not as a psychologist! Yet, he focused his first work in the social sciences on the scientific problem of the crisis in psychology6 (1926/1997). Actually, his first work was about the inability to deal with the crisis in the social sciences in general. He took a very critical stance towards psychology as a science, with quite a few unsolved nagging questions. This work remained unpublished for a very long time, probably because it was too critical for potential readers in his day in Russia. Another reason might have been the problem of the survival of doing science in those days, because a science like psychology was under continuous attack by a communist regime, seeking to legitimate its own worldview and that of the role of the human being in communist society. It was Lev Vygotsky, who stated that the crisis in psychology was primarily a methodological crisis (Vygotsky 1987a, b, p. 54). It is therefore no surprise that his theorizing on the crisis had its focus on the methodological principles of this science (cf. Whitehead 1925/1967, p. 201, about the methodology of reasoning meeting its limits). But those are the principles which are general principles for the social sciences. They were constitutive of unreflective systems of thought, of what Vygotsky described as “old habits of thought”, and a concomitant kind of repression of more reflective thinking (see Sandywell 1999, p. xv). It is for this reason that Vygotskian thoughts about what may be called the crisis in psychology have general value for these sciences (cf. Sandywell 1999, p. xv). He stated as a first general principle that the most basic question for doing science is “how science relates to the real.” This is the question which is directly related to what is known as the problem of ontology and the epistemological question: “How do we know what we know?” (cf. Juarrero 1999, p. 243). These are the very problems and questions which have troubled philosophy and the social sciences for centuries. They are, however, still the problems that are inevitably with us in our viewing and doing science. One may say that a large part of the problems can be attributed to a kind of neglect of these problems because they almost always seem too difficult to answer. One may think here of Herbert Simon (1996) who stated that the scientists doing their science prefer to focus on good answers to questions, thereby disregarding the answers to questions which seem unknowable. Henceforth, the answers to the difficult questions ‘simply’ remain

 Maybe his very first work was about educational psychology around the same age or before (Vygotsky 1926/1997).

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unknowable. It is this attitude of being satisfied with the given answers and ­disregarding the more difficult questions that makes scientists ‘satisficers’, as Simon (1996) has called them in this kind of role of doing science. From a more general point of view, this phenomenon may lead to what Daniel Dennett (2003) has described as ‘the hidden agenda,’ with all of its collateral damage: of distorting theorizing in the social sciences and life sciences (see above; cf. Prigogine and Stengers 1984, p. 309, about the hidden questions in science). It is this hidden agenda, leaving questions unanswered, hampering the learning within the unknowable, which, in our history of the development of the sciences, has led to the social sciences becoming the wrong copy of natural sciences. This has led to old habits of thought, and to mechanisms of inertia fully operating in the sciences. It has also led to scientists playing a role as ‘satisficers’ in their viewing and doing science, and, as a consequence, to a kind of science with a concomitant inability to ‘produce’ novelties of fact or theory (cf. Kuhn 1970, p. 52, on ‘normal science’). This is an inability which may be conceived as resulting from effects being ‘produced’ by the operating of ‘blinding paradigms’ (Morin 2001), the blind alleys, the blind spots and of myopia in the field of concern (see the collective works by Vygotsky, i.e. 1926, on the crisis in psychology). So, it is time to be critical about the social sciences. The social sciences have neglected the specific subject of study in the social sciences: the whole human being. They reduced it to the individual with its responses to a pre-specified environment. It was a rather easy step to disregard the complexity of the whole human being. To enforce the picture of the social sciences as real sciences, like the natural sciences, the focus was on good answers to questions which were answerable from the very start. This implies a focus on the role of satisficing for the sake of the survival of the social sciences in our society. This phenomenon has been responsible for a kind of science which may be characterized as ‘normal science’ in our history of the sciences in general (see Kuhn 1970, p. 24). A science which is fundamentally unable to produce real innovation and “novelties of fact or theory” from its own sources of knowledge, for the simple reason that it does not aim at that kind of results (see Kuhn 1970, p. 24, 52). Phenomena “that will not fit the box are often not seen at all” (Kuhn 1970, p. 24; emphasis added). This attitude of scientists doing their science has resulted in a reductive stance, characteristic of the ‘black hole of reductionism’ (Reid 2007, p. 9), and the concomitant neglect of the inherent complexity of reality, of all kind of complex phenomena and of the complexity of the human being. One of the results was the stripping of most attributes which might be called ‘social’ of the human subject. This stripping led to ‘producing’ an individual as a closed system, with a functioning which was taken as independent from external factors and influences (Elias, in Sociology and Psychiatry; cf. Follett 1924; Stacey 2003, p. 55; Juarrero 1999, p. 243). It may be concluded that this reduction brought with it a concomitant ‘amputation of internal states’: the very states “which generate unpredictability and novelty” (von Foerster 1993, p. 196; cf. Juarrero 1999, p. 258). This very reduction, which may be regarded as a voracious kind of reductionism, ultimately became the road towards a dehumanized world, by being unhappily uncreative in viewing and doing science. This black hole of reductionism prevented the development of a psychology which

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is humanized (cf. Vygotsky 1997b, pp. 58–59; emphasis in original). Connected to that, a rather different, unexpected question may be addressed, as Juarrero (1999) has put forward: “Is it possible to learn to embrace uncertainty?” (p. 258; see also below). A question that is closely connected to creativity: to creating novelty, of fact and theory, and of innovation. We may be critical about the methodology in use in the social sciences as well. The methodology of study of the subject of psychology has been dominated by what has generally been called the approach of ‘methodological individualism.’ Basically, the work of Vygotsky was based on a rejection of this methodological approach. Actually, he embraced the notion of the human subject as the subject of study in psychology as a complex, inherently social human being. His famous adage was: “It is (only) through others that we may become ourselves.” His writings started from a better understanding of the individual human being as a radically social understanding of individuals (see also Stacey 2003). A second basic problem for the social sciences has been the concept of causality. The concept of causality has always been – and still is – a problem for philosophers as well. This is especially true for the mechanism involved in what can be called ‘the causal dynamics’, as in the dynamics playing a role in the processes of learning and development (Vygotsky 1978). This is a dynamics which goes beyond the mechanistic, ‘billiard ball model’ of causality and causal processes. However, conceiving of causality of processes between elements as entities is not only a difficult problem for philosophers: causal analysis of these processes is a hardy perennial in social science (Buckley 1967). It is therefore no surprise that causal modelling of these processes is a rather recent phenomenon in the social sciences, developed from unexpected sources such as the field of biology and that of the economy: see Box 3.2. It may be concluded that there is still an unexplored part of causal modelling of reality (cf. Long 1987). It is about a form of causality which is not Newtonian (mechanistic) causality; a form which does not take fixed entities (agents) as interacting

Box 3.2  Causal Modelling in the Social Sciences Causal modelling was originally developed by the geneticist Sewell Wright, in the nineteen thirties. Later, in the nineteen seventies, it was picked up by Karl Jöreskog and Dag Sörbom, and developed by them into a computer program for analysis (known as LISREL, with different releases in the decades thereafter). Theorization of the dynamics of causal interaction is only developing slowly. One of the reasons is that the topic of the causal dynamics as such has not been recognized as fruitful. This is demonstrated in the books on causal models (e.g. the LISREL-manuals by Jöreskog and Sörbom, the latest in 1993). Although they deal with reciprocal relationships in their modelling of causal interaction, they do not give the formulae which show the potential nonlinear total effects of such interactions within reciprocal relationships.

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over time. It seems a new view for the social sciences that: “There is no tidy, linear pairing of causes and effects in human action as there is in the realm of classical mechanics” (Juarrero 1999, p. 61). So, it seems of utmost relevance to rethink causality for the social sciences and humanities, and to bring the causal powers of human action and conversation into our scientific vocabulary (Archer 2000, 2003). Powers which may be considered to be generative powers (Archer 2000, 2003, p. 7). These generative powers are considered to be linked with the generative mechanisms which are hitherto unknown. These are to be regarded as the potential generative powers of reciprocal transformation and (self-) transformation (Nakkula and Ravitch 1998; Archer 2003, p. 75). These powers can be linked to what has been called causally generative processes of ‘bootstrapping’ (Jörg 2007). To enable this kind of connection in our new thinking, we need a different notion of causality; one which is based on the reciprocal influences and the interplay of impelling forces exerted within relationships (Vygotsky, in Van der Veer and Valsiner 1994, p. 213; cf. Follett 1924, on this interplay of forces and their effects on the partners in communicative human interaction). The new form might be a solid form of analysis which, as a transdisciplinary tool for analysis of causal processes, may be used to bridge the different disciplines (cf. Sandywell 1996). This new form may show the potential nonlinear complex reality of phenomena: both in nature and in our world of radically social human beings. Modelling causality as a potential nonlinear process may be a new building stone for thinking in complexity, about a different kind of reality. This will be a reality which is essentially a greater reality (Vico 1744). Thinking in complexity along these lines will ultimately enable the foundation of the social sciences anew. This will be a foundation which is ultimately opening for scientists, enabling them “to work in a different world” (Kuhn 1970), by enlarging the spaces of the possible. All of this may hold the promise of a better future for the sciences, e.g. the science of education. It may be stated that it is for this reason that we need to reform and revolutionize our sciences (see Luhmann and Schorr 2000, p. 169). The reality of learning and education may, then, become a nonlinear reality; a (new) reality, of unexpected travels and adventures (cf. Bohm 1996, p. ix); with a new potential, of what has been described as ‘explosive possibilities’ The price we pay for the potential of true novelty and creativity is uncertainty (Juarrero 1999, p. 258)

(Barab and Kirshner 2002). With these explosive possibilities within the enlarged spaces of the possible, we may create a surprising efficiency of learning (Sternberg and Spear-Swerling 1996, p. 119; Morin 2001, p. 12). Are we able to develop … a world view “to counter the paralyzing belief that social reality is too complex to be mastered” (George Plekhanov, Russian philosopher, referred to in Joravsky 1989, p. 190)

The Crisis

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The Crisis To start with a discussion about the crisis for the better, we may start by warning the reader that there is not an easy way to deal with the crisis, as some seem to suggest, lest of ‘solving’ the crisis at hand. It is not simply a change of use of metaphors, of creating a new language with those new metaphors. Of course, we need to leave behind the old metaphors in use, and be creative, by turning complexity into creativity: the creativity needed to create a new language with a new set of metaphors (Brockman 2006). However, it is not only a way of becoming creative, but also a way of becoming more scientific about the subject of study in our viewing and doing science. It may be stated, right from the start, that quite a bit more is needed to solve the crisis we are in, as will be shown below. Science itself is the subject for reflection and change, as well as the tool for bringing about the changes needed: of novelty and innovation of viewing and doing science in our society. The ultimate goal is to revolutionize the sciences to be able to solve the very crisis of our sciences and society. What does it mean to say that we may ‘solve’ the crisis? Is the blunt idea of solving the crisis a fruitful idea anyhow? Is it not a pure rational expression, derived from the old habits of pure rational thinking applied to the new, still to be developed ways of thinking? Maybe the only way to convince the reader of the use of the term ‘solving’ is to show how to do it. To put it differently: by showing the performance of doing it. This may be demonstrated, for instance, by showing the very danger of linear thinking and the opportunities of thinking in a nonlinear fashion. To be more general, it may be shown what is needed to enter the new field of the unknowable and the enlargement of the spaces of the possible. It may be shown how to escape the traditional ways of viewing and doing science as constitutive elements of what Kuhn described as ‘normal science’; the science, with its characteristic features of science before a scientific revolution. Reading Kuhn’s book about the structure of scientific revolutions, it may be derived that to escape ‘normal science’, with its characteristic lack of innovation and incapacity to create “novelties of fact or theory” (Kuhn 1970, p. 52), may imply a kind of revolutionizing science. It can mean the start for escaping dear old habits of thought, and getting out of the blind alleys of our social sciences. In other words, it means that we have to learn to think within the space of the unknown. But to do so, we first have to become aware and ‘see’ the space of possibilities and potentialities within the space of the unknown, before creating the power to realize these possibilities. To be able to do so, we may have to unlearn the dear old habits of thinking (Dennett 2003), and the learned incapacities of scientists doing science (Wertsch 1998). In the end, we may have to learn not only a new kind of thinking, of thinking in complexity, but also the development and the learning of a new language. We think, only with this new language, it will become possible to speak about a different reality: a reality which is a richer reality. But how different can a new reality be or become? May reality ‘really’ become a domain of potentiality, in the words of the renowned physicist David Bohm? What kind of thinking do we need to create such a new domain of potentiality within a potentially enlarged, greater reality? Thinking along these lines about ‘big questions’,

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may bring with it a feeling or attitude of rebellion against reality as we ‘know’ it, or as we have always thought to know it. This rebellion against reality may end in liquefying and complexifying the reality as we assume it to be (cf. Zilsel 2000, about Darwin’s rethinking of the reality of his day, turning it into a fluid kind of evolving reality). This feeling of rebellion may imply an awareness of the possibility of being at a qualitative turning point in thinking about the world: in our case about the reality of complexity of real-world complexity: about “the fact (is) that complexity is self-potentiating” (Rescher 1998, p. 28). This awareness, we think, is a real turning point, turning old concepts and habits of thought ‘simply’, but also complexly, upside down. Not just a turning point for a new science, that of complexity, but a turning point for society at large. For this to happen, a turning point of new thinking, of thinking in complexity, is needed. It may be characterized as a precondition for a way of humanizing the social sciences: by opposing and rejecting the voracious reductionism, so much dominating our sciences as a kind of ‘black hole’ in our way of thinking about reality, with its resulting trivialization of the main subject of study in the social sciences: that of the human being.

Mission of the Book To express the mission of this book, it may be stated that the goal of addressing the very complexity of reality and the thinking in complexity about this real-world complexity as self-potentiating, is finding a new path of both creating a new science of complexity, with a new method, bringing with it a new framework, based on a new epistemology and a new methodology. It is our firm hope that new thinking in complexity may enable the cultivation of humanity. It may be shown that the crisis may essentially contain more of the notion of an opportunity, a turning point, than a danger for our sciences and society at large. In short, solving the crisis in the social sciences means the creation of a new foundation for these sciences, of delivering a new reality, by reclaiming it (see e.g. Bhaskar 1989). A reality, which is a complex, richer reality, with a new language to speak about this richer reality we may then have created. It is this richer reality, which will be a kind of language-effected reality, which offers a new opportunity for cultivating humanity. We may leave the flatland of the field of social sciences and enter the more mountainous landscape of the future of our viewing and doing science. This will be the new landscape of the possible: of uncertainty, of the unpredictable, but also of enlarged spaces of the possible, with (explosive) possibilities and potentialities. Opening this new landscape will have the power to bridge to the unknown. It implies the picture of a new landscape of complexity which we may seem unable to ‘master’ because of its complexity. To be honest, to create this alternative landscape for our social sciences, we need quite a bit of rethinking. This is what this book will be about, the rethinking of our viewing and doing science, as a precondition for enabling a shift towards a new science of complexity.

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‘Solving’ the Crisis To start solving the crisis it must be stressed that we have to become more reflective, and more critical, about what is going on in the field of our sciences. We should not take for granted what is so commonly accepted in our sciences. The question to be addressed before reflection and rethinking becomes possible at all is: “How can we ‘see’ assumptions that are so taken for granted?” (Senge et al. 2000, p. 27). This was the meaning of the very question already put forward by Vico (1744/1968), in his publication The New Science, expressing the state of art in his own day with the metaphor of the eye which cannot see itself. To solve the crisis anyhow, we may need a mirror to ‘see’ what ‘normally’ cannot be seen. We should become aware that, to change the social sciences in a really innovative way, we may need to cross the borders of our very system of thinking. It may even be necessary to step outside of our own system of thinking to create novelty and innovation (cf. Kuhn 1970). This whole enterprise of exploring the unknowable, by learning within the unknowable, may imply “the thinking of the unthinkable” (see Blunkett, in Desforges 2001). This new learning demands quite a bit of rethinking of the thinkable. Of course there is no single path to the unthinkable. There are only unknown spaces, with unknown trajectories in those spaces of the unknown possibilities and potentialities. It is in these spaces of the unknown that the solving of the crisis may be enabled and fostered. This seems true both for the crisis in science and for the crisis in our society. If it is true that the scientific crisis is primarily a methodological crisis, based on a wrong notion of reality to be studied, then this methodological crisis may be conceived as being linked to the crisis in our society at large because of this wrong notion of reality. This wrong version of the reality of our society, of what may be called “the lived social reality” (Archer 1995, p. 2), may as well be taken as a society that “suffers from a severe dysfunction” (von Foerster 1993, p. 196). The society we live in has become a kind of delusive society. Both the sciences and society have been shown to be unable to think the unthinkable. This incapacity, to be regarded as a learned incapacity, shows itself in the lack of innovation and novelty in our sciences and society. So, the reality of our sciences is strongly connected to the reality of our society. Consequently, it seems logical to start with elaborating on the need for a new method of science and a new methodology, based on a different version of reality: a reality which is essentially a richer reality (Morin 2002, p. 383). This is a version which takes it as a challenge to avoid the trivialization of what is called the common, assumed version of reality (cf. von Foerster 1993, p. 196). To do so, it may be necessary to think of the possibility of a nonlinear reality as a fundamental part of our common reality. It may be shown how the common assumed, linear version of reality is linked with the nonlinear part of reality. So, reality as we know it, may be expanded for good methodological reasons, and may expand complexly to a richer version of reality: as a domain of creative potentiality. This seems to be creating a new reality as being just a kind of choice. But it will certainly not become a richer reality just by invention or construction, as philosophers, psychologists and

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e­ ducationalists have often tried to do in our history. It may look like a truism that one may also turn to a kind of realism in the approach to viewing and doing science, and start studying the human being with Vygotsky’s question about “how an actual and real man would act in a real situation” (Vygotsky 1997b, d4, p. 45). Following this expression he states openly that: “When the question is posed in this way, naturally, the situation itself, the reacting subject and the research path all change” (Vygotsky 1997a, b, p. 45; emphasis added). It is this kind of thinking which made Vygotsky sensitive to phenomenon of emergence (Vygotsky 1987a, b, p. 89) and of the role of what he called autostimulation: “the creation and use of artificial stimuli-devices and determining one’s own behaviour with their help”7 (Vygotsky, D4, p. 54). It seems a basic truth for him that: “Before studying development, we must explain what is developing” (Vygotsky, D4, p. 44; italics in original). According to him, methodology is needed to explain the what that is developing, “to disclose the real basis of our methodological formula” (Vygotsky, p. 44). It may be stated that it is here, both to Vygotsky’s mind and our minds as well, that this is where complexity enters into the picture of viewing and doing science. To be able to deal with this complexity we first have to recognize the very complexity of reality. It may help us “to counter the paralyzing belief that social reality is too complex to be mastered8” (Plekhanov, in Joravsky 1989, p. 190; cf. Noddings 2003, p. 164, about the ambiguity of education). To see complexity as real may help to escape that very paralyzing belief. It may convince us of the need for using new tools as well. The retooling needed may be of help to deal with that new complex reality. The basic idea for developing new tools of thinking in complexity is “to use our knowledge of complexity to do better” (Axelrod and Cohen 1999, p. 9). To do so, we need a better understanding of the complexity of reality, e.g. as self-potentiating in the real, nonlinearly in time and space! Only then it might be possible to harness the real complexity of our new reality. According to Axelrod and Cohen it may be stated that: “To harness complexity typically means living with it, and even taking advantage of it, rather than trying to ignore or eliminate it” (Axelrod and Cohen 1999, p. 9; emphasis added). Harnessing complexity can be linked with the notion of self-potentiating. To enable such harnessing, we ‘really’ need a new method of science, with a more explanatory methodology. To enable this we need a focus on what Margaret Archer describes as “the tripartite link between ontology, methodology and practical social theory” (Archer 1995, p. 3). She stresses the need to become explanatory about social reality: “The practical analyst of society needs to know not only what social reality is, but also how to begin to explain it” (Archer 1995, p. 5; italics in original). Her stance corresponds with the thoughts of Vygotsky (1978) about becoming more explanatory instead of keeping descriptive about reality, to be able to explain the actual causal-dynamic relations that underlie the phenomena  cf. the role of agency in the recent book of Margaret Archer 2003.  To master, here, is to be taken as very much different from the notion of control, of the calculable, of the predictable.

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‘Solving’ the Crisis

37

of study in psychology (p. 62; emphasis added). The new methodology will be a methodology, with a new framework of thinking, which starts by taking the complexity of reality not for granted, but as part of real-world complexity. It can be assessed that there is still no solid framework for doing so at our disposal. According to Stuart Kauffman (1995a, b), in his book At Home in the Universe, it still seems to be true that “a new conceptual framework (for the study of this kind of complexity) does not yet exist” (p. 185; emphasis added; cf. Axelrod and Cohen 1999; Archer 1995, p. 5; and Vygotsky 1978, in his book Mind in Society, using a similar expression about the need for a new analytical framework). In the same book, Stuart Kauffman makes the rather bold statement that: “Nowhere in science have we an adequate way to state and study the interleaving of self-organization, selection, chance, and design” (Kauffman 1995b , p. 185). How, then, may we start thinking about a possible adequate way? Is it thinking along the lines of Axelrod and Cohen (1999) who stress the key role of variation, interaction and selection as fundamental processes of complexity in reality? Or do we need very different lines of thinking, to be able to develop a new framework: a framework that, according to Kauffman (1995a, b) still does not exist? From the very beginning, however, betrayal and delusion have been common practice when approaching the vexatious fact of society and its human constitution (Margaret Archer 1995, p. 2)

So, based on the thoughts above, we may express the need for a new kind of agenda for our view of science, as a science about the very complexity of reality. This agenda goes beyond the fragmented view of the separate disciplines of our sciences. What we need is a new method and methodology for dealing with complexity, which correspond with the so-called ‘transdisciplinary approach’ (see e.g. Koizumi 2001, 2004). It may be of interest, and not only for historical reasons, to mention the two paths for a new methodology, which Vygotsky sketched for changing the view of thve science of psychology in his day. In a chapter about ‘Research Method’, Vygotsky (1997) proposes two different methodological paths for studying the specific uniqueness of human higher behaviour: 1. the (more general) path of complication, enrichment, and differentiation of the same phenomena that experimental study ascertains in animals (p. 54). 2. the other path is the path of psychological research. The specific uniqueness (of human higher behaviour) is considered “not only in its subsequent complexity and development …. but primarily in the social nature of man and in a new method of adaptation, as compared with animals, that sets man apart” (Vygotsky 1997, p. 54; emphasis added). These two paths, now, may be linked to recent thinking in complexity in the social sciences and humanities. The first path corresponds to the notion, and

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the urgency of complexifying in the social sciences by Edgar Morin (2002a), to enable the humanizing of these sciences. This process of complexifying implies not only a radical different kind of ‘delivery’ of reality, but, even more importantly, it offers a possibility of reclaiming reality, to enable a shift of mind, a shift of worldview, that is, for viewing a different world (cf. Bhaskar 1986). Taking this shift seriously means an expanding of reality as we commonly assumed it to be, making it more meaningful, more human. This path may, therefore, be linked to Margaret Archer’s notion of an enrichment of reality. It opens up the space for a richer reality (Morin 2002). The second path corresponds to the dynamic conception of ‘human nature’, and its connection with society, as described by Mary Clark (2002), in her book In Search of Human Nature: “The beliefs a society holds about the universe and about human nature in particular tends to create the very behaviour they predict” (p. 11; italics in original). For her, it seems a basic truth that: “How we see the world does shape who we are” (Mary Clark 2002, p. 11; italics in original). This truth seems to offer a radical new perspective for complexifying and humanizing the social sciences and the main subject of study in these sciences: the human being. To express it concisely: it is all about the celebration of complexity for the sake of cultivating humanity. A perspective that may open up new spaces of human possibility: both at the personal level and at the more collective level in our society. The second path may be linked also with the radically social understanding of individuals by the complexity thinker Ralph Stacey (2003). The two paths as described by Vygotsky, taken together, seem to correspond rather strongly with the conception of ‘harnessing complexity’, by Axelrod and Cohen (1999). This harnessing of complexity may be conceived as a real challenge for our sciences and society. There may be a strong link, as well, with the tripartite link between ontology, methodology, and the practical social theory, proposed by Archer above (Archer 1995). This link, shown in Fig. 3.2, may be summarized as follows: the recognition of the complexity of reality, and the reality of complexity, demands an alternative methodology, which connects the theory about the complexity of reality with the view of the (potential) practice and theory of social, human behaviour.

methodology

Fig. 3.2  Tripartite relationship, according to Archer (1995), between ontology, methodology, and practical social theory

ontology

practical social theory

Steps to Be Taken

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It seems a good starting point to realize beforehand that: “The principles of this methodology deliver a heuristic scheme for constructing models of nonlinear complex systems in the natural and social sciences” (Mainzer 2004, p. 406). On the basis of these principles a new research program becomes possible which is not only interdisciplinary but truly transdisciplinary; a program “in which several natural and social sciences are engaged” (Mainzer 2004, p. 407). The beliefs a society holds about the universe and about human nature in particular tend to create the very behaviour they predict (Mary Clark 2002, p. 11)

Steps to Be Taken To summarize, we need to take some steps to solve the crisis in our day. We may start at the most general level, by becoming more reflective about our social sciences. We should better recognize the hidden agenda of these sciences, and see how they operate in our society at large, with the blind alleys and blind spots, fostered by the blinding of paradigms ‘in use’ by scientists. The focus should be on the relationship between these sciences operating and the way we view reality, as a kind of reality which is a ‘delivered’ reality by scientists in the field of social sciences. This is the starting point for departure: for the rethinking of a reality we commonly take for granted in our viewing and doing ‘normal’ science. To solve the crisis we first need to take steps to escape the reality as assumed, by becoming critically reflective, and to start rethinking our ways of knowing of that reality, commonly taken for granted in ‘science as usual’ (Longino and Doell 1983/1987; cf. Kuhn’s ‘normal science’). We may start ‘delivering’ a different reality by liquefying reality, turning reality into a dynamically fluid reality, about a world of being through becoming (see Prigogine and Stengers 1984, p. 310). It is about a reality which no longer ‘unfolds’, but one which shows transitions and transformations, and even metamorphosis, enabled by complex ‘bootstrapping processes’ with nonlinear effects over time. The key question is: “How can we describe, understand, and explain such a dynamic, (potentially) nonlinear, complex reality?” To address this question, we need to rethink the common concepts in use for our viewing and doing science. These are, for instance, concepts like causality, complexity itself of course, and the concept of interaction. Doing so already implies a new kind of methodology as well: a methodology which is not only focused on the description of a static version of reality but one that may really capture the changes in the subject of study in the social sciences. The methodology should address the processes of change in the real, by taking into account the role of time, as Darwin has done for evolution in the scientific realm of biology. His conception of evolution is still expanding our view of reality and the scientific objects of study in the different scientific realms of our sciences in a dramatic way (cf. the mission of the European Institute Para Limes, in the Ruurlo manifest 2006). The challenge, then, is to dis-cover the principles which play a role in explaining the changes that take

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place in the real. To do so, it may become possible to ‘master’ the complexity of reality, even when it is a nonlinear, complex reality. Conceiving of a new reality of complexity of real-world complexity implies the conception of a kind of dynamic complexity of that very reality, with its own specific real world dynamics. This means that complex reality is not to be taken as just linear, but as a potentially nonlinear complex reality (Mainzer 2004, p. 407). It offers the opportunity to become more aware of old habits of thinking, and of the need to escape the danger of linear thinking, and the very danger of becoming blind to the shortcomings of our own “working theories”,9 in this new expanded version of reality. The focus is on what Archer (2000) describes as “bringing real people back in”10 (p. 306); that is, about the discarded, but very important role of agency of the human being. This can be taken into account through a new way of thinking in complexity. As a consequence, the very nature of human being may be envisioned as a more complex being: actually as a potentially nonlinear human being. This notion of the complex human being may have implications for our thinking about complex, concomitant states of human being and their dynamics involved in these states (cf. Sassone 1996, about generativity as a state of the human being; cf. Wimsatt 1999). Even more important is, how a theory of change can be developed about those states of being, i.e. about their transitions and transformations over time, through subsequent evolution (see Prigogine and Stengers 1984, p. 310; cf. Vygotsky about the role of evolution, involution, and revolution in development through interaction). It might be a theory of nonlinear human being through becoming, linking the linear with the nonlinear as both very much part of reality: not opposed to the other, but as expressing “two related aspects of reality” (see Prigogine and Stengers 1984, p. 310). Viewing reality this way has consequences for the study of those states of (nonlinear) being and their transitions. The study of learning and of knowing and the ways of learning and knowing, of getting knowledgeable, may become very different as well (cf. Jörg 2010). The general idea is to turn thinking in complexity and about complexity into real creativity about that very same reality. We may become realistic in a new, more dynamic, and more creative way. In the next chapters the focus will be on the rethinking of our view of the world, and of the rethinking of our viewing and doing science in the world we live in. In Chap. 4, a programmatic view will be delineated about how to change our worldview, and start building a new science for the field of social sciences. We may start with the question: “How can we ‘deliver’ a different reality in our viewing and doing science?” The focus, then, is on inventing by building anew the social sciences, by rethinking the very foundation of those sciences. We may wonder if it is possible to ‘see’ what is lacking or taken for granted in theorizing about those social sciences. What kind of new building stones may be necessary for building a new science?

 See Dewey, in Freedom and Culture, about the greatest danger of becoming blind to the shortcomings of our own “working theories” (in Clark 2002, p. 388). 10  See Margaret Archer 2000, p. 306. 9

Steps to Be Taken

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It should be clear to the reader that this building of a new science is not just a vision thing,11 or an alternating of visions, but a truly scientific enterprise. We really need to escape the blind alleys, the conceptual deadlocks etc. of our science,12 to be able to become scientific about the very complex subject of study in our viewing and doing science. It is only by rethinking and by finding new tools of thought that the birth of a new science may be fostered, based on a new framework for the field. This is the field of the unknowable, and about a framework that does not exist yet. All of this rethinking may ultimately result in new avenues for our social sciences and humanities, thereby opening panoramic vistas of complex landscapes of possibilities and potentialities of development within the enlarged, hitherto unknown spaces of the possible; that is, within “a vast landscape of poorly known elements” (Scheffer 2009, p. 328). Ultimately, all of this rethinking has its relevance and significance for the sake of a better future for our social sciences and humanities. In the end, and at the end of this book, we hope to sketch a new science of complexity, with the promise of turning science as usual into a new science of complexity, to be conceived as a new foundation and a new tool for viewing and doing social science. For this reason, we fully agree with the Dutch ecologist Marten Scheffer, who stated in his recent book that to bridge with the unknown, “we need good science to help us shape the future in the best way” (Scheffer 2009, p. 8).

 This seems to be the usual misunderstanding in viewing the role of theory, and that of practice.  See Dewey, in Freedom and Culture, about the greatest danger of becoming blind to the shortcomings of our own “working theories” (in Clark 2002, p. 388); cf. situation of deadlock, in Archer (1995), p. 26, about programs of Methodological Collectivism and Individualism. 11 12

Chapter 4

Giving Birth to a New Science – Setting the Agenda

We are observing the birth of a science …. that views us and our creativity as part of a fundamental trend present at all levels of nature (Prigogine 1996, p. 7)

Introduction Inspired by the original thoughts of Thomas Kuhn (1970), we believe that crises are “a necessary precondition for the emergence of novel theories” (p. 77). To develop new theories, we first need to become aware that scientific theories are not mere reflections of nature. To deal with the very crisis we are in at this moment, as described in the preceding chapter, we need to take some steps to ‘solve’ the crisis, in the sense of making a transition to a new way of thinking, i.e. new thinking in complexity. This may lead to a new worldview, which will ultimately be an enlarged worldview. We take the position that we might look afresh at nature in all of its complexity. Of course, we recognize the problems of this new thinking, such as the need to escape old habits of thinking and “to unlock people from their mindset prison” (Stevenson 1999). Henceforth, we may conclude that for real new thinking, we need to start to think outside the box. We not only need to escape the hidden agenda of the social sciences (cf. Dennett 2003), but also have to set a new agenda for a new future for these social sciences and humanities (Tindemans et al. 2002). We propose here that the key for new thinking is in the new thinking in complexity. The question of how complex complexity really actually and factually is seems still largely unknown, and for a large part unanswered. This ignorance about complexity as real may be ascribed to a kind of provincialism or parochialism. This has led to major exclusions of reality (Whitehead 1925; Wallerstein et al. 1996). As an example of this exclusion, we may demonstrate the effects of reductionism, which have been dominant for centuries, and still are.

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_4, © Springer Science+Business Media B.V. 2011

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These effects are both positive and negative. In a real sense, this reductionism is to be feared more for its success than for its failure (see Doll, in Fleener 2002, p. xii). The negative effects, however, are real. It is because of these negative effects that some even view reductionism as destructive (Bohm 1996, p. 127). In a similar vein, scientists of the Dutch Committee of the PPCCS,1 spoke openly about “the ‘scandal’ of reductionistic theories” (2001, p. 29). This scientific committee admits that “an integrative theoretical account of ‘real’ cognition still seems a far cry” (p. 29). We think this state of art of the science of cognition is part and parcel of the very crisis we are in, in our viewing and doing ‘normal’ science (in a Kuhnian sense). The proposed new thinking in complexity, therefore, may be regarded as expanding reality. Such expanding may be regarded as bringing forth the whole of reality, as an unbroken totality (Bohm 1996, p. 76). After all, we may dis-cover that we may reclaim reality (see Bhaskar 1989). We therefore conclude that reality is actually a kind of choice to be made by us as scientists, implicitly or explicitly; that is, in our viewing and doing science (see Jörg 2009). In literature, different answers have been given to the problem of complexity from different perspectives and disciplines. Some of these are opening for the social sciences. They lack, however, the setting of the agenda for a new science or a new way of thinking in complexity. For developing a new science, we start with the basic truth, that you cannot find a (new) science; you ‘simply’ have to build it yourself, as already expressed in the work of Vygotsky (see Van der Veer and Valsiner 1991, p. 153). This is not an easy task. We are of the opinion that the question of complexity itself as a concept is in need of a rather different, more complex answer. So, we have to start thinking in and about complexity in a different way. This may imply a shift of paradigm, that is, towards a new paradigm of complexity (cf. Morin 2008).

Thinking About Complexity The concept of ‘complexus’ originally has the meaning of “that which is woven together”,2 and that is what thinking in complexity essentially is about. Thinking in complexity is thinking about the dynamic complexity of the real-world dynamics. The explicit aim is “to conciliate philosophical conceptions of a real world with the world of daily experience” (Whitehead 1929/1978, p. 156). This new thinking, in dynamic complexity about real-world complexity, with its real-world dynamics, may be understood as “a new way to deal with new realities” (Bellah et al. 1985, in Flyvbjerg 2001, p. 64).

PPCCS (Program Preparation Committee for the Cognitive Sciences) (2001). See Morin (2001), p. 31.

1  2 

Giving Birth to a New Science?

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In a fundamental sense, thinking in complexity goes beyond the linear way of thinking, by considering reality, in terms of the real-world dynamics, as a potentially nonlinear complex reality. In a basic sense, this is the new reality of complexity as the subject of study. We may also speak about the new complexity of reality. Therefore, the focus of new thinking in complexity for the social sciences is on the dynamic complexity of the real-world dynamics. By taking ‘complexus’, and complexity as “that which is woven together”, we view complexity not only as a result of weaving, but also as the very process of dynamic weaving, as a very complex process with potentially unexpected, nonlinear effects. It is this dynamic complexity, which is essential for a new science. It is such thinking in complexity, which is according to Ilya Prigogine is the key for scientific novelty and innovation. To be more precise, we mean here the capacity to utilize unexpected novelty: in terms of effective novelty (see Wilden 1987, p. 310; Goerner 2007, p. 491). This is the very kind of novelty and innovation which we need to enter what Prigogine has described as a new scientific era: We are at the beginning of a new scientific era. We are observing the birth of a science that is no longer limited to idealized and simplified situations but reflects the complexity of the real world3

Giving Birth to a New Science? The aim of this book is to build a new science by developing a new transdisciplinary approach. This new approach is based on the new thinking in complexity. This aim is very much inspired by the work of Vygotsky, who was fully aware of the complexities involved in describing and understanding reality anew. To do so, to start new thinking, one needs a kind of rebellion against the old way of thinking. Vygotsky himself started out in 1926 as a rebel indeed, with his contribution about the crisis in psychology being one of his first original contributions in the field. He knew very well that he had to invent the new science, to give birth to it. Our aim to give birth to a new science is therefore in line with his attitude and new ways of thinking, i.e. for the discipline of psychology. With the new approach advocated here, we believe we can open up the social sciences, and to set a new agenda for these sciences.4 This new approach may foster a new future for the social sciences and humanities (cf. Tindemans et  al. 2002). We strongly believe that this opening of the social sciences may open new spaces of possibilities, and can bridge to the hitherto unknown domains of potentiality (cf. Doll, in Fleener 2002, p. xii; see also Bohm, in Morgan 1997). It may not only

Ilya Prigogine, as quoted in the Program Book of the Conference on Complexity Research, Liverpool, CCR Centre for Complexity Research 2005. 4  Cf. the report “Open the Social Sciences”, of the Gulbenkian Commission on the restructuring of the social sciences, by Wallerstein et al. (1996). 3 

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change the nature of things, as active and creative, but also offer a new possibility, to re-imagine what it is to be human, creating a new life, a new way of being, infused with meaning and purpose (Fleener 2002, p. 194; cf. Wallerstein et al. 1996, p. 61; Stevenson 2008, p. 10). As a consequence, the very nature of human being may be envisioned as a more complex being: actually as a potentially ‘nonlinear human being’ (Stanley 2005, p. 143). This new vision of the human being may be viewed as a really promising finding of the new path to be taken in the social sciences (cf. Bohm 1996, p. 136). The new approach of thinking in complexity may also be very promising for understanding and explaining the fundamental nature of creativity, novelty and innovation (cf. Wallerstein et al. 1996, p. 63). These phenomena are all-important for practice in various ‘applied fields’, such as the field of learning and education, and in so-called ‘Communities of Learning’ and ‘Learning Organizations’ (Jörg et al. 2007; Jörg 2007, 2008a, b, 2009). These can be conceived, then, in terms like ‘healthy collectivities’ and ‘healthy learning organizations’, as examples of complex, healthy social organizations (see Stanley 2006).

An Agenda for a New Science The first question, about how to deal with the problem of complexity, is how thinking in complexity may look like for the field of the social sciences and humanities.? This question involves two basic problems: 1. How to conceive of the real-world complexity of reality? What kind of steps do we need to take for that? 2. Is it possible to understand and express that new conception of complexity in the old lexicon, or do we need a new lexicon and a new vocabulary for the new thinking in complexity? Giving the answers to these basic problems demands a new kind of thinking; a way of thinking which is different from the traditional ways of thinking. It may be stated that to start such new thinking, one first needs to escape the old habits of thought, as “our own particular conditioning to certain habits of thinking” (Bohm 1996, p. 113). In practice this means that the new thinking and its effects can be orthogonal to those old habits of thought (see e.g. Vygotsky 1926/1997; Keynes 1928; Dennett 2003). This brings with it a real problem of communication, which may be compared with the problem of a shift of paradigm, as described eloquently in the work of Thomas Kuhn (1970, 2000). Complexity, as conceived in the next chapters, is a really complex concept. Actually it may be too complex for the reader. The reader should become aware that thinking about complexity as usual is different from thinking in complexity as put forward in this book. Understanding our conception of complexity may be rather different. Our focus is on the very complexity of complexity itself. This is the key of new thinking in complexity for the social sciences and humanities. The reader

Understanding Complexity Anew – A Note for the Reader

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will be able to think in complexity, as we conceive of and develop this complex concept itself, only after having made all of the steps needed for that. They are the precondition for the development of a new science of complexity. After making all of these steps the new science may open up new vistas and a new foundation for the social sciences. We discern several of such steps of new thinking. These steps comprise a kind of complex, entangled web of concepts that is constitutive of our approach for a new science of complexity. All of these steps are necessary. Taken together, they may offer a new trans-disciplinary approach for the social sciences that is of use for all disciplines in this broad field of the sciences. This trans-disciplinary approach is a fully integrative approach.

Understanding Complexity Anew – A Note for the Reader For the reader there may be a real problem in reading this book. In trying to describe and explain what new thinking in complexity may mean, he or she has to enter the field of new thinking which is largely developed and explained in a new language, with the use of a new vocabulary. We may remind the reader of the validity of the conclusion of Thomas Kuhn, that a new science cannot simply be understood and explained in the ‘old’ lexicon. For the social sciences it seems a basic truth that: “The choice of language often predetermines the outcome” (Wallerstein et al. 1996, p. 89). The reality, mostly taken for granted by scholars, is very much a languageeffected reality, like in the field of education (see Davis 2004, p. 99). The need for a different language makes the communication about a new complex reality a rather complicated affair. It may even become a threat for a fruitful conversation. This specific problem of communication in building a new science has been described and emphasized by Thomas Kuhn, in the 1960s of the last century, in his famous book The Structure of Scientific Revolutions (Kuhn 1970; see also Kuhn 2000). So, we may put the question: “How may the reader understand the new thinking in complexity as developed in this book?” as a key question for reading and understanding. From the work of Thomas Kuhn, one may derive that a shift of paradigm is not for free. The process involved in fostering such a shift is not just reading of the text. There is more ‘work’ to do for understanding. Actually the demand can better be understood as a reform of thought (Morin 2001). So, it should be clear to the reader that reading about new thinking in complexity may be complex itself. This is definitely true as well for the writing of this book! This is very much the topic of communication about complexity. The real difficulty involved in communicating the aim of new thinking in complexity may be illustrated by referring to the more recent work of Gregory Bateson (1972), in his book “Steps to an Ecology of Mind”. In this book, he tries to convince the reader of the need for new thinking: “The most important task today is, perhaps, to learn to think in the new way” (p. 462). Surprisingly, his own answer to this is as follows: “Let me say that I don’t know how to think that way” (Bateson 1972, p. 462;

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italics in original). The reader may, therefore, wonder why this is the case. Seemingly the complexity involved in new thinking is too complex. But there is the more general problem, of becoming aware of our assumptions in viewing and doing science as part and parcel of the paradigm ‘in use’, with the language and vocabulary as a natural part of this paradigm. As a result, we may easily be a kind of prisoner of our own habits of thinking. This is what makes it so hard “to comprehend the possibility that there might be other ways of thinking” (Lincoln and Guba 1985, p. 9). In conceiving and writing this book, we also recognize the extreme difficulty of learning to think in a new way, that is, by thinking in complexity. The task is not only to learn to think anew but as much a process of unlearning the old ways of thinking about the basic concepts ‘in use’ in our viewing and doing science. The rethinking of each of these basic concepts is already complex in itself. For a real reform of thought we may need a kind of web of new thinking for reframing complexity, to deal with the complexity of new thinking in complexity. This means that, as a reader, one needs to put some real effort into understanding how to think in this rather complex way. Many steps are needed for that purpose, to “open the social sciences” (cf. Wallerstein et  al. 1996). We discern several steps. These steps are delineated and elaborated more fully in the next chapter, which is about the new agenda for the social sciences. This is inclusive of a programmatic view for new thinking in complexity for the social sciences and humanities. These steps are: 1 . starting to become reflective about the nature of things 2. escaping old thinking about the complexity of reality 3. becoming aware of potential new ways of knowing 4. new thinking about interaction 5. new thinking about causality 6. new thinking about the unit of study All of these steps are needed and necessary steps for new thinking in complexity for the social sciences and humanities. We hope to convince the reader that these steps, taken together as a unity, are also recognized as being sufficient for the aim of this book: to build a new science, of complexity, by learning to think in complexity.

Starting New Thinking in Complexity We may start at the most general level, by becoming more reflective about the social sciences. Only then, we may escape the danger of linear thinking and the imprisonment of meaning in our viewing and doing science. We should better be able to recognize the hidden agenda of these sciences, and see how they operate in our society at large. We should become aware that “scientific truth is itself historical” (Wallerstein et al. 1996, p. 58). The focus, therefore, should be on the relationship between these sciences in operation, the nature of reality, and the way we view reality.

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To become a real thinker in complexity, one needs to learn to think in complexes; that is, of that which is interwoven. To put it differently: one needs to accept the fundamental complexity of reality. We fully agree with the report of the Gulbekian Commission on the restructuring of the social sciences as regards their following goal: “The complexity of social dynamics needs to be taken more seriously than ever” (Wallerstein et al. 1996, p. 78). This is not an easy task, as recognized by Bateson (1972; see above) and Lincoln and Guba (1985; see above). Reality is not given but, from an historical perspective, always an invented and constructed reality. So, reality can be different. We want to state here that reality implies a kind of choice that can be made, be it implicitly or explicitly. In line with the thinking of the mathematician and (later) philosopher Whitehead, we believe reality is a process, and nature is a structure of evolving processes (see Whitehead 1925/1967, p. 72). From the very start of our new thinking in complexity, we strongly believe that there is no simple map for thinking in complexity about reality. To be (more) clear: every notion of a map of reality of complexity should not be taken as the territory. To think in complexity, we need to be more open to solving the problems concerning ever more complex phenomena (see Wallerstein et al. 1996, p. 61). It may be stated that the path to be taken for new thinking in complexity may turn out to be a really tortuous path. It may seem a basic truth that thinking in complexity cannot be made simple. This difficulty, however, is not only a hindrance for the progress of our sciences, but may also mean that something really new can be discovered along the tortuous path. We are of the opinion that this path is the path of novelty of fact and theory, so much needed for the invention of a new science, which is based on a shift of paradigm (see Kuhn 1970; Lincoln and Guba 1985); in this case, the very paradigm of complexity, with its new thinking in complexity. Following the steps of new thinking, one may not only become aware of a greater complexity but also of a larger reality, and of a richer reality. The steps needed for that are not just individual, separate steps but should be taken as fully intertwined and integrated, as an entangled, dynamic web. One cannot simply leave a step out of the thinking anew. Every link in the complexity of the web may be considered to be a kind of missing link in the new thinking in complexity. The steps are complexly interwoven indeed! They form an intertwined, complex web of new thinking, to be considered as constitutive of a new science and of a new transdisciplinary approach for the social sciences and humanities. That means that the reader has to take all of the steps, to be able to fully understand how the new thinking in complexity may ‘work’ in practice, in our viewing and doing our activities as scholars within these fields of our academic disciplines. Based on new thinking in complexity, one may get acquainted with the new concepts in their full interconnectedness. The different steps, presented in the following chapters, will be presented sequentially, in a successive treatment of the steps. Reading the steps for new thinking should actually be considered to be taken simultaneously in thought, as a unity (cf. Whitehead 1929/1978, p. xii). Reading the steps separately, one does not get acquainted with their interconnectedness directly. Reading the next chapters, therefore, will not always be easy.

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One needs to consider these steps as fully integrated for the understanding of the paradigm of complexity. We take an integrative perspective ourselves in the chapter about ‘the complexity of complexity’. So, it seems largely up to the reader to connect the steps to be taken while reading: step by step. Meanwhile, we will try to make clear how the very concept of complexity increases by making the different steps; that is, how they are complexly connected. After making all of the steps, the reader may get an impression of how the new thinking in complexity can be used for getting trans-disciplinary in our approach to doing science, henceforth heading for a new, fully transdisciplinary approach. To get the job done well, we need not only describe the steps, but also understand the steps to be done and to explain how these steps are a kind of tools for explaining how complexity may ‘work’ in practice. We hope to describe and explain how complexity may turn, and, even more importantly, be turned into effective complexity. This job can be done, we believe, by connecting the thinking in complexity with theorizing about the nature of generative processes: to describe and explain “how complex novelties are generated, how they integrate with what already exists, and how new, more complex whole organisms can be greater than the sum of their parts” (Reid 2007, p. 9; emphasis added). This kind of theorizing, we think, opens a new perspective for the field of the social sciences and humanities. We believe that all of such new thinking in complexity about generative processes may be of use for integrating e.g. “the developmental, evolutionary, and cognitive sciences” (Reid 2007, p. xii). This kind of integrative, new thinking makes this approach a real transdisciplinary approach: “that which is at once between, across and beyond all disciplines” (Bertea 2008, p. 2; italics in original 5). In line with this author, we also consider transdisciplinarity as “a superior manner of understanding the world from a scientific, systemic and holistic perspective” (Bertea 2008, p. 2). To conclude, we believe that the new thinking in complexity, as a transdisciplinary approach, with its new language, offers a way of decoding reality and creating reality at the same time (Whitehead 1929/1978; cf. Pinar 2006). The new thinking in complexity, about the dynamic complexity of real-world complexity, may therefore open up new ‘possible worlds’. It may be shown that social scientists, adopting the new thinking in complexity, may “practice their trades in a different world” (see Kuhn 1970, p. 150). This is as much true for biologists, who focus on the nature of complexity in their viewing and doing science (Sole and Goodwin 2000): “The sciences of complexity show us that we are embedded in a world fundamentally different from that which has previously characterized modern science, with its emphasis on prediction and control” (p. 28). In the next chapters the focus will be on the rethinking of our view of the world, and of the rethinking of our viewing and doing science in the world we live in.

Retrieved on 2 October 2008 from: http://www.redebrasileiradetransdisciplinaridade.net/file. php/1/Artigos_dos_membros_da_Rede/Trabalhos_apresentados_no_II_Congresso_Mundial/ Artigo_Mircea_Bertea.doc 5 

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Finally, we will try to show the consequences of our new thinking in complexity for practice: for the field of learning and education and the field of complex collectivities such as communities of learning and learning organizations, with their own complex, real-world dynamics. We believe that the new way of ‘seeing’ and thinking may enable and promote a new more viable type of education. A type of education that creates the possibility of a new kind of being of the human being: of “an education that addresses the open totality of the human being” (in Mircea Bertea 2008, p. 29; cf. Fleener 2002, p. 194; see also Jörg et  al. 2008; and Jörg 2009a, b). The human being, then, may be conceived as a dynamic being through a dynamic process of becoming; that is, of a process of ‘coming into presence’ (Biesta 2006). This will be a rather complex process of becoming, which is “a becoming of ourselves through others” (Vygotsky 1981). Vygotsky was very much aware of the complexities involved in this very process of becoming, where he described the process of learning and development, that is, “the growing complexity of children’s behaviour”, in terms of the entire process of development, and the reconstruction of this process (Vygotsky 1978, p. 73). In the 1920s and 1930s of the last century, he described this process of growing complexity in his chapter about the new method, thereby using the concepts of (more) complex inner operations, the intertwining of internal and external factors, and even the current popular concepts of turning points, metamorphosis and qualitative transformation already, as characteristics of his new method of approach to development (Vygotsky 1978, p. 73). He rejected the Darwinian view of gradual change, that of the straight line, and of gradual accumulation as the dominant view about cognitive development (Vygotsky 1978, p. 73).

Chapter 5

A New Agenda for the Social Sciences

You may not want to hear You may want to hear You want to hear You may not hear You may hear You hear From Bruce Nauman1

Introduction To recap, this book is about new thinking in complexity for the social sciences, to promote the building of a new science. For sure, it may be hard to imagine how a new science can be built. Actually, it may seem that one has to invent the science anew. So, the problem is how to start this very process of invention and, maybe even more importantly: how to go on in this rather complicated process. The particular problem to deal with now, is how to find the right entry to new thinking in complexity as the fundamental building block for the foundation of a new science. In the preceding chapter we gave several distinct steps of new thinking that are needed to make up this fundamental building block. Every step comprises one element of new thinking in complexity. Each step is not only needed but, as a unity, these steps are also fully constitutive of a new transdisciplinary approach with a new, unified way of thinking in complexity. In our approach to build a new transdisciplinary science, we may make a distinction between the description of complexity, with a special focus on the dynamics of complexity and the scientific explanation of the dynamics of complexity.

 Bruce Nauman, American artist, shown at an exhibition of a project in the Tate Gallery in London, 2005.

1

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_5, © Springer Science+Business Media B.V. 2011

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Box 5.1  The Metaphoric Description of New Thinking in Complexity New thinking in complexity is an adventure of following a tortuous path, full of uncertainties. It is the path towards a new, dynamic, complex space of possibilities, within an ever-evolving landscape of unknown dimensions. This new landscape is conceived as part of a dynamic unified reality. This dynamic reality consists in both the linear and the potential nonlinear. It is a complex reality, of a fluidly integrated kind, with processes of enabling being through becoming within the social real (m) of our real-world dynamics.

In the end, however, these complexities should be integrated in an all-encompassing view. This makes the dynamic interweaving part and parcel of the new thinking in complexity. How may this interweaving be described, understood and explained in our viewing and doing science? In Box 5.1, a metaphoric description is given of what new thinking in complexity may actually involve. This is only a description but reading a description like this, the reader may obtain a clear impression of the task and of the rather tortuous path to be followed. We hope for the reader that it will be a shared path, of reading but also of inventing the unknown path: a path that leads towards a new ‘domain of potentialities’ (see Bohm, in Morgan 1997) and of opening new spaces of possibility. Thus, the reading of the next chapters demands a kind of readiness to open up new spaces by learning within the hitherto unknown of the seemingly unknowable. For the reader, learning to think in complexity might be a process, with distinctive steps, about the development of new states of being, as formulated in the statement of the American artist Bruce Nauman above (at the beginning of this chapter). Instead of the very complexity of the process of hearing in the social space of possibilities, the focus here is on the opening of new spaces with their possibility of being in different states. We view the reader as a professional reader in the field of Social Sciences and Humanities. In advance, it may be unclear for the reader how to enter these states and realize a transition from one state to the next. A transition like this is essentially the transition within the space of possibilities, within the domain of potentialities of the new science.

New Thinking for a New Science In this chapter all the steps mentioned in Chap. 4 will be shortly delineated. They may be considered as an agenda for the ‘building’ of a new science. Actually, it will be more of a process of invention. We give a short description of the steps needed for this process of invention. In the next chapters we go deeper into every separate step to be made.

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On Becoming Reflective About Our Viewing and Doing Science It is not easy to be reflective about our own viewing and doing science and to find the courage and power needed to escape our habitual modes of thought and expression. The reader may (still) wonder why there is still no adequate complexity thinking for use in the field of social sciences, to build up a new science. We may refer here to the work of Kuhn (1970) about the problem of shifting paradigms in our history of sciences. It seems that the problem of inventing a new science is too complex to deal with. That makes becoming reflective so important to start with, for new thinking in complexity as a foundation for a new science. Many more steps have to be taken for new thinking in complexity, to develop adequate tools as a kind of building block needed for a new science. It is only by becoming reflective, in a self-critical mode and by standing on the shoulders of some giants in the field of social sciences that we may succeed in escaping the dear old habits of thought, to be able to disentangle the complexity of the problem and find the tortuous path of inventing the new science. It is only by becoming critically reflective that we may discern how many steps are needed to learn to think in complexity and build a new science. We hope to elucidate that we really need all of the steps delineated below for this scientific enterprise. Steps which are not to be taken in sequence but have to be taken as fully intertwined. These steps are fundamentally interrelated, as will be shown below. The new conceptions of causality, interaction and complexity for instance are fully interrelated. This connection is not always dealt with in an adequate way in literature about complexity science. It is the very complex interrelatedness of all the needed steps to be taken that may make it clear for the reader why this challenging enterprise of inventing a new science has not been done before in the social sciences. It is time to become really innovative in developing a new way of thinking in complexity in and about social sciences and turn them into a social science of transition. This science of transition will be a new kind of (social) complexity science. Ultimately, this will be a trans-disciplinary science, of use to all the disciplines in the field of social sciences. Starting with the rather diffuse notion of complexity, we take up the challenge to turn this concept of complexity of (human) agents in communicative interaction into a new concept of dynamic complexity and finally, develop the new concept of effective complexity: effective in the sense of bringing about ‘complex’, potential nonlinear cumulative effects over time. It is this notion of effective complexity that is of utmost importance for pragmatic use in our social sciences. Actually, it is the quality of interaction and the quality of relating within reciprocal relationships, turning communicative human interaction into effective interaction, which is contributing to the effective complexity as the quality of dynamic complexity, as characteristic for effective communicative interaction between (human) agents. It may be demonstrated that we need to take all seven steps to obtain a better picture of complexity in terms of the dynamic complexity as a subject of study in the new science of transition, about the processes of being through becoming over

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time. Below, we sketch the steps to be taken in terms of a programmatic view. We believe that the new science can be invented in the process of invention, made possible by taking all of the steps needed for that. By giving a kind of programmatic view, the reader may become aware of the full interconnectedness of the different steps. Reading all of these steps may be rather abstract. To make new thinking in complexity a little bit less abstract, we give a specific, concrete example of complexity that may be well understood. This may help the reader to obtain a better idea what new thinking in complexity is about. It is about the complexity of (dialogical) interaction. This example is from the work of Mary Parker Follett (1924). It gives a nice description of the complexity involved in human interaction. At the same time, this description demonstrates the interconnectedness of the different steps to be taken to understand and explain how this interaction ‘works’ in practice. Follett’s description of human interaction underscores that “human interactions are quite complex” (Basu et al. 2008). We believe this specific example may give better insight into the complexities involved in interaction in general and of those in human interaction in particular. It describes not only the complexities involved but also tries to become more explanatory about these complexities. In this sense it is a unique example. After the presentation of this example we go on with the next steps to be taken. Case from Mary Parker Follett (1924) It is possible to link our new thinking in complexity with her work. For illustration we may ‘simply’ concentrate on a single quote from the chapter “Relating: The Circular response”, in her book “Creative Experience” (1924), to show the many links. In this quote, many elements of our new thinking are already there. The first element to stress in her conception of interaction in human relations is her notion of influencing each other in that interaction through the complex responses of each partner, conceived as reciprocal influences within a circular interaction (cf. Vygotsky 1981, p. 162). However, the most important element in Follett’s description is the role of relating for human interaction: “response is always to a relating”.2 It is not a separate fixed “I” and a static “you” but a fluid mixing of both partners in interaction, both involved in a dynamic process of interweaving in that interaction. Follett conceives of interaction as a process of dynamic interweaving in and through the relationships.3 Both partners seem to constitute a kind of web in such a process of interweaving, each weaving their own web through the dynamics of interweaving between them.

 This notion links very well with the complex responsive responses by Stacey (2001) and his description of the involvement of partners in communicative interaction as “complex responsive processes of relating” (p. 6), or as “ongoing participation in patterns of relating” (p. 210; emphasis added). 3  See also Chia (1998) for a similar view. 2

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Follett also recognizes well that the effects may be different for both partners: “both become different”. These effects may become cumulative effects over time. Implicitly she shows how the effects become cumulative over time: through influencing each other with the concomitant effects of this influencing. She even conceives of the possibility of modelling these cumulative effects mathematically, linking this notion of modelling with the possibility of “working it out to the nth power”. Although she is not explicit about the consequences of it, this actually means that the total (cumulative) effects may be nonlinear! Implicitly one may derive from her description that these potential nonlinear effects may be different for each of the partners in interaction. So, the effects may be asymmetrical in human interaction. Follett’s description is illustrative of the complexity, in terms of ‘that which is interwoven’ and of the dynamics of the network involved, of the web. It shows the process of dynamic interweaving of a network, with the network of actors not treated as fixed but as dialectically constituted by social relations, which, in turn, are kind of ‘produced’ by the movement of people and things (cf. Nespor 2002, p. 368). We may conclude from our analysis of Follett’s quote that she has described eloquently the very complexity of human interaction as a process of dynamic interweaving through complex responses within a process of human relating with effects, which seems unpredictable because of the dynamics of complexity involved but may become potentially nonlinear. It may be no surprise that Follett was well aware of the significance of her thoughts. She knew they were foundational for “a new approach to the social sciences” (Follett (1924), in Drucker et al. (1995), p. 50) All of the elements mentioned above, including the conclusion, will return in our conception and modelling of the dynamic complexity of human interaction. This makes her a prophet for us as well: a prophet of thinking in complexity.4 In this and the next chapters, we show that all of the elements derived from Follett’s description are constitutive for our new thinking in complexity. We may think of these elements as necessary conditions for understanding complexity: both of the description and the explanation of how complexity may work in practice. Description is taken here as description of both the dynamic, complex processes and the structural description of the dynamic, complex relations involved. However, are these conditions also sufficient conditions? We do not think so. We also need some additional elements, like the causal dynamics involved in human interaction (see Vygotsky 1978). In their combination, the elements are fully enabling to turn the more basic notion of complexity into the concept of dynamic complexity. Ultimately, we try to become explanatory in our modelling by showing how to turn dynamic complexity into effective complexity with its cumulative effects over time. We do so by inventing an adequate modelling of the inherently causal dynamics involved in the dynamic complexity of human interaction. This notion of causal dynamics and the modelling of it was lacking in Follett’s description of the dynamics

 Although she is not the only one (see the work of Vygotsky for a different complexity view, also operating in this era), she is definitely the most complete in this respect.

4

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Box 5.2  Quote from Mary Parker Follett (1924)5 In human relations, this is obvious: I never react to you but to you-plus-me; or to be more accurate, it is I-plus-you reacting to you-plus-me. “I” can never influence “you” because you have already influenced me; that is, in the very process of meeting, by the very process of meeting, we both become something different. It begins even before we meet, in the anticipation of meeting. We see this clearly in conferences. Does anyone wish to find the point where the change begins? He never will. Every movement we make is made up of a thousand reflex arcs and the organization of those arcs began before our birth. On physiological, psychological and social levels the law holds good: response is always to a relating. Accurately speaking, the matter cannot be expressed, even by the phrase used above, I-plus-you meeting you-plus-me. It is I plus the-interweaving-between-you-and-me meeting you plus the-interweaving-between-you-and-me, etc., etc.!!! If we were doing it mathematically we should work it out to the nth power.

of human interaction. The causal framework, so common in use nowadays in the social sciences, had still to be ‘invented’ in her day (see Chap. 3 in this book).

Escaping Old Thinking About the Complexity of Reality Above we made a first step, of becoming reflective about our viewing and doing science. We may do a next step by considering the option to develop a different view about reality, to rethink reality. It may become clear that “linear thinking may be dangerous in a nonlinear complex reality” (Mainzer 2004, pp. 15, 407). Most people in the field of social sciences simply stick to describing complexity, assuming that “an approach that works well for describing complexity (decomposition into parts and interactions) is an explanation of how the system’s operations came to be what they are” (Clancey 1997, p. 243; cf. Zilsel 2000, p. 187, about this misunderstanding). These people are taking complexity as a kind of ‘given’ reality, taking the relationship of complexity with that reality for granted as well (Jörg 2007). Thus, we need to become aware that we, by our organization of knowledge, may actually have a misleading picture of reality (Rescher 2000, pp. 77–78). 5

 See Mary Parker Follett (1924), pp. 62–63; or in Drucker et al. (1995), p. 42 (emphasis added).

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As an alternative, we propose to focus on the reality of the dynamic complexity of the real- world dynamics. The rethinking of reality, with a possibility of redefining of that very reality, may in the end lead to a reclaiming of reality.6 Resulting from this reclaiming, we may speak about the ‘delivering’ of a new, more complex reality for the social sciences. Reality is ‘simply’ more complex than we have always thought in the social sciences. The conceived reality of complexity is very much about the (causal) dynamics of dynamic complexity.

On Becoming Aware of Potential New Ways of Knowing Complexity science has offered a way of rethinking reality, by rethinking our ways of knowing. By thinking in complexity we may go beyond the fragmentary of studying reality, by taking complexity of reality as ‘really real’. We may better understand how complexity turns into dynamic complexity and how this, in turn, may develop into effective complexity. Thinking in terms of (dynamic) complexity in general may be considered as a way of opening new ways of knowing about the dynamic complexity of the real-world dynamics. A way of knowing this is at the same time opening the social sciences for a different future of these sciences (Wallerstein et al. 1996; Tindemans et al. 2002). New thinking in complexity addresses relevant topics like ‘the problem of life’, the nature of things and the complex unity of the human. All of these are related to what we see as the epistemological problem concerning the complex unity of the subjects of study, i.e., that of the complex unity of the human (see Morin 2001, p. 39). The new thinking in complexity may offer a reform of thinking, by enabling forms of thinking that are “more adequate to the task of revealing the whole spectrum of human lived experience” (Chia1998, p. 341). Opening the social sciences and turning these into a transdisciplinary approach of science demands not only a reform in thinking but also for a rethinking of our ways of knowing. How do we know what we know when we start to think in complexity? How can we learn to think in complexity? And of course, we may put the question why we should learn to think in complexity? This question, we believe, is connected with the problem of the nature of things: with “the process of the actual world” (Whitehead 1929/1978, p. 96). All of this questioning, about the nature of things, raises an epistemological problem related to “the impossibility of conceptualizing the complex unity of the human by way of disjunctive thought” (Morin 2001, p. 39). As a consequence, we are inclined to be blind to the real complexities of life. We do not know what novelty and innovation is really about, because we have not learned to think about these concepts in the separate disciplines of (our) study (in higher education). New thinking in complexity may offer a way of re-imagining what it is to be human (Stevenson 2005, p. 10).

 See the book of the critical realist thinker Roy Bhaskar, 1987, with the title “Reclaiming Reality”.

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Based on new thinking in complexity, the dynamics of it in the real (m), we may find a possible answer on what Whitehead has called ‘the problem of life’: “How can there be originality?” (Whitehead 1929/1978, p. 104) This is essentially the same problem as that of the creation of novelty and innovation (see above, in Chap. 4). Life is to be understood here as an unbroken totality, like the “open totality of the human being” we referred to above in Chap. 4. Inspired by Whitehead’s problem of life, we may wonder how we can conceive of the actual world, of actual human beings evolving complexly over time, developing into potentiality. We conceive of complexity science as the science of such potentialities. We may not only describe but also try to understand and explain how the ‘working’ of totalities of the human being may work in practice, by explanation of the new, generative principles and mechanisms at work in the processes involved. The new complexity science for the social sciences, then, may turn into a new generative social science (cf. Epstein 2007).

New Thinking About Interaction For the new thinking in complexity, we need as well a new thinking of interaction, i.e., about the nature of interaction (See e.g., Stacey 2001, p. 141). To our surprise, not many scientists in the field of complexity sciences make this link in their thinking in complexity. We view communicative human interaction as inherently and complexly linked to the relating between the partners in such interaction, to hidden connections of relationships, to loops of relationships within dynamic (learning) networks; that is, as potential, dynamic transition networks. We may take notice of the lack of an adequate theory of interaction (e.g., Stacey 2001, p. 60). Will it be possible, then, to develop a new theory of interaction; a theory of interaction that describes and explains the potential generative nature of interaction, for the benefit of describing learning and of development through (human) interaction? We think that new thinking in complexity may offer a new venue for dealing with the notion of interaction as a scientific concept, enabling not only a different description but also the explanation of the very complexity of interaction by (human) agents. We will show interaction to be more complex than ever expected, conceiving communicative human interaction as a real complex subject of study! For this, we need a different unit of study, thereby moving away from the split between individual and social (Stacey 2001, p. 61). We need a more dynamic unit of study. We fully agree with Follett’s belief that “parts and the whole are bound together in dynamic interaction” (in Graham 1995, p. 29). The profound reality remains always the same, essentially; but the alternation of its rest and movement creates the play of causes and effects, an incessant coming and going In comments on Book 1, Chapter 2, of the Tao-Te-Ching7 7

 2005, p. 17, in a translation by Derek Bryce and Léon Wieger. New York: Gramercy Books.

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New Thinking About Causality The concept of causality has always been a difficult subject for thinking: not only for philosophers but also and maybe even more so, for social scientists. This makes the topic of new thinking in causality a rather difficult topic. Yet, we believe the concept of causality is basic for our new thinking in complexity. Of course, we recognize that not many complexivists take this position. So, we may not refer to the literature of complexity science for support on this rather difficult topic. Actually, this may be the hardest topic to understand in our proposal for new thinking in complexity for the social sciences. Thinking in terms of causality is basic for understanding the dynamic complexity of real-world dynamics. Our fundamental stance about causality is fully in line with that of Edgar Zilsel (2000): “Either we understand the mutual relations of things in terms of causes and effects, or we don’t understand anything” (p. xxxix). This is fully in line as well with Vygotsky’s thinking about the causal dynamics in the real(m). We really need to understand causality to be explanative of reality. To put it straightforwardly: if we do not understand causality, we keep being the ‘prisoners of description’ (Edelman and Tononi 2000). So, we view the principle of causality as a serious precondition of knowledge (Zilsel 2000, p. xxxix). It will be along these lines of new thinking, standing on the shoulders of Mary Parker Follett and Lev Vygotsky, that we may link the new concept of (potentially nonlinear) causality with the new concept of interaction. This linking might be done in terms of interactive causality, reciprocal or mutual causality, opening up paths of spiral development, of sudden leaps, of potential transformation and even of metamorphosis (e.g. Follett 1924; Vygotsky 1978).

New Thinking About the Unit of Study We may rethink the unit of study, thereby replacing the common unit of the indivi­ dual, of the human being and of the single object and its environment (see e.g., Follett 1924; Stacey 2001, 2003). Archer (2007) nicely describes this relation between the individual, social agent and the world in terms of a relation of ‘ontological complicity’ (p. 41). This is a relation of a dynamic network, of a web, with the agent being both the weaver and the (dynamic) patterns woven (see Rose 1997). In such a network the agent may generate self-change through the dynamics within loops of the network (Archer 2007, p. 355). We may think of such a process of generating self-change as taking place through the processes of generating influences in and through human interaction; influences that manifest themselves within the causal loops of ‘ongoing self-cause’ (see Juarrero 1999). Webster and Goodwin (1996) conceive of the generative dynamics that include the environment: “The organism is influenced by and influences, its habitat” (p. 249). Related to this notion of a dynamic unit evolving over time, some biologists speak about niche-construction as a kind of generative mechanism in the evolution of forms in nature.

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In the new unit, we conceive the human (causal) agents involved in the generative (causal) dynamics of interaction as ‘complex nonlinear entities’ (Mainzer 2004, p. 15). This turns the unit of study, of two human agents in interaction, into a new dynamic, potentially nonlinear entity. Webster and Goodwin (1996) link the behaviour of such a dynamic unit with the “intrinsic unpredictability of successive trajectories that nevertheless remain confined within a domain” (p. 250). We fully support this description. Later in this book, we will link these unpredictable trajectories with the complex notions of ‘spaces of possibility’ and ‘domains of potentiality’. The problem remains how to explain the paths of these trajectories taken in and through the interaction by the (human) agents in interaction. To make the picture even more complex but more close to reality as well, we take the role of the human agents as so-called ‘generative bricoleurs’ (Sassone 1996). In this role, they are part of the new dynamic unit, involved in the inherently unpredictable process of the unit as a whole, somehow wondering what to do in the interaction, somehow searching for “Knowing how to go on” (Wittgenstein, in Lord 1994, p. 193). To see that everybody not merely depends on everybody, but actually is everybody in a deeper sense (Bohm 1996, p. 135; italics in original)

Linking of All New Thinking – A Programmatic View This may be the right place to be somewhat more explicit about the ambitions of rethinking of all the concepts mentioned above, i.e., how they relate to each other. Of course, this is the ultimate, rather ambitious aim of this book. Linking the steps mentioned above so far, we may obtain a different picture of the complexity of reality and of the real-world dynamics. Reality itself may become really different and so will science and the scientists, as a kind of ‘deliverers’ of reality. We fully subscribe to what Stacey (2001) has stated: From the perspective of complex responsive processes, there is no ultimate reality underlying the appearance of interaction between people. Instead, patterns of relating are mutually causing themselves (Stacey 2001, pp. 207–208; emphasis added)

From this complex statement, we may derive “new ways of understanding complexity”, by understanding the dynamic causal relations, making use of a different theory of causality (see Clancey 1997, pp. 228–229). These notions give a rather complex, broad idea of new thinking in complexity and correctly so! We aim at linking our new thinking in complexity with thinking in (complex) dynamic networks. We consider the parts and the complex whole as connected within dynamic networks through processes of downward and upward causation as a two-way causal relationship, with mutual interaction and reciprocal causality (Érdi 2008, p. 32; cf. Corning 2005; Vygotsky 1981, p. 155). This is an inherently complex relationship, which is potentially nonlinear as a relationship but also in its total causal effects over time. The causal framework serves as a tool for becoming explanatory about the causal dynamics involved in developing networks of interaction,

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evolving through a dynamic process full of upheavals, sudden changes, reversals, transformation and even of metamorphosis (sees Vygotsky 1978, in his chapter about method; Vygotsky 1986, in Kozulin, p. xxvix). By the use of this causal tool, we may develop the explanatory power needed for the explanation of the dynamic complexity involved in networks of (human) interaction (cf. Edelman and Tononi 2000, p. 220). We may not only recognize the human being as homo complexus (Morin 2001, p. 48) but also allow for a description of the human being in this network as being both the weaver and the patterns woven, as essentially constitutive of the complex dynamic web woven over time. In such a network the agent may generate self-change through the dynamics within loops of the network (Archer 2007, p. 355). We may think of such a process of generating self-change through the causal loops of ongoing self-cause (Juarrero 1999); that is, by the generative dynamics of the self-enhancing processes within those loops. It is through generating self-growth that the individual (as weaver in the web) constitutes itself by its relationship to others, confirming the basic thoughts of Vygotsky: “it is through others that we develop into ourselves” (Vygotsky 1981, p. 161; cf. Cilliers 1998, p. 120). We may also express this adage of Vygotsky, in terms that are more subjective: “True subjectivity is a ‘self-and-other’ relationship” (Wilden 1987, p. 125). So, subjectivity ‘simply’ goes beyond the subject. That notion turns subjectivity into a complex concept. Douglas Hofstadter expressed this kind of complex understanding of the complex subject in the title of his recent book “I am a strange loop” (Hofstadter 2007; emphasis added). The loop of self-and-other, as ultimately defining the subject, is central in his book. We take the same position in our new thinking in complexity for the social sciences. This brings us to a short description of our new framework in use for the invention of a new science.

New Framework Our new framework for use in our new thinking in complexity is essentially a generative causal framework, explanatory of the dynamic complexity, of the generative dynamics involved in the complex networks of patterns and causal processes within reciprocal causal relationships. With this framework, we may ultimately ‘invent’ a new generative social science (cf. Epstein 2006, 20078); a new science with a focus on the creation and development of novelty and innovation (cf. Vygotsky’s ambition about inventing a new science). This generative social science bases itself on generative causal principles and generative causal mechanisms. This new science,

8  We will not go into the differences with Epstein’s approach to the Generative Social Sciences. However, we may state that we like to think as generativists do but even more so as thinkers in complexity about reality-constituting processes (cf. Chia 1998, p. 367). The differences may show up in the language for use in describing and explaining the performance of the common subject of study.

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with its causal potency, may have the explanatory power, as a kind of generative power needed to transform the social sciences into a different kind of sciences. The generative social sciences conceived this way are, in certain ways, similar to the generative biology, proposed by Webster and Goodwin (1996). They propose a new theory about complex dynamic systems that are capable of learning (in Chap. 12), which describes and explains how nested, ordered complexity generates itself in dynamic learning networks. To do so, they make use of terms like causal power, causal agents, causal events, generative mechanisms, generative relationships and generative processes. In a similar way as Vygotsky has already described in the twenties of the twentieth century, they link the causal dynamics of generative processes with the emergence of structures and functions, conceived as a result of transforming those processes itself (see e.g., Vygotsky 1981, pp. 163; Vygotsky 1978). It is worth noticing here that both Joshua Epstein and Brian Goodwin have been active participants at the famous Sante Fé Institute as a centre of complexity thinking. In chapter 14, we will describe some of the similarities and differences between their particular approach of complexity, in their specific fields of science and our new thinking in complexity. In this description, we may make clear that our new approach has the power of becoming trans-disciplinary, for use in different disciplines as a method of viewing and doing science from a general complexity perspective. It is our firm belief that by adopting the new thinking in complexity, with new tools of thinking, we may find the start for explaining what David Jardine has described as “the generativity of new life” (Jardine 1990, p. 231; emphasis added): a generativity that we love “as a gift bestowed from the Earth” (Jardine 1990, p. 231). Adoption of this new thinking may be the ‘rupture’ required to overcome the profound sense of crisis, about the sense of connectedness that has been lost (Jardine 1990, p. 221). It might be the way to unlock people from their dominant mindset (cf. Tony Stevenson 1999, p. 8). We may become aware that we, as human beings, are a kind of ‘gift’ from the Earth itself. As in spinning a thread, we twist fibre on fibre. And the strength of the thread does not reside in the fact that some one fibre runs through its whole length, but in the overlapping of many fibres (Wittgenstein 1968, p. 32).

What Is the Use of a Programmatic View? At the end of this chapter, we put the question “What is so programmatic about a programmatic view of new thinking in complexity?” Answering this question gives a kind of summary of our basic points of departure and the aims we strive at in this complex book. It seems right to state here that the programmatic view is definitely not a blueprint for thinking in complexity! We hope, however, that this chapter has given a better idea of the issue of thinking in complexity as a new foundation for the Social

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Sciences. The delineation of all the steps needed may explain why there is actually no such thing as a real science of complexity in the Social Sciences as yet. This seems, however, a general state of art, which is true as much for the Natural Sciences. It is for this very reason that Kauffman (1995b) stated, “We are seeking a new conceptual framework that does not yet exist” (p. 185). There is not a quick single fix for such a new framework. We hope that the reader may understand how much rethinking we need to be able to build this new framework. What is of utmost importance is that the reader understands that we need to take all of the steps above for building the complex framework. You cannot simply leave something out! To deal with dynamic complexity of real-world dynamics, you need a complex toolkit enabling new thinking in complexity about these dynamics. Only by the use of the new tools, in a connected way and by showing their general core relevance for any science, it is possible to deal with a complex subject like the tapestry of life and find the means for a solid trans-disciplinary approach. Only then, we think, we may be able to deal with ‘complexus’, with “that which is interwoven”, in real life. It is this subject that Kauffman (1995a, b) has described as the (dynamic) ‘architecture of the tapestry of life’ (p. 185). With Kauffman we may wonder, “What is the weave?” (Kauffman 1995a, b, p. 185; cf. Goethe, in Starobinski 2003, p. 256) The new science is opening for dealing with what Kauffman has called the ‘evolvability’ of life (Kauffman 1995a, b, p. 185; emphasis added), as characteristic of such architecture of tapestry, as a dynamic network with processes of interaction and potential nonlinear effects, evolving dynamically over time. The new science is also opening for what Jardine has called “the generativity of new life” (Jardine 1990, p. 231; emphasis added). The programmatic view shows simultaneously to what extent we are critical about the Social Sciences and to what extent we need rethinking for the Social Sciences. We have to escape old habits of thought and to escape the quest for certainty that is still dominating the Social Sciences. By doing so, we may not only become closer to reality, by obtaining an improved (dynamic) map of reality but also obtain better access to a more active reality (Wallerstein et  al. 1996). Ultimately, we believe that, by the use of such a complex, fluid map, we may better navigate life in the seas of uncertainty than before (cf. Elias 1991; Goerner 2007, p. 482, p. 489). Better, in the sense of understanding how dynamic complexity may turn into effective complexity in the real(m). For us, viewing reality complexly this way comprises a new way of ‘reclaiming reality’9 (Bhaskar 1989). The use of the new ‘toolkit’ for new thinking is opening for the building of a new science about a new reality, with a new framework with new tools to address the new reality. The new reality will be about a more organic model of human reality; about “the whole of the reality in which we live” (Bohm 1996, p. 80). This new reality implies “a much richer reality” (Bohm 1996, p. 140). The question, then, is how to turn reality into a richer reality? This is not an easy question. Old thinking is not sufficient for dealing with this question. We really have to learn to think the

9

 Title of the book by this English philosopher and critical realist Roy Bhaskar.

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new way, to be able to find new ways of thinking (cf. Bateson 1972; Bohm 1996; Stevenson 2005). That brings ourselves, our own role, fully into the discussion. How can we participate in the discussion? We may need to become more aware of the more or less hidden, agentive role of ourselves for the new understanding of the complexly participatory nature of reality as essentially a human reality. We agree with Bohm (1996) that “We have got to see that thought is part of this reality and that we are not merely thinking about it, but that we are thinking it” (p. 141; italics in original). This means that we do not see that the problems we try to solve are actually the problems that are “due to the way we think” (Bohm 1996, p. 141). Bohm, like Bateson (1972), underscores the difficulty of thinking in an alternative way: a way that focuses both on a new way of thinking and knowing and a new way of human being. Once we may become aware of this difficulty, we may want to hear and finally recognize the relevance of new thinking in complexity as part and parcel of reality, so essential for life itself. It can be stated that the aim of this new thinking in complexity is to answer the questions, which only seemed unanswerable or even unthinkable before. We may show the potential of this new thinking for a new science with a transdisciplinary approach. It will be an approach that is not only fully descriptive of reality but also fully explanatory of the complex real-world dynamics. The new science, based on a reform of thought, is fundamentally opening for understanding the complex topics of ‘novelty’ and ‘creativity’ (cf. Chia 1998, p. 349). The new thinking in complexity about these complex topics is opening for a new so-called ‘possibility-oriented’ approach, opening the domain of potentialities and spaces of possibility in different areas such as in the field of education or learning organizations (Jörg et al. 2007; Jörg 2008b, 2009, 2010a, b; cf. Bohm 1996). We are convinced that the key for creativity and potentiality is in the interaction: in the interaction as newly conceived in the new framework of the new science. Interaction, conceived this way might be taken as a process of dynamic interweaving in communicative human interaction (Follett 1924; also in Drucker et  al. 1995). With Morin (2001), we believe that “interaction between individuals ensures the perpetuation of culture and the self-organization of society” (p. 45). This view corresponds with that of Bohm (1996) concerning the building of a new, more coherent culture based on dialogue (pp. 143–144). We think dialogical interaction, as described by Follett (1924) might be conceived as the ‘engine’ of evolution of such a new culture, creative of novelty and innovation. It will be such an interaction between (human) agents as active agents, making use of diversity as a resource, which is fundamentally generative of nature. This makes the new framework a generative framework, so apt for dealing with the description, understanding and explaining the complex processes of dynamic interweaving. The focus is on the “intimate interweaving and intertwining among the specific historical, biological, and social dynamics” (Chandler and Van de Vijver 2000, p. xi). According to these authors it is these dynamics that “generate the forms of behaviour, value, and character of the individual” (Chandler and Van de Vijver 2000, p. xi). We believe, it is the hitherto unknown dynamics of generativity, with its equally unknown constitutive dynamic architecture of relationships,

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Fig. 5.1  Disc of Phaistos (see http://www.crystalinks.com/phaistosdisc.html)

which generates the spaces in the domain of potentialities and possibilities, enabled by the hitherto unknown generative mechanisms, which make this framework so abundantly opening for the description and explanation of novelty and innovation as fundamental complex phenomena. All of this comprises a complex, generative view of an active, potentially nonlinear reality, as part of a new, deeper level of reality. This is a level of reality that represents a dynamic, essentially open, complex, causal nexus as part of the real-world dynamics (cf. Bhaskar 1989, p. 188). It is about the spiralling nature of reality: see Fig. 5.1 A spiralling nature, which is also opening for what may be called ‘the proximal zone of human being’, as a complex, multi-dimensional space for the generative development of human beings. This new kind of reality may turn the Social Sciences into a science of potential nonlinear being through processes of becoming. We view reality, then, as dynamic, as a potential outcome of complex processes and generative mechanisms (cf. Roepstorff 2007, pp. 191–192). This new view offers a way of humanizing the Social Sciences. All of this new kind of thinking in complexity about a more dynamic reality may lead to a better knowledge of the tortuous path to finding dynamic quality, enabled by the unknown role of diversity, the unpredictable, the unforeseen of (human) interaction (cf. Pirsig 1991, 1998; see also Fay 1996, p. 229). Although this role of diversity seems hitherto unknown, we agree with Wilden (1987) that there seems a deep truth in the notion that “Complexity is a quality based on diversity” (Wilden 1987, p. 172). It is from such a perspective that complexity receives a dynamic quality mark. We think it is by understanding the complex, causal dynamics of generating dynamic quality, of how the world works, how the generating of this world ‘works’ in practice, that viewing of processes of interaction may become (so) different. The new science may turn the Social Sciences into a full transdisciplinary science: a science about the generative causal dynamics of transition in networks that are self-generative and self-generating by transforming the process itself and the concomitant changes of structure and functions that take place in and through (causal)

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interaction. These dynamic learning networks may be considered a kind of woven dynamic webs, enabling the emergent potentialities and possibilities of dynamic quality. A new science, that goes beyond the Kuhnian boundaries of ‘normal science’. It takes quite a few steps of new thinking outside the box, to step outside the system we are in as scientists and start a new culture. This new culture may become representative of a new synthesis: that of “the third culture” (Brockman 1995). The next chapters will deal with the steps to be made. The path to be taken will not be a linear but a tortuous kind of weaving of a web of meaning and sense making. Hopefully the reader may experience this process as a creative experience towards a more coherent whole. What distinguishes us from animals and microbes … is the vast extent and great complexity of human goal seeking, which does not simply include the capacity to change goals but also the capacity to invent entirely new ones (Wilden 1987, p. 79; emphasis added)

Chapter 6

On Becoming Reflective About Our Viewing and Doing Science

If there is to be renewal, it begins with us (Starhawk, in Fleener 2002, p. 194)

Introduction In this chapter, we will deal with the first step of the new agenda for the social sciences, with the purpose to give birth to a new science. It is the step of becoming reflective about our viewing and doing science: the science that Kuhn (1970) described as ‘normal science’, as a state of art in the field of the sciences operating in a society. Reading of his main work about scientific revolutions gives the impression that the need to become reflective has been disregarded by Kuhn as a first step for a fundamental change in viewing and doing science. It is no coincidence that Prigogine wrote the famous work “Order out of Chaos” (1984) with Isabelle Stengers, a philosopher from Belgium. They offer a very critical stance towards viewing and doing science as usual. On page 94, they describe the science as being “the prisoner of confusion”. This is, however, not a permanent state of art for science: “Science is not doomed to remain a prisoner of confusion” (Prigogine and Stengers 1984, p. 94). In this chapter, we delineate the first step, of becoming critically reflective, as a necessary first step in the fostering of new thinking in complexity. We take this step to get out of the prison of confusion of our sciences, i.e., our social sciences: a confusion that is mainly about the foundations of these sciences. The focus in this chapter is therefore on what the goal and role of reflection is for our main topic: of fostering new thinking in complexity for the social sciences. This new thinking should lead to a fruitful transdisciplinary approach; an approach that we view as a better way of understanding the world we live in. For enabling such new thinking we have to take account of the following issues around the role and place of reflecting:

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_6, © Springer Science+Business Media B.V. 2011

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( a) Why should we become reflective? (b) What is the meaning of becoming reflective? (c) What to reflect about? (d) How to reflect? Of course, this chapter about the role of becoming reflective for the sake of the overall goal of new thinking in complexity for the social sciences will partly overlap with the making of all of the steps in the next chapters of this book. Yet, we think the perspective of becoming reflective about our science may be stressed and clarified by reflecting about the science-as-we-know-it. It stresses our own particular role in following an often implicit or even hidden agenda of these sciences and, in exerting this role and following this agenda, being kind of ‘deliverers’ of a realityas-we-know-it from our common viewing and doing science. By reflecting on this we may be able to recognize how provisional our conception and inherently social construction of reality must be seen. Prigogine and Stengers (1984) are also clear about this inherently limiting way of constructing reality: Whatever we call reality, it is revealed to us only through the active construction in which we participate (Prigogine and Stengers 1984, p. 293)

In the next chapter we will go deeper into that process of construction of ‘realityas-we-know-it’. We may as well be reflective about the role of language: how it may create reality. Some consider reality to be a kind of ‘language-effected reality’ (Davis 2004, p. 99; emphasis added). However, we think language may as well decode reality (cf. Pinar 2006, p. x). So, we may reflect on the use of our vocabulary in the effective construction of reality. With Prigogine and Stengers (1984), we concentrate on “the search for a new language”, to describe and explain the nature of things; that is, of the new reality (Prigogine and Stengers 1984, p. 308). We may develop such a new language as a language of science for science (cf. Biesta 2006, p. 14, about a similar goal for education). The task, then, becomes one of reinventing a language for a new science: the science of complexity. This task, we think, will be opening the social sciences and humanities (Wallerstein et al. 1996; emphasis added) and will ultimately help us shape “the future of the sciences and humanities” in a more promising way (see Tindemans et al. 2002). By using a different language, we may express a different reality. For instance, we may describe the functioning of complex systems as complex adaptive systems, in terms of morphogenesis, with their characteristics of structure-building and the processes of self-regulating, self-directing and self-organizing as characteristic elements of these complex systems, taking place within mutual causal relationships with mutual, deviation-amplifying causal effects (see Buckley 1967, p. 58). We may refer to the chapter on step 5 (Chap. 10) for a more extended description and explanation of these processes that are involved in complex systems, functioning as complex adaptive or complex generative systems with their processes of morphogenesis. As a consequence of all of this kind of reflective thinking and of creating the new language for creating a new science, we may open up the possibility of stepping outside of traditional ways of thinking and language use. The new thinking may

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offer the potentiality of escape from this reality as ‘delivered’ by scientists, i.e. by those working in the scientific realms of the social sciences and humanities.

Why Should We Become Reflective? The main reason to become reflective is to recognize that we can really make a difference: by solving the crisis of the social sciences by new thinking in complexity (Fig. 6.1). We may be able to recognize the hidden agenda of the social sciences and start to replace this agenda, with its inherent blind spots and myopia (cf. Buckley 1967 on replacing outmoded models of society). The new agenda and the new thinking focus on the relationship between science and the real[m]. This focus is enabling to give birth to a new science that is expanding beyond the science-as-we-know-it. The new challenge is to reinvent the science-as-we-know-it (cf. Kuhn 1970). We may do so by escaping the closure of the science-as-we-know-it (cf. the situation in physics at the end of nineteenth century).1 Ultimately, we hope to find an answer to the question “What will science look like in the new era?” It is our firm belief that the science in the twenty-first century will not be like the science-as-we-know-it (cf. Rip 2002, p. 100). We fully agree with Stephen Hawking that it will be the century of complexity. But it will take many steps to get that far. We need to be very creative in inventing “novelties of facts or theory” (Kuhn 1970, p. 52), such as “the fact is that complexity is self-potentiating” (Rescher 1998, p. 28; emphasis added). It is the imperceptibvle that produces effects and results (Tao-Te-Ching, Book 1, Chapter 11)

enlarged worldview worldview

Fig. 6.1  Broadening our world view

See f.i. David Bohm (1985).

1 

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What Is the Meaning of Becoming Reflective? We are convinced that by becoming reflective about the science-as-we-know-it, we may become able to head towards a new future of the social sciences and humanities (see Tindemans et al. 2002). We may do so by opening up that new future; that is, by new thinking about the relationship between science and the real[m]. The focus is on the fundamental complexity involved in that relationship, in terms of that which is interwoven. The question is what this complexity in the real[m] is really about. We think philosophy is the key for becoming reflective about complexity. Philosophy is not like the science-as-usual divided in separate disciplines. Another reason is that philosophy has always its focus on our common way of thinking about the real[m] and has always been reflective about these habitual ways of thinking. In principle, as history has shown, philosophy has always been opening for new ways of thinking by being critical on the historically evolved ways of thinking. This history showed not just a cumulative process of new thinking but, more importantly, also showed significant leaps in thinking, like for instance in the period of Enlightenment (cf. Kant, on Enlightenment). We believe philosophy may still have this important role for our science and society, in its critically reflective stance on the general problem of complexity of reality and the real[m]. Philosophy may make us aware of the blind spots and even of blinding paradigms that bring about the shortcomings and learned incapacities in our common ways of thinking about the real-world dynamics. But philosophy may also be very helpful in developing new ways of thinking about the real[m] and thus make us aware of the unexpected complexity of it. Philosophy may make us aware of the difference of complexity, which makes a difference, by making us aware of the role of “the imperceptible that produces effects and results” (Tao-Te-Ching, Book 1, chapter 11). Being aware of that, we may also recognize the potential for reclaiming reality,2 as elucidated by the English philosopher Roy Bhaskar (2011). He rejects the view of reality as a given reality and puts the rather surprising, original question for viewing and doing science: “What must the world be like for science to be possible?” (p. 23; emphasis added) The new way of thinking about complexity and about the very complexity of reality is a way of escaping old habits of thought and replaces them by new ways of thinking about science and the real[m]. It may offer a new view about how order may be generated from this complexity for science. This is essentially the main line of thinking about complexity of the real[m] in the work of the American philosopher Nicholas Rescher (1998). In line with Rescher’s critical thoughts about complexity, we may be able to become more aware of “the self-generation of order in a universe of chance” (Rescher 1998, p. 206; italics in original). This was also the essence of the new thinking in the work of Prigogine and Stengers (1984),

This is the title of a book by Roy Bhaskar that appeared in 1987 and appeared in 2008 in a new version.

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enlarged worldview worldview

enlarged reality reality

Fig. 6.2  An enlarged worldview and its relation with a larger reality

as expressed in their title of the book “Order out of chaos”, with the subtitle “Man’s new dialogue with nature”. Becoming reflective along these lines of new thinking, we may ultimately open up new spaces of possibility and new domains of potentiality. In essence, the new science for the future will contain an enlarged worldview about a larger reality, ‘simply’ by including the complexity of the real-world dynamics: see Fig. 6.2. This figure shows the relationship between science and the real[m] as a dynamic relationship. Both science and the real are dynamic themselves and may evolve over time. This picture visualizes that science, as part of the enlarged worldview, is definitely not an “independent variable” (see Toffler 1984, in Prigogine and Stengers 1984, p. xii). Complexity is very real and reality as-we-know-it is more complex than expected from old ways of thinking about the real[m]. Our mission is to go beyond the fragmented view of reality and the split into different disciplines: a fragmentation into different disciplines that the philosopher Nicholas Rescher (1998) has described as “the cognitive domestication of the real” (p. 32), as a way to get in control of nature. Our very notion of reality has always been a kind of “invented reality” (cf. title book, “The Invented Reality”, edited by Paul Watzlawick 1984). In inventing this reality, we were confronting our own limits of thinking about the real[m]. In a way we were constructing a world that was not very much the real world after all! For instance, as phrased by David Byrne, “Linearity and order seemed to be being enforced on a world which isn’t really like that” (Byrne 1998, p. 3). At the same time, he recognized that he ‘simply’ had no language for escaping this situation and ‘simply’ “no vocabulary for doing more than worry” (Byrne 1998, p. 3). Niklas Luhmann (2002) was also very sceptical about the way we have always constructed reality and spoke about “the cognitive program of constructivism and the reality that remains unknown” in a very critical way. In a similar vein, Rescher (1998) phrased a similar view as follows: “Our conception of reality must always be seen as provisional and subject to change” (Rescher 1998, p. 25). So, in line with Rescher’s new way of thinking, we may become aware that “the world’s complexity means that there is, now and always, more to reality than our science is able to dream of” (Rescher 1998, p. 28; emphasis added). So, we may conclude that we must be ready to reclaim reality for the sake of the extension of it (cf. Bhaskar’s view of the world for making science possible). We may conclude the discussion about reality, with the statement that we, as social scientists, may make a difference that makes a difference in our outlook to

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the world, by offering “a larger scientific image of reality” (Toffler 1984, p. xiv). We may do so, for instance, by taking care of the role of time and that of linearity in our equations, in mapping the terrain of study in our viewing and doing science. We may especially realize the role of time, in the sense that “time is a construction” (Paul Valéry, in Prigogine and Stengers 1984, p. 301). With Prigogine and Stengers (1984), we may dis-cover the primacy of time and change for our social sciences as well (p. 306). Actually, we need “a novel, comprehensive theory of change” (Prigogine and Stengers 1984, p. xv); that is, a theory that takes time into account and is able to show “how the complex is emerging from the simple” (Prigogine and Stengers 1984, p. xxix; emphasis added). As social scientists, we are able to become aware that we may have a different role in our society by ‘delivering’ a new reality that is not only a larger reality but also a richer reality. The situation may be compared with that of physics at the end of the nineteenth century, when physicists wrongly thought that they were almost ready with their science. In fact, as history has shown, it was time for a revolution in physics. So, it seems in general, possible, in our role as scientists, to be expanding of reality-as-we-know-it in our viewing and doing science. How, then, can we start to expand the notion of reality in our science-as-we-know-it? We may start by becoming critical realistic in our new way of thinking about reality (cf. the work by the philosopher Roy Bhaskar). In its critical stance, based on critical philosophical thinking, new thinking in complexity may therefore get very close to critical theory about the real[m], without being the same (cf. Davis and Sumara 2008). This critical attitude may imply not only “a way of seeing reality but that of a rebellion against reality itself” (see Gohr 2000, about the surrealist painter René Magritte). In a similar vein we read Glick’s statement about Vygotsky: “We find Vygotsky fighting against theoretical reductionism, and attempting to understand developmental issues as representing a complexly woven tapestry of functions” (1997d, p. xiii). The role of critical science, then, may get very close to that of art in our society. Not only for science or art itself, by enriching the sciences and art but for humanity at large too, by fully enriching humanity! We return to this topic in the chapter on “The complexity of complexity”. What Must the World Be Like for Science? Taking a complex, larger reality seriously, we may speak about the complexity of real-world complexity. This very complex reality may have the hitherto unknown characteristics of a dynamic complex network: of that which is dynamically, complexly interwoven over time. It may be a network that diverts from the commonly known network, “representing a complexly woven tapestry of functions” (Glick 1997, p. xiii).3 We have to realize, however, that this kind of complexity of reality is still a domain to explore for the future: “we are beginning to pick out In the foreword of the Collected Works of Vygotsky, 1997, Vol. 4.

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themes, strands in the tapestry” (Kauffman 1995b, p. 185). But, in line with Kauffman’s view on this, we believe it still to be true that “a new conceptual framework does not yet exist” (Kauffman 1995, p. 185; emphasis added). Because of this fundamental deficiency of our knowing about the world-as-we-know-it, we may ask ourselves the still unanswered question of our science-as-we-know-it about the real[m]: “What is the weave?” By finding an answer to this question, we may understand and “discover what is ‘really’ happening in the world” (Dent and Umpleby 1998). Once we become aware of this lagging behind of what our science may tell us about the real[m], we may see the truth that, as a result of this, the fundamental problems of our time are actually “pushed out of disciplinary time” (Morin 2001, p. 33). We may recognize these bad effects of old thinking that seem to be productive of the very crisis of our time in viewing and doing science. This situation demands for a new start of new thinking: of thinking in complexity about the real[m]. To conclude, we may start to invent a new science by setting a new (research) agenda for the social sciences; an agenda that “reflects the complexity of the real world”.4 This is the mission we want to advocate in this book, as part of the series “Springer: Complexity”. It is a mission that can be relevant for various, different disciplines. For example, in the field of educational research, some scholars demand explicitly for such a new research agenda, to get out of the so-called ‘black-box’ models in use in this field of research (Lemke and Sabelli 2008). Overcoming the Crisis We may overcome the present crisis of our social sciences and humanities by becoming critically reflective of these fields of the sciences as-we-know-them. This is fully in line with Vygotsky’s thinking about the crisis in his day. We believe that the crisis of his day is very much similar to the crisis of our time. In essence, it is the crisis of habitual ways of thinking and the incapacity to escape from these habits. We think the way of new thinking in complexity may be helpful in overcoming the crisis in the social sciences. We may do so by recognizing the temporary closure of thinking in the science-as-we-know-it. This is the very lesson to be learned from the work of Kuhn (1970, 2000) on scientific revolutions. Such a closure may be viewed as to be strongly linked with the effects of what Morin described as so-called ‘blinding paradigms’ (Morin 2001, p. 21). We mean here for example the closure of thinking and the effects of a blinding paradigm as manifested by the danger of linear thinking, as an example of old ways of thinking and of the danger of common prejudices and blind alleys in viewing and doing science. By ending the closure of thinking we may become capable of producing new and

Ilya Prigogine, quoted in the opening document of the Complexity, Science & Society Conference 2005, at the University of Liverpool.

4 

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better knowledge about the world-as-we-know-it and become progressive again in our history, like in the early Age of Enlightenment (cf. Eve 1997, p. 16). In the last chapter we will return to this topic of promise and hope for our time. From the work of Prigogine and Stengers it may be derived that we are still more or less imprisoned in a world of our own: that is being kind of prisoners of the science-as-we-know-it. However, contrary to common assumptions and prejudices, the reality of this world has always had a provisional character. We may refer here to philosophers like Whitehead who pointed to what may be described as “the basic inadequacies of the theoretical scheme developed by seventeenth-century science” (Prigogine and Stengers 1984, p. 94). It may be concluded that our notion of reality has always been a kind of invented reality. Or, as phrased by the philosopher Nicholas Rescher: “Our conception of reality must always be seen as provisional and subject to change” (Rescher 1998, p. 25; italics in original). The Problem of Science Science has the inherent problem that science itself is not a subject of study in regular science, in what Kuhn (1970) described as ‘normal science’. It may be recognized as somewhat peculiar that science is itself not the object of study of science. From a historical point of view it seems as if science ‘simply’ develops according to its own ‘laws’ of development. So, science seems not a problem for scientists viewing and doing science. There is no recognition of the problem of science and the real[m]: about how science relates to the real[m]. In the chapter before, we stated that it was not easy to be reflective about the fundamentals of our viewing and doing science. The main reason is that it is directly related to our basic assumptions, which are largely hidden. That is probably the reason why Dennett (2003) speaks about the agenda of the social sciences as the hidden agenda of these sciences (p. xi). Some describe the situation of viewing and doing science as one that is dominated by blind spots and/ or myopia. It was Vygotsky who wrote already about what he called ‘the blind alleys’ of psychological science and the crisis in psychology in his day (Vygotsky 1997d, pp. 3, 13). More recently, Edgar Morin (2001) was also very clear in his expressing the role and significance of what he called ‘blinding paradigms’ in doing science (p. 21). So, it may be derived from these clear opinions that scientists are kind of used to living in their own closed world. It is a specific world, of viewing and doing science, not able to escape that world and even lest for a transition to a different world (Kuhn 1970). The economist John Maynard Keynes wrote eloquently about this struggle to escape old habits of thinking, to enable his own transition in thinking from the old paradigm (Keynes 1936, p. xxiii). Of course, he was not the only one. This may make clear how difficult it can be for scientists to escape the common world of ‘normal science’, as described by Kuhn (1970), as the regular way of viewing and doing science.

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What Is the Meaning of Becoming Reflective About Science? The topic of the ‘functioning’ of science itself, how it ‘operates’, has actually only recently become a more serious topic of discussion in the history of the sciences, with the work of Thomas Kuhn.5 His work did not actually appear as a systematic effort to criticize the sciences and the way they operate in our history of the (natural) sciences. Nevertheless, his publication had enormous impact. Even for himself, the impact of his publication was unexpected (see Kuhn 2000). The work appeared more or less as an incident without strong expectations about the significance of the analysis, made by Kuhn himself. His critical approach of viewing and doing science was too different from the historical analysis as usually made by historians. The impact was great and overwhelming, also for Kuhn himself. It took, however, many years before Kuhn’s analysis got that impact. That makes clear how difficult it may be to become deeply reflective about our viewing and doing science as scientists. This is not only true for the history of the natural sciences that Kuhn depicted in his work but also for the social sciences. Yet, scientists like Vygotsky already took a very critical stance on the science of psychology in his day, around the twenties of the last century (Vygotsky 1926/1997). He was clearly aware of the crisis in psychology and about what he called ‘the blind alleys’ of viewing and doing (psychological) science. In Chap. 3, we referred to his notion about the crisis of psychology and the book Vygotsky wrote about the crisis. A book that remained unpublished for a long time. Not because it was not good enough. On the contrary!6 In this book about the crisis he took a rather critical stance towards the Marxists who tried to formulate a new Marxist psychology in his day, which was rather more political than scientifically based.7 He showed why it was needed to be so critical about the viewing and doing science in general and by the Marxists in particular. Vygotsky fully addressed the complexities of the subject to be studied in psychology. For this reason he rejected what he called “the sham blind empirism” (Vygotsky 1926/1997). His main focus was on the relationship between science and the real[m]. Reality was very much more than just a constructed reality. He was convinced that reality was more complex than commonly assumed by most scientists of his day. But becoming reflective is not enough. Above, we made mention about the need to escape old habits of thinking to build a new reality and become inventive of a new science. Reading Vygotsky’s work, one can state that he was fully aware of that. He knew that the crisis of the science of psychology was very much a methodological crisis. Science was too descriptive and seemed unable to become (more) explanatory in its approach of the complex subject of study. He was Originally this work was published in 1962. In 1970, a second edition appeared. It is still a delight to read his original text and enjoy his polemic style of writing. 7  We believe that he was sympathetic with Marxist thinking, mainly because of the promise of its dialectical approach of the real, but do not believe that he was a Marxist thinker or a political Marxist. 5  6 

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fully aware that science had to deal with the complexities of the reality that science focuses on. This notion turns reality into a new reality: a complexly rich reality. That was the very reason why he was convinced that a new science had to be invented, with a new method! But this is not an easy task, as shown above. Vygotsky tried to convince the reader that (s)he needed to learn to see the world anew and to think in a new way. More recently, the cybernetic thinker Gregory Bateson (1972) was on the same track in his approach of how to change science. He knew very well that he had to think better and stop what may be described as ‘bad thinking’ (Engel, in the foreword of Bateson 1972). In general, such kind of bad thinking can be considered to be very much constitutive of what can be called “bad science” (Oyama 2000, p. 147). Bateson himself was very much aware of the importance of better thinking. According to him the most important task is “to learn to think in the new way” (p. 462; emphasis added). He was quite open in his contention that he was actually not able to give an adequate answer to this perennial problem: “Let me say that I don’t know how to think that way” (Oyama 2000, p. 462; emphasis in original). This original creative thinker, like the famous economic thinker Keynes, made clear that new thinking is a real struggle of trying to escape old ways of thinking. In general, the history of our sciences and humanities has shown that it is not easy to invent a new way of thinking. Becoming reflective seems therefore the first step to be made to think better. But what makes thinking better? How to think better, then, may be considered the real issue. So, we arrive at what may be described as the real challenge for inventing a new science: to become critically reflective about our common ways of thinking about science and the real[m]. We think that only by taking this challenge seriously, one will be able to start new thinking and become innovative about our viewing and doing science and be productive of the novelty of fact and theory, in ways of thinking about science and the scientific realms (cf. The The Ruurlo Manifest 2006, as the ‘mission’ of the European Institute Para Limes).

What to Reflect About? Above we dealt with the questions “Why to reflect?” and about “The meaning of reflection”. We hope the answers the reader has got were satisfying enough to get involved in becoming reflective himself. As a next step in becoming reflective, we would like to share the topic of reflection: what should we be reflective about? This is a rather complex topic to deal with. The focus is on ways of thinking. In Table  6.1 we present a list of elements that are constitutive for those ways of thinking. They represent kind of different worlds, in the sense that Kuhn described (Kuhn 1970, p. 121, p. 150). Although Kuhn recognized that new paradigms were born from old ones, the constituent elements of paradigms that had been previously employed are seldom employed in the traditional way (see Kuhn 1970, p. 149). Actually, he stated clearly and somewhat provocatively that “paradigms are not corrigible by normal science at all” (Kuhn 1970, p. 122; emphasis added).

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Table 6.1  Elements of common and new ways of thinking Common ways of thinking New ways of thinking Underlying reality Complexly participatory nature of human reality Process view of reality (Buckley 1967, p. 19) Reality as given/assumed/ New thinking brings forth new reality constructed Reality as ‘a choice’ Research brings Complex, spiralling reality (Jardine. p. 273) forth reality Static Dynamic Quantity Quality Rational Imagination Analytic Synthetic Convergent Divergent prescriptive Emergent Mechanical system Complex system Complex generative system Complex self-adaptive system Complex, self-generative system Complex, bootstrapping system Complexity Organized complexity (Buckley 1967, p. 38) Reductionistic stance Complex, living dynamic totality Fragmentation Focus on the whole Individual things-world Integrated life-world Individual as discrete Individuals as loops (Hofstadter 2007) Social self/mind (Vygotsky 1978; Valsiner and van der Veer Individual self/mind (Freud, in Stacey 2003, p. 216) 2000; see also Mead, Elias) Methodological individualism The radical social understanding of the individual (Stacey 2003) Self-enclosed Outwardly open Primacy to the individual Primacy to the social Distinction between No distinction between inside and outside (the paradox inside and outside of the individual and the social by Elias and Mead, in Stacey 2003, p. 172, p. 225) Centred view De-centred view Ends-oriented Possibility-oriented Certainty Uncertainty Predictable universe Counterintuitive universe (Sole and Goodwin 2000, p. 303) Fixed Fluid Mind inside (Stacey 2003, p. 225) Mind as minding (Bogdan 2003), with the outside Isolated mind Minding others minds (Bogdan 2003) Reflexive mind Socialized minds (Bogdan 2003, p. 13) Autonomous individual Relational and intersubjective (Stacey2003, p. 217) Exclusive Inclusive Morphostasis Morphogenesis (Buckley 1967, p. 58; Archer 2007, p. 48) Cycle Hypercycle (Sole and Goodwin 2000, p. 229) (continued)

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Table 6.1  (continued) Common ways of thinking Structure State State Progressive state Dualism Mind as (knowable) internal world (of representations) (see Stacey 2003, pp. 221, 224) Wrong questions Linear Linear process Singularity Order from order Linear Linear thinking Cause-effect relation Cause as effect Unidirectional Closed loop Causal relation Straight line Line Line Plane Unity Things as entities Logic of things (Fleener 2003, p. 89) Monocausal Linear causality Determinism Mechanistic determinism Deterministic Predictable Feedback Social interaction as exchange Isolated

New ways of thinking Hyperstructure (Smith and Stevens 1997) Fluid structure (Buckley 1967, p. 48) Hyperstate (Sole and Goodwin 2000, p. 302) Fluid state (Small, in Buckley 1967, p. 18) Critical state (Sole and Goodwin 2000, p. 223) Paradox of ‘forming while being formed at the same time’ (Stacey 2003, p. 172; cf. Rose 1997) (Unknowable but real) state of the organism as the basis of mind (Stacey 2003, p. 221) Questioning our questions (Fleener 2003, p. 194; cf. Simon 1996) Nonlinear Generative bootstrapping process Simultaneity Order from disorder Non-linear Thinking beyond the linear Causal loop Causal chain Cause as influence Cause as impelling force Multi-directional Open circular loop Causal network of causal relations (Buckley 1967, p. 38, p. 40) Danger of straight line (Hundertwasser 2002; Jardine et al., p. 241; Stanley 2006, p. 143) Indra’s network or web Matrix Complex pattern Multi-dimensional hyper-space (Globus 1995) Diversity Dynamic entities Logic of relationship (Fleener 2003, p. 89) Multi-causal Circular, causa sui (self-cause) causality (Fleener 2003); holistic causality (Bhaskar 1986) Determinations (Toffler 1984), determinative (Buckley 1967, p. 58) Self-regulation, self-directing, self-organizing processes Chance, possibility Unpredictable Deviation-amplifying (Maruyama 1963, in Buckley 1967, p. 59) Social interaction as enabling and shaping (Stacey 2003, p. 236) Wholeness (continued)

Introduction Table 6.1  (continued) Common ways of thinking Simple explanation Traditional way of human being Meaning as static Either-or Interaction as exchange

Interaction as exchange Entity as fixed Interaction Connection Generation Mono-disciplinary

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New ways of thinking Paradox of circular explanation (Stacey 2003, p. 217) New way of being (Fleener, 03, p. 194); nonlinear being (Stanley 2006, p. 143) Meaning as fluid (Stacey 2003, p. 238) Both-and Degree of wholeness or unity (Buckley 1967, p. 44) Reciprocal interaction Complexity of interaction (Buckley 1967, p. 20, p. 22) Mutual interaction (Buckley 1967, p. 22) Interaction as influences on each other at the same time (Stacey 2003, p. 105) Fluidity of interaction (Buckley 1967, p. 20) Transactional nature of interaction (Backström and Döös 2008, p. 5) Auto-catalytic interaction (Backström and Döös 2008, p. 8) Interaction itself has intrinsic pattern forming properties (Stacey 2003, p. 238; see also Mouzelis 1998, p. 17) Degree of “entitivity” (Buckley 1967, p. 42) Degree of entitativity (Wimsatt 1989, 2000) Degree of interactivity Degree of connectivity Degree of generativity Transdisciplinary (Nicolescu 1996)

From our perspective of new thinking for the social sciences and humanities, we fully support his view on the role of paradigms in viewing and doing science. In Table 6.1, one may actually read how many elements can be distinguished in constituting the ways of thinking. This may come as a surprise for the reader. The table shows that so many elements are crucial for the distinction between the two ways of thinking. This does not mean, however, that the ways of thinking are really separated in practice. Actually both ways of thinking may be approached from a perspective of a kind of unity of opposites. So, the ways of thinking can be separated but need not always be separated for alternative ways of thinking. It can be the synthesis of the ways of thinking that is essential of the new way of thinking! What is also of importance is that all the elements of each way of thinking are somehow related. In what way and to what degree they are interdependent is a very complex topic for science itself: both for the science-as-we-know-it and for the new science based on new thinking. This demonstrates the inherent complexity of science itself as complex; as “that which is interwoven”. The different elements are also constitutive of the six steps of new thinking in the next chapters. That is why most of the elements will be discussed in the next chapters about new thinking. Consequently, the reader may become aware of the problem of how to connect all of these elements of new thinking for giving birth to a new science in a consistent and convincing way.

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The reason to present these elements already at this place is to give the reader a clear impression of the complexity that is involved in giving birth to a new science. It shows as well how much new thinking may be needed for the invention of a new science. The diversity of elements in the table shows what is involved in setting the agenda for new thinking, as described in the next chapters. Of course, we need rationality to do the job. But this does not mean that we follow a strictly logical sequence of steps. The real problem of new thinking is to escape old ways of thinking. We need to be critically aware of ourselves as professionals in our doing science as usual. Being professionals has its dangers. Whitehead (1925/1967) warns us for the situation that the minds of these professionals, following the standards of their science, are apt to become minds in a groove (see p. 197). Simon (1996), in turn, is critically aware of this danger in describing the role of professional scientists in terms of ‘satisficers’. We may conclude from these critical comments on doing science as usual that to actually escape from this state may in practice be a real struggle of escape (see Keynes 1936, p. xxiii). In the next chapter we return to this problem of escaping the notions of reality that are a kind of ‘delivered’ reality by scientists doing science as usual: of what Kuhn (1970) has called ‘normal science’. So, one may wonder what is wrong with our common ways of thinking? And, maybe even more importantly, we may question how to reflect on this and start new thinking about our viewing and doing science as usual.

How to Reflect? We may state that, in essence, starting to reflect means no more and no less than learning to see the world anew and of learning to think the new way. In a deeper sense, the challenge is to invent a new science by shifting the paradigm ‘in use’ in the science-as-we-know-it. Although this change of paradigm does not mean a change of the world, according to Kuhn (1970), the change may imply that the scientist, after such a change of paradigm, works in a different world (see p. 121; see also p. 150). We also referred to this problem as a hardy perennial for individual scientists. We mentioned the renowned thinker Gregory Bateson (1972) who didn’t know how to do so: to think the new way. The problem is linked to the epistemological problem or question “How do we know what we know?” The problem is also linked to the ontological question “what is reality about?” To find answers to these epistemological and ontological questions, then, is to dis-cover the prejudices, the blind spots and myopia operating in the field of our science, as part and parcel of our viewing and doing science-as-we-know-it. This is a necessary condition to be able to find our own particular, personal entries for new ways of seeing and new thinking and for leaving old ways of seeing and thinking the world behind. This is not only a rational problem. We may also recognize the defensive attitude towards the uncertainty created in the fundamental changes needed (Bohm 1985). Taking up the challenge of finding new and innovative ways of thinking, we may start with getting the courage to become critical and leave old

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ways of thinking behind. We may recognize the challenge as a struggle to escape a taken-for granted reality, as a pre-condition for creating novelty and innovation. The still undiscovered path to follow is a tortuous path. We may follow this path with the expectation of spiralling upward towards new levels of growth and development of thinking for the future of our sciences. To phrase it more poetically, we may become, like Vygotsky, a “visitor from the future” of social science and humanities.8 A future that is, or is expected to be very different. One of the main difficulties for individual scientists to start new ways of seeing the world and new thinking is where to begin. The answer can be and will be different for scientists as individuals, operating in different fields and disciplines. The reader may take any favourable entry that is relevant for the process of his/her own process of change. The reader may already be fully aware that the change in any entry for new thinking is a change in the complex network of elements that are fully interconnected, in kind of webbed networks with their specific kind of webbed architecture (Kauffman 1993, p. 428), like an Indra’s Net.9 So, there is not a sequence of steps to follow. One may reach a similar end-state from different initial conditions (according to the principle of multifinality; see e.g., Buckley 1967, p. 60). One may reach a similar end-state by following different developmental routes (principle of equifinality; Buckley 1967, p. 60). The chapters to follow show the different entries for new thinking in complexity. They deal with the problem of the reality of reality (Chap. 7), the problem of interaction (Chap. 8) and the problem of causality (Chap. 10). In these chapters, most of the elements of new thinking from Table 6.1 will be dealt with. These chapters are the basic chapters for new thinking in complexity and for the giving birth to a new science: a science that offers a fundamental transdisciplinary approach of complexity for the social sciences and humanities. Taking account of all of these distinct elements shows the very complexity of the new science and the new thinking in complexity that is needed for it. The reader may get (more) fully aware that the new science of complexity is itself very complex indeed. We hope it may convince the reader that there is no such thing as a complexity theory yet, based on such kind of reframing complexity, as already noticed by Stuart Kauffman (1995). It has to be invented, as a hardy perennial problem for science. The sequence of entries and of chapters that we follow in this book is not obligatory for understanding the new thinking in complexity. The reader may start with any of these chapters he or she prefers. The reader may both view and experience that the new thinking is a kind of circular process. It may also be a very personal, complexly path-dependent process. In general, it may be stated that our approach is more possibility-oriented than ends-oriented for new thinking.

Vygotsky has been described as such a visitor by Jerome Bruner (1987), in the foreword of the Collected Works of L.S. Vygotsky, Vol. 1, p. 7. 9  This is a spherical jeweled net from the Avataska Sutra, in which every element is connected and reflected in every other element (see Clark 2001; Jardine et al. 2006). 8 

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Yet, promoting new thinking for viewing and doing (new) science is the clear aim of this book. All of this means that different options of following different paths of reading and thinking are possible, for opening new spaces of possibility in viewing and doing so. Each of the chapters has the quality of stepping outside of the system of thinking in use and of getting out of the vocabulary in use, by replacing the very vocabulary in use in our viewing and doing science. The different chapters may be read as an invitation to go beyond the rational, linear approach of linear thinking and hopefully appeal for the use of both parts of the brain; that is the intellectual left and the more intuitive functioning of the right brain. Reading the different chapters can be inviting as well to learn about the use of a different kind of language for thinking (Wilden 1987, p. 151): a different language that may effect reality as assumed and ‘delivered’ in our viewing and doing science as usual. We hope that the reader may discover the inherent power of such use of a new language for “the future of the sciences and humanities” (see Tindemans et al. 2002). It is the very constitutive power to create a different reality that is based on the power of decoding reality as commonly assumed (cf. Pinar 2006). It is the very power needed for novelty of both fact and theory in the sciences (Kuhn 1970, p. 52) and of novelty for innovation too. We need the power afforded by the new tools to describe and explain phenomena like the emergence of coherent novelty (Webster and Goodwin 1996, p. 251). Only then, we will be able to turn novelty and innovation into a kind of ‘progressive, emergent innovation’ (Reid 2007, p. 15). These are the promising prospects we hope to offer with the building of a new science of complexity based on a new kind of thinking in complexity for the social sciences and humanities.

Chapter 7

The Reality of Reality Unleashing the potential of the real that has remained unknown

Whether psychology is possible as a science is, above all, a methodological problem (Vygotsky 1997a, p. 328)

Introduction In the preceding chapter we posed the general problem for science: what the world is about to enable our viewing and doing science. The English philosopher Roy Bhaskar has put this question in the following words: “What must the world be like for science to be possible?” For him this is the central problem for inventing a new science (Bhaskar 1975/2008, p. 23). He makes thereby a link with what he considers to be distinct domains: the domain of the real, of the actual and the domain of the empirical (p. 13). Vygotsky (1926/1997) was of the same opinion on this fundamental problem for science, in mentioning the principle of science for science to be possible. He described this as “the principle of a science about [what is] the real” (p. 328). We think, we may formulate this principle best in terms of the problem of ‘the reality of reality’. Vygotsky openly criticized Marxists about their view of finding a science that was based on Marxist thinking. Although he admired Marx, it was quite clear for him that you cannot simply find such a science; you have to invent it, e.g., by starting the creation of a new methodology! (see van der Veer and Valsiner 1991, p. 153; see also Vygotsky 1997, p. 331). What the Marxist psychology did not take into account is, that the crisis in psychology is in essence about the methodological nature of the crisis (Vygotsky 1997, p. 332). According to Vygotsky, the new methodology will be the first step forward, beyond doubt (Vygotsky 1997, p. 332). Only by taking this problem fully into account, we may develop an explanatory approach for a new science about the real (cf. chapter 5, about method, in Vygotsky 1978). It may be clear from the statements above that science itself is not sufficient to define itself in an adequate way. It is typical for science that it cannot define itself as a process in motion (see Bhaskar 2011, p. 179). Science-as-we-know-it has the inherent problem of conceiving of a reality that is in essence a larger reality; a T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_7, © Springer Science+Business Media B.V. 2011

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larger reality that can as well become “a richer sort of reality” (Bohm 2004; see Chap. 6). Disregarding of this inherent problem of science may bring with it the danger of closure, of excluding even the possibility of becoming a real science (Vygotsky 1926/1997; cf. Bhaskar 2011, p. 215). Science itself (too) easily ‘forgets’ its own roots, of what science actually is. This ‘forgetting’ is also what has happened with the Newtonian paradigm. But not only for this paradigm! According to the famous physicist Louis de Broglie, the danger of entering a cul-de-sac has been present in physics since, i.e. of quantum physics (in Bohm 1957, p. x).1 For real science to be possible, the science needs to generate its boundaries every time anew. This is actually the essence of Kuhn’s message about scientific revolutions! For science to evolve and to bring ‘real’ fruit, it needs to become self-generative, as a kind of self-generating network. Only then, science may develop the power of shaping the future, as surprisingly unexpected and emergent. Only then, science may dis-cover its own untapped potential for knowing, even when recognized as being based on the very ‘uncertainty of knowledge’ (cf. Luhmann 2002, p. 152). This possibility, we recognize, is only possible by becoming deeply reflective and creative; that is, being creative in the sense of “being able to relax into uncertainty and confusion” (Capra 2003, p. 110). We mean deeply creative, in the sense of being able to step outside of the system as a necessary step to reflect on the system-as-usual, with its inherent ways of thinking, with the purpose to turn it into a better, more promising system of thinking. We think this is the rather tortuous path of development from ‘science as usual’ to good science, as history has shown (cf. Kuhn’s work on paradigms and scientific revolutions). It is simultaneously the path of bad thinking to better thinking as a more adequate, fruitful way of (new) thinking (cf. Engel 1972, p. viii). Of course, this is a kind of value-laden statement. It means that we can always do better. Doing better as scientists, we think, is linked to central values of viewing and doing science. This is a central part of the message put forward by Kuhn (1970; see also Luhmann 2002). For the thinking of scientists, about their viewing and doing science, this means that to follow the tortuous path of better thinking is vale-laden indeed! We have the impression that this message, in general, has been disdained in science (cf. Vygotsky 1987a, b). This was very much the line of thinking by Vygotsky, about the very building stone for a new science, as the stone disdained by the scientists of psychology in his day. For him it was the stone of new thinking that needed to become explanatory about the very transitory nature of being through becoming, with evolving states of human being, such as in the case of ‘the transitory child’, as the subject of study in psychology (see Vygotsky 1987, p. 91). The being of human being is always linked to (complex) ways of becoming. Taking this seriously as scholars may be considered to be the start of “a science of being through becoming” (cf. Prigogine 1980). It will be a science of being, conceived of as successive states of being, as states of evolvability, evolving over time (cf. Kauffman 1995b, p. 185).

We may refer here as well to “The Trouble with Physics” by Lee Smolin (2006) and “A Different Universe” by Robert Laughlin (2005).

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We may (later) expand on this by speaking about self-generated systems and their self-generated states of affairs (cf. Sole and Goodwin 2000; Luhmann 2002). We may conclude from the above, that we, as scientists, can and should be critical about our (uncritical) attitude in viewing and doing science. Bhaskar (1975/2008) put it as follows, in his critical Humean account of our understanding of the basic of mechanics: we have to ask why for three hundred years scientists and philosophers found this paradigm so compelling (p. 90)

For scientific practice, of viewing and doing science, it meant for scholars of all different kinds, that it was very hard to escape from the dominant ‘paradigm in use’. As a scientist one had to struggle to escape that paradigm and to define the relationship with the real anew. This is still the problem of our day for the science as-weknow-it, i.e. that of the social sciences. It still requires courage to make a distinction that makes a difference in our worldview (cf. Niessen 2007, p. 36). It has to define itself as a way of viewing and doing science from its relationship with the real anew. The science-as-we-know-it needs to take account of the inherent complexity of reality as real. We subscribe what Rescher (1998) has stated on the fundamental relationship between complexity and [what is] the real in reality: one of the most striking and characteristic features of reality in general – and indeed of anything in particular that is real – is its complexity (p. 35; emphasis added)

The key question, then, is how to think of complexity as apt for study in the field concerned. To become able to do so, the ‘normal science’, as Kuhn (1970) called it, has to step outside of its closure, of a cul-de-sac (see Luhmann 2002; de Broglie 1959) and begin with reflecting about its relationship with the real, as a precondition for science itself to be possible. This kind of reflection may lead to a theory that can be characterized as a meta-theory (Smolin 2006, p. 126). To develop such a theory, we need a critical realistic outlook to the complex world we live in. This will be an outlook that takes the crisis of our sciences fully into account; that is, the crisis as we have described in Chap. 3. This is the very crisis of today as well, noticed by different scholars; both in the social and in the natural sciences alike (see e.g., Laughlin 2005). We may repeat here that, to ‘solve’ the very crisis we are in, we need to escape the danger of old habits of thinking, such as ‘the danger of linear thinking’ (Mainzer 2004/2007). We are of the opinion that this is the very foundation stone for new thinking, for building a new science by invention. For Vygotsky (1926/1997), this was what he marked as “the whole meaning of the crisis” (see pp. 306, 314). In line with Vygotsky’s thinking, we may speak about the need for new theorizing, on what he called ‘a theory of the crisis’ in our viewing and doing science-as-we-knowit. His notion of a crisis was in essence a methodological crisis for him. The theory of the crisis we may think of should deal in an adequate way with the problem of science about [what is] the real, for the new science to be possible. Below, we like to argue that Vygotsky not only analysed the deep problem of the science-as-usual as a kind of ‘normal science’ of his time but has also laid the foundation for a complexity view of the real. That position makes him a precursor of the invention of the new science we are heading for in this book. His effort to

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develop an explanatory theory for what he called ‘a general psychology’ can be regarded as a full meta-theory. We hope to show that the realization of psychology as a science, for Vygotsky, was actually about a science of transition: a science of being through becoming.2 Interestingly, he may be considered to be a precursor of a transdisciplinary approach for science too (see Vygotsky 1997a, p. 254, Vol. 3)! He took a general approach for the problem of viewing and doing science for the future of the social sciences and humanities. His notion of a foundational general science referred to “The need for a fundamental elaboration of the concepts of the general science – this algebra of the particular sciences” (Vygotsky 1997a, p. 269). He described the role of this general science for the particular sciences as “even more obvious when we borrow from the area of other sciences” (Vygotsky 1997a, p. 269; italics in original). This is for us an important reason why we like to stand on his shoulders. We will later in this book argue that the new science can be conceived as a general tool for retooling the social sciences and humanities. This retooling, described by Kuhn as an inherent part of a shift of paradigm enabling for novelty and innovation, we think of as utmost importance for a new kind of thinking in the field of the social sciences and humanities. We take it as inevitable, in turn, that this new thinking is very much about establishing new facts (Vygotsky 1997a, p. 250). We may refer here for instance to the fact that complexity is self-potentiating (see Rescher 1998, p. 28; emphasis added). So, ‘real’ facts may turn into scientific facts within a new system of knowledge (see Vygotsky 1997, p. 249). Based on the new thinking, sketched above, we view the retooling of our viewing and doing science as enabling “the transition from a paradigm in crisis to a new one” (Kuhn 1970, p. 84). It is such a transition that can be understood as the shift of paradigm needed for viewing and doing science in practice, from a ‘more realistic’, practical perspective. It is the new paradigm that may help us to get out of the crisis we are still in, to help us shape a better future for the social sciences and humanities. It is a way of defining the order of nature and the nature of things anew, thereby inventing a ‘methodology of science’, which is a reflection of the ‘methodology of reality’ (see Vygotsky 1997, p. 255), thereby taking account of the very complexity of the transitory unity of the subject of study like the human being in the real. We may conclude that, in a way, “an investigator realizes the real” (Vygotsky 1997, p. 257; emphasis added). Henceforth, we are to argue here that the complexity view of reality is actually a kind of ‘solution’ of the crisis of psychology! This being the case, because it presents not only “a new way of seeing and thinking” (Wittgenstein, in Fleener 2003, p. 127) but also realizes the real in a different, more complex way: as a nonlinear complex reality. This is also the meaning to be derived from the table in the chapter before (Table 6.1). To be clear, it does not mean that we can sketch how the new science will look like when it arrives. We may only sketch a difference, of seeing and thinking, that, as we hope, will make the difference in our viewing and doing science: for enabling a different way of realizing the real and

See also Prigogine and Stengers (1984) for this perspective on a new science.

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the shaping of “the future of the sciences and humanities” (cf. Tindemans et al. 2002; Scheffers 2009). one of the most striking and characteristic features of reality in general – and indeed of anything in particular that is real – is its complexity (Rescher 1998, p. 35; emphasis added)

New Thinking About Reality We take the next step3 in our new thinking in complexity for the social sciences by considering the ‘real’ problem of reality: this is the problem of taking the complexity of reality for granted, as a kind of ‘given’ or ‘delivered’ reality. Of course, the new thinking is also about the nature of things.4 We opt to define the nature of things anew. It is our intention to invent a ‘methodology of science’ that is based on and a reflection about, what Vygotsky has called ‘the methodology of reality’ (Vygotsky 1926/1997, p. 255). This methodology is essentially about the correspondence between thinking and being in science (Vygotsky 1926/1997, p. 256). For him and for the invention of a new science, this means a new way of methodological thinking that is evidently about ‘the nature of reality’ (Vygotsky 1926/1997, p. 257). Vygotsky argues that this correspondence is actually the key to general psychology (Vygotsky 1926/1997, p. 256; emphasis added). For him, it means a correspondence that is fully linked with the laws of nature. Only an investigator that takes this correspondence into account seems able to realize the real (Vygotsky 1926/1997, p. 257; emphasis added). Arguing along these lines, he makes very clear what he means by the real for science: No science can be confined to the subjective, to appearances, to phantoms, to what does not exist. What does not exist does not exist at all. This must be understood. We cannot say: in the world there exist real and unreal things – the unreal does not exist (Vygotsky 1997, pp. 326–327; italics in original)

We take Vygotsky’s view of science as a rather pragmatic view about viewing and doing science, being linked to a philosophy of practice. Our own new thinking in complexity is in line with his thinking about what he views as the key to psychology as a science. It is for this reason that we, in our thinking in complexity as a foundation stone for a new science. We will take into account the complex, transitory unity of the subject as the dynamic subject of study in the real. This will get its proper place in our new system of knowledge. We suppose, this will be the difference that makes a difference in our approach. Again, we like to stress that each step is connected to the complexly woven tapestry, which is the essence of new thinking in complexity about the inherently complex real-world dynamics. 4  See also Bhaskar (2011), about science and the nature of the world (at p. 30) 3 

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A Transdisciplinary Reality? In the preceding chapter, we showed (in Fig. 6.2) how science relates to the real. We assessed that science is not an independent variable but is related to the real. This is a kind of variable of its own, as history has shown convincingly. The problem, then, is not only if reality can be different but how science and its relationship to [what is] the real can be ‘really’ different from what is taken for granted in our science-as-we-know-it? We define this problem as the problem of “the reality of reality”. This is not just a problem for the social sciences alone. On the contrary! The natural sciences, i.e., in the field of physics, scholars have wrestled with this very real problem about reality within their scientific realms of study. The problem of the nature of reality is a problem of transdisciplinary nature indeed (cf. “Ruurlo Manifest” IPL, 2006). To become explanatory about the nature of reality, which is about a different type of reality (see e.g., Clayton 2004), we may start to think of “the foundation for the reality of the system” (Luhmann 2002, p. 137). We agree with Luhmann that this implies a consideration of “its operation with the conditions of reality that sustain it” (Luhmann 2002, p. 137). We also fully agree with Luhmann in his stance about the implication for theory (for him, of systems theory): a “de-ontologization of reality” (Luhmann 2002, p. 132; italics in original). This implies a different type of reality indeed: that is, a nonlinear complex, dynamic kind of reality (cf. Mainzer 2004/2007). We may think about a corresponding complex theory that focuses on the complexity of the real (Rescher 1998), which is very much about this new type of reality. The core question for science, then, is to explain how events in the real may be generated, through what kind of generative mechanisms, being part of our theory of the real; generative mechanisms that are considered to be hitherto unknown, according to Roy Bhaskar (1986/2008). For him, the generative mechanisms are the corner stone for becoming explanatory in viewing and doing science: “The real basis of causal laws is provided by the generative mechanisms of nature” (Roy Bhaskar 1986/2008, p. 14; emphasis added). The general problem of becoming really explanatory about how events may happen is very much present in theoretical physics as well (see footnote 1 above). Smolin (2006), for instance, defines the problem as “the question of the relationship between reality and the formalism” (p. 6). He noticed that this problem (and question) “has bedevilled the theory from the beginning” (Smolin (2006), p. 6). So, we may argue that this question or the problem, as defined here, is still not resolved for science (see e.g., Laughlin 2005; Smolin 2006, for the natural sciences and physics in particular). The fundamental question for defining the viewing and doing of science may also be recognized as defining the epistemological and ontological problem. It was also and again Vygotsky5 already in his day, who warns for the danger of putting these fundamental

This kind of putting problems for viewing and doing science makes Vygotsky sometimes so much a philosopher, of science; maybe as much as a psychologist (cf. Dorothy Robbins 2001, “Vygotsky’s Psychology-Philosophy”).

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problems wrongly.6 Based on Vygotsky’s fundamental and foundational analysis of the problems involved, he warns for the danger of mixing up these two problems for science: When one mixes up the epistemological problem with the ontological one, by introducing into psychology not the whole argumentation but its final results, this leads to the distortion of both (Vygotsky 1926/1997, p. 323; italics in original)

Still nowadays scholars, like the English philosopher Roy Bhaskar (in his book A Realist Theory for Science), are very critical about the mixing of the problems involved in viewing and doing science. He puts the question as follows: What must the world be like for science to be possible? (Bhaskar 1975/2008, p. 23)

In dealing with this question, he makes mention of what he calls the epistemic fallacy: this fallacy is “the substitution of how matters are taken to be for how they in fact are, even if we cannot or do not know the latter” (Archer 2007,7 p. 16). According to Roy Bhaskar, this is a fallacy8 that still dominates our way of thinking in viewing and doing science. The problem seems, again, a problem for all of the sciences. So, we may correctly describe the problem as a transdisciplinary problem; a problem that is essentially about what Vygotsky (1926/1997) called “the differentiation of the epistemological and ontological problem” for viewing and doing science (see p. 326). All of this kind of reflection about the nature of reality brings us to the possibility of a different answer to the problem than commonly assumed in the social sciences. We think this can and should best be done, within the framework of the relationship between science and [what is] the real (Vygotsky 1926/1997, pp. 328–329). In his effort to invent psychology as a science, he fully recognized the problem as a foundational, methodological problem. For him the crisis in psychology was very much a methodological crisis. Based on Vygotsky’s principle of science and his reflection on the crisis of our (social) sciences, he was able to develop a new science by what he described as “the creation of a methodology that the struggle is for a general psychology” (Vygotsky 1926/1997, p. 329; emphasis added). It is of interest that he views the invention of a new science as a struggle too! At the same place, Vygotsky comes to the conclusion that you cannot have a solid foundation of science until you have solved this problem: “Anyone who attempts to skip this problem, to jump over methodology in order to build some special psychological science right away, will inevitably jump over his horse while trying to sit on it” (Vygotsky 1926/1997, p. 329). So, we may conclude from his way of thinking about the foundations of a science of psychology that methodology is the key for ‘solving’ the crisis of psychology in his day. He notes idealism and materialism as the diverging paths chosen in our history of philosophy and psychology, e.g., by Husserl (phenomenology) and Feuerbach (materialism). 7  Footnote 21, referring to Andrew Collier, Critical Realism, 1994. 8  Bhaskar (2011) describes the epistemic fallacy somewhat differently: “that statements about being can always be transposed into statements about our knowledge of being” (p. 16; emphasis added). 6 

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Reality as a Choice? Reality is a term we must learn to use (Bohr, in Robert Pirsig 1999).

Above we have chosen the option to develop a different view about reality for our viewing and doing science. We may become aware that reality is commonly considered to be a kind of ‘construction’. In practice, this means that we may know how it can be constructed. So, we become familiar with how it is constructed and we get easily used to it. In this way we ‘construct’ our own habits of thinking as well. This makes it rather difficult to escape from such a ‘constructive’ way of thinking. We can illustrate the problem by referring to what may be called “the paradox of the real, of reality”: If a tree should fall in the forest unheard by any living creature, would it make a noise? (Wilden 1987, p. 72; emphasis added)

This paradox may be compared with Smolin’s view about physics and reality. He states that “it should give a picture of what reality is” (Smolin 2006, p. 7; italics in original). Interestingly, he presents the topic of reality from a historical perspective as a choice to be made, thereby referring to the debate between Einstein and Bohr. He boldly declares that, not only Einstein but also Erwin Schrödinger and Louis de Broglie were realists. Not surprisingly, then, Smolin himself also takes a realist point of view as a way of doing science (Smolin 2006, p. 7). He relates his view to the great foundational problems of contemporary physics. Even more interestingly, defining himself being a realist, he defines reality as the relationship between what is measured and the scientist measuring what is measured (Smolin 2006, p. 8; emphasis added). According to Smolin (2006), physics is not yet able to offer a satisfying theory for the foundational problem of contemporary physics. He comes to the conclusion that we (physicists) have “to invent a new theory that does make sense” (p. 8; italics in original). In his book, he puts forward the new option: that of “the discovery of a new theory that will be more amenable to a realist interpretation” (Smolin 2006, p. 9). Vygotsky was also very much concerned about this problem of the real as regards the foundation of a new science (see also above). He was clear on this problem for viewing and doing science. Although it may seem somewhat redundant, we like to refer again to his thoughts about the very problem of the real, because of his original view on this, which he formulated around 1926! He stated his position about the relation between science and reality as follows (see also above): No science can be confined to the subjective, to appearances, to phantoms, to what does not exist. What does not exist does not exist at all (Vygotsky 1997, pp. 326–327; italics in original)

The reader may notice the close correspondence between the foundational views of Smolin and Vygotsky about their corresponding sciences. Both were dissatisfied with the contemporary theory in doing science and both take philosophy as the key to the invention of a new science. Their views show the foundational problem of science,

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of the nature of reality, as a transdisciplinary problem. It seems that physics finds itself still in a kind of ‘cul de sac’ situation (de Broglie, in Bohm 1957, p. x), imprisoned in a language of description. Physicists seem not able to escape and develop a more explanatory approach about reality as we may know it, from a general, critical realistic perspective. It seems we are in need of a kind of meta-theory, to find the solutions to the fundamental problem from a more fundamental theory (Smolin 2006, p. 126). The ultimate hope is to reach towards a larger and richer type of reality. We think this is of utmost importance for all of the disciplines in our sciences. We may think for example about the field of learning and education, which is strongly dominated by strongly reductive views about “what is real”. For example, we may refer to Heinrich von Foerster’s view about what he calls ‘the trivialization of the learner’ and the disdain for the bothersome ‘states of being’ of learners (Von Foerster 1993, p. 185). These are states that have been easily disregarded as ‘bothersome internal states’ in the field of learning and education (Von Foerster 1993, p. 185). These states of learners are regarded as bothersome because they “generate unpredictability and novelty” (Von Foerster 1993, p. 185; cf. Luhmann and Schorr 2000). But from a complexity perspective, of thinking in complexity, they show the very promise of possibilities of human beings in their interaction for the field of learning and education. Returning to the problem of ‘construction’ in our viewing and doing science, we seem to acquire a kind of ‘learned incapacity’ to reflect on our ways of constructing scientific knowledge in the field of our social sciences (cf. Wertsch 1998). It was Niklas Luhmann (2002/2003) who made us deeply aware of the limits of constructivism as a way of thinking about the scientific real[m]. He concluded that constructivism had the inherent danger of leaving (part of) reality unknown. Ziman (2000) puts his argument even more strongly by arguing that “constructivism is anti-realist” (p. 318). Actually, this was also the critical stance originally taken by Vygotsky (1926), who had started his new way of thinking about the crisis in psychology at that time with a critical analysis of the relationship between science and the real[m]. He fully recognized the complexities involved in the real-world dynamics of human behaviour, such as the development of the child (Vygotsky 1997, Vol. 4). So, he took the complexity of the real[m] not for granted but as really real, stating that “the unreal does not exist” (see quote, above). His attempt to understand the complexity of reality can be understood as an answer to the rather fundamental, methodological question put forward by Roy Bhaskar, as a critical realist: “What must the world be like for science to be possible?” in his book A Realist Theory of Science (Bhaskar 1975/2008, p. 23). … a causal law would operate even if unknown, and even if there were no-one to know it (Bhaskar 1975/2008, p. 37; see also p. 39; emphasis added)

Vygotsky About the Reality of the Real[m] We think it is of interest to elaborate somewhat more about Vygotsky’s view about his view regarding the principle of science and [what is] the real. We would like to focus on the deep link between the fundamental and the practical. From a historical

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perspective, it may be hard to tell what Vygotsky really thought in his day. Most of his work remained unpublished for a long time, this being the case both in Russian and in English! Only in 1987, the first volume of his collected works appeared, followed by later volumes, appearing from 1997! This situation made it difficult to get a comprehensive view about his original ways of thinking. More recently “The Essential Vygotsky” appeared (Rieber and Robinson 2004), with the original contributions of Vygotsky and with interesting comments from various authors in this field of psychology. This book, with an overview of his main contributions to the field, makes Vygotsky’s ways of thinking more accessible. According to Joseph Glick, one of the contributors to this book, Vygotsky strongly rejected the dominant theoretical, reductionistic stance of science in his day: “Vygotsky fights against theoretical reductionism, attempting to understand development as a complexly woven tapestry of functions” (Glick 2004, p. 355). In practice, that position meant a struggle of escape from reality as assumed and ‘delivered’ by the scientists of his time (cf. Keynes 1936, on this very struggle of escape). We think Vygotsky’s work can be read as such a struggle, with the ultimate goal of new thinking in complexity about the complex processes, involved in the development of the child, leading to a complex webbed tapestry of functions. We will illustrate this below. Vygotsky tried to develop a more complex view about the development of the child, by taking the deeply transitory nature of the processes involved in this development seriously. In essence, this is for us the significance of Vygotsky’s famous statement about the building stone of the new science he tried to build: “The stone that the builders have disdained must become the foundation stone9” (Vygotsky 1987, p. 91). At this place, he referred to Goethe’s concept of ‘the transitory child10’ (Vygotsky 1987, p. 91). We are of the opinion that the reality of the child (for the child) in his development is in essence about a transitory real[m]. The science he was heading for, as a general science, was essentially a science of being through becoming. He openly rejected “the negative description of the child that resulted from existing methods”, which was based on what the child lacked in comparison with the adult (Vygotsky 1997, p. 98, Vol. 4; emphasis added). Vygotsky was convinced that a positive picture was possible of the child’s development but only “if we radically change our representation of child development” (Vygotsky 1997, pp. 98–99). In practice, for viewing and doing science, this view meant a kind of reinventing the scientific method in use for describing and explaining the processes involved. For Vygotsky, this was the ultimate challenge: to go from the reductive to He chose this quote as an epigraph to the work about the crisis of psychology. In Vygotsky (1997), we read a somewhat divergent translation: “The stone which the builders (of the science of psychology) rejected has become the headstone of the corner” (see footnote 1, ibid, p. 404). This quote has been confusing for the translators, not knowing precisely what was meant by Vygotsky. They make mention of the practice and philosophy in their unity (Vygotsky (1997a), ibid, p.404). We believe the real meaning is in Spinoza’s thinking about reality. Although he argued for the existence of a permanent reality, he also asserts that “all phenomenal existence is transitory”. To our mind, this is the essence of the choice Vygotsky himself made as the building stone for inventing a new science. 10  See footnote 4. 9 

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the more complex view of learning and development. According to him, we have to take into account that this process of child development is fundamentally “a complex dialectical process that is characterized by complex periodicity, disproportion in the development of separate functions, metamorphoses or qualitative transformation of certain forms into others, a complex merging of the processes of evolution and involution, a complex crossing of external and internal factors, a complex process of overcoming difficulties and adapting” (Vygotsky 1997, p. 99; cf. Vygotsky 1978, p. 73; see also Rieber and Robinson 2004, p. 355). At a different place, Vygotsky advocates an even stronger position about the complexity of reality and the new, complex way of thinking needed for dealing with that complex reality. In Vygotsky (1987), he writes about the foundation of the complex: The foundation of the complex lies in empirical connections that emerge in the individual’s immediate experience. A complex is first and foremost a concrete unification of a group of objects based on the empirical similarity of separate objects to one another. This is fundamental to all the characteristics of this mode of thinking. The most important characteristic of complexive thinking is that it occurs on the plane of concrete-empirical thinking rather than on the plane of the abstract-logical thinking (p. 237; emphasis added)

We may derive from this original text that Vygotsky was a real complex thinker who knew about the need to change the method of doing science in and for practice, needed for new complex thinking. This is a complex way of thinking that is about the very complexity of the real[m], which is the concrete-empirical thinking. His complex way of thinking may also be illustrated by his view about child development as a self-referential, recursive kind of development that involves a kind of (recursive) loop in the very complex process of development. He refers to this kind of development as a fundamental, general law of development. He describes the essence of this law as follows: The essence of this law is that in the process of development, the child begins to apply the same form of behaviour to himself that others initially applied to him. The child himself assimilates the social forms of behaviour and transfers them to himself (1997, p. 102, Vol. 4; emphasis added).

We may conclude from the above that Vygotsky actually teaches us how to learn to think in a complex way, which is essentially not a linear way of thinking. So, he is giving up the classical view of reality and escapes the danger of linear thinking, which is still considered as being the greatest danger of our time (see e.g. Mainzer 2007).

New Reality for Science? Based on the new way of thinking, as described by Vygotsky and by others such as the English critical realist philosopher Roy Bhaskar, we may become critically aware that the classical view of reality is not a map of a reality that gives access to

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a given reality. According to Rescher (1998), we must “maintain a clear distinction between our conception of reality and reality as it really is” (p. 124; italics in original). In other words: “the world that we describe is one thing, the world, as we describe it is another” (Rescher (1998), p. 124; italics in original). The map is not the territory indeed! Actually, based on the new thinking, we may become aware that, in a fundamental sense, reality is a kind of choice one ‘makes’ in science; that is, a kind of implicit choice, which is actually always uncertain about the ‘real’ nature of the choice made. Such new thinking about reality is an essential part of the new agenda for the social sciences. This agenda may comprise the birth of a new, larger and more complex reality. We may start to think of the interconnected, dynamically interdependent, fluid-like, ever-evolving nature of reality. A similar transformation has taken place in the natural sciences by the development of quantum physics (see Prigogine and Stengers 1984, pp. 224–225). The changes in view in this field of science brought with it a new agenda for the natural sciences. A similar kind of change might take place in the social sciences, with fostering a new agenda for these social sciences. But what does this agenda look like for the future of our social sciences? First, we need to escape the notion of reality as a kind of ‘given’ reality, because this is regularly a strongly reduced version of reality. We reject this reduced version of a reality that is so often only a simple, linear view of reality. The new step in our new thinking may actually lead to reclaiming reality (cf. Bhaskar 1989), conceived as a process of invention. We can come to the invention that reality is much more complex than we are used to thinking of.11 It is for this reason that, to be inventive about the real[m], we ‘really’ need to complexify our very notions of reality. We have to go beyond the notion of a ‘given’ or constructed reality, escaping the danger of taking constructivism as a single view of reality. Only by taking this danger into account, we may begin to invent reality anew. We may invent the new reality by developing new ways of thinking. The elements of these new ways of thinking are presented in Table 6.1 of Chap. 6. At this point it seems correct to stress, again, that the elements of old and new thinking in Table 6.1 are not considered to be final, opposite ways of thinking. We prefer to view the new elements of thinking as ways of thinking that go beyond the old ways of thinking. We think, for good reasons, that some of the opposites may be considered as a kind of unity of those opposites: that is, as “a complex interplay and synthesis of opposites” (Tarnas 2006, p. 497, foot note 3; emphasis added). To describe the complexity of this unity, the synthetic concept of (dynamic) “unity of opposites” may play an important role. For this notion, the concept of the so-called ‘unitas multiplex’ may be an adequate concept (Valsiner 1998, p. 209; see also Morin 1992, p. 375; Morin 2001, p. 45).

See e.g., the quote of Nietzsche, above in the Introduction; see also Basarab Nicolescu, 2005 and the books by Roy Bhaskar and Margaret Archer, representing the strand of ‘critical realism’ in philosophy. 11 

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Fig.  7.1  Frank Gehry, Guggenheim Museum Bilbao (© FMGB Guggenheim Bilbao Museoa. Photo, Erika Barahona Ede. All rights reserved. Partial or total reproduction prohibited)

A Realist Version of Reality The more realistic notion of reality we would like to propose is a complex, dynamically interconnected, fluid kind of reality (cf. Hofstadter 2007, p. 236). It is a notion that takes time (more) fully into account. The new reality is a kind of dynamic tapestry of a web, conceived as a webbed network with a webbed, fluid-like architecture, with a generative matrix of structures of relationships with relational interaction and with fluid entities. For a representation like this in ‘real’, fluid architecture, see Fig. 7.1 above. Both the structures and the entities are ever evolving over time according to the generative principles and generative mechanisms of the (causal) dynamics involved; a dynamics that is complexly ‘productive’ of the fluid tapestry of the webbed network and architecture of complexity of generative functions in the real, evolving over time. One of the consequences of the complex view of reality, with its inherent temporality, is that we may link together the world of trajectories of development with the world of processes (Prigogine and Stengers 1984, p. 253). Similarly, we may link together the world of being and becoming (Prigogine and Stengers 1984, p. 255; emphasis added), as essential, constitutive elements of a new fluid conception of reality. Ultimately we may (re-) consider the nature of reality and the modelling

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of this nature and turn it into the modelling of the dynamics of complex weaving within the webs12 and into the emergent spiralling nature of processes and of trajectories, in short: of reality itself (cf. Whitehead 1926, 1925/1967, p. 72; see also Vygotsky 1978, Ch. 5; Vygotsky 1981, p. 163). Sandywell (1996) is of the same opinion where he states that “the reflection on ongoing practices may also change the norms of traditional action; a transformation which, in a spiralling movement, gives rise to new modes of reality and reflection” (Sandywell 1996, p. 6; emphasis added). To put it more simply but also complexly: our new thinking in complexity about the complexity of the real is a reform of thought, that is of reframing complexity of the real, which leads inevitably to a reform of modes of reality. This reform of thinking offers a way for escaping old habits of thought. With Roy Bhaskar, we may become aware that “The event-sequential past is an unreliable guide to the future” (Bhaskar 2011, p. 219; emphasis added). What we really need for opening a new mode of thinking about the new reality and for reflection on this reality is a new trans-disciplinary framework to open up a new, more complex reality: that is, the nonlinear complex nature of reality, with its hitherto unknown potential for opening a new horizon of unlimited possibility in practice (see Maturana and Varela 1980, p. 38; Tarnas 2006, p. xv). The kind of new thinking in complexity about the complex nature of reality is very much about the deep link between the fundamental and the practical. The new thinking in complexity is the opening for a new method of enquiry. This method, we think, may help us engage the crisis we are in, in a more creative way (see Tarnas 2006, p. xv), such as the crisis in psychology (see Vygotsky 1926/1997) and the crisis in the system of education (Morin 2001). We contend that this new method of thinking in complexity and enquiry about the complexity of the real is opening the social sciences and humanities. We are of the opinion that we may ultimately create the opening of new spaces of possibilities for practice, like in the field of education (Davis 2004; Davis and Sumara 2006; Osberg 2009; Jörg 2009). The view of a spiralling nature of (processes in) reality is as much of an appliance to the development, the life-course of a human being, conceived as a process of morphogenesis with potential qualitative generic transformations (Vygotsky 1978; Archer 2003, p. 124). This brings us to the essential notion of so-called ‘generativity’ as a state of being representing the general (dynamic) capability of human beings to transform themselves over time (cf. Sassone 1996, pp. 520–521). Generativity, then, may at the same time be considered as a norm for education in pedagogy; that is, a norm that can be linked to a general Nietzschean pedagogy (Sassone 1996, 521). This dynamic state of (human) being, then, may be acquired as a capability during a lifetime, e.g., in education. According to Sassone, it may therefore function simultaneously as a norm for the quality of development and as a goal for the qualitative transformation in human development (Sassone 1996, pp. 520–521). It is the very dynamic of generativity that may bring human beings into states and trajectories involving concerns ® projects ® practices ® (Archer 2003, p. 133).

Cf. Goethe and his conception of “nature as a great Weaver”, in Starobinski 2003, p. 256.

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According to Archer, it is through internal conversations that such trajectories are accomplished (Archer 2003, p. 133). These notions link with notions of the causal, generative mechanisms and causal power, envisioned by critical realists like Bhaskar and Archer, in their conception of a realist social theory. These notions may be part of a new framework about self-generative or selfgenerating networks of communications (see Capra 2003, p. 72). The processes going on in these networks can be described as encompassing different kind of processes of evolution, involution and revolution (Vygotsky 1981). Through this complexus of dynamically interwoven processes, evolving over time, individuals may acquire their identities as members of these networks as social networks, by acquiring the human capability of generating new possibilities in hitherto unknown spaces of the possible (see Capra 2003, p. 72; Osberg 2009). These are the very spaces within ‘a new horizon of possibility’ (Tarnas 2006, p. xv), to be taken as a fundamental, unlimited possibility of enlargement of the cognitive domain (see Maturana 1980, p. 38; emphasis added).

Reality and New Thinking in Complexity To make the link between reality and the invention of a new science, we may resume here the primary aim for this study. The focus of this book is on new thinking in complexity for the social sciences. The primary aim may be described as “giving birth to a new science” (cf. Prigogine 1997); a goal that has also been advocated at the beginning of the twentieth century for the science of psychology by Vygotsky (1926/1997; 1978). Although for Vygotsky this goal was rather clear, in practice the new science was not so clearly defined or developed. Being wellknown with philosophy,13 he was very much aware about the difficult relation between science and reality. It was for this reason that he accepted reality not as a ‘given’ reality. He rejected the empirism of his day, which he described as ‘the sham blind empirism’ (Vygotsky 1926/1997). At the same time he was also very much aware that science is certainly not “an independent variable” (see Toffler 1984, p. xii). It was probably for this reason that his thinking about the possibility of a new science was very much about what he described as “the principle of a science about [what is] the real” (Vygotsky 1997, Vol. 3, pp. 328–329). His view about a new science was inspired by a different idea about the real[m] (see also Rescher 1998, on this topic). For Vygotsky, reality was certainly not a ‘given’ reality. It was, however, also not ‘simply’ a constructed reality. His view about a new kind of reality went beyond the certainty-driven, the calculable and the predictable. His focus on reality was very much on the complex processes and the emergent functions of the complex effects, brought about by these processes. For him these were processes like evolution, revolution and involution as dynamic processes and the functions

See D. Robbins (2001) and her book Vygotsky’s Psychology-Philosophy.

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were the broad cognitive functions of the mind. He regarded the development of these functions ‘simply’ not as gradual but as a revolutionary change (Vygotsky 1926/1997, p. 110). His focus was on the complexity of how these processes were intertwined. In this sense, he took account of the role of time in the emergence of the various functions of the mind. The thinking of the ‘essential Vygotsky’ may be viewed in terms of understanding developmental issues, as “representing a complexly woven tapestry of functions” (Glick 1997, p. xiii; emphasis added). Underlying this complexly woven tapestry of functions is a dynamic structure with its causal dynamics, which may bring forth these functions over time, in their complex interdependencies. This brings us to the very Vygotskian question: “How may we describe and explain this complexity of developing functions?” This question is still the key question for thinking in complexity about this very complexity of functions. It is also the question that has been left un-answered in our (social) sciences and humanities. So, the ‘real’ challenge is to find the answer to this unanswered question about the complexity of the real, being operative in the real. What kind of new thinking in complexity do we need for this?

New Thinking in Complexity About the Complexity of Reality Starting from the dynamic notion of the complexly woven tapestry as a nonlinear complex reality, linear thinking may be shown to be dangerous (see Mainzer 2004, p. 407; emphasis added). So we need new thinking about the nonlinear dynamics of complexity. With Lev Vygotsky, we take these dynamics as essentially causal dynamics14 (see Vygotsky 1978, p. 62; emphasis added). This kind of new thinking (in complexity) is fully in line with the recent thinking about the tapestry of complexity, for example as demonstrated by the thinking of Stuart Kauffman (1995): “we are beginning to pick out themes, strands in the tapestry” (p. 185). This description is very close to what complexity is ‘really’ about: “that which is interwoven15” (in Morin 2001). But although we may have found a kind of start in new thinking about complexity, it still seems to be true that “a new conceptual framework (for the study of this kind of complexity) does not yet exist” (Kauffman 1995, p. 185; emphasis added). In the same book, Kauffman makes the rather bold statement that “Nowhere in science have we an adequate way to state and study the interleaving of self-organization, selection, chance, and design” (Kauffman 1995, p. 185). We agree with Kauffman that this is very much the state of art in complexity thinking in our sciences. It is the aim of this book to make a beginning with the programmatic view and the conceptual tools needed for the study of the complexity of reality along the lines

14  His focus on the causal dynamics has mostly been overlooked or neglected by almost all of those following the footsteps of Vygotsky or trying to stand on his shoulders. 15  The Latin word ‘complexus’ means “that which is interwoven” (see Morin 2001).

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sketched above: as that which is causally and dynamically interwoven. What is ‘really’ interwoven is kind of ‘webbed networks’ with a particular kind of ‘webbed architecture’ (Kauffman 1993, p. 428). These web-like structures may evolve dynamically over time, as ‘emerging hypercyclic webs’ (cf. Kauffman 1993, p. 366). We may, then, rightly ask the key question: “What is the weave?” (Kauffman 1995, p. 185) To find the answer to this difficult question, we need to make several steps. The necessary steps will be made from a trans-disciplinary perspective, for the very reason that complexity, as described in this way, is a trans-disciplinary concept. It is a concept about structure and emergence, for the use of explanation (Kauffman 1995, p. 23). We may take complexity as a concept linked to the generation of emergent realities; that is, as a kind of self-generated state of affairs (cf. Luhmann 2002, p. 157; emphasis added). That’s why we may better call complexity ‘generative complexity’, because of the dynamics involved in complexity of the real (cf. Rescher 1998). Using this concept of complexity may expand our notion of reality, by becoming familiar with the unknown potentialities of causal interaction within the dynamic tapestry of complexity and its inherent ‘explosive possibilities’ (cf. Kauffman 1993, p. 395; Kauffman 1995a, b, p. 28; emphasis added). Reality, then, with this kind of inherent complexity, may imply a new choice to be made about reality for the social sciences, being a choice that is obviously different for the social and the natural sciences (cf. Rescher 1998, p. 72; Vygotsky 1926/1997). All of this reasoning implies a choice for a new science about this different reality for the social sciences. This is also the very choice that seems so much implied by the question from Roy Bhaskar about science: “what must the world be like for science to be possible?” in his book A Realist Theory of Science (Bhaskar 1975/2008, p. 23). From the considerations above, it may be derived that it is no surprise that the state of art of our sciences is still a very bad state. Kauffman, f.i. notices that “In the biological and social sciences, we badly lack a body of theory, indeed even a means of addressing these issues: what is a functional whole and how does it transform when its components are altered?” (Kauffman 1993, p. 370; emphasis added). From this position of the state of art in these different kinds of sciences, it will neither be a surprise that the new science will be a science that still has to be invented, for the ‘simple’ reason that it does not yet exist: “We are seeking a new conceptual framework that does not yet exist” (Kaufmann 1995, p. 185). However, based on the steps in Chap. 4 and in the footsteps of Vygotsky, it will be a science that is “integrating natural, humanitarian, and social knowledge” (see Sobkin and Leontiev, in Robbins 2001, p. 124; cf. Ogilvy 1996). In line with Vygotky’s thoughts about determinism it will be a determinism that is humanized, because it  leaves open a space of the possible, which is an unpredictable open space (cf. Hofstadter 2007, p. 71). The hope and perspective for the new science is to leave ‘the self-inflicted wounds’ of our viewing and doing science behind (Burkhardt and Schoenfeld 2002).16

16  See see also the interview of John Brockman with Brian Goodwin, to be retrieved at http://www. edge.org/3rd_culture/goodwin_p4.html

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The building of this new science, which is a science about the reality of complexity and the complexity of reality, will very much take place in the footsteps of Vygotsky: as a visitor from the future (see Bruner, in Vygotsky 1987). It is his original way of thinking, beyond the limits of ‘normal science’ of his time, which makes this description of Vygotsky as a futurist thinker so true. He showed many features of rebellion in his writings17: for instance, where he makes mention of the denial of the complexity of reality of wholes by ‘simply’ reducing them to elementary parts (cf. Vygotsky 1997c, p. 262). Vygotsky called such a restricted view on performing science straightforwardly “a testimonium pauperitatis”18 (Vygotsky 1997c, p. 26).

A New Science About a New Reality We may put the question if science can be really different by taking reality as complexly different? We think this might be the case indeed. Not by constructing a different reality but by taking reality as ontologically different (see Bhaskar 2011, p. 23; cf. Rescher 1998). Rescher, for instance, declares that “the complexity of social science lies in the final analysis not so much in the multiplicity of its internal parameters as in the changeability of their interrelationships” (Rescher 1998, p. 73). It is the dynamics of complexity that is of relevance here. It is therefore necessary to make clear that our focus on reality is not on reality as a kind of given reality. We desperately need to go beyond that, to open up a new space for thinking about the invention of a new kind of science. Of course, this is not an easy task. Else, others would have succeeded before (cf. Kauffman 1995). The reason is that the social sciences have been wrongly founded. Too many bad elements are constitutive of the social sciences, in a way that is self-sustaining and self-strengthening the ill foundation of these sciences. Every element is dependent on the others in this constellation. You cannot change just one element to have a different science. Taken together, these bad elements seem to end up in a kind of Kuhnian ‘normal science’, manifesting itself as not able to produce novelty and innovation (Kuhn 1970, p. 51) and even strongly resisting change. So, we need the courage and the strong will to overcome this resistance. Only then, we may become inventive of a new science, by creating novelty of fact and theory (Kuhn 1970, p. 52). It seems the right place here to remind what Vygotsky stated about the very idea of a new science: “you cannot find a science; you have to invent it” (Vygotsky 1926/1997). Not by just changing one element of this science but by changing the whole architecture of it. It finds inspiration in the work by Frank Gehry (see Fig. 7.1 above).

Cf. Einstein, described as being both creator and rebel, in a biography by one of his pupils (Banesh Hoffmann 1972). 18  “Declaration of poverty”. A declaration that you needed in those days to get some food from the church, not to starve. 17 

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To start with, we need to escape or leave behind what Barry Sandywell has described as “the ocularcentric model of reality and world-orientation” (Sandywell 1996, p. xiv). Our view about the relation between science and the real is very much based on how we perceive reality. We ‘simply’ tend to believe what we see. At the same time we are not fully aware and knowledgeable about our seeing itself. We should become more aware that we ‘simply’ cannot see our seeing (cf. Vico 1744/1993; Wittgenstein 1926; Luhmann 2002). Like Wittgenstein’s example of ‘the fly in the bottle’ and the problem of how to get the fly out of the bottle, we have to face the problem of how to escape the very bottle we are in ourselves, in our doing and viewing science as usual. We first have to become aware that we are kind of prisoners, caught in the bottle by our own thinking. For this reason, we have to become fully aware of the situation we are in. What kind of Western thinking has led us into this situation? We agree with Sandywell that “forms of thinking are contextual inventions with specific ontological effects” (Sandywell 1996, p. 414; emphasis in original). Sandywell speaks openly about ‘the crisis of Western Reason’ (in the title of his book); a crisis that has led to “the contemporary crisis of the sciences and humanities” (p. xv). So, we may become aware how our Western science has been ‘invented’ in our Western history of viewing and doing science, by specific modes of world disclosure, which can be opening but also limiting, because they are products of self-interpretation and self-construal (Sandywell 1996, p. 414; emphasis added). After being aware of all of that kind of complication, we can take the first step for building the new science: by new thinking in complexity. This seems in line with Sandywell’s plea for an ontological approach to science (p. 414), referring to what he calls a ‘realist turn’ in the work of Bhaskar (1991). This is an approach that is also critical about a constructivist epistemology. We agree with Sandywell (1996) that “scientific research is not merely ‘socially constructed’ work” (p. 413). It is as much “a creative, truth-disclosing process” (Sandywell (1996), p. 413). This is the stance we prefer to take in our new thinking in complexity for the social sciences and humanities, as a new tool for building a new science with a new conceptual framework.

Thinking in Complexity Our new thinking in complexity starts with the notion that we should take complexity of reality not for granted but as real. That is, we take complexity as a concept as being inherently linked with the very complexity of the real. This brings us to the key question of this book: “How can we learn to think in complexity about this very complexity of reality?” This question demands for a kind of learning to think anew (cf. Bateson 1972, p. 462, about learning “to think in the new way”). We may start to imagine a new dynamic complex reality, a potentially nonlinear reality, encompassing the dynamics of the real world (see Sandywell 1996, p. xviii). It will be this new reality, which encompasses our selves as constitutive ‘elements’

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of this dynamic, complex reality. We may conceive of ourselves, as active agents, enacting this new reality (Senge et al. 2000, p. 49). Once we understand how these dynamics of the real world may ‘work’ in practice, we may even make it real generative, potentially changing the world with a hitherto unknown speed. We may become able to recognize and understand the hitherto unknown generative mechanisms and generative principles in the real[m]. All of this may be an opening for new vistas, by making use of what Kenneth Gergen has called “the generative power of the Social Sciences” (see Van Langenhove 2000, p. 112; emphasis added). According to Gergen this is the power of theories to “unset the common assumptions within the culture” (1982, in Van Langenhove 2000, p. 112). Most of our theories in social sciences do not have this power yet. By increasing this generative power, however, we may finally dis-cover a path to a new world: “the world of the possible” (Kauffman 1993, p. 375). That is, the possible of the spaces of possibility of a hitherto unknown world. This will be the unknown path to an unknown reality; a reality that is only seemingly beyond our imagination. We want to stress here that the new thinking wants to escape the danger of linear thinking about a reality that is essentially a nonlinear complex reality (Mainzer 2004). We may speak, for instance, about the danger of thinking of linear causality (Mainzer 2004). The new thinking in complexity wants to deal with the dynamic complexity of the real-world dynamics as being potentially both linear and/or nonlinear. The focus will be on a trans-disciplinary approach, with different tools of thinking, of relevance for all of the different disciplines (cf. the work by Edgar Morin and his demand for a reform of thought). Therefore, the new thinking means a kind of rethinking too. It is because of such rethinking that a new framework can be built: a framework that does not yet exist. It will be one of the main goals of this book: to show how such a new framework will look like. The focus will be as well on how it differs from the different theories about complexity, which are around in the field of science, such as the chaos theory, catastrophe theory and computational complexity theory. The rethinking, as sketched above, may not only offer the opportunity of building a new science, as a more promising science but is also enabling a new kind of future of the social sciences and humanities by opening a world of transformation (cf. Giddens, in Sandywell 1996, p. 412). This may demand quite a bit of rethinking indeed: a rethinking of the basic assumptions of our doing science as usual (cf. van Langenhove 2000, on rethinking psychology). The promise is not only a new science about a richer reality but also the promise of a new, richer culture. This does not imply that we may ‘really’ know reality by new thinking in complexity (see Morin, in French, 1997). Instead, the focus is on the fundamental uncertainty of knowing about the complexity of the real. Yet, we believe that the new thinking in complexity has the full potential of dealing with the problems and the good questions that have remained very much unanswered for so long in our sciences (Simon 1996). In  a way, science, then, may become the subject of study itself, by taking this critical position on viewing and doing science as usual. We must be aware that the creation of a new science is “not a matter of agreement, but of a rupture” (Vygotsky 1926/1997, p. 301).

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By taking the complexity of reality seriously and not for granted, we may be able to humanize the sciences, i.e., the sciences related to the study of the human being as a complex human being. The new thinking may become a possibility for everyone to escape the situation of being a prisoner of theories, both at the theoretical (Edelman 1992) and at the practical level, like that of a teacher with his own subjective theory (Holt 1967, p. 271). It is a way of escaping reality as we think we know it. With Nicolescu, we like to put forward that “by “Reality” (with a capital “R”) we intend first of all to designate that which resists our experiences, representations, descriptions, images, or even mathematical formulations” (Nicolescu 2005, p. 419; emphasis added). This, we contend, is the challenging way of opening the social sciences (Wallerstein et al. 1996) and of opening up new spaces of possibility as unexplored spaces for these sciences and the humanities as well (cf. Shotter 1995, p. 169).

Complexity and Science Introducing complexity may have important consequences for the viewing and doing science; that is, for the science as usual. This brings us to the most important question of this book, which is about the relevance of complexity for viewing and doing social science. To put it bluntly: What is the use of complexity and thinking in complexity for the social sciences and humanities? From this point of departure for new thinking, we may wonder if it is possible to imagine that the concept of science itself may change fundamentally by new thinking in complexity. Could this new thinking in complexity be the kind of cornerstone so fiercely disdained by the builders of science, as Vygotsky has put it (Vygotsky 1987, p. 91)? If we are finally able to use this cornerstone, how hopeful can we then be about the use of this new cornerstone for building a new science? Are there ‘really’ hitherto unknown possibilities to transform science as usual and the common beliefs and assumptions of scientists in their viewing and doing science as ‘normal science’, as Kuhn (1970) has put it in his book about scientific revolutions? This kind of transformation of our science, we argue, may only become true if we really go back to the basics of science: by starting to become reflective about the viewing and doing science as usual. So, we may put the question what science actually is or can be taken for? We go deeper into this question below. Maybe the essence of science is its generative power of transforming itself: the generative power of innovative transformation by unknown forces. These forces are truly unknown in advance (see also Kuhn 1970). Will it, then, be possible to learn within the unknowable? This is the very kind of learning, the kind of aim, we may formulate for the giving birth of the new science. Actually, it is our ‘real’ hope to enter new paths and learn to see and think in a new way (Bateson 1972, p. 462).

http://www.metanexus.net/conference2005/pdf/nicolescu.pdf

19 

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This may be the new beginning, of entering a different world, enabled by escaping the ‘normal science’ that hampers real innovation (Kuhn 1970). It is our firm belief that it will be possible “to find beautiful and deep theories” (Kauffman 1995, p. 18). It may be a kind of theory about a reality that has remained hitherto unknown (Luhmann 2003). We open up a new understanding of the world: of a hypercomplex world (Luhmann 2002). That is, the very world we live in (see Cilliers 2005). We may, then, discover unknown emergent realities, as self-generated states of affairs. To be able to do so, we may need different tools, i.e., the tools of new thinking in complexity, for the description, understanding and explanation of this hitherto unknown hypercomplex world. In becoming reflective about our viewing and doing science, we may start to be critical about the ontology in common ‘use’ in our viewing and doing science (cf. Luhmann 2002, on de-ontologization of reality, at p. 132). In the same vein, we may be critical about the dominant epistemology in the social sciences. In line with Mainzer’s thinking, from a philosophical point of view, we like to put forward “new standards of epistemology” (Mainzer 2004, p. viii). According to him, these are “the standards, which the complex problems of nature, mind, economy, and society demand” (Mainzer 2004, p. viii). From these standards, we may ask questions like “What can we know about the world?”, “How do we know it?” and “What is the status of our experiences?”, which are the kinds of questions to deal with (see Paul Cilliers 2005, p. 607). According to Klaus Mainzer, the first question is inviting “a demand for scientific research, in order to improve our knowledge about complexity and evolution” (Mainzer 2004, e.g. p. 311). In our view, this implies a demand for reconsidering fundamental problems like the problem of action and reaction in their very interaction, “as a dynamic unity” (Starobinski 2003, p. 268; cf. p. 114, about this problem for physics). We may also reconsider the very ‘problem of causality’ for the social sciences. For causal analysis has remained “a hardy perennial of social science” (see Buckley 1967, p. 66, p. 71). By answering these fundamental questions, we may become enabling of a new thinking in complexity and ultimately of a new science (see Cilliers 2005, p. 606). It may be time to reconsider not only what reality is about in our viewing and doing science but also to reconsider the question “how we know what we know?” as the basic epistemological question. The focus, then, may not be the drive for gaining certainty but instead giving room for an epistemology, which is opening the space for dealing with uncertainty (Prigogine 1997; Luhmann 2002; Peat 2002). We may, then, start a very different journey: a journey into the unknown hypercomplex space of possibilities. A journey that is not just based on new principles and mechanisms but also on rules and laws “that are native to the system” (Davis et al. 2005, p. 2). This implies a full acceptance of the inherent complexity of the system of study and a firm rejection of the fragmentation of science, as shown in the isolation of their separate disciplines. Speaking about epistemology, we agree with Klaus Mainzer (2004), in his book about Thinking in Complexity, that we need ‘a new epistemology’, about a reality that is nonlinear and complex (p. 15). In line with this, he contends that it is time to go beyond “the illusory model of deterministic as well as computable nature”

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(Mainzer 2004, p. 37). Thinking in complexity about a nonlinear complex reality, then, may afford such a new epistemology. This will be an epistemology with a  focus on the hitherto unknown. This focus is not only on “how do we know what we (already) know?” but also on “How do we know what we do not know?” It will be very much an epistemology of the uncertain and unpredictable complex phenomena (Prigogine 1997; Luhmann 2002; Peat 2002). Mainzer’s position about complexity and science is in agreement with the position of Daniel Dennett (2003). Both authors are making us aware of the hidden agenda of the social sciences, with the dear old habits of thought of those participating in these sciences. These are old habits, which are still productive of a distorted kind of view of these sciences, about a very much distorted reality. These views of science and the real and how they relate, are not only of utmost relevance for theorizing but also of importance for practice; that is, for a philosophy of practice (see Vygotsky 1926/1997). We strongly believe that the new thinking in complexity may finally link the fundamental, of theory, with the practical. We can think, for instance, of training teachers in higher education, which is focused on “making sense of their teaching practice” from an emerging, epistemological perspective (Niessen 2007). Such training may start with theory and the finding of corresponding facts and experiences, or start with the acceptance of facts and experiences and, because of such acceptance, the building of a (local or general) theory based on these facts and experiences, enabled through interaction with others in the group of concern. These positions about science and the real[m] may demonstrate that ultimately, in our viewing and doing science, reality is a choice! This position implies that a theory about this reality is a choice (cf. Chalmers 1978, p. 108). We may, therefore, go beyond the assumed view of reality and go beyond the accepted theory in use. We may conceive of reality in a different way. The reality may be shown to be a fluid kind of reality, with its spiralling nature. Like Paul Cilliers, we may describe this complexity of reality, which is a dynamic complexity of reality, in the following terms: “Everything is always interacting and interfacing with others and with the environment; the notions of ‘inside’ and ‘outside’ are never simple or uncontested” (Cilliers 2005, p. 611; cf. Escher’s graphic picture of the Möbius Band above). What we strive for in our new thinking in complexity about reality is an active engagement within the world; a world “in which we seek to achieve the unity of theory and practice in practice” (Bhaskar 1993, p. 9; emphasis in original). Reading Mainzer’s position in this discussion about epistemology, ontology and their relationship, we may conclude that he is fully aware and for good reasons we think, that the new epistemology may have serious consequences. At the end of his book Thinking in Complexity, he states, “The principles of complex systems suggest that the physical, social and mental world is nonlinear, complex, and random. This essential result of epistemology has important consequences for our present and future behaviour” (Mainzer 2004, p. 387) The challenge, then, will be to start to learn to think in complexity about the nonlinear complex reality. The learning is about the hypercomplex space of the

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Fig. 7.2  M. C. Escher’s “Möbius Band II” (© 2010 The M.C. Escher Company B. V. – Baarn – Holland. All rights reserved)

­possible. This implies a strong demand for re-thinking. This may be the place and time to ask the reader if he/she is actually ready for this demand of rethinking: see the text below, inspired by the American You may not want to be ready You may want to be ready You want to be ready You may not be ready You may be ready You are ready Text inspired by Bruce Nauman

artist Bruce Nauman.20 As you may read from this text, with its different stages, you can be ready in different degrees. 20  Bruce Nauman, American artist, original shown at an exhibition of a project in the Tate Gallery in London, 2005.

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Building a New Science About a Complex Reality Maybe the most general aim for the new science as a new science will be the aim of liquefying reality as the subject of study in this science, implying a fundamental de-ontologization of reality (Luhmann 2002, p. 132; emphasis in original). The liquefying of reality, we argue, provides the new science with a different kind of ontology: not a ‘things’ ontology but one which is about a fluid kind of entities and their fundamental interconnectedness (cf. Hofstadter 2007, p. 25). In line with what Darwin did for the biological science in his day, that is, the liquefying of the assumed static version of reality, we may show reality of the social sciences to be a real complex, fluid kind of reality for these sciences. So, the main elements of our focus may be taken as ‘really’ fluid: both reality itself, the science as ‘operating’, with its focus on reality and the relation between science and reality. Of course, the stance to be taken implies that we take the complexity of reality seriously. To be more specific, from the very start of our project, we take the Complexity of Reality (C of R) and the Reality of Complexity (R of C) as essential elements of our new thinking in complexity. This means that we reject the notion of reductionism as a fruitful idea for the future of our sciences and humanities. We need to take the true nature of ‘things’ seriously, with their inherent complexity. Complexity, as we conceive it, may not ‘simply’ be reduced for free. The empirical attitude for viewing and doing science may not suffice for dis-covering the true

Fig.  7.3  Frank Gehry, Guggenheim Museum Bilbao (© FMGB Guggenheim Bilbao Museoa. Photo, Erika Ede. All rights reserved. Partial or total reproduction prohibited)

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nature of the real. Already at the start of his scientific career, Vygotsky made mention of what he called “the sham blind empirism” of his contemporaries, at the beginning of the twentieth century. We are also critical about reductionism, because it is a kind of antagonistic to the very notion of complexity. As a consequence, we take reductionism and the different kinds of manifestations of it in viewing and doing science, as a fundamental damaging kind of entry for the social sciences and the humanities. This may be true as well for humanity in general. Reductionism is, in its strictly reductive stance, too reductive of reality for viewing reality adequately: that is, in its full, complex richness. It is for this reason, we argue, that the reductive view may turn into a kind of dehumanizing view of the human being. Inspired by the philosopher Max Velmans, we may therefore say “goodbye to reductionism” (Velmans 1998) and say hello to a science, which is very much about (dynamic) qualities (see interview John Brockman with Brian Goodwin; see also footnote 1 in this chapter). To take a complexity perspective means that we may take the seemingly unknowable, all that is related to the complexity of reality, as a subject of study. Doing so, we may start to learn anew: we may start to learn within the unknowable. This may enforce a bridging to the unknown, of unknown territories and multidimensional hyper-spaces. This field of the unknowable is at the same time the field of the unpredictable and of the uncontrollable. But this does not mean that a different kind of knowing would not be possible. On the contrary, we want to argue. But this kind of knowing may be a different kind of knowing. It will be a knowing about the complex nature of the subjects of study in the social sciences, i.e., the inherently complex nature of the human being as a subject of study (Clark 2002). It is about the human being, as a potentially nonlinear being (Stanley 2005; emphasis added). This description is very similar to Vygotsky’s concept of the transitory child as the focus of study in the new science he wanted to build. Henceforth the new kind of knowing demands for a new kind of thinking. That is, of thinking in complexity about such nonlinear being of human beings, with a potential of qualitative transformation, of leaps and turning points in their development and even of metamorphosis (see Vygotsky 1978, p. 73). We may stress, again, that it is not one new step that is needed for the delineation of new thinking in complexity and the development of a trans-disciplinary approach but all of the steps to be delineated in the next chapters. These steps make our view and approach a real programmatic one, like the theory of evolution has shown to be a programmatic view, for centuries already. However, it does not mean that you need to consider all of the steps, all of the time, in viewing and doing science that is based on the new thinking in complexity for the social sciences and humanities. But one may draw the general conclusion that we need to be more reflective about the foundation of our sciences in general and of the social sciences and humanities in particular (cf. the need to be reflexive of social scientists, in Brian Fay 1996, p.  230). Questions like “what is reality about?” and “how do we know what we know?” need to be asked, now and always, to enable a better future of these sciences. These questions may be the source of inspiration for escaping old habits of thought and to start rethinking in a fundamental way. This critical stance has also

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consequences for our approach of complexity thinking that is already present and manifest in the field of our (social) sciences. The very concept of complexity in use in the different sciences has already its own history, which has not always been favourable for the development of the sciences. Some version of it, the cyberneticbased version of complexity, may be considered as having had damaging and ­de-humanizing effects from the very start (cf. von Foerster 1992). The same may be true for the systems-based version of the human being as linked with the notion of complexity (see e.g., Morin 1992; Stacey 2003). Both versions are to be considered as essentially reductive versions of a nonlinear, complex reality (see e.g. Bhaskar 1993, p. 147, on the colonization of ‘life world’ by ‘system’; emphasis added). Of importance is also the role of language and that of the use of metaphor in the development of the sciences. This role and use may be quite misleading for that development. Umberto Eco speaks about ‘the scandal of metaphor’ and noticed that using a metaphor is always a form of lying (Eco 1984). The history of the social sciences has shown many examples of the wrong use of language and of metaphors, as well as the devastating effects of that use, by ‘delivering’ a distorted notion of reality and of the social sciences themselves (Dennett 2003). This is the dark side of it. There is, however, also another, more positive, enlightening version of it; a new version that may give hope. We think it is very true that “language creates as it decodes reality” (Pinar 2006, p. x; emphasis added). So, it is opening as well for the creation of a different reality; a reality, which we consider to be opening of the social sciences and humanities (cf. Wallerstein et  al. 1996). It is opening new spaces of possibility and hitherto unknown territories, with unlimited possibility of enlargement of the cognitive domain (Maturana 1980, p. 38; emphasis added). Our view of the complexity of reality and the reality of complexity is very much inspired by the philosophy of critical realism described in the work of Roy Bhaskar and of Margaret Archer. Their view can be considered to be not only opening for the social sciences by the take of reclaiming of reality but also by taking the nature of the human being as a free, creative, non-dualist loving nature (cf. Bhaskar 2002, p. viii). It may be stated that Bhaskar’s view of the human being, as a species or being with its generative kind of state of being, derived from a ground state, is very much alike that of Vygotsky (1997/1926). Below, we go deeper into this kind of thinking about the hidden nature of the complex human being.

A New Reality To summarise the discussion above about reality, it is clear that for viewing and doing science from a paradigmatic view, the subject of study, linked to that view, presupposes a conception of reality. Chalmers (1978) states the following about the relationship of reality with the notion of paradigm: “Each paradigm will regard the world as being made up of different kinds of things” (p. 95). For the new science, this implies that the subject of study will be rather different, presupposing a different reality. Our take of the complexity of the real is about a dynamic complex reality,

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containing the complex causal dynamics of the real world, as part of the subject of study of the different scientific realms. The new science will therefore override and not “be hampered by dividing lines between the conventional scientific realms” (Ruurlo Manifest 2006). It will be opening new avenues for research about the complexity of a new reality. This new reality is about a world, with entities, which are essentially complexly dynamic, fluid and evolving over time, manifesting themselves as complex, emergent realities, of self-generated states of affairs. Clearly, this means that we go beyond a so-called ‘things ontology’ (Saljö 2002). This conception of reality, about the complex, fluid, (causal) dynamics of reality, may certainly have important consequences for the study of the human being as well. Based on Rescher’s notion of complexity as self-potentiating as a fact, we take the complexity of the being of human being as a generative kind of being, which is self-potentiating. This is the key of our approach of the complexity of the human being as the subject of study of our social sciences and humanities. This complexity of human being, then, is conceived as being a fundamentally complex, ‘transitory’ being. We may conceive of this fundamental transitory nature of human being as developing complexly over time. To be more specific, we think of this complex kind of transitory (human) being as an augmented, potentially expanding transition network (Hofstadter 1987). The entities involved are manifesting themselves as emergent realities, of self-generated states of affairs, dynamically evolving over time into states of evolvability. This description of fluid entities evolving over time is very much like the very complex processes taking place in evolution (Kauffman 1993, 1995). They start from ground states and develop into these self-generated states of affairs by acquiring their degrees of entitativity (Wimsatt 1989; 2000). It is the generative complexity ‘at work’ in the real, which is enabled by the increasing degrees of social and interactional complexity in the real. All of this kind of new thinking in complexity is very much in line with Vygotsky’s way of thinking about the inherent complexity of learning and development of the human being and the causal dynamics involved in the generation of complexity. We may conclude that it is the very generative nature of complexity that is so much needed to get the cognitive functions of human beings operating adequately in the real. We may also conclude that the common scientific approach in the social sciences and humanities is insufficiently complex to describe and explain the complex phenomena in our complex world. We may now take some steps further on the road in our new thinking in complexity about reality. We may take reality as ‘really’ different, consisting in entities and relations, which are dynamic, fluid entities and relations by nature (cf. Fay 1996, p. 231; emphasis added). Our conception of reality is about relations and dynamics, with effects that may transform the processes and may change the very structures in which these processes take place as well. From this view of reality, we may conceive of the complex being of potential human being as possibly linked to the notion and concept of ‘generativity’, linked to ‘states of knowingness’ (Bohm and Peat 2000), to be conceived as creative states of “knowing how to go on” (Lord 1994). These states can now be taken as inherently complex, generative states of being which are, however, real (von Foerster 1993; emphasis added). These creative,

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generative states can now be linked with psychic events and processes of dynamic interweaving. For the ‘organizing21’ view of the human being as a complex, whole human being, this means that both (social) relations and functions are fluidly evolving with the evolving of structures, as fundamental elements of learning and development (cf. Vygotsky 1981, p. 163; see also Fay 1996, p. 232). We may look at these relations not as randomly ordered but as a kind of potentially ‘organized’ relations. The learning (and development), taking place within these relations, which are dynamic themselves, are comparable with Hebbian learning, with Hebblike learning rules and Hebbian learning strategies referred to by Mainzer (2004, pp. 148, 170, and p. 10). Learning, then, is a kind of self-organization22 in a complex brain model (see Mainzer 2004, p. 147). All of this new kind of thinking in complexity has the potential of opening the domains of potentiality and the space of possibilities within a world of the possible, which will ultimately be a richer sort of world (cf. Bohm 2004, p. 141). The real challenge for the new science of complexity, which is about the complexity of reality, is to enlarge the space of the possible for the human being in what it means to be human and to be the inherently complex human subject of study for the social sciences and humanities (cf. Osberg 2009, on this view for education and being educated). This kind of complexifying the subject of study implies not only a kind of humanising the social sciences and humanities (Morin 2002) but also of the very human subject of study in these fields of complex thinking. To enlarge the space of the possible for a richer sort of world, we need to be really creative of “creating a richly webbed architecture”, of webbed networks (Kauffman 1993, p. 428) and link these with the emergent realities of complex, self-generated states of affairs (Luhmann 2002). We may find the tools to link this fundamental notion of self-generation to “behaviour which is self-generated in loops” (Edelman 1992, p. 29; emphasis added). These inherently complex, ‘underlying’ webbed networks may be linked with equally complex notions of ‘bootstrapping configurations’, ‘bootstrapping processes’ and ‘bootstrapping effects’, like the Snowball phenomenon, as effects taking place over time, as f.i. in the field of learning and education (Anderson et al. 2001). Kauffman (1993) describes the process of “functional ‘bootstrapping’” as a process of generating order in complex phenomena in evolution (p. 373). We may start to think about complex phenomena, linked to complex “emergent systems ‘bootstrapping’ themselves into existence” (Johnson 2001, p. 112). From our new scientific complexity approach, we may finally “begin to understand that we’re part of an ever-changing, interlocking, nonlinear, kaleidoscopic world” (Brian Arthur, in Waldrop 1992, p. 333). We fully agree with Brian Arthur that the alternative Although many scholars speak about the notion of ‘self-organizing’, we are critical about the use of this term, because it seems to imply a cybernetic kind of notion of ‘control’. We prefer the notion of auto-constitutive processes, based on autocatalytic processes within autocatalytic sets, operating within webs that “govern their own possibilities of transformation” (see Kauffman 1993, p. 370). 22  See footnote 21. 21 

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complex approach “is a powerful approach” (Waldrop 1992, p. 331). It is a new scientific approach “that makes use of the natural nonlinear dynamics of the system” (Waldrop 1992, p. 331; emphasis added). In our complexity approach, we try to link the fundamental with the practical. We would like to stress that this is very much a Vygotskian approach. It was his philosophy of practice, which was the point of departure of his analysis of the crisis and his mission to build a new science. The rest of this book is very much about exploring and expanding the new world of the possible, by opening up new vistas of possibility, of new spaces of possibility and enlarging spaces of the possible in this new world through new thinking in complexity. It may not be a surprise for the reader that we may desperately need a new language, with a new grammar and vocabulary, to be able to describe and explain all the complexities involved in the study of complex phenomena in the social sciences and humanities.

Chapter 8

New Ways of Knowing About the Complexity of Reality: The Epistemological Problem

One of humankind’s most ancient dreams is to reduce complexity to simplicity (Taylor 2001, p. 137)

Introduction In this chapter we deal with the epistemological problem of the new science of complexity. This is, in short, the problem of our knowledge and the process of knowing, of getting knowledgeable about the complexity of reality: “How do we know what we know about this new, real complex reality?” Right from the start we may realize that this problem is not just an epistemological problem. In this chapter we will show how this problem connects with the problem of method, of methodology and with ontology and how all of these problems in the new science relate to the real(m). For our viewing and doing science, this implies: “the scientific realms as to what is possible” (Ruurlo 2006; emphasis added). As a consequence, we may become aware that, to deal adequately with the epistemological problem, we may and should better broaden this problem into a more general problem. After having done so, we will elaborate about the consequences for the new science with its transdisciplinary approach. To start with the general problem, we may transform our epistemological problem into a more extended form: How do we know what we can know about a complex, nonlinear, and random world? (cf. Mainzer 1994, pp. 431, 438; emphasis added)

This way of knowing demands for a new kind of thinking in complexity: of what Edgar Morin nicely and complexly describes as “a thinking which thinks itself” (Morin 2008, p. 97). This new thinking escapes the old ways of thinking. The new thinking implies new principles of thinking (see Table 6.1, with old and new ways of thinking, in Chap. 6). The new thinking about the complexity of

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reality goes definitely beyond the orthodoxy of the traditional scientific method. Friedrich Hayek (1964) was already very much aware of this, as can be shown with his next statement: What we must get rid of is the naïve belief that the world must be so organized that it is possible by direct observation to discover simple regularities between all phenomena, and that this is a necessary presupposition for the application of scientific method. What we have by now discovered about the organization of many complex structures should be sufficient to teach us that there is no reason to expect this and that if we want to get ahead in these fields our aims will have to be somewhat different from aims in the fields of simple phenomena (Hayek, in Bunge 1964, p. 349; emphasis added)

By recognition of the very complexity of the epistemological problem, which demands for a new complex way or form of thinking, we may face the very problem of thinking in complexity that is needed for the challenge about what Morin described as “giving birth to a new type of science” (cf. Morin 2008, pp. 84, 88; emphasis added). We argue that this complex thinking and complex knowing will be a part of the new agenda for such a new science. To be more specific: for rethinking the structure of science and its modus operandi (cf. van Benthem 2002, p. 87). Ultimately it may lead to the liberation of science from a self-imposed tutelage. Taking up a challenge as sketched above is certainly an uncertain adventure. An adventure that demands for a certain kind of courage1 (Morin 2008, p. 97), which is not natural; a courage that “seems sadly lacking today” (van Benthem 2002, p. 89). The demand, therefore, is for a kind of courage that, at least in the beginning, gets close to a kind of rebellion. It is, as we think, a kind of rebellion that we may better recognize as part and parcel of our history of humanities, like philosophy (see Kant’s famous text on the topic of ‘enlightenment’) and that of art as well.2 Morin (2008) recognizes and we think with good reasons, that “we seem incapable of thinking in a complex manner” (p. 97). We fully agree with him that “complex thinking is not omniscient thinking” (Morin 2008, p. 97). It is for this recognition and that of the broader epistemological problem, that we have to face that the text of this chapter will definitely not be a kind of straight linear text. This being the case for the ‘simple’ reason that the path of new thinking in complexity is not a single path but a path full of bifurcations. Actually the complex path may be better described as a web-like structure, with an unknown directionality. We describe the fundamental problem of finding the path towards a new science from different angles, with different paths and phrasing of the complexities involved in thinking and knowing complexly. The aim of this chapter is to give the reader a  Cf. Kant and his ‘Sapere aude!’ (Have the courage to think!) as foundational for the start of Enlightenment. 2  e.g., René Magritte, in Gohr 2000. Cf. Banesh Hoffmann, with his book about Einstein as rebel and creator. See also Stuart Kauffman (2008), in chapter 3, about “The physicists rebel”, on more recent rebels in the field of physics like Robert McLaughlin and Philip Anderson. 1

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more solid feeling about the need for such new ways of knowing by new thinking in complexity; that is, about the dynamic complexity of real-world complexity, with its inherent real-world dynamics. We hope the reader will join us in becoming fully aware that “we cannot isolate the world from our structures of knowing” (Morin 2008, p. 91). Our point of departure is that we take both a kind of critical constructivists and a critical realist approach as foundational for our new thinking in complexity. In practice, for dealing with the problems of the new science, this means that we believe that a critical approach is necessary for the advancement of knowledge and for knowing as essentially a process (cf. Bunge 1964, p. viii). So, the extended problem of epistemology has its place within the larger problem of giving birth to a new science by invention: by inventing a new program, based on setting a new agenda for this new science. In a general sense this problem is strongly related to the relationship between science and the real(m), the topic we reflected on in the chapter before (Chap. 7). Taking these two topics together in their fundamental, dynamic, the reciprocal relationship has broader implications for science, for what may be called ‘a general theory of science’. Of course, this has implications for ontology as well, which is to be understood as the philosophy of reality, dealing with the nature of being; here understood as the philosophy of the complexity of reality, which is taking the very nature of that complexity as real (cf. Churchman3 2008, p. 1). To be more specific, as far as the epistemological problem concerns both the process of knowing and the reality of the complex real-world dynamics, we may wonder about the general epistemological question, inspired by Mainzer: “How do we know what we can know about a complex, nonlinear, and random world”4 (cf. Mainzer 1994, pp. 431, 438; our emphasis). It may be no surprise for the reader that we reformulate the problem in regard with the new science in terms of “How can we know what we may better know or should know about the complexity of reality, to be taken as real complexity?” The reader may also recognize how this question has a link with the problem of theory and practice. For us it is a basic truth that the ongoing challenge of giving birth to a new science implies the bringing together of practice and theory; that is, of linking the fundamental with the practical. Henceforth, we aspire we may do so in such a way that “we can theorize our practices and practice our theories” (Taylor 2001, p. 233). This does not mean that we believe that thinking in complexity can be easily applied in the traditional way. In this sense, we fully agree with Stacey (2003), that “complexity sciences can never simply be applied to human action” (p. 53; emphasis added). The main reason for this lies, according to Stacey, in the inherent interdependence of ways of thinking and practice: “As one thinks differently so one practices differently”5 (Stacey 2003, p. 2; 3  Retrieved on the 1st of December 2008 from http://groups.haas.berkeley.edu/gem/essays/ complex.html 4  In Rosser (2004), the problem, which really is a transdisciplinary problem, is nicely formulated for economists as follows: “how to know what they (the economists) know in a complex reality” (p. 2). 5  This also being the case for teachers and their epistemological beliefs concerning their own practice (see e.g., Niessen 2007).

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emphasis added). Stacey relates this view to what he calls a paradox, that of a reciprocal dynamic relationship of forming and being formed. This paradox seems to be linked to the paradox of unity, which Luhmann described in the following way: “All unity is the unity of self-reference and other-reference and thus is constituted paradoxically” (Luhmann 1995, p. 363). Stacey (2003) strongly argues for the elimination of this paradox as being a “taken-for-granted feature of current Western thought” (p. 2); that is of our Western way(s) of thinking. We consider the elimination of this paradox as an essential element of our fostering the new thinking in complexity for the social sciences and humanities. We hope to show that, by doing so, we may find the bridges to the (hitherto) unknown and be creative of enlarging the space of the possible within a complex world of the possible, as a fully new space with unexpected possibilities. From this perspective, we may prelude on a new epistemology about complexity as an epistemology of the possible, which is linked to “the fact that complexity is self-potentiating” (Rescher 1998, p. 28; emphasis added). From the above arguments about new ways of knowing, we may derive that the concept of complexity and new thinking in complexity, can be connected both with the idea of a new science, with a new method of thought and with a new worldview (see Delgado Díaz 2007, p. 48). We return to this below.

Epistemology, You Never Walk Alone! From the above, we may wonder “How to go on?” in founding an adequate epistemology for use in our new thinking in complexity about the inherently complex real(m) for the social sciences.6 For this is a complex problem in itself. This is not only the case because of the dynamic relationship between science and the real(m) in the field of the social sciences (see Chap. 6 on this topic).7 We recognize very well that the acquisition of knowledge of the very complexity of reality may always be provisional (Cilliers 2008). This is i.e., of relevance for the problem of linking theory with practice. To make a distinction that makes a difference, we try to take our epistemology about the complexity of reality, of the real(m), as a start and not as a consequence of the new thinking in complexity (cf. Luhmann 1995). Of course, the emerging epistemology can be considered to be a result of escaping old thinking and ways of knowing and consequently, as the transformation into new thinking and the concomitant new ways of knowing. We may, then, speak about a new mode of knowing and of a new way of the ‘production’ of knowledge (cf. Gibson et al. 1994). To put it differently, we may say that finding the path for new ways of knowing is very much

 cf. Smolin 2006, p. 258, about this problem of how to go on in the physics of these days.  In this chapter, it was shown in Figure  6.2, that (the question what is) science itself is not an object of study in science (cf. Philipse 2002, p. 158). 6 7

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part of a process of invention that can only take place by unlearning of the old ways of thinking and knowing. This may imply that we may learn that we actually do not know. The challenge is not only to bridge the gaps in our understanding (Ruurlo 2006) but also to find the bridges to the hitherto unknown. For this reason, we think that to learn to think in the new way is not just a rational process of thinking (cf. the quote with the different steps of hearing by Bruce Nauman, in Chap. 7). That makes the learning to think in the new way so difficult, as recognized by Bateson (1972, p. 462). Thinking in the new way is really a kind of adventure without any certainty about paths to find or to follow. The only kind of certainty one can have is opening new avenues for understanding and enlarging the known spaces of possibilities. The whole process of invention that is needed for developing a new science is a dynamic process. It involves not only epistemology but also ontology and methodology, in their complex interdependence (Archer 1995, p. 3; cf. Rescher 1998, p. 61). Archer, for instance, speaks about their dynamic relationship as a tripartite link that is constitutive for her approach (Rescher 1998, p. 3). As the reader may have noticed, we view this tripartite relationship as a dynamic relationship. None of the elements are taken for granted. Each of the three elements is potentially evolving over time, in and because of these dynamic relationships. For this kind of dynamic relationship and its relationship with the real(m), we refer to Fig. 8.1. The picture of interdependence between methodology, epistemology and ontology is actually really complex. This being the case underscores the view that, to learn to think in a new way, one really needs complexity to be able to deal with complexity in the real(m). The welcome role of methodology is not only to find a solid grounding of simplicity and systematicity in dealing with complexity (cf. Rescher 1998, p. 61). Simultaneously, it brings with it the notion of ‘keep it simple!’ (Rescher 1998, p. 61) This notion is of importance because it will become easily too complex to deal with. At the same time we must not forget that, according to the same author, “It would be naïve – and quite wrong – to think that the course of scientific progress is one of increasing simplicity” (Rescher 1998, p. 66; emphasis added; cf. the quote of Mark Taylor at the beginning of this chapter).

New science

New real(m)

epistemology Old real(m) methodology

ontology

Fig. 8.1  The dynamic relationship between epistemology, ontology and methodology

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In our view, as shown in Fig. 8.1, epistemology, ontology and methodology are very much interconnected. This interconnectedness, we think, is the case, not only for the social sciences in general but can be regarded as typical for the case of transdisciplinarity. For this reason, we may consider from a transdisciplinary perspective, “whether or not the epistemological problem is really an ontological problem” (Rosser8 2004, p. 2; emphasis added). He considers and for good reasons, how complexity implies an ‘essentially ontological’ foundation.9 He refers to this rather bold statement to an earlier publication of his, where he had been stating that “the epistemological problem of complexity may be ‘effectively ontological’ ”(Rosser 2004, p. 15; emphasis added). As a consequence of this line of thinking, he relates the epistemological problem with regard to “the possibility of (acquiring) a substantial degree of knowledge” and with the possibility of a substantial degree of predictability (Rosser 2004, p. 7; emphasis added; Rosser 2004, p. 8). Ultimately, however, as stressed by Rosser (2004), we may run “into the fundamental epistemological problem of all, how do we know that we understand true ontology?” (p. 17). Both problems can be considered as being co-constitutive of each other. So, we have the fundamental problems of ontology and epistemology, to be considered as fully intertwined problems. Again, these kinds of problem are already very complex and a hardy perennial for the social sciences in general. If everything seems so interrelated and intertwined already from the start, how then can we go on? What can be taken for certain if “in fact there is no inside and no outside”? (Stacey 2003, p. 5). This is also very much the case for the well-known picture of the Möbius Band II, by Maurits Escher: see Fig. 7.2. This Möbius Band is also a kind of paradoxical unity, which is complexly real, as a fact! Figure 8.1 gives an idea how difficult it will be, in practice, to develop an adequate methodology for a new, general science of complexity, with a focus on the dynamics between epistemology and ontology. We fully agree with Churchman (2008) that “It takes a genius to create simplicity out of complexity” (p. 1). Anyhow, we should avoid the danger that we take nature itself as simple (see Rescher 1998, p. 61; cf. Morin 2005). It may be for this very reason that Rescher warns us to take great care to distinguish the ontological and the epistemological dimensions. He demonstrates this by giving the next two columns about the status and possibility of knowledge: Unexplainable By chance Spontaneous Random By whim

Not (yet) explained By some cause we do not know of Caused in a way we cannot identify Lawful in ways we cannot characterize For reasons not apparent to us

Interestingly, he is an economist. Being an economist, his new way thinking confirms that a transdisciplinary approach can be engendered by any scholar who is reflective, from any discipline. 9  Again, Rosser states the problem for economists and their related problem of fundamental uncertainty in economic analysis (Rosser 2004, p. 3), which is, as we view it, a real, transdisciplinary problem. 8 

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We dare to state here that the status of our knowledge in the (social) sciences leaves us too often stuck in the left column, without being aware of a possibility to enter the right column: the column of the unknown, of a reality that has remained unknown, with its hitherto unknown domains of potentialities and spaces of possibilities. We believe that a new understanding of the complex, dynamic, tripartite relationship in Fig. 8.1 constitutes in a way ‘a general theory of science’ and a general theory of knowledge as an essential part of this general theory of science about the real(m) (cf. Luhmann 1995, p. 488). We may derive from this tripartite relationship what Vygotsky may have meant with his statement that the crisis in psychology was a methodological crisis: a methodological crisis about the relationship between epistemology and ontology and how their relationship could ‘fit’ with the real(m). He seemed very much correct about the social scientists in his time, being in need for a new understanding of that ‘fit’. This new understanding, now, we consider to be foundational for giving birth to a new science, with a concomitant transdisciplinary approach.10 Based on this notion of a new kind of understanding, we may fully recognize, with Morin (2006), that “transdisciplinarity is inseparable from complexity” for the new science (p. 23; emphasis added). This means that the study of real complexity goes beyond the complexity within the different, separate disciplines! To get acquainted with the complex dynamics of this rather complex approach, we have to take many steps. We recognize as well, with Luhmann (1995), that the complicated conceptual relationships, as visualized in Fig. 8.1, may actually intimidate sociologists (Luhmann 1995, p. 488). But this seems to be true not only for sociologists! Figure 8.1 shows us the real complexity of viewing and doing science about the real(m). For us this is the foundation stone of a new science about the inherent (dynamic) complexity of reality; the stone that the builders (of science) have always rejected (cf. Vygotsky 1997a, Vol. 3, p. 233). To begin with, in our building of a new science of complexity, we may learn to know how we can turn the complexity of real-world dynamics into an adequate conception of dynamic complexity. This will be a real challenge, already complex in itself. This new conception, of dynamic complexity, may involve the new thinking about e.g., the unit of study and the concept of interaction and that of causality. Ultimately, the challenge will be to turn this conception of dynamic complexity into a hitherto unknown form of knowledge; that is, of effective, dynamic complexity, be it qualitative or quantitative dynamic complexity. This problem, of thinking and modelling transition and transformation of forms of complexity, is actually a methodological problem. This problem is closely linked with the ‘true reality’ of complexity in the real(m) and the related question, “how to develop an adequate approach to it?” Of course, we recognize the difficulty of posing

10  For Vygotsky, we believe, this overall focus on how science operates in and relates to the real(m) was what Vygotsky has always been up to, in his mission to invent a new science.

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this problem for new thinking in complexity about reality. To do so, to make this new thinking possible, we may think of different levels of reality. Some prefer to speak about an underlying reality. Others, in turn, argue about the deep structure of this concept of ‘true’ reality as real: as part and parcel of an underlying reality (see Rosser 2004, p. 16). In the words of Vygotsky (1997a), this problem is very much about what he calls ‘the methodology of reality’ (Vol. 3, p. 255; see also below). To what degree, then, will we be able to acquire a substantial degree of knowledge about the very complex, real-world dynamics of reality? This is not an uncommon question for science in general. For us, however, this question is directly related to the problem of turning complexity into effective complexity in our new ways of knowing about the real(m). This, we think, is the crucial question for new thinking in complexity; a crucial question, which is also of utmost relevance in practice. It may show a way of linking the fundamental with the practical, of complexity as real-world complexity. The stance we take here implies that our approach is fundamentally a possibility-oriented approach. This approach should replace the strongly ends-oriented approach that has dominated our sciences for so long. With this possibility-oriented approach, we believe, we can escape the normative tension, which is so dominant in the operation of our ‘normal’ science, with a too limited view of such science as a “science-as-usual”, evolving in the course of time into a kind of “bad science” (Longino & Doel, in Oyama 2000, p. 147; cf. Rip 2002, p. 105). We may open, then, a discussion about the question “what is good science” (Rip 2002, p. 105; Scheffer 2009, p. 8) or, in opposite terms “what is bad science” (see also Oyama 2000, p. 147) and link this discussion with the general human endeavour of “shaping the future in the best way” (Scheffer 2009, p. 8). It makes clear that we need a theorizing about science to turn science into a more adequate kind of science. We may, then, call this more adequate science ‘good science’, in its relation with ‘normal science’, as circumscribed by Thomas Kuhn (1970). Of course, this notion of ‘good science’ is very much a time-dependent notion. But this is true as much for the case of ‘normal science’, with the inherently related ‘bad’ features, as formulated by Kuhn: “normal science does not aim at novelties of fact or theory and, when successful, finds none” (Kuhn 1970, p. 52; emphasis added). For good science the aim is to reach to the opposite: of finding novelties of fact and theory, by linking the fundamental with the practical. So, we may come to the conclusion that we desperately need good science “to open new avenues for understanding in ways that are beyond the dreams of our predecessors” (Ruurlo 2006), with the promise of a possibility-oriented approach, which makes it possible to open up new spaces of possibility within a new world: ‘the world of the possible’ (Kauffman 1993), which is about a richer reality; all for the sake of shaping the future in the best way. And in view of the history of science, the theory of science is a belated product of science-in-operation (Luhmann 1995, p. 478)

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How to Go On? For now and for good reasons delineated above, we may ask ourselves “What is the world really like from our perspective of new thinking in complexity?” for solving the epistemological problem. This foundational question has been the starting point for Lev Vygotsky (1987a, b) as well, in his effort to build a new science of psychology as a general science: “The stone that the builders have disdained must become the foundation stone” (p. 91; emphasis added). His thinking was very much inspired by the idea that “the methodology of science is a reflection of the methodology11 of reality” (Vygotsky 1997a, Vol. 3, p. 255). The nature of reality is not ‘simply’ given to him but is to be considered as very much dependent on the epistemological stance taken in our history of science. Vygotsky was also quite charmed by the writings of Hegel about the relationship between thinking and being: the laws of thinking and the laws of nature correspond necessarily with each other as soon as they are known properly (Vygotsky 1997, Vol. 3, p. 256; emphasis added)

From a similar kind of perspective Mark Taylor (2001, p. 87) also refers to Hegel’s approach of thinking about reality, thereby referring to a constitutive ontological principle that is related to the phenomena of complexity in the real(m). We hope it may be recognized by the reader that this relationship is foundational for the new science we are heading for in this book. A new science that is simultaneously a science of being through becoming, a science of transition and a generative science for the near future: the future of the twenty-first century. The intellectual realities of science are multi-dimensional, and hence, as a matter of principle, there is no natural fixed architecture for it (van Benthem 2002, p. 71; emphasis added)

A New Foundation To start with the foundational question for the building of a new science, based on new thinking in complexity about real-world dynamics, we may underscore that “There really are no adequate grounds for supposing the ‘simplicity of the world’s make-up” (Rescher 1998, p. 61). On the contrary, as we would like to stress here!

11  In Russia, the word ‘method’ means two different things: (1) the research method, (2) the epistemological method or methodology, which determines the research goal, the place of the science and its nature (see Vygotsky 1997a, Vol. 3, p. 274).

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Complexity, although neglected for so long in the history of evolving separate disciplines in science, is very real (cf. van Benthem 2002). So, we may conclude at this place that we do not take knowledge of the complex real-world dynamics world for granted. In the same line of thinking, we do not take the complexity of this world ‘simply’ for granted (cf. Bak 1996, p. 1). As the history of science has shown, we may consider a new kind of thinking; a kind of thinking that was clearly impossible before in the history of viewing and doing science (cf. Vygotsky 1997, p. 243; see also Kuhn 1970). Old habits of thinking, therefore, may be replaced by new ways of thinking. This new thinking is a way of thinking about the transitory nature of a nonlinear complex reality that once was disdained as a building block for a new foundation of the social sciences. Now this block may become the foundation stone. The new way of thinking in complexity we are heading for in this book is, as we believe, is opening up a new future for our social sciences, replacing the scienceas-we-know-it and turning it into a richer view of a reality: a reality that is fundamentally a richer reality.

A New Framework of Knowing It takes a genius to create simplicity out of complexity (Churchman 2008, p. 1)

Old ways of thinking, as manifested in Table  6.1 in Chap. 6, seem simply to exclude complexity as real. However, once we accept that reality is not simple but complex, we may put the question “how may we get knowledgeable about this very complexity in the real(m)?” This difference of realities is a difference that ‘really’ makes a difference. We think one can only speak about a shift of mind in thinking when we leave old ways of thinking and knowing behind. At a general level, those of a community of scholars, this can imply a stepping outside of the current framework (see e.g., Gibbons et al. 1994; Devlin 2002). At a more personal level, such a shift can imply a personal struggle of escape for scientists viewing and doing their science (cf. Morin 2008, p. 98, on this struggle). There may be so many changes involved and decisions to take, as Table 6.1 in Chap. 6 shows. One way or another, one has to follow a path of reflection about (old) elements of thinking and knowing about the real(m) that one has to escape, to replace these with new elements, for which it is not always clear in advance that they may be beneficial for one’s own viewing and doing science. One can only hope that the new ways of knowing may open up the spaces of possibility for the persons involved.12 But there is no guarantee that this may happen. Not at all, one may say. For as an individual scholar, one has to face uncertainty, which can be too much to deal with. So, at a personal level we may conceive of a struggle, accompanied by potential resistance 12  See e.g., Niessen 2007, p. 57, about teachers and their opening up of new ways of knowing and outlook about their inherently complex practice.

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for a change, all of which demands for real courage to reflect on and being open to enable changes in one’s own beliefs. In practice, this may imply a stepwise kind of change, of realizing a potential that was not there before, as exemplified in the quotation by Bruce Nauman, at the opening of Chap. 5. The very process one goes through, the struggle of escape, may be described as a form of navigating the sea of uncertainty: “Without throwing oneself for a time into the sea of uncertainty one cannot escape the contradictions and inadequacies of a deceptive certainty” (Elias 1991, p. 93). So, we have to face uncertainty in our viewing and doing science, if we like it or not. It is or should be very much part of our viewing and doing science. We may leave the notion of control behind, of a controlling style of doing science to subdue nature itself (Bacon), which has dominated science for so long. The overall focus for the social sciences and humanities should not be on control only, for gaining power but on the interpretation and understanding of processes and indivi­ dual trajectories of development that change over time (cf. Robbins 2001, p. 83). New knowing about the very reality of complexity implies a transdisciplinary approach that goes beyond the limits of the different disciplines, which, by their learned incapacities, could afford only a limited view of the complexity involved, thereby disregarding the ontological complexity involved in the study of the object of science; that is, disregarding the relation of what may be termed one of ‘ontological complicity’ between the scientist studying this object and the world which determines it (cf. Wacquant, in Archer 2007, pp. 41–42). The new way of knowing may also imply full recognition of the role of time, another stone, which is disdained as a building stone in our sciences. We need to find a way of bridging to the unknown by turning time into the equation, in the same way as Darwin did for his thinking about evolution, without time as a variable itself. We are convinced that we may build a new science with a better perspective for the future. Without really believing in ‘progress’ of science as a kind of normative idea, notwithstanding we fully support the notion that “progress has been held up as a result of insufficient concern for the epistemological foundations of scientific paradigm” (PPCCS 2001). We think that, for this very reason, most scientists have become the captives of the blind spots and myopia of our science (Van der Veer and Valsiner 1994). From this perspective it may not be a surprise that some scientists are still a kind of ‘prisoners of description’, as Edelman and Tononi (2004, p. 207) described them for their own field of science: the study of the brain and the complexity of its dynamics of wiring and functioning over time. So, we may come to the conclusion that we may indeed escape old notions of the real(m) and old ways of seeing and thinking the world. Recent developments are in line with this need for escape and show some kind of new ways of thinking about viewing and doing science. Gibbons et al. (1994), for instance, sketch a new way of production of knowledge, dealing with problems, which are not set within the disciplinary framework. As they state openly, “It arises out of the existing dysfunctionalities and breakdowns of disciplinary modes of problem-solving” (p. 29; emphasis added; cf. van Benthem 2002). The new production of knowledge, called Mode 2, diverges from the old way of knowledge production (Mode 1), which is historically based on the Newtonian model (cf. Hayek, above). It may be stated that

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new thinking in complexity offers a way of thinking that does not rise over but arises among other discourses. Rip (2002) also deals critically with the science-aswe-know-it version of the social sciences. He warns for the danger of lock-in situations in viewing and doing science and the role of disciplines in this development of science (p. 105). He questions as well the too limited view of science in general, in the way it is based on the dominance of the science of theoretical physics (Rip (2002), pp. 105–106). This author makes a plea for a new mode of knowledge ‘production’, by overtaking the Mode 1 production of knowledge. He seems to subscribe the transdisciplinary and fluid Mode 2 of knowledge production to escape the science-as-we-know-it. We may better speak, then, of the richness of knowledge production as a quality of science itself. Following this path and by embracing variety within a heterogeneous knowledge management process, we may sketch a different future of the social sciences and humanities. Brian Fay (1996) is also critical about the social sciences and makes a plea for a new philosophy for these sciences, thereby making an interesting distinction between knowing and being (p. 27). It is for this reason that we like to speak about the hitherto unknown and neglected states of human being.13 These states are inherently complex, because they are dynamic and multidimensional in a hitherto unknown number of dimensions. These high-dimensional states of being result from the self-generating and self-producing processes in dynamic networks. We return to this topic in the last chapters of this book.

Epistemology and the Real Complexity of Reality From the triangular dynamics between methodology, epistemology and ontology in Fig. 8.1 we may conclude that we ‘simply’ have to escape the oversimplification of the real world and, consequently, have to face the complication and complexities of the real-world dynamics. Often, or mostly, the complex nature of the real world with its real-world dynamics is not appropriately represented by language, methodology and ontology.14 We may conclude that we do not believe in a single coherent ontology, epistemology, or methodology as adequate for viewing and doing science. We may replace this view with the notion of ‘ontological complicity’ (Archer 2007, p. 41; see also above), which is a relational, more fluid kind of notion about the study of the very complexity of a nonlinear complex reality (Mainzer 2004). We may never know how complex this reality ‘really’ is. Maybe we may speak about different kinds of realities, as in the case of the study of light, of photons and electrons. What we do believe, however, is that the dynamics of the tripartite relationship may offer new ­opportunities of including the very complication and complexities of the real world. That is, of including the opportunities of new ways of knowing about the Cf. von Foerster 1993, about so-called bothersome states of learners. See e.g., Niessen (2007, p. 57), about epistemological perspectives in understanding teacher’s education and experience. See also Dennett (2003), chapter 7. 13  14 

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very complexity of reality, with a new method and methodology and a new language for dealing with all the complexities involved in the new viewing and doing science beyond the science-as-we-know-it. We also subscribe Davis’s notion about reality: that the reality or realities as we conceive it (them) is regularly what he calls ‘language-effected realities’ (Davis 2004, p. 99). His notion corresponds with that of Dennett (2003) concerning the role of language around Darwin’s strange theory of evolution that afforded us with a new language, responsible for “an inversion of everyday reasoning in several regards”: A new language, which was very much ‘a foreign language’ (Dennett 2003, p. 47). This very new foreign language enabled a very different kind of reasoning that went beyond the orthodoxies of the time (Dennett 2003, p. 47). This makes language such a relevant issue for the new science, as a way for the invention of new ways of viewing and doing science by new thinking, with a new vocabulary. It was this basic insight that was also leading the work of Vygotsky, in his mission of inventing a new science: If one would like to get an objective and clear idea of the contemporary state of psychology and the dimensions of its crisis, it would suffice to study the psychological language, i.e. the nomenclature and terminology, the dictionary and syntax of the psychologist (Vygotsky 1997a, Vol. 3, p. 281)

This view makes us aware that the science-as-we-know-it is always the outcome of viewing and doing science (cf. Rip 2002, p. 102; see also Kuhn 1970; Luhmann 1995, p. 478). This awareness indicates, again, the need “to step outside the current academic framework of scholarly books, papers, and peer reviewing” (Devlin 2002, p. 93). This opinion corresponds strongly with that of van Benthem (2002). Another problem for stepping outside the current academic framework is the traditional academic writing style in use; a style that is ‘dreadfully limited and limiting’ (Montuori 2004, p. 18). So, the step of going outside our common viewing and doing science-as-we-know-it is not an easy step, as the reader may become aware of, little by little. Actually all of the steps of new thinking in complexity to be made can be considered as a kind of struggle of escape. The view we like to put forward, therefore, is that the new transdisciplinary approach of new thinking in complexity can only be invented and communicated by the introduction of a new language. A language that is apt to deal with all the complexities in the different fields of science, including the different strands in complexity science. We think this should be done, not for making rigid distinctions for unknown reasons15 but because we believe that it opens up a richer description of real-world complexity, with its real-world dynamics. Richer, because the transdisciplinary approach transcends the disciplinary boundaries. It may be stated that new thinking in complexity offers a way of thinking that “does not rise over, but arises among other discourses” (Davis and Sumara 2006, p. 8). Such new thinking in complexity in a new

15  We agree that we live in a kind of conceptual quicksand but we do not agree with van Fraassen (1999) that we function perfectly well (p. 14).

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discourse is definitely not “a ready-made discourse” (Davis and Sumara 2006, p. 8). The invention and development of such a new discourse may imply a kind of cleansing of the common language in use, which takes place in and through the process of an evolving new vocabulary. Although this may seem impossible, as van Fraassen (1999) believes so,16 we think it is not only possible but also desperately needed, to make a shift to new ways of seeing, thinking and knowing about real-world dynamics. Not just for getting simply a better ‘picture’ of this world but for the simple reason of a better understanding of the real-world complexity, with its real-world dynamics. All of this new thinking about old reality may be illustrated by an example like that of the flying of the bumblebee, in Dennett (2003, p. 199): see Box 8.1. This example demonstrates that the assumed model of the assumed (or delivered) reality is “an oversimplification rather than a reflection of something in the real world” (Dennett 2003, p. 199; emphasis added). This example demonstrates how science may operate like the Kantian fisherman, “whose net only catches fish larger than the size of its mesh, and who proudly proclaims as a ‘law of nature’ that all fish are larger than that size” (see Ziman 1978, p. 59). This demonstrates the danger of lock-in and closure in science and the production of knowledge, also known as specialization in our academic world (Rip 2002, p. 133; van Benthem 2002, p. 79). This (first) author speaks about the old mode of production of knowledge (Mode 1) as a locked-in socio-epistemic constellation. At the same time he warns for the possibility that “it may be too early to think of a new regime” (Rip 2002, p. 131). Our position in this is that we fully disagree with this rather deceptive notion about the future of science, in its development for shaping the future in a better or best way. Rip’s view ‘simply’ seems to neglect the significance and power of the Vygotskian notion of critical reflection at all fronts, by analysing the crisis of science and that of invention that is desperately needed for the invention of a new science (see above). As stated more recently and more broadly by van Benthem (2002): Science needs to rethink its structure and modus operandi vis-à-vis a fast-changing technological, cultural and political environment (van Benthem 2002, p. 87; emphasis added).

Van Benthem’s statement corresponds with the notion of a reform of thought that is needed to get a broader scientific view of complexity: a view that goes

Box 8.1  On the Mythic Discovery of Bumblebee’s Flying in the Real World …according to the common aerodynamic model, bumblebees can’t fly. Something must be wrong with the model, since there goes an airborne bumblebee. The model must be too simple, must be leaving out a complication that is actually a key to the bumblebee’s manifest success.

16  Although we respectfully agree with Wallerstein (1991) that “the only epistemology that is plausible lies in the swampy middle ground of the concept of a historical system” (p. 271).

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beyond the restricted view of complexity, which has mostly developed within the separate disciplines (see Morin 2005). Based on a better understanding of the real-world complexity with its real-world dynamics, we may go beyond the richer description of the inherent complexity of these real-world dynamics and become more explanatory about the generative causal power of mechanisms involved in these complex dynamics. Ultimately, as we hope, we may get explanatory about the phenomena of transition and transformation in nature; that is, of processes of involution, evolution and revolution, leading to spiral processes of development (Vygotsky 1978, 1981). By doing so, we may even broaden our view about the origin and nature of life and become (more) complexly explanatory about this ‘big question’ for science. As we view it, this question is still left unanswered because of the inherent limits of our habitual ways of thinking and understanding (see example of bumblebee above). For finding an answer, we certainly need a better understanding of the complexity involved; a complexity that is about “the unity of the dynamics of non-living and living phenomena” (Capra et al. 2007, p. viii). With Lee Smolin (1997), we are optimistic about finding a different kind of answer to this big question for our sciences: see quote below. For sure, we need to learn to think in complexity, to find a kind of answer, based on a new epistemology that addresses the ontological complicity involved in the study of life itself. It will be an epistemology of the possible. the movement from the Newtonian world to the modern one is a transition from a universe in which life is impossible to one in which life has a place (Smolin 1997, in Taylor 2001, p. 84; emphasis added)

How Complex Are the New Ways of Knowing? This chapter is about new ways of knowing about the very complexity of real-world dynamics as the subject of study in our social sciences. This challenge of acquiring new ways of knowing, we think, demands for a reform of our habitual ways of thought. We really need to replace our common preferences in the general practice in scientific theory construction. From the above text on epistemology, we may derive that getting knowledgeable about our dynamic, complex world is inherently complex itself. This quest for knowing the complexity of real-world dynamics demands for a different methodology. Understanding of the very real dynamics of the complexity as part and parcel of this world may be linked with a critical realist approach to epistemology.17 This approach makes it acceptable to recognize the potential ‘working’ of hitherto unknown generative principles and mechanisms in the real(m). Ultimately, based

17  See e.g., for the discipline of economy, in Rosser (2004, p. 11), making reference to the publication by Lawson (1997) “Economics and Reality”; see also Archer (1995) and Byrne (1998) for a similar inspiration from the scientific realist approach, which is very much inspired by the work of Bhaskar.

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on a different methodology and this critical realist approach, we may better understand that “Our preference for simplicity, uniformity, and systematicity in general, is now not a matter of a substantive theory regarding the nature of the world, but one of search strategy – of cognitive methodology” (Rescher 1998, p. 62; emphasis added). This is essentially what new ways of thinking and knowing about the very complexity of reality is really about. In the preceding chapters, we sketched the struggle of escape from the old ways of thinking about the ‘old’ reality. We dealt with the questions “How does science relate to the real?” and the ontological problem “What is the reality of reality?” for science itself. Thereby we dis-covered a new kind of dynamic reality that went way beyond the taken-for-granted reality of ‘normal’ science. The new reality was about complex processes with hitherto unknown generative principles and mechanisms. In the first chapters of this book we have set the new agenda for the social sciences. In Chap. 5, we sketched the new ways of thinking for giving birth to the new science. These new ways of thinking in complexity can be considered as a foundation for a new, transdisciplinary approach within the field of social sciences. How, then, can we develop our ways of knowing within this new approach? Will the new ways of knowing be about the new subject of study for the social sciences? For sure it will be a knowing within the new transdisciplinary science of complexity. It is this new science of complexity that will be conceived to be simultaneously –– a science of transition; –– a science of new (states of) being through a process of becoming; and –– a generative science. Based on these different perspectives of the new science, we may develop a better, that is a more complex understanding of how to get knowledge about the real complexity of our world by new thinking in complexity. So, we first have to escape our common fallacies of thinking about the real and recognize our “natural inability to comprehend the dynamic complexities of life” (Chia 1998, p. 346); that is, the dynamic complexity of living reality (Chia 1998, p. 346). Only after such an escape we may become able to recognize and reflect on the danger of knowledge construction along the old lines of thinking and their repressive force in practice (Taylor 2001, p. 81; emphasis added; cf. Sandywell 1996, about the repression of reflection). The new science, then, may best be described as a science that focuses on describing, understanding and explaining potential new states of being through alternative processes of becoming, i.e., though processes of involution, evolution and revolution, as processes of transition and transformation and even of metamorphosis.

The Struggle of Escape Although there has been a growing awareness of the complexity of reality among scientists of different disciplines, it has not led to a common view of complexity and how to deal with complexity. As Stacey (2003) correctly notices, “There is as yet no single science of complexity but, rather, a number of different strands”

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(p. 44; emphasis added; cf. Morin 2007). It is therefore no surprise that, in agreement with Stacey’s observation, Elliott and Kiel (1997) notice that “there is still no generally agreed on definition of even the term ‘complexity’” (p. 64). Juarrero et al. (2007) make a similar observation and conclusion: “Everything about complexity is open to many interpretations” (p. xvii). Some scholars in disciplines ‘simply’ use the concept of complexity in a rather selective way. They still seem to take a reductive stance towards the complexity of real-world complexity. For Juarrero et  al. this means that they have “not accepted the complexity science whole” (Juarrero et al. (2007), p. xvii). We may conclude that it is really hard to know how to harness complexity in our viewing and indeed doing science! We may conclude as well that the challenge to develop an adequate view or science of complexity still seems a hardy perennial. It stands for a kind of liberation: see Fig. 8.2. There is ‘simply’ no single path for new thinking in complexity; not

Fig. 8.2  M. C. Escher’s “Liberation” (© 2010 The M.C. Escher Company B. V. – Baarn – Holland. All rights reserved)

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for science in general and not for social sciences in particular. The path within the disciplines itself seems too narrow a path to be successful. The alternative philosophical path, which is that of reflection about our viewing and doing science, seems too broad for approaching an adequate conclusion. The philosopher Churchman, in his ‘philosophy for complexity’, is quite open about the possibility of such a conclusion: “So if you sense that I seem approaching a conclusion and get as far away as possible, you sense correctly” (2008, p. 1). That gives not much hope for new thinking in complexity in practice. However, to give it a start, we can state that escaping old ways of thinking is a necessary condition for starting new ways of thinking: of thinking in complexity. To put it rather simple, we can state that the struggle of escape is for a large part the struggle of escaping “the general practice of scientific theory construction” (Rescher 1998, p. 61), a (general) practice that gives preference to 1 . one-dimensional rather than multidimensional modes of description 2. quantitative rather than qualitative characterizations, 3. lower- rather than higher-order polynomials, 4. linear rather than nonlinear differential equations How, then, can we bridge the gap in our understanding of complexity? We may refer, again, to Table 6.1 with the many differences between old and new ways of thinking in (social) science. This table shows the multidimensionality of new ways of thinking and the potential power of escaping the old ways of thinking. Altogether, this gives a nice but also a rather deceptive description of our viewing and doing science as usual, with the inherent imprisonment of the common construction of meaning. In the field of complexity science or thinking in complexity one meets a lot of different views about complexity. In literature with a focus on complexity, we may read rather different approaches for escaping this imprisonment of meaning and the common ways of delivering reality by scientists. Most of these approaches start from a single discipline. In practice, for the invention of a new science with a new way of thinking and knowing about the real(m), that means a lot of confusion in the field of complexity science and of thinking in complexity in the different fields of science. There is still no accepted view of how to escape and formulate an adequate approach to the problem of complexity in the field of our science. Some argue simply that there is not a science of complexity yet. Some openly state that we are still seeking for “a new conceptual framework that does not exist yet” (Kauffman 1993, p. 185; cf. Morin 2007). It is also the case that not many authors in the field of the social sciences and humanities take a serious, transdisciplinary approach for their thinking in complexity. We can conclude that a transdisciplinary approach is not a dominant way of thinking about the topic of complexity in these separate disciplines. How in the world, then, can we learn to know about the dynamic complexities of life? In what way can we view this living reality of life by new ways of knowing? Will it be the complexity of the living reality that determines these new ways of

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knowing, or do we have to increase the complexity of our knowing itself?18 We think it will be both sides of the coin that may increase our knowledge about the inherently complex real(m). What seems clear is that both sides will enlarge our worldview and the real(m) as subject of study for our transdisciplinary approach of science. Thinking in complexity for such extended, more complex knowing about the real(m) is very different from what has been described as “simplicity thinking”, in a real sense. It demands for a new kind of method and methodology of viewing and doing (social) science.19 It may be clear as well that, to be able to start thinking in complexity, we ‘really’ need to escape from the blind alleys of our science (Vygotsky 1997), of the learned incapacities of our (isolated) disciplines (Wertsch 1998) and from the dear old habits of thought (Dennett 2003). We may fully realize that all of these have their inherent limits, i.e., for describing, understanding and explaining the complex living reality we live in; a reality that is different from the assumed reality, or the reality that is delivered by the science-as-we-know-it. We may illustrate this state of art by an example about evolution, from Kauffman’s book “At home in the universe” (Kauffman 1995b, p. 163): see the quote below in Box 8.2. Capra et al. (2007) describe this living reality of our world as a web-like world. What is of importance here is that they notice that “The appreciation of a web-like world also leads us to acknowledge the ontological creativity of the entire world” (Capra et al. (2007), p. xi; emphasis added). We wonder, then, if we, in the end, may become better able to describe, understand and become really explanatory about this ontological creativity in our viewing and doing science. We may, then, be very much in need for a different method and methodology for our ways of viewing and doing science, to deal with this so-called ‘ontological creativity’!

Box 8.2  About Darwinian Evolution Almost 140 years after Darwin’s seminal book, we do not understand the powers and limitations of natural selection,20 we do not know what kinds of complex systems can be assembled by an evolutionary process, and we do not even begin to understand how selection and self-organization work together to create the splendor of a summer afternoon in an Alpine meadow flooded with flowers, insects, worms, soil, other animals and humans, making our worlds together.

18  This seems very much the problem of the ontological complicity for scientists, doing science, referred to above (Wacquant, in Archer 2007, p. 41). 19  cf. Vygotsky on ‘solving’ the crisis of psychology in his day. 20  The understanding of natural selection was also a problem for scholars around Darwin, like his famous friend Lyell, the geologist, who was not able to grasp the concept of natural selection, even after repeated explanation.

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Finding an Answer to the Methodological Challenge The methodological challenge for new thinking in complexity is to find an answer to new questions about the rather unexpected complexity of reality as the subject of study and develop an epistemic framework for developing knowledge about what may be described as ‘the ontological creativity of the real-world dynamics’ (see above). To do so, we have to step outside the common ways of viewing and doing science. Again, we may reiterate that this is not an easy step to make. Ultimately, it implies a rethinking of the structure of science (van Benthem 2002, p. 87; emphasis added); that is by science itself and through rethinking of our role as scientists. This rethinking is only possible by reinvention, which is based on the very struggle of escape from the old structure. Doing so, we may develop the causal, explanatory power that is needed to explain the (plural) generative, emergent powers of transient, causally generative processes in the real(m) (see Archer 1995, pp. 192, 194). This epistemic framework may become the foundation for the new science that is simultaneously a science of transition, a science of new (states of) being through a process of becoming; and a generative science. The new science may be able to deal with the phenomena of transition, qualitative transformation and metamorphosis, as phenomena evolving over time, opening up new avenues for understanding: that is, of alternative “ranges of possibilities” (Rescher 1998, p. 55) and new, unexpected ‘spaces of possibility’ (Davis and Sumara 2006), within an enlarged space of the possible within a new ‘world of the possible’ (Kauffman 1993). Based on the new notions for a new science, we may become deeply aware that “human knowledge, having limits, has no borders or frontiers” (Cilliers; italics not added here).21 This lack of borders or frontiers embodies our real hope for the future of the new science as becoming very much part of the future of our social sciences and humanities. All of this rethinking of the very structure of science, conceived as a kind of reinvention of science, may lead to the development and use of a different language to express the new thinking in complexity about the real(m); that is, the fundamental ontological creativity of the world. The new language will be constitutive of a new science that can deal with the complexity of real-world complexity, with its inherent real world dynamics. Actually, we may desperately need a new language as a tool of thought for this new thinking in complexity about the new world; a tool that is a necessary tool and a necessary condition for the invention of a new science about a new kind of world: as ‘a world of the possible’ (Kauffman 1993). The new science may foster the complex process of “making our way through this world” (cf. Archer 2007), by fostering human reflexivity as a fundamental precondition for this.

 Stressed by Cilliers, 2007, in Capra et al. 2007, p. viii (italics in original)

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New Language For developing new knowing about a new reality, we also need a new language based on new thinking in complexity. We consider language as a tool of thought for this new knowing (cf. Vygotsky 1997a, Vol. 3, p. 281); a language that is able to open up a new space of thinking and to open up the causally generative, explanatory power for a new social science. In the next two chapters we go deeper into this by developing a new concept of interaction and an extended causal framework; a new concept and a new framework that goes beyond the linear. This may be illustrated by an example of the new vocabulary in use in these chapters: see Box 8.3. It shows nicely the increasing complication of language use that is needed for describing the real-world complexity with its real-world dynamics as the subject of study in the real(m). Actually, this is only still a simple illustration of the more extended language that is needed for description, understanding and explanation of the complexity involved in the new science. It is very much the new language that is needed for opening new ways of seeing and thinking (cf. Wittgenstein, in Fleener 2002): not only for philosophy but for science as well! It may be considered as a methodological tool that can be used simultaneously for decoding reality and for coding reality anew in a creative way (cf. Pinar, in Jardine et al. 2006, p. x). It is only through the use of new language that we may deal with the concepts of real-world dynamics like self-organization, dynamic complexity, emergence, spontaneous order, order out of chaos, fitness landscape, Butterfly-effect, the so-called ‘Matthew effect’ and the hitherto unknown ‘Comenius effect’ (in education22), as causal effects over time, the interdependent concepts of connectivity, interactivity, generativity, etc. They may develop into a

Box  8.3  Example of the New Language About the Real Complexity of Interaction Interaction Interaction within relationships Dynamics of interaction within relationships Reciprocal dynamics of interaction within relationships Reciprocal causal dynamics of interaction within reciprocal relationships Reciprocal causal dynamics of interaction within reciprocal causal relationships Reciprocal causal dynamics of interaction within dynamic causal loops of reciprocal causal relationships

 Also known, for the more general case, as the Jörg-effect!

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new vocabulary and a new terminology, connected with the new framework, making use of the transdisciplinary, integrative principles and generative mechanisms that will be developed in the next two chapters. This new vocabulary of the new framework, as we think, extends the frontiers of our science. All of this may also demonstrate why there is not a conceptual framework of the complex tapestry of life yet (see Kauffman 1993, p. 185). The question that has remained unanswered still is “What is the weave?” (Kauffman 1993, p. 185) Kauffman openly recognizes that “no one yet knows” (Kauffman 1993, p. 185). We may therefore start to realize that we, so far, really have to face “our inherently limited epistemic possibilities” (Juarrero et al. 2007, p. viii). This is also the central tenet of Morin’s contribution to the state of art of thinking in complexity (e.g., Morin 2007). It may be stated here, right away, that we fully agree with the recognition of this state of art in the field. Until now, we have put great effort to show that it takes many steps to enter the new framework and develop the new vocabulary based on new thinking in complexity. We also underscore the basic epistemological difficulty of a new science, as phrased nicely by Juarrero et  al.: “From an epistemological angle, complexity thinking clearly points to the limits of our knowledge of the ­living” (2007, p. viii; emphasis added). This statement can be convincingly illustrated by the example of Kauffman (1993), in Box 8.2 above. Altogether, it means not only the acknowledgement of the ontological creativity of reality, by grasping the inexhaustibly complex realities of interconnectedness in nature but also of finding the complex and tortuous scientific path for describing, understanding and explaining the very complexity of this new kind of reality.

Chapter 9

An Introduction to the Chaps. 10–12

Indeed, the dominant way of scientific thinking is so much a particular, analytic view of mechanism, laws and causality that to suggest that complex systems may develop and operate in a different way may sound at first like an attack on science itself (Clancey 1997, p. 233; emphasis added)

The Art and Practice of Building a New Science – A Transdisciplinary Approach The last part of this book is about the art and practice of building a new science of complexity that is based on the rethinking of the core concepts in use in the social sciences: that is, (1) the concepts of interaction, (2) of causality and (3) the unit of study. It will be shown how this rethinking demands for a kind of relearning, which is also implying a kind of unlearning of the use of the old concepts in our viewing and doing science. The new science will follow a transdisciplinary approach that goes beyond the separate disciplines but will be of real use for all of the disciplines. We regard this approach as a superior manner of scientific understanding the world. Although we recognize that the world may not change with the adoption of this new approach, we strongly believe that the scientists who are viewing and doing social science will afterwards work in a different world (see Kuhn 1970, p. 121). We may speak then about a genuinely transdisciplinary paradigm for the social sciences, for the twentyfirst century (Luhmann 1995, p. xxii). The building of a new science, with the shift of paradigm as a necessary condition for it, is inspired by this mission for creating a different world to work in as a social scientist. In the next chapters we try to make a link between the fundamental and the practical: the fundamental of what thinking and knowing in and about complexity may actually be and the practical, of understanding and explaining how complexity manifests itself in practice, in the real world. For this, we focus on the practical of the development of tools and a new language with a new vocabulary, a new terminology and a new kind of grammar that is needed for “the contemporary change from

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simplicity to complexity” in the description, understanding and explanation of complexity of reality (see Najmanovich 2007, p. 99). We may bring forth such a change from simplicity to complexity by unifying the three perspectives on complexity, mentioned before: 1 . complexity as a new method of thought, 2. as a new worldview and 3. as a new science. We need to escape the confusion brought about by what Morin (2007) has described as “the illusion that complexity is a philosophical problem and not a scientific one” (p. 24; emphasis added). So, the unifying change we want to bring about in the new science of complexity may be viewed as a paradigmatic change. For we think that it is only though such a fundamental change that we may grasp the complex notion of complexity for use in practice: i.e., for knowing how to turn the hitherto unknown underlying dynamics of dynamic complexity into effective complexity, to show how complexity can be self-potentiating indeed, as a fact (Rescher 1998, p. 28). It is a dynamics that thrives on interaction, which is fundamentally a kind of relational interaction. It is a dynamics of interaction between the parts that gives meaning to the whole that is the key factor in this complex process of self-potentiating. We strongly believe that Sotolongo (2007) correctly emphasizes “the dynamical and processual nature of these interactions” (p. 125). We think this processual nature of interaction has been misunderstood for too long. It was Lev Vygotsky and Mary Parker Follett who showed already this very nature of relational interaction as a process with shaping forces exerted on the entities as partners in this very processual interaction, to be taken as real. We may speak, then, of the constitutive ontological principle that is at work in the ontological creativity of the complex reality of our world. We better recognize that a “process is difficult to analyze because the fundamental units are elusive” (Wilson 1973, p. 300). By focusing on interaction as a process, rather than static categories, the complexity theory also makes it possible to consider different aspects of the process. It does this not only in the general sense of providing a language with which to talk about dynamic interactions but also specifically in relation to the importance of histories of interactions through time. We should become aware that without time, there is ‘simply’ not a process of emergence with emergent effects. So, for developing new thinking in complexity about real complexity as a building stone for a new science of complexity, we have to struggle to escape the Newtonian paradigm that has been blinding us for so long. The new thinking in complexity may afford a new epistemology and a new kind of methodology for the study of the dynamics of interaction, which is to be taken as the causal dynamics of interaction, i.e., of human interaction, with its processual and relational nature. Both the new way of knowing and the new methodology are essential for the development of new tools of thought, as fundamental elements of the new science. Through clarifying the new methodologies that are needed to study the processual nature of interactions and its effects over time and by recognizing the fundamentally

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causal and generative mechanisms and generative principles at work as “dynamic properties of the unknown generating system” (Takens, in Fernàndez et al. 2007, p. 181; emphasis added), we may be able to bring about change through understanding of how complexity really ‘works’ in the real(m). The real challenge, again, is to escape the danger of linear thinking in a nonlinear complex reality (Mainzer 2004). Consequently, the new path to follow will not be a linear path. We should better become aware that there is no simple road to follow. We better realize that “the road is made through walking” (Maldanado 1999, in Delgado Díaz 2007, p. 51; emphasis added). To deal with real complexity, we may as well realize that we need to face the end of certainty. This implies that to escape the contradictions and inadequacies of a rather deceptive certainty, we may better take the advice of Norbert Elias seriously: by throwing ourselves into the sea of uncertainty we can start to learn how to navigate in this very sea of uncertainty.1

The Agenda for a New Science Until now we have left pretty much open what complexity will actually be like in our new thinking in complexity for the social sciences. We only gave some steps of rethinking (in Chap. 4) and a sketch of the new elements of thinking for the new science (Table 6.1, in Chap. 6) and we formulated the link between complexity, the dynamics of complexity and the important notion of effective complexity for the use of complexity in and for practice. So, we think it is time to become more practical. To recap and anticipate the core of theorizing in the next chapters, we would like to stress that the two steps of rethinking, of rethinking interaction and rethinking causality, are the very building stones for the new concept of dynamic complexity. We can demonstrate that the concept of dynamic complexity has the potency of a generative concept. The next two chapters deal with these two topics of rethinking and how they connect for conceiving complexity as a fully generative concept. They are foundational for the new thinking in (dynamic) complexity as the building stone for a new science, with new ways of knowing about the complex reality of the real(m). In the preceding chapter we showed how the new ways of knowing are connected to the role of ontology and that of methodology of viewing and doing science. How, then, can we connect this tripartite relationship with the complexity of the real(m)? And how, then, can we connect with the dynamics of complexity and bring it to a fruitful concept of effective dynamic(s) (of) complexity for practice? What will be the path to follow for building the new science?

 We refer here to Ilya Prigogine (1997) with his book The End of Certainty and Norbert Elias (1991) with his book The Society of Individuals.

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All of these basic questions for a new science actually open up the problem of finding a new methodology for viewing and doing science. In the preceding Chap. 8 we saw how this new methodology has strong links with the problem of epistemology and ontology (see Fig. 8.1 in Chap. 8). Methodology, then, will be a different methodology for the new science, of what Vygotsky (1997a) has called ‘the methodology of reality’ (p. 255). We think this methodology can be the link between the fundamental and the practical. It will be the difference that makes a difference in viewing and doing science with a focus on the ‘real’ complexities of the new real(m); that is about the fact that complexity is self-potentiating (Rescher 1998, p. 28). For practice this means not only an enlarging of the worldview but also of viewing reality as a richer reality. Of course this has consequences for the practical, of doing science, by taking the real complexity in the real world seriously, as part of the ontological creativity of our world. We may describe this relation as connected to our own relation with the world as one of ‘ontological complicity’ (Wacquant 1992, p. 20); that is, as a fundamentally fluid kind of relation, implying a fluid state of both subject and object over time, in the history of our viewing and doing science. The new approach advocated in the next chapters will be based on new thinking in complexity, with the awareness that this new thinking may and should correspond with the (fluid) nature of the world as we may know it, by knowing the laws and regularities of nature properly2, in terms of “a correspondence between thinking and being in science” (see Vygotsky 1997, p. 256; cf. Dewey on this topic, in Archer 2007, p. 41). We may interpret this correspondence as linked to the ontological complicity, described above. The being of the object of study can only be grasped by a theorizing on becoming. This makes the being dependent on such theorizing, in a deep sense. We think this interpretation has a deep link as well with a science of being through becoming. The ultimate challenge of this book and of the next chapters in particular, is to reframe our understanding of the world by rethinking the structure and modus operandi of science-as-we-know-it and turn it into a new science (see van Benthem 2002, p. 87, and Rip 2002, p. 100). This reframing implies a kind of reform of thought (Morin 2001). The need for such a reform is sketched in the preceding, fundamental part of this book. This reform of thought and understanding of the world is to be taken as opening and foundational for a different, transdisciplinary (TD) approach on the study of the very complexity in the real(m), with its supposed actual power of self-potentiating as the main feature. It is this very feature that makes the concept of complexity so important for our viewing and doing; that is, in shaping the future of our social sciences and humanities. The new TD approach connects the separate disciplines with the general view about science and its modus operandi, in terms of a general science as “a system of defining laws, principles and facts” (see Vygotsky 1997, pp. 256–257). It does so by

See Vygotsky (1997, p. 256), referring to the writings of Engels (1925/1978). We prefer regularities above laws of nature because laws are too much connected with modernity of the science-aswe-know-it with its ‘rhetoric of simplicity’: that of the straight line (Najmanovich 2007, p. 95).

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A Programmatic View for a TD Approach Fig. 9.1  The link between a TD approach and the ­separate fields of science

141 Transdisciplinary approach

Natural sciences

Social sciences & humanities

clarifying the role of the new elements of thinking for the description, understanding and explanation of complexity of reality, as conceived and manifested in the diffe­ rent scientific realms of our disciplines (cf. Ruurlo 2006). In turn, the description, understanding and explanation of complexity of reality within a single discipline may contribute to a more general level of description, understanding and explanation of complexity of the whole of reality and the real(m). This relationship between the TD approach and the separate fields of science and their separate disciplines is visualized in Fig. 9.1 above.

A Programmatic View for a TD Approach There are black holes in every totality – blind spots, zones of shadow, and ruptures (Morin 2008, p. 103)

Our new science is linking our way of seeing and thinking in complexity with the very rich notion of evolution that is complex in itself. This being the case because the idea of evolution “unifies the realm of life, meaning, and purpose with the real of space and time, cause and effect, mechanism and physical law” (Dennett 1995, p. 21). In literatures on the topic of complexity, one may simply discern that until now, “there is no consensus on the exact meaning of ‘complexity’” (Lee 2004, p. 110). The different views on complexity only seem to share the same method and/or methodology. Actually the state of art in the field of complexity is such that most views of complexity are pretty much standing on their own feet and have an epistemological stance, that seems not very much aware of itself. It is known that it may be a perennial problem for a scientist to situate oneself outside of one’s own epistemological stance3 (cf. Vygotsky 1997, p. 266). Dennett (1995) describes this fundamental position for science and scientists in general as follows: Actually, this seems like the core message of Kuhn (1970) in his book about the structure of scientific revolutions.

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[But] there is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination (p. 21; emphasis added)

In line with these kind of thoughts about this perennial problem indeed, one may conclude that it is hard to make a distinction between a methodological and an empirical problem, i.e., between the complexity problem and the problem for complexity, which is for thinking in complexity in general. It is for this reason that we would like to stress the new method for viewing and doing science and the new kind of methodology that is needed for new thinking in complexity for the social sciences and the study of complexity in the real(m). What is really needed for harnessing complexity of real-world complexity is a new methodological basis for the new science, to enable “a solid grounding of simplicity and systematicity in dealing with complexity” (Rescher 1998, p. 61). It seems a basic truth that, in defining the world and by reducing its complexity, we come to grasp it (Akkerman 2006, p. 91). However, this may and should be done without unduly reducing complexity to simplicity for doing science in practice, by not being aware of “the limited nature of categories and perspectives created in defining the world” (Akkerman 2006, p. 89). Instead, we better try to show how complexity may evolve from simple notions like that of interaction within causal loops and their potential, self-enhanced loop effects (see, e.g. Hofstadter 2007; Hayduk 1987, 1996). By taking all of the above elaborations on complexity and thinking in complexity into account, we may be able to critically regard the different views on complexity that are abundant in the fields of natural and social sciences. What they actually miss is the connection between complexity and causality and the epistemological consequences of this natural connection. The blinding of paradigms seemed too powerful to see this as the key for new thinking in complexity. Only Morin (2007) seemed to have become aware of this in his more recent work. He based his view on the work of Maruyama, who expressed the notion of ‘deviation-amplifying mutual causal processes”, conceiving of “processes of mutual causal relationships that amplify an insignificant or accidental initial kick” in his work (Maruyama 1962, p. 164; see also Buckley 1967, p. 59). The significance of his work was not fully recognized. Maruyama himself seemed not reflective and convincing enough concerning his own ideas, to have the impact on the social sciences as might have been expected. As far as we know, he did not make a connection with those people who developed the causal framework in the 1960s and 1970s of the last century.4 So, his work did not really grow into a source for new thinking about the complex role of causality in the field of methodology in the social sciences. He did not make the connection with a view about causality that really complexifies causality and the inherently causal dynamics involved in causality as a process with causes and effects, evolving over time. That is, causality in more dynamic, processual terms,

Only Walter Buckley (1967) referred to him in a positive way without fully recognizing the potential of his work for complexity (see pp. 59–61).

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linked with causal loops and their potential nonlinear total effects over time. He did not recognize that this new thinking was desperately needed for new thinking about the complexity and the ontological creativity of reality.5 The Newtonian paradigm and its effects seemed still too strong and were dominating the fields of concern in the social sciences. So, the trivialization of causality and therefore of reality, continued. No link could be made with self-generating networks, consisting in causal loops of reciprocal relationships, which are ‘productive’ of ‘bootstrapping’ processes with potential nonlinear ‘bootstrapping’ effects as self-enhanced causal loop effects, mentioned above (Hayduk 1987, 1996). Causes produce effects that are necessary for their own causation (Morin 2007, p. 14)

A Short Preview In the next chapters, we present a view that can be regarded as synthesizing the three views of complexity mentioned above: complexity as a method of thought, as a worldview and as a science. The new thinking in complexity takes complexity both in terms of the variables or elements and in their connection with interaction. These elements may be put and analysed within a causal framework like Structural Equation Modelling (SEM). It is, then, possible to show a different kind of complexity: one that is founded in causality and causal interaction as dynamic processes involving chains of cause and effect. Within this new framework causality may be taken in terms of “Causes [that] produce effects that are necessary for their own causation” (Morin 2007, p. 14; emphasis added). From this general causal perspective we may understand the operating of entities within new units of study, like that of the ensemble (Grannott 1998), or the more complex ‘cyclical-helical unity’ (Valsiner 1998, p. 251); that is, in terms of complex processes in which these entities “generate the sources of their own transformation” (Fogel 1997, p. 223; emphasis added). In general, it may be the case that “Causes produce effects that are necessary for their own causation” (Morin 2007, p. 14). Such causes may be taken as productive of systems that tend to maintain themselves; that is, of a kind of so-called ‘recursively self-maintenant system’ (Bickhard 2009, p. 5; italics in original). We think that the new causal perspective may be viewed as a new, general entry and opening for “facing the real-world complexity” (Simon 1996, p. 28). Although Buckley recognized the relevance of Maruyama’s work and linked it with the notion of morphogenesis and morphostasis in nature (see p. 58), he kept being descriptive and not really explanatory about causality and networks of causal relations, in terms of how the nonlinear effects can be generated in these networks in the real(m).

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Fig. 9.2  M. C. Escher’s “Spirals” (© 2010 The M.C. Escher Company B. V. – Baarn – Holland. All rights reserved)

We may demonstrate that in the new causal framework continuous causes can produce non-gradual processes and potentially nonlinear effects over time. These are processes that take place within the new unit of reciprocal causal relationship, to be taken as causal loops, as part of a causal network that is dynamic itself over time, potentially expanding over time (Wolfram 2002) and with causal effects and patterns that are ‘produced’ in time within this dynamic unit. Complexity, then, can be defined in terms of the hitherto neglected causal dynamics of causal processes, with their hitherto unknown real, generative mechanisms and their total effects over time, ‘produced’ by a causal shaping force in causal relational interaction. This view of complexity, with its fundamentally generative, transitory nature, is very much like the building stone that Vygotsky (1987a, b) has recognized as being disdained by the builders of science in general and those of the social sciences in particular. It makes up the tapestry of life, of what may be described as “the transition from a [Newtonian] universe in which life is impossible to one in which life has a place” (Smolin 1997, p. 26, referred to in Taylor 2001, p. 84). This description is opening up a new conception of life as a kind of ‘self-organized being’ (see Taylor 2001, pp. 85, 87, 90, thereby referring to Kant and Hegel). The key is in the very process of generating through processual (causal) interaction within reciprocal relations, as a causal dynamic that is complexly constitutive in systems; in systems that have “the power to generate themselves” (Kauffman 1995b, p. 274). From this we may derive the recognition of the ontological principle that is ‘at work’ in the ontological creativity of complex reality; a principle, which affords the epistemological basis for our new thinking in complexity about this new reality.

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But taking this relationship between ontology and epistemology into account, we may and should realize that “No description of an absolute reality is possible” (Maturana and Varela 1980, p. 121, referred to in Taylor 2001, p. 89). We may better speak about the ontological complicity that is involved in the new study of complexity as part of real-world complexity. The question is which mathematical terms and models refer to ontological structures (Mainzer 2005, p. 46)

A New Methodology with New Tools of Thought We may wonder what does all of this thinking about the nature of causal interaction within reciprocal relationships mean for thinking about the method and methodology of viewing and doing science beyond the ‘science-as-usual’. In what way, then, can we go beyond description and become explanatory by using the causal framework for modelling interaction and the underlying dynamics of it as a dynamic self-generating process within the causal framework? What kind of path are we able to imagine and take for this task? How tortuous will this path be? Will it be possible to follow this path in our viewing and doing science? Again, we would like to stress here that it will be a kind of navigating in the sea of uncertainty. At the same time, we are of the opinion, that the navigating may offer a realistic escape from the Newtonian paradigm, thereby opening new spaces of the possible. It may also offer an escape from science as a science of description only and that of scientists being kind of ‘prisoners of description’ (Edelman and Tononi 2000). Ultimately, we may become more explanatory about the complexity of realworld complexity with its real-world dynamics, which is a causal dynamics indeed (Vygotsky 1978). It is a dynamics, thriving on interaction, which in turn is based on the interplay of impelling forces that may operate as causal shaping forces over time. Our very first aim in the next chapters is to go from a descriptive to a more explanatory approach of complexity. In Box 9.1, we have given a preliminary sketch of the path from a description of complex processes, described in literature, towards more increasing complexity, implying complexly self-realizing, self-organizing being as self-maintenant systems (Bickhard 2009). It shows a kind of historical overview as well as the strong intuitions that were already expressed there many decades ago by people who are only (more) recently recognized as a genius (Vygotsky) or as a prophet in their field (Follett, in Drucker et al. 1995). We think we may be optimistic in following them in their footsteps and find an adequate start for our navigating in the sea of uncertainty, by following the strong hints about navigating in their visionary work. Starting from this position, we may be heading towards a new science of complexity that is about complex processes of being, of systems and/or entities, through complexly becoming.

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Box 9.1  From Complex Processes Towards Self-Realizing Systems Self-generating (Follett 1924, 1995; Holland 1998) Self-creative (Fleener 2002) Self-creating (Follett 1924, 1995) Self-organizing (Halley and Winkler 2008, p. 12) Self-assembling (Halley and Winkler 2008, p. 12) Self-maintaining (Wimsatt, in Oyama et al. 2003, p. 232; Seibt 2009) Recursively self-maintaining interactions (Seibt 2009) Self-amplifying (Wimsatt, in Oyama et al. 2003, p. 223) Self-maintenant system (Bickhard, in T. Brown and L. Smith, eds. 2002) ↓ Autocatalytic processes (Holland 1998) Autocatalytic loops (Halley and Winkler 2008, p. 12) ↓ Causal framework with self-causation Causal framework with ongoing self-cause ↓ Self-enhanced causal loops Self-enhanced causal loop effects Generative structures (Wimsatt, in Oyama 2003, p. 220) ↓ Bootstrapping = Self-generative, self-sustaining, self-maintaining process ↓ Self-realizing systems Self-organizing being (Mainzer 2007, p. 91; Maturana and Varela 1980)

In the next chapters we hope to sketch the foundations of a new science of complexity with a focus on these very complex processes. We are aware that this can only be a preliminary foundation. The knowledge about real-world complexity is always a kind of provisional knowledge. We may for instance expand on the notion of complexity in terms of a more generative kind of complexity, which is linked to the generative order of the really complex world. This kind of complexity can therefore be called generative complexity. We will return to this in the next chapters, i.e., in Chap. 13.

Chapter 10

Rethinking Interaction

We are obliged to de-trivialize knowledge and our worldview (Morin 2007, p. 17; emphasis added)

Introduction In the next chapters we will show how the concepts of interaction, causality and complexity are linked. By linking these concepts beyond the ‘normal’ paths of ‘normal science’, we argue, it will be possible to build a new science by invention. Actually, we may do so by reinvention of these core concepts of our sciences in general and of the social sciences in particular. It should be stated in advance that the development of the new concepts of interaction, causality and complexity, as new tools for building a new science, should not be taken in their successive treatment of particular topics but “to determine them in reference to one another”, as a unity (see Luhmann 1995, p. xlix; italics in original; and Whitehead 1978, p. xii). We may call it a tripartite relationship. This means that every concept is implicated in the other! Although that may sound rather abstract, we will show how this can and should be done. In the next chapters, which may or should be read as a unity, we connect the concept of complexity to those of interaction and causality. In Fig. 10.1, we show how the three concepts, as fundamental building stones for the new science, are actually related in our theorizing. These building stones are fully interdependent and interwoven for the invention, or ‘building’, of a new science. It may be shown that causality is the key for becoming explanatory about (causal) interaction and complexity, in a sense. These concepts, taken together, are the tools of thought needed for conceptualizing new, complex concepts like dynamic, self-generating networks that are based on the dynamics of ‘bootstrapping’ processes of (human) interaction as a self-generating or self-producing process within reciprocal relationships; bootstrapping processes in which causes produce effects in and through (human) interaction that are necessary for their own causation (see Morin 2007, p. 14). The causal mechanisms, responsible for these effects, are considered as potentially generative mechanisms, explaining the possible ‘working’ of bootstrapping processes in practice. The total effects that

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_10, © Springer Science+Business Media B.V. 2011

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Fig. 10.1  The concepts of interaction, causality and complexity in their dynamic tripartite relationship

interaction

causality

complexity

may be engendered through these generative mechanisms may be potentially nonlinear effects, for example the (causal) Matthew and the causal, hitherto unknown, ‘Comenius effect’. Both nonlinear effects are of utmost importance for social forms of education, like cooperation through social interaction within relationships but are still not recognized as operating in such forms and even less understood so. For us, these effects are part of the real-world dynamics of a nonlinear complexity of reality (cf. Mainzer 2004/2007). For thinking about all of this we need a more expanded view of the common causal framework. What is needed is that it takes time into account, for time plays a decisive role in such causal processes producing nonlinear effects like the Matthew and Comenius effect. Actually, we try to link the notion of auto-catalysis as an essentially generative process and that of bootstrapping as a generative process of mutual causal dynamics. We view these processes as to be modelled within the causal framework, dealing with causal interaction within causal relationships, to be conceived as relational (causal) interaction within causal loops. To enable this, we need a different notion of causality and of the mechanisms that play a role in the notion of interaction, conceived as causal interaction. We return to this topic in the next chapter.

Interaction The notion of interaction is rather new in the history of our sciences (Starobinski 2003). In the field of physics, interaction has often been described in Newtonian terms of action and reaction. The same holds true for psychology. An adequate concept of interaction has not been developed in the social sciences yet. Neither an adequate theory of (human) interaction has so far been developed (see Mercer 1996). It is, therefore, no surprise that Bates et al. (1998), in the Companion of Cognitive Science, put the question “what will a good theory of interaction look like when it arrives?” (p. 590). But to develop such a theory we need some clarification about the concept of interaction. The concept of interaction is itself still in need for clarity. This seems also to be the case for the concept, as described in the different dictionaries available. In the Collins Cobuild dictionary, for instance, interaction of people is defined in terms of communication but differently for things: “When one thing interacts

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with another or two things interact, the two things affect each other’s behaviour or condition.” In an English (short Oxford) dictionary one finds (reciprocal) interaction circumscribed as “action or influence of persons or things on each other.” The last description clearly implies influence and the concomitant effects one may have on another in interaction (see also Webster’s dictionary). This, however, is no common knowledge for (educational) psychology (cf. Magnusson and Stattin 1998). It is this (last) description that will be of use for our theorizing on interaction. As we read Vygotsky about the causal dynamics of interaction, we think this is the very focus of Vygotsky’s work (e.g., in Vygotsky 1978). This makes his work so distinctive from others in the field of learning and development (e.g., compared with Piaget). It enabled him to escape the trap of functionalism and constructivism as a way of explaining learning and developmental processes through interaction. It may be stated that an adequate process-view of interaction was hampered by the rationalist-objective view (Magnusson and Stattin 1998). We are of the opinion that a good theory of (human) interaction will not arrive naturally but only through invention, by a reform of thought; that is, by new thinking. For this process of invention through new thinking, we first have to break down, or unlearn, the old notions of mainstream thinking about interaction, i.e., the linear thinking about interaction. This is only the first step of reinvention of the concept of interaction. To go on, we need to step outside the common notions about the Newtonian paradigm, which are still dominating the field of social sciences. Actually, it may be shown that this very Newtonian paradigm is a kind of wrong version of the original way of thinking by Newton. After having done so, we may try to invent the common linear concept of interaction anew and turn it into a potentially nonlinear version. For this reinvention we need the causal framework. We may recognize that mainstream thinkers “do not reflect upon the underlying causal framework” (Stacey 2001, p. 29). There seems only an implicit theory of causality present in their thinking. Ralph Stacey shows that we need a different kind of causality; one that goes beyond the old version of causality. He makes a plea for a different causal framework, with a different notion of causality (Stacey 2001, p. 59). He links the notion of interaction with that of causality as follows: “This is a view of causality in which the future is under perpetual construction in the detail of interaction between entities” (Stacey 2001, p. 59; see also p. 60; emphasis added). This means a shift from a focus on cause to a focus on effect. We can link this new view of causality with processes that take place in a kind of recursive loop in which causes produce effects that are necessary for their own causation (see Morin 2007, p. 14). We may also conceive of this process in terms of ongoing self-cause. Causality, in our view, is directly linked with dynamic patterns of loops, or relationships. From this dynamic perspective, we may think of interaction within (human) relationships as “patterns of relating that are mutually causing themselves” (Stacey 2001, pp. 207–208; emphasis added). These processes that may start with small deviations may result into what Morin describes as ‘chain transformations’ (Morin 2007, p. 15). They may be linked with the nonlinear temporal processes, described by Maruyama (1962), as a kind of processes that lead to potentially nonlinear total causal effects over time: “processes of mutual causal relationships that amplify an insignificant or accidental initial kick” (p. 164). Ultimately, we may bring these notions together

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into dynamic networks of developmental (causal) relationships with potential complex reciprocal chain transformations as their concomitant effects. With these new basic concepts, we may build an adequate conception of dynamic self-generating networks with potential nonlinear bootstrapping processes and potential nonlinear effects over time. We may, then, show these kinds of nonlinear effects as examples of kinds of butterfly effects within the new causal framework. These are effects that may be of tremendous practical use for the practice of education, in which learners ‘bootstrap’ each other, fully engaged in relational interaction within mutual learning relationships in small (sub) communities of learning (cf. Bruner 1996, p. 21). So, we can conclude that we need not only to reinvent interaction but to reinvent causality as well. We may, then, connect interaction with mutual causation, as a form of generative (self-) causation and show the potentially nonlinear effects of it. To conceptualize such a process, we need to expand the causal framework in ‘normal’ use in the social sciences. We may turn it into a new framework that encompasses the nonlinearity of causality (cf. Mainzer 2004, p. 6). Then, we may be able to handle the complex nonlinearity of reality in an adequate way and escape the danger of linear thinking in a reality that is essentially a nonlinear complex reality (Mainzer 2004, p. 15).

Reinvention of Interaction Below we try to show how the concept of interaction can be reinvented: in theory and for practice. This is fully in line with our mission to link the fundamental with the practical. We start with memorizing the description of Follett (1924) we presented in Chap. 5 (see Box 10.1). Below we present a short version of it.

Box 10.1  Quote (shortened) from Mary Parker Follett (1924)1 In human relations, this is obvious: I never react to you but to you-plus-me; or to be more accurate, it is I-plus-you reacting to you-plus-me. “I” can never influence “you” because you have already influenced me; that is, in the very process of meeting, by the very process of meeting, we both become something different. On physiological, psychological and social levels the law holds good: response is always to a relating.

See Mary Parker Follett 1924, pp. 62–63; or in Drucker et al. 1995, p. 42 (emphasis added). Also retrievable from http://link.library.utoronto.ca/booksonline/digobject.cfm?Idno=99002019&CFI D=8316028&CFTOKEN=97408987#jpeg

1 

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Fig. 10.2  M. C. Escher’s “Whirlpools” (© 2010 The M.C. Escher Company B. V. – Baarn – Holland. All rights reserved)

From her description we may derive a conception of human interaction that is of use for an alternative theory of interaction, with a focus on human interaction. Our theory of interaction goes beyond the idea of communication and that of constructivism about human interaction. The core idea of Follett’s description is about influencing and about interaction as a process of interweaving in which the participants are not only influenced but also changed in and through the very process of interweaving in which they participate. This interweaving is directly related to the complexity involved: of complexus as that which is interwoven (Morin 2001): see picture of M.C. Escher above in Fig.  10.2. This picture shows nicely the complexity of a dynamic process of relating. For Follett (19952) it was clear that “The response is always to a relating” (p. 42; emphasis added). This description of human interaction is very close to a recent description given by Steven Rose (1997) on the role of the participants in interaction, which he describes as kind of weavers, weaving a web. By weaving this web, they are very much weaving themselves too! Such a complex process of weaving, which is very much a process of mutual weaving can be modelled as follows: see Fig. 10.3 below. What is of importance in this figure is the multidimensionality of the participants A and B, with their variable elements ait1 en bit1 at a specific point in time, in their complex interconnectedness: both between and among themselves internally. The figure also shows how the network may be expanded (below), as evolving over time. What is of importance here is that each of the participants may be considered to be both the weaver

Follett (1995) should be read as originally Follett 1924, in Drucker et al. 1995.

2 

152 Fig. 10.3  Two participants in their interaction as dynamic interweaving

10 Rethinking Interaction

A

B

a1t i

b1tj

a2t i

b2tj

a3t i

b3tj

a4ti

b4tj

anti

bmtj

and the (dynamic) patterns woven (see Rose 1997, p. 171). They generate selfchange through the dynamics of weaving that is influencing each other, within the dynamic network that is being woven over time. For Rose himself, this is the central message of his book (Rose 1997, p. 171). It is a complex message about the notion of complexity itself, to be taken as ‘complexus’: as that which is fundamentally interwoven (see also Morin’s thinking about complexity for the social sciences and the field of education). Similarly, we may take interaction as interaction that patterns itself, like conversation (see Stacey 2001, p. 144). This is an alternative view of interaction, which is opening a new avenue for understanding complexity in the scientific realms of our sciences. This notion of interaction within a web, of interaction between entities evolving over time, is also a fundamental part of the new thinking in complexity in this book, with its focus on the social sciences and humanities. Now, the complex description of human interaction as a process of dynamic interweaving may easily be connected with the notion of reciprocal influence and reciprocal effect and of self-generating as a mode of thought, by Mary Parker Follett (1995; see pp. 38, 44, 51) and that of bootstrapping as a self-generating and self-sustaining or self-maintaining process through reciprocal influences. She was (in 1924!) already very much aware that these notions meant “a new approach to the social sciences” (Follett 1995, p. 50). This approach is very much about creating “novelties” and takes the notion of progressive experience seriously (Follett 1995, p. 50). It is an approach that is based on the notion of auto-catalytic processes in the physical sciences (Follett 1995, p. 50). She views her method as a

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building stone for a new approach in the social sciences. In presenting this new method of approach for the social sciences, Follett was a real prophet, by being already transdisciplinary in her general approach of building the social sciences. Her approach for the social sciences was very much an ecological approach as well. Not surprisingly, she was very much on her own in her new thinking, in the twenties of the last century. This makes her distinctive of Vygotsky who, however, was a genius in his own way. Both were seeking for new building stones and a new method for the social sciences. For both these were very much the building stones that were disdained by the contemporary scholars of their time. But more importantly, both were very much trying to escape the ends-oriented approach of the social sciences in their time and focused very much on a fundamentally possibilityoriented approach of these sciences.

How to Go On? We may take a next step in new thinking in complexity for the social sciences by connecting this alternative theory of interaction with a different concept of causality. To do so, we need to take influence as causal influence and the effects on the two participants in human interaction as causal effects, to be taken as effected by impelling forces; these forces, in turn, should be taken as potentially shaping forces (Lincoln and Guba 1987). What is of importance here, is that time is put into the notion of interaction (cf. Follett 1995). The process of interweaving, then, becomes a process of dynamic causal interweaving of forces and effects of action, taking place over time within a causal network of (dynamic) evolving relationships (cf. Juarrero 1999, on the dynamics of action). In this dynamic network the causal effects are responsible for the causation of the evolving dynamic effects within the web. The causal effects are also constitutive of the strength of the causal relationships within the dynamic network. That turns the causal dynamics of weaving into a self-generating and self-maintaining process for the constituted network (web). The generative principle at work is “a principle that conceives the relation of whole-part mutual implication” (Morin 2007, p. 10; see also Chia 1998). This is a causally generative principle that is a new building principle for the new science of complexity; that is, not of a restricted but of a generalized complexity (Morin 2007). It shows how the tripartite relationship between interaction, causality and complexity is constituted in principle. It may be shown that this conception of the tripartite relationship may actually solve ‘the fundamental problem of complexity’. It is in line with Morin’s thinking that this fundamental problem may only be solved by complexifying instead of decomplexifying it (Morin 2007, p. 10). For him, it means that we have to go beyond the notion of a restricted complexity and better go towards a more extended notion of complexity: that of general complexity. In the next chapters, our new thinking in complexity focuses on the theoretical process of complexifying that is needed to ‘solve’ the fundamental problem of

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complexity. For this, we need an expanded version of the causal framework in use in the social sciences, which brings us to a rethinking of causality itself. This expansion makes it possible to connect the notion of self-organizing interaction with the notion of ongoing self-cause, as a way of amplifying small differences in iteration within self-generating causal networks. We hope to show how this may connect with the phenomena of ‘bootstrapping’ and other nonlinear processes and effects.

Chapter 11

Rethinking Causality

Those things whose causes are not perceived are still unknown and must be investigated, precisely because their causes are not perceived (Averroes,1 1126–1198 A.D.; emphasis added)

Introduction Rethinking is the central concern of this book. Not simply of single concepts but of central concepts in their fundamental interconnectedness. This kind of focus makes the topic that we address in this book complex indeed. The basic idea of our new thinking in complexity is that these concepts may not be that simple as often presupposed in viewing and doing science. Our mission is to build a new science with a focus on thinking in complexity to overcome the trivialization of the relationship of our sciences with the complexity of reality. This is the very complexity that we take as a nonlinear complexity of reality. To do so, we need to escape the danger of linear thinking, by recognizing “the seductiveness of this type of thinking” (Starobinski 2003, p. 265) and start to learn a new kind of thinking about a nonlinear, complex reality (Mainzer 2004, p. 1). In his book, Mainzer states clearly that the idea of mono-causality, as has been used in politics and history, is “a false and dangerous way of thinking” (Mainzer 2004, p. 11). This traditional mono-causal way of thinking escapes the need to take into account the complexity of “the real-world processes involving change and reciprocal causation” (Namboodiri et  al. 1975, p.  23; emphasis added). We think that only by taking this complexity of causal processes into account we may develop a more realist theory of the social sciences, with a different logic of explanation (cf. book of Archer 1995; Juarrero 1999, p. 5). We may, then, find better tools for analysis: tools that may help to dis-cover the ‘mutual regulation’ between ontology and methodology (Archer 1995, p. 27; see also p. 28). New thinking in causality may afford, then, the basic tools both for a 1

 In David R. Heise, 1975, Causal Analysis, p. 2.

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_11, © Springer Science+Business Media B.V. 2011

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more adequate social ontology and a better explanatory interdisciplinary methodology, as part of a theory of complex systems, for the analysis of the nonlinear causality of an inherently nonlinear, complex reality (cf. Mainzer 2004, pp. 7, 15). In this chapter we want to show how the expanding of the known causal framework of Structural Equation Modelling (SEM) can become foundational for a new transdisciplinary approach in viewing and doing science. Based on this new approach and with this tool of SEM, we will be able to address the topic of realworld dynamics of development and growth in the nonlinear complexity of reality more adequately.

New Thinking About Causality To start new thinking about causality, we must relinquish what Susan Oyama (1989) described as “the Central Dogma of one-way flow of causality” (p. 29). Although one-way causality can be recognized as ‘an inevitable category of causal apperception’, as Karl Jaspers noticed, he was also very much aware that “it (causality) does not exhaust life’s possibilities” (Jaspers 1963, p. 453). He (Jaspers) stated about the role of causality and causal relations the following: causal relations do not run only one way, but take reciprocal effect; they extend in this circular fashion so that they either build life up or as ‘circuli vitiosi’ foster a process of destruction (Jaspers 1963, p. 454; see fn. 99, in Starobinski 2003, p. 424; emphasis added)

He places the role of causality beyond the old line of demarcation between the living and the mechanical. The key for escaping the orthodoxy of this traditional dichotomy is lying in the use of the concept ‘wechselwirkung 2’ (action and reaction as reciprocal). It is hard to believe that Jaspers wrote this text almost a century ago 3 (in German)! Starobinski (2003), elaborating on Jaspers’s original way of thinking “that seems to foreshadow the more recent theories of self-organization 4” (p. 209) comes to the conclusion that “Causal thinking opens perspectives both exciting and fraught with difficulty” (Starobinski 2003, p. 210; emphasis added). This is a difficulty that, however, is neglected in most textbooks about the common causal framework. We, ourselves, have come to the preliminary conclusion that, to escape the dangerous way of linear thinking, we need to take a different path in our thinking about causality.

 This is hard to translate in English. It contains both the process (by ‘wechsel’ or exchange) and the effects (by ‘wirkung’ or force) in one single term. 3  Jaspers (1883–1969) work General Psychopathology was published in 1913. 4  Starobinski calls the book General Psychopathology “the only true ‘monument’ of twentiethcentury psychiatry” (p. 205). 2

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Namboodiri et al. (1975) describe how this thinking in causality has been derived from mathematics, in regard with “the use of the terms dependent and independent variables” (p. 20). They notice, however, that this use may be very misleading for the notion of causality: “… in a causal sense, X may affect Y and also Y may affect X” (Namboodiri et al. 1975, p. 20; emphasis added). More importantly, they have an open eye for the relationship between the causal models of reality and the real complexity of reality with its (complex) causal processes (see p. 21). But the most important remark they make is about the nature of these causal processes: It is obvious that such processes cannot be inferred from fixed characteristics of any ­number of samples. In the analysis of social relationships, we might further want to know how such structural changes would affect the character of the games which could be played and the interrelationships of the players (Namboodiri et al. 1975, p. 21; emphasis added)

So, we may conclude that we need to open our scientific minds to the dynamics of these structural changes. They may show up to be nonlinear in their causal effects. For the concept of causality this means that theorizing about the role of nonlinear causality in the real-world processes should be an essential part of the theory of complex systems, to make it possible to study and analyze for instance “the nonlinear causality of ecological systems in nature” (Mainzer 2004, p. 7). Based on our notion of a transdisciplinary approach, we would like to address the issue that nonlinear causality is also a basic concept for nonlinear thinking about the nonlinear real-world processes of a nonlinear, complex reality as the subject of study for the social sciences. Only then, we argue, we can more fully address the ontological creativity of reality (see above). This parallels the intrinsic creativity of nature (Solé and Goodwin 2000, p. 20) and the evolutionary ‘creativity’ of nature. All of this has consequences for the ways of knowing about this reality, including our knowledge about the human being as a potential nonlinear being (Stanley 2005, p. 143; emphasis added). The complexities involved demand not only for a more complex kind of description and understanding but also for an explanation of this nonlinear being. We may therefore better recognize and realize that in the real(m) of our inherently complex world there is no such thing as a linear human being. We need to de-trivialize our knowledge about the inherent complexity of the potential nonlinear being. We have to escape being the ‘prisoners of description’ in our viewing and doing science and become more explanatory about the complexities of life, with their underlying causal dynamics of processes of development (see Vygotsky 1978). Following the line of thinking about causality by Namboodiri et al. (1975), we may become aware of the need of adding complexities to a model to get a better idea of “the explanatory power of alternative models” (p. 19; emphasis added). Based on the elaborations we made above, we may start to learn to think more complexly about circular causality within loops of reciprocal relationships, which are part and parcel of causally interactive circular systems. We may think of entities and levels that are strongly connected, which cannot be separated or “neatly sealed

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off from each other” (in Juarrero 1999, p. 207) as entities, as a form of this ­so-called ‘circular causality’. Elias suggested circular causality to be “a kind of circular, paradoxical causality in which individuals form social relationships while being formed by them at the same time” (Stacey 2003, p. 43, referring to Norbert Elias and his view on human interaction and on social evolution; emphasis added). Solé and Goodwin (2000) give a nice, simple example of ants: of individual ants that respond to the field and change it (p. 150; emphasis added). The total causal effects that are being brought forth by the causal dynamics within this circular form of causality, may be described, understood and explained as so-called ‘self-enhanced loop effects’ (Hayduk 1996). This notion may turn our description of these causal processes, involved in the causal dynamics, into self-generative processes. It may be shown that these processes, in turn, can be linked with the concept of ‘bootstrapping’ processes that may have an important role in the description and understanding of self-generative, self-maintaining, self-realizing (complex) systems in nature. The new thinking in causality may be of use in building ‘a theory of network causality’ that goes beyond the notion of linear causality, as envisioned by Paul Weiss (1978), in his contribution about the nature of causality5 (p. 14; italics in original). To us it seems he was very right in noticing that such a theory “becomes increasingly indispensable” (Paul Weiss (1978), p. 14; emphasis added). The new thinking in causality may be considered and experienced as a tool of thought for a new kind of thinking in complexity: as a way of “tinkering at the edge of our own thinking” (see Jewett6 2005, p. 293). It may lead to a new language with a new terminology and a new vocabulary, which can be used as a better tool7 for explaining what Juarrero et  al. have described as “the ontological creativity of ­reality” (2007, p. xii). It may be stated here that in rethinking the notion of causality, we face the very limits of our knowledge. But, as we hope to convince the reader, it certainly will not be ‘the end of science’ (Horgan 1996). On the contrary! We actually take our new thinking in complexity about causality as a new beginning of our viewing and doing science. Instead of causality being part of the problem, which is constitutive of the problem of science, we hope that the new thinking in causality may be considered to be part of the ‘solution’. We think it is enabling for new thinking in complexity about the nonlinear complex reality. This new thinking for the social sciences will be the central element of the new transdisciplinary approach of these sciences. But, again, the path to be taken will be a complex, tortuous path.

 In the special book Psychology and Biology of Language and Thought, edited by George A. Miller and Elizabeth Lenneberg, with essays in honor of Eric Lenneberg; special, because it takes an interdisciplinary approach. 6  In Doll et al., 2005, referring to the struggle of escape, from old towards new thinking by Gregory Bateson, 1991, in “A sacred unity: Further steps to an ecology of mind”, ed. by R. Donaldson. New York: Harper Collins. 7  See e.g., Paul Weiss, 1978, p. 14, on the need to take care in the choice of language about causes and effects. 5

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Complexity of Causality In the next part of this chapter we would like to show that the fundamental problem of complexity in the social sciences has a direct link with the hardy perennial of causality and causal analysis in these sciences. Our focus is therefore on the role of causality in the social sciences. Of course, we cannot have the idea that we may ‘solve’ this fundamental problem of complexity in a straight way but we may give a different perspective about it and a different approach, which we have called the transdisciplinary approach. All of this demands for a rethinking: not only of a rethinking of causality but also of interaction. Only then we might be able to rethink complexity as foundational for this new approach and, ultimately, for building a new science that is based on this new approach. We will show the link between rethinking causality and the ‘results’ or ‘outcomes’ of all of the rethinking in the preceding chapters. Our focus is on ‘delivering’ a different reality, which is about the delivering of a nonlinear reality of causality by invention. In the end, it may be shown that reality and the real is not something to be delivered ‘simply’ by scientists but as something to be invented beyond our common ways of viewing and doing science. This was also the central message of Thomas Kuhn (1970) in his book about scientific revolutions in our history of the sciences. History has shown how different these inventions and constructions of causality and explanation may actually be in viewing and doing science (cf. Kennedy 2002, on the ‘reality’ of the atom; Saris 2009, on the ‘reality’ of the electron). For the social sciences we may refer to the reality of learning as being a historical invention and construction. It is for this reason that Buckley (1967) speaks about the “The problem of causality in social theory” (p. 66) and about ‘traditional causal analysis’ in the social sciences (p. 71). They are very much indicative of the science-as-usual in the social sciences; the science that Kuhn (1970) described as ‘normal science’ (p. 24, p. 52). It is this science that “does not aim at novelties of fact or theory” (Kuhn 1970, p. 52). This chapter of our book takes a different stance. It is very much about the topic of rethinking of causality from a historical perspective, to enable the delivery of a new reality: a reality that is based on the nonlinear complexity of reality. Our approach that describes and explains the underlying causal dynamics of reality may be viewed as a way of liquefying reality: that is, a liquefying that goes beyond the orthodoxy of the Newtonian, mechanistic worldview (cf. Zilsel 2000, about Darwin’s view as a way of liquefying reality). It was very much because of this (mechanistic) worldview, with its use of mechanistic principles, that scientists were actually not able “to develop a sophisticated method of dealing with complex, interactive systems” (Allen 2002, p. 44). Henceforth, we need to think about the method and the methodology in use for viewing and doing science beyond the usual. As a methodologist, we think, one needs to go beyond this mechanistic worldview to open up new ways of thinking about causality. Only then, we may be able to deal with these complex, interactive systems. We can conceive of these systems as

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s­ o-called ‘generative systems’ (Wimsatt 1999, p. 146). The processes taking place in these generative systems are to be conceived as generative processes (Morin 2005, p. 259). How then, can we become explanatory about these inherently complex processes and their effects over time in our nonlinear, complex reality? We think we desperately need new thinking in complexity about the real-world complexity. Such new thinking in complexity, as a way of an explanatory analysis about the real-world complexity, as fundamental of a fluid kind of reality, implies that the new reality can also and even better, be regarded as an effect, or an outcome of our fundamental analysis (cf. Kennedy 2002, pp. 36–37). Thinking in complexity along these lines shows that elaborations on the tripartite relationship of methodology, epistemology and ontology are very relevant here. For thinking in complexity about the notion and nature of causality has to do with the characteristics of knowing, of what is real and with the method in use in viewing and doing science.

A Short History of Causality in the Social Sciences Causality has always been a problematic concept in our history of the sciences. Even for Newton, it was not self-evident to use the concept of causality in his theory of gravity.8 Actually, he thought about forces of attraction between the planets. His notion of planets attracting one another in space by force was quite unusual. Although his view of gravitation about planets based itself on the notion of determinism, he knew very well that determinism did not mean that you could always predict the trajectories of the planets in space.9 The deterministic idea, with the wrong notion of linear causality and concomitant predictability, has had enormous impact on the Western view about reality. It gave way to the notion of the calculable (see e.g., Starobinski 2003) and a mechanistic, machine-like version of reality in the eighteenth and nineteenth centuries. The impact is still very much present, also in the field of the Social Sciences and Humanities. In the beginning of the twentieth century, for instance, ‘social physics’ seemed a real option for this field (see Wallerstein et al. 1996). However, analysis of processes of development in general and the causal analysis of processes in complex systems in particular, remained “a hardy perennial of social science” (Buckley 1967, p. 71). It is therefore no surprise that, in his book Sociology and Modern Systems Theory, he speaks about “The Problem of Causality in Social Theory” (Buckley 1967, p. 66). In an almost prophetic way, he warns that “a simple model of causation and correlation and its

 Actually there was a strong opposition to this view, i.e., by the Dutch scientist Huygens (see e.g., Kuhn 1970). 9  With three planets in interaction, it was not possible to predict these trajectories exactly over time (later in history this problem was known as the three-body problem in physics). 8

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methodology is woefully inadequate in the face of complex adaptive systems” (Buckley 1967, p. 67; emphasis added). Twenty years later, Lincoln and Guba (1987) are still wrestling with the very concept of causality itself, by reflecting on the viability of causality as a concept. In Chap. 8 of their book On Naturalistic Enquiry, they wonder if the concept of causality is dead (Lincoln and Guba 1987, p.  129). They notice that “there are fundamentally different and often conflicting views about the nature of causality” (Lincoln and Guba 1987, p. 132; emphasis added). Yet, this has not been a hindrance for the historical development of an elaborated causal framework for use in the social sciences; a framework that has been invented by different scholars, with different backgrounds. This shows the topic of causality as a fundamental interdisciplinary topic. It is our intention to show that the topic of the nature of causality is essentially a transdisciplinary topic of study.

The Introduction of the Causal Framework In the course of the twentieth century, a new causal framework of Structural Equation Modeling (SEM) has been developed for the field of the Social Sciences. Interestingly, a biologist, the geneticist Sewell Wright, made a start in the twenties and thirties of that century (see Wright 1986). He based his very first ideas on empirical research with genetics: that is, on the simple correlations between measured entities, as measured over time. These entities were fluid kinds of entities. Therefore, the correlations were also fluid in space (and also in time). This made the causal relationships fluid as well! Based on this fluid notion, he conceived of a so-called ‘fitness’ landscape, showing the relationships between organisms, with their genetic make up and their environment. His causal analysis was later known as ‘path analyses’ in the causal framework of the social sciences. Later, in the seventies of the twentieth century, Karl Jöreskog and Dag Sörbom picked up thinking about causal modelling from the common perspective of multivariate analysis and developed an important extension to structural analysis of relationships between so-called ‘latent variables’ in the causal networks of such variables. They developed a computer program for this kind of analysis, better known as LISREL, with different releases and versions of the user’s guide in the decades thereafter; e.g., Version VI, of 1986. They started with linear relationships (LISREL is an acronym for LInear Structural RELationships). They were quite successful with their new framework, in different fields of science like the field of the Social Sciences and Economy. In a way, their framework is very limiting, however. They do not include the notion of causal dynamics in their framework. There is no place for the role of time in the equations. This fact remains hidden in the LISREL-manuals by Jöreskog and Sörbom (e.g., 1993, in chapter 5). Although they deal with reciprocal relationships in their modelling of causal interaction between so-called ‘latent variables’, they do not give the formulae, which show the potential nonlinear total effects over time of such interactions within reciprocal relationships. Henceforth, it may be derived that there is still an unexplored part of causal

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modelling of reality (cf. Long 1987; Lincoln and Guba 1987). It is about a form of causality, which is not Newtonian (mechanistic) and that leaves out the ‘hydraulic dynamics’ involved (cf. Archer 2007). It does not take fixed entities (agents) as interacting over time. So, we may think of a new kind of causality. The new concept of causality is inspired by the alternative metaphor of causality as ‘mutual simultaneous shaping’ (Lincoln and Guba 1987, pp. 150–151; italics in original). This notion of shaping has the same causal power as that of propagating causal influence by force (Solé and Goodwin 2000, p. 163; cf. Stacey 2003, p. 314, on causal power within the dynamics of interaction). In the last ten years, a simple causal model has been developed that deals with the dynamics of (mutual) causal interaction between ‘latent’ causal variables and their time-dependent effects (Jörg 2004a, 2007). The modelling of this mutual interaction based itself on reciprocal (causal) influencing within reciprocal or mutual relations, conceived as circular chains with processes of causal influencing over time (cf. Buckley 1967, pp. 68–7010; see also Lincoln and Guba 1987). The causal dynamics of such interaction may be conceived as a self-reinforcing process of the causal interaction with potential non-linear effects in time, dependent on the strength of the influences the agents may exert on the other in the interaction. These total effects can be shown in a three-dimensional space, a ‘transition space’ that shows the amplification of changes in the (latent) variables involved and the potential nonlinear transitions of effects in the changes of these variables (see Holland 1998, p. 240). The whole idea of causality in this process of causal interaction with time taken into account needs some new thought about what may happen in the real.

How to Go On? With Lincoln and Guba (1987), who rightly questioned the viability of causality as a concept for the Social Sciences, we believe that shaping through influencing is a viable concept of causality. It implies the notion of an impelling force and that of causal power. These influences and forces may be viewed as real ‘producive’ of causal effects (Salmon 1993; see also Sandywell 1996, pp. 12–13), ‘producing’ their effects through impelling causal forces (see also the work of Bhaskar, and of Archer; cf. Van der Veer and Valsiner 1991, p. 213; Edelman 2004; Hofstadter 2007; Bechtel and Richardson 1993, on forces operating through causal influence). All of this implies a fundamental, generative way of producing these causal effects through impelling forces (cf. Vygotsky’s thinking about causal dynamics

10  On page 69 in his book, he refers to the discussion about this kind of modelling and the dominant view of the known cyberneticians in those days. The last group took purpose as a core concept in their thinking, which led to an ends-oriented approach. We return to this important discussion in Chap. 15.

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of interaction). The causal dynamics at hand are a kind of self-reinforcing process of causal interaction with potential non-linear effects in time, dependent on the strength of the influences one may exert on the other. These total effects can be shown in a three-dimensional space, a ‘transition space’ that shows the amplification of changes in the (latent) variables involved and the potential nonlinear transitions of effects in the changes of these variables (see Holland 1998, p. 240). The dynamics of causal interaction within dynamic reciprocal relationships is similar to the process of learners ‘bootstrapping’ each other in a small sub-community (in Bruner 1996, p. 21; see also Davis 2004, p. 152). These processes and their total effects over time can be conceived as to be linked to ‘real-time activities’ in education (Burbules 1993, p. 49).

Bootstrapping Within the Causal Framework To understand this process of ‘bootstrapping’ within the causal framework of SEM, we have to realize that the responses of the participants in their interaction are always to a relating, to a changing environment (cf. Follett 1924, in Drucker et al. 1995). This process has already been envisioned by Follett as a potential mathematical process of geometrical progression, speaking about the increment of the increment as the nature of this process (in Drucker et al. 1995, pp. 43, 50). She likens this process with the better known autocatalytic process in chemistry (Drucker et al. 1995, p. 50). She brings this notion even further (in 1924!), by linking this process with the concept of a self-creating and self-generating process, all for the sake of creating coherence (ibid., p. 51; emphasis added). So, many years later, we may link the original, innovative thoughts of Follett with those of Wimsatt (1999), about the processes of evolution and development. He speaks about ‘generative systems’. To explain their operating, he makes use of the hitherto unknown generative foundations of these systems as a dynamic evolutionary foundation (Wimsatt 1999, p. 147). He considers his own thinking about this basic topic of becoming (more) explanatory about evolution as a process that is based on generative structures. Thinking along this new line of thinking may be considered as foundational work that meets some (natural) resistance,11 as has been the case with the work of Brian Arthur in economics. It is no surprise that Wimsatt (1999) makes reference to the work of Brian Arthur in economics (p. 174, in fn. 6). This demonstrates that this foundational thinking is relevant for different disciplines. This is also our basic view in finding the new tools for new thinking: for use as building stones for a new science. For this reason, the concept of ‘bootstrapping’ as a self-generating and self-maintaining process, leading to ‘a self-creating coherence’, may be viewed as a real trans-disciplinary concept (see Follett, in Drucker et al. 1995, p. 51; emphasis added). That is, bootstrapping as a

 Cf. Kuhn (1970) on this resistance.

11

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new concept that can be used in different disciplines such as biology, economy and cognitive psychology (see e.g., Kauffman 1995b, p. 288; Koneko 2004; Edelman 1992, p. 119; Edelman 2004, pp. 116–117; Lotman 1990; Holland 1998; Van Geert 1991; Wimsatt 2007; Clark 2008). The use of causality in terms of a framework that deals with the causal dynamics of the real-world dynamics is a causality, which goes beyond determinism-as-usual. It is about a causality, which goes beyond that of a narrow notion of ‘social causation’ in terms of social physics (cf. Capra 2003), of a so-called ‘hydraulic dynamics’ (Archer 2007). Instead of determinism we may better speak about a process of determining, with different determinants, with outcomes that are fundamentally unpredictable. Our view of causal dynamics leaves open room for a different notion of causality, like that of a circular type of causality, which “is a form of (ongoing) selfcause” (Juarrero 1999, p. 5; italics in original): a type of causality that operates as kind of “self-generating activities which generate themselves” (Follett, in Drucker et  al. 1995, p. 51). We may think of such activities as operating in kind of selfgenerating networks. We may speak, then, as well of a process of a peculiar – and creative – circularity of self-cause (Juarrero 1999, p. 243; emphasis added). The notion of a creative kind of causality operating in the real, in networks of relating entities, is the corner stone for new thinking about causation for the social sciences. It goes beyond the common idea of a functional theory of causation. It is about a creative process of causation that can be linked with so-called ‘self-creating coherence’ (Follett, in Drucker et al. 1995, p. 51). This kind of self-creating coherence is thriving on functional relating in the networks of relating. In line with Follett’s thoughts about this relating for creating ‘novelties’, we think “it is impossible to overemphasize this point” (Drucker et al. 1995, p. 50). The very notion of circular causality within a network of relating within loops has the implication of so-called ‘multiplier effects’, like the ‘self-enhanced loop effect’ (Hayduk 1987, 1996). These kinds of effects, showing the causal power of interaction within dynamic loops, may be incorporated within the concept of a causal, autocatalytic network (cf. Stacey 2003, p. 314). It is an ongoing self-cause with self-enhanced loop effects within such networks that has the potential of ­‘producing’ nonlinear effects over time. Although this kind of producing is also based on interplay of forces, it is a way of creative producing that goes beyond the notion of determinism-as-usual. This is foundational for the new causal framework. Within the new framework, causality may be taken in terms of “Causes [that] produce effects that are necessary for their own causation” (Morin 2007, p. 14; emphasis added). With this new conception of causality, operating as a kind of generative, creative causality, we may better describe the functioning of complex (adaptive) systems as generative systems with self-creating coherence, thriving on interaction within networks of relating. In this interaction every response is always a response to a relating (Follett). This interaction can simultaneously be viewed as an interaction with an inherent interplay of forces. The functioning of the system as a generative system is a functioning “in which the product of the process is necessary for the process itself ” (Juarrero 1999, p. 5; emphasis added).

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Overcoming the Explanatory Gap The kind of rethinking of causality, as a building stone for a new science, with a general, trans-disciplinary approach, may bring us closer to the explanatory ideal: to discover the basic causal powers of the causal dynamics of interaction between entities as part of our real-world complexity (cf. Robert A. Wilson, in Valerie G. Hardcastle 1999, pp. 364; cf. Stacey 2003, p. 314). With Wimsatt (1999), we think these causal powers are fundamentally to be considered as a kind of ‘generative power’ (p. 160; emphasis added). These generative powers, we believe, are the very creative powers evolution is thriving on in the real. These powers can be linked to the hitherto unknown generative mechanisms operating in the real, as described in the work by the philosopher of science Roy Bhaskar (1986). He is delineating a critical realistic perspective in all of his work since. The explanatory ideal, then, may bring us to the modelling of fundamental, nonlinear concepts like ‘generativity’ and ‘bootstrapping’, as representing the (causal) dynamics and the exerted forces in interaction, which are involved in the real-world dynamics underlying real-world complexity; that is, of a nonlinear complex reality (see Mainzer 2004). We intend to show in the next part of this chapter the explanatory power of our rethinking and modelling of the causal dynamics of causality in such an interaction. It may be taken as a start for rethinking complexity, as being part and parcel of the fundamental and foundational causal dynamics involved in this interaction. Henceforth, this will be the path as delineated in the last part of this book. In this part, we will show how we can bridge the fundamental of thinking in complexity with the practical of dealing with complexity for practice, as for example in the field of learning and education (see Jörg 2009). This new path of new thinking will enable thinking about the link between complexity as a general concept and complexity as dynamic complexity. This linking may lead us to the notion of effective complexity as an important theoretical and empirical notion of new thinking in complexity for the social sciences. In doing so, we may escape the confusion in the field of complexity science, brought about by what Edgar Morin (2007) has described as “the illusion that complexity is a philosophical problem and not a scientific one” (p. 24; emphasis added). This confusion is linked to the use of metaphors only in this field for describing the reality of complexity in terms of real-world complexity. This is a use that prevents to go deeper and to develop a scientific approach of this scientific problem. Only then it will be possible to link the fundamental with the practical; that is the fundamental thinking about complexity with the complexity of practice. To turn the problem of complexity into a real scientific problem, we need to rethink our common ways of thinking and start to rethink complexity by rethinking both interaction and causality. We need to develop new concepts and a new language, with a new vocabulary, to describe and explain the new fluid reality with their underlying causal dynamics: see image of Guggenheim museum as a new kind of fluid reality. Only by taking such a fluid kind of reality seriously, we may open the possibility of a process of reinventing science and find the opportunity to

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become the visitors from a new future. We need to connect with fundamental new scientific concepts like those of ‘interactivity’, ‘connectivity’ and ‘generativity’, in terms of their degrees, such as the degree of interactivity etc, as fundamental ­characteristics for dynamic, generative processes. These are generative processes, which are based on generative principles, generative mechanisms and more ­elaborate notions such as ‘mutual entrainment’ (Juarrero 1999, pp. 115–116) and ‘generative entrenchment’ (Wimsatt 1999, 2007). What we need is to replace the linear version of causality and the causal framework as the ‘framework-as-usual’ and take the nonlinear version of the common causal framework in use for the social sciences. This step, we argue, will be essential for what may be called “the retooling of the social sciences and the new thinking in complexity for the social sciences and humanities”. In facing the fundamental problem of real-world complexity and the real-world dynamics underlying this complexity, we need to be able to become explanatory about the fundamentally generative nature of this complex reality. We intend to show this possibility of getting explanatory by use of the new, expanded version of the causal framework-as-usual. We may think of ‘solving’ of what may be called ‘the fundamental problem of complexity’ by addressing the basic question: Can causality, conceived as causal dynamics, of underlying processes, underlying reality as nonlinear complex reality, be taken as constitutive of the dynamic real-world complexity?

Picture 11.1  Frank Gehry’s Guggenheim Museum. Photo Myk Reeve

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We shall elaborate on this question and wonder if the causal dynamics of real-world complexi ty can be conceived of as self-patterning, self-generative, selfmaintaining processes. The new thinking in complexity goes beyond the descriptive approach in a very fundamental and foundational way, which enables a truly scientific approach of complexity. The new science is based on an analytic, explanatory, transdisciplinary approach. We may face, then, the real-world complexity as part and parcel of our new, fluid, (potentially) nonlinear, complex reality. This real-world complexity, we think, can better be linked to the fundamental complexities of real life. El-Hani and Pereira (1999) give a nice example of the very complexity of their subject of study and their elaboration on how to study this subject: A higher level of complexity, for example, living matter, differs from the preceding level, for example, inanimate matter, due not only to the interactions between its elements, but rather to a new mode of coordinating these interactions. Parts randomly gathered also display relational properties, but there is no higher-order system coordinating these relations (El-Hani and Pereira, in Hardcastle 1999, p. 342).

The subject of study of the new science may therefore be formulated as the generative, inherently causal dynamics of complexity of an entity that is not fixed but fluid, as a pattern evolving over time. This is a pattern that emerges from connectivity as much as a pattern that connects, as a way of dynamic patterning over time. It is the patterning of relationships, with their relational interaction, which is responsible for the self-generative and self-creative coherence of the entities to be studied (cf. Follett 1924). It is the very process of causal interaction within the dynamic patterning of causal relationships that is of importance here. This kind of new thinking puts time into the equations of development, as an important factor for the explanation of processes and their effects over time, produced by shaping forces. This preference for process thinking corresponds to that of Wesley Salmon (1993) who prefers to take processes rather than events as basic entities in his approach of causality12 (p. 155). He argues that “processes have much greater temporal duration” (Salmon 1993, p. 155). The analysis of these processes of relational interaction within patterns of interactive relationships within fundamental dynamic units as basic units for causal analysis is to be focused on how the causal dynamics of dynamic complexity may turn into a new, unexpected form of effective complexity in the real. The very dynamics involved is to be regarded as part of the dynamics of the real-world complexity of life, through evolutionary processes of selective generative synthesis. The study of the generative processes of synthesis for coherence, to be considered as self-generating, self-creating and self-sustaining processes within self-maintenant causal networks, goes way beyond the framework-as-usual. It replaces the dominating

12  He also argues, on p. 158 that Hume was not able to find that “causal processes constitute ­precisely the causal connections” as part of the causal structure of the world.

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ends-oriented approach, with its characteristic of closure, for a more opening, possibility-oriented approach of science. The causal, generative mechanisms, operating in generative systems, producing generative power, produced according to generative principles within a dynamic causal network, can be considered as fundamental tools for thinking in complexity. They are urgently needed for explaining the dynamic complexity in reality (like in cells; see Solé and Goodwin 2000, p. 64). This description corresponds nicely with Wimsatt’s description of amplifying through recurrent processes, which brings us closer to a nonlinear generative concept of causality in complex, interactive systems as well (Wimsatt 1999, p. 140). The new tools, described above, can ‘deliver’ a different kind of reality, which is a nonlinear complex reality; that is, a reality that is about fundamentally generative systems, with inherently generative causal dynamics, produced by a kind of fluid, generative structures and generative, fluid, entities. It is our deep conviction that the concepts of ‘causality’ and ‘generativity’, in their interconnectedness as core concepts of describing, understanding and explaining the real-world dynamics, are ultimately responsible, in terms of producing the real-world complexity. So, we ‘really’ need to understand these two core concepts of new thinking in complexity “to face complexity of the real-world dynamics” as the new subject of study in the social sciences (cf. Simon 1996, p. 28). All of this new thinking may lead to a different notion of reality and of new ways of knowing about this reality: a reality that is very much an emergent and expanding, or augmented reality (Luhmann 2002; Mainzer 2007, p. 14, p. 411, p. 434; emphasis added).

Extending the Causal Framework In the next part of this chapter, we focus on the more technical part of causal modelling within the causal framework. The aim is on extending this causal framework. We start with modelling causal interaction anew by taking time into account. It may be shown that the causal effects of interaction may increase over time in a potentially nonlinear way. This is congruent with the notion described by Follett (1924): that of human interaction as a process of exerting reciprocal influence on one another. Central to this is her view, expressed as a basic thought, that ‘reaction is always a reaction to a relating’ (Follett, in Drucker et al. 1995, p. 41); a relating that may evolve itself over time (Drucker et al. 1995, p. 51). So, both the response and the relation itself may vary over time. She viewed the process as a causal, self-sufficing process. It is a relational and interactive view of development that underlies Follett’s view of human interaction.13 This new conception of interaction,

13  See Eric Lenneberg’s view on this, which was described as “far ahead of his time”, in Wimsatt 1999, p. 173.

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to be taken as modelling human interaction, will bring us to the modelling of this type of interaction within the causal framework. This modelling shows the nonlinear effects of causal interaction, evolving over time. In her description of this process, which she took as a process of interweaving with reciprocal effects developing over time, as a form and law of geometric progression, Follett was amazingly prophetic.14 Concordia res parvae crescent15

Modelling Causal Interaction Causal interaction within a reciprocal relationship can be visualized in a causal framework in three ways: see Fig.  11.1. Figure 11.1a shows the most often used type of representation. It shows how one (latent) variable A has an effect on another (latent) variable B, whilst B in its turn has an effect on A. So this very well expresses the idea of reciprocity and circularity. Circularity means that a variable A influences a variable B, which in turn influences variable A, next the change in A induces a further change in B, et cetera. It is a form of self-cause but not as immediate self-cause, which is considered to be impossible (see Michael Tooley

a

ß1 A

B ß2

b

At1

ß1

Bt2

ß2

At3

ß1

Bt4

ß2

At5

ß1

…… etc.

c At

At+1

At+2

At+3

A

Bt

Bt+1

Bt+2

Bt+3

B

Fig. 11.1  Three different representations of a causal reciprocal relationship

 This is certainly the case, in comparison with the view of Eric Lenneberg (1974) as being far ahead of his time (see fn. 13 above). 15  “It is through unity (unitary power) that small things grow”. The historical message on a statue at a place along a Dutch dike at the edge of the river Lek. 14

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1993, p. 191). The causal interaction takes place within a reciprocal relationship. We intend to show that these relationships and their features “provide evidence for causal connections” (Tooley 1993, p. 191), that is: in the real. So circularity between variables in a causal model may make clear that the social phenomena, as represented by the model, are in a dynamic process. Another advantage of this type of representation is its simplicity. Especially models with relatively many variables connected by reciprocal relations become visually very complex when the two other types of representation are used (in Fig. 11.1b, c). A disadvantage of this way of representing a reciprocal relationship, however, is that it does not show that causality needs time for the exertion of impelling, shaping forces. Although any type of causality needs time, short as it may be, it is especially important for non-recursive models. The reason is that, because of its circularity, the total effect of the causal process within a reciprocal relation is actually constituted over time in a special way. The second representation in Fig. 11.1b turns the argument around. Here time is very well expressed but the idea of reciprocity is not visualized. In fact, only this representation should be used if the researcher can make use of a longitudinal database; that is data that are periodically gathered over a long period. This makes it possible to calculate for each time interval the effect-parameters, indicating the direct effect of a variable A on another variable B during that particular time period. This may be an important elaboration of the model, as this effect may change over time. This b-type of representation also makes clear that it is important to choose the right time interval for measuring A and B. Some causal effects need more time to mature than other ones. So, if we take the interval too short, the effect may not yet have matured, whereas if we take it too long it may have partially faded away (Bollen 1989). This type of representation also very well expresses that variable A at time 1 is not the same as it is at time 2. So, this presentation of causal interaction over time stresses that the variables are developing over time themselves. The third representation, the one in Fig. 11.1c, has the same qualities as the one in Fig.  11.1b. The only difference is that it shows better that, starting at a given point in time, there are two causal chains instead of one. This implies that if we want to intervene in a reciprocal causal mechanism, we either may start with A or with B. This may be an advantage when a causal model is used in public policy or in strategic management. In all three representations the b’s are taken as fixed. This, of course, needs not be the case in practice (cf. Bollen 1989, p. 3).

Causal Effects over Time From an interpretative point of view a reciprocal causal relation between two ­variables A and B and its effects are complex. Actually, three different components are involved in producing the total effect of one variable A on another variable B: (a) a direct effect of variable A on B and of B on A, (b) an effect of A or B on itself, the so called self-effect and

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(c) a circular effect, or reciprocal effect, which is the effect of a variable A on B, respectively of the variable B on A, after the circular mechanism has done its shaping ‘work’ in time. We will firstly scrutinize the characteristics these different components have. Ad a. Direct effect: The direct effects of variable A on B and of B on A are to be represented by the parameters b1 and b2. In this context a direct effect means the effect of a variable A on B (or of variable B on A) without any intervening variable that transmits that effect. These effects are regularly non-symmetric. Compared to the two other effects, the direct effect operates in a narrow span of time. Ad b. Self-effect: The self-effect is the effect of a variable on itself via the feedback mechanism, after an infinite number of cycles. A cycle is a causal chain going from one (latent) variable, passing over some other (latent) variable to the original (latent) variable (see Jöreskog & Sörbom 1986, p. III.93). In this very process of an ongoing cycle, the effect of variable A on B is multiplied by the effect of B on A. Therefore, the self-effect indicates the rate of change in a variable over time. It is calculated by multiplying the direct effects involved, i.e., the linear coefficients b1 and b2, cycle after cycle, leading to an infinite geometric series of products (Jöreskog and Sörbom 1993, p. 154):

β 1* β 2 + (β 1* β 2 ) + (β 1* β 2 ) +…(β 1* β 2 )  2

3

n

(11.1)

In the limit this expression of so-called ‘geometric progression’16 is approaching the next formula: b1*b2 / (1 − b1*b2). This is true under the general condition that | b1*b2 | < 1 (see Jöreskog and Sörbom 1993, p. 154). In literature, this cumulative effect is to be found under the labels of reciprocal, circular or total effect. However, from our point of view these names may be rather confusing, as we use them to indicate other effect-components of a reciprocal relationship. For that reason we will call this effect a self-effect (see Verschuren 1991, p. 174). This effect (in time) is clearly symmetric, which means that the change in variable A as a consequence of B is the same as the change in variable B produced by A. Ad c. Circular effect: The circular effect may be regarded as the result of a compound causal pathway of repeated cycles. It equals to the self-effect multiplied by b1, the effect of A on B, respectively b2, indicating the effect of B on A. Following the multiplication rule of path analysis (see Verschuren 1991, Ch. 5), the circular effect can be calculated as follows. The circular effect of A on B:

β 1*  β 1* β 2 / (1 − β 1* β 2 ) = β 12 * β 2 / (1 − β 1* β 2 ) 

(11.2)

 This corresponds with the geometric progression that was mentioned by Follett (1924), as increasing effects on one another in the ongoing interaction. She relates this geometric progression with organic growth. She speaks here about the “law of social relations” (in Drucker et al. 1995, p. 43). 16

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And the circular effect of B on A:

β 2 *  β 1* β 2 / (1 − β 1* β 2 ) = β 1* β 2 2 / (1 − β 1* β 2 ) 

(11.3)

In these calculations the direct effects are involved and as these are regularly non-symmetric, the circular effects are non-symmetric too. This is in full accordance with the fact that the causal mechanism(s) that constitute(s) the effect of variable A on B is mostly different from the effect of B on A. An example is the reciprocal relation between motivation and performance. Under adequate conditions an increase in motivation raises performances and an increase in performances in its turn further raises the motivation of people. But the deep, underlying mechanism that is ‘at work’ in the direct effect of motivation on performance is, at face value, of a different flavour than the effect vice versa. Finally, the total effect of a variable A on a variable B, both involved in a reciprocal relationship, is the effect that A has on B after an infinite number of circular effects, produced by indefinite interactions. Following the summation rule of path analysis (see Verschuren 1991, Ch. 5), the total effect of variable A on B and of B on A can be quantified as the sum of the direct effect and the circular effect, as formalized below. The total effect of variable A on B, then, gets the next expression:

β 1 +  β 12 * β 2 / (1 − β 1* β 2 ) = β 1 +  β 1* β 2 / (1 − β 1* β 2 ) * β 1  (11.4)

By equating the expression  β 1* β 2 / (1 − β 1* β 2 ) with the function ∆ (β 1, β 2 ) , the total effect can be formulated as follows: = β 1 + ∆ (β 1, β 2 )* β 1 This means that the total effect of A on B is a simple cumulative effect of a direct effect and a corresponding increase of the very same direct effect, through the function ∆ (β 1, β 2 ) . This turns the expression of the total effect on B into a generative function! The total effect on B is generated through the function ∆ (b1, b2), which is a function of the cyclic causal process between A and B. In a similar way we may develop the expression of the total effect of variable B on A:

β 2 + β1* β 2 2 / (1 − β1* β 2 )] = β 2 +[β1* β 2 / (1 − β1* β 2 ) * β 2 = β 2 + ∆ (β1, β 2 )* β 2

(11.5)

The generative function ∆ (b1, b2) is exactly the same as for the total effect on B! This shows the basic, symmetric properties of the total effects within a reciprocal relationship. It does not mean, however, that the total effects are symmetric themselves. This being the case because the b’s themselves are different. After some calculations these forms reduce to very simple formulas for the total effects of variable A on B and vice versa: e.g., for the total effect of A on B:

β1 +  β12 * β 2 / (1 − β1* β 2 ) = {β1 − β12 * β 2 + β12 * β 2  / (1 − β1* β 2 ) = β1 / (1 − β1* β 2 )



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Table 11.1  Formulae for the effects of a reciprocal relationship and of their features Component Formula Form Direct effects Non-symmetric Linear b1 b2 Symmetric Non-linear Self-effect (β1* β 2) / (1−β1*β 2) Circular effects

β1* (β1* β 2 ) / (1 − β1* β 2 )

Non-symmetric

Non-linear

β1 / (1 − β1* β 2)

Non-symmetric

Non-linear

β 2 * (β1* β 2) / (1 − β1* β 2) Total effects

β 2 / (1 − β1* β 2) Note. This is a basic assumption in SEM (see e.g., Bollen 1989, p. 3). It is, however, not known how this assumption is representing reality (cf. Namboodiri et al. 1975)

So, the total effect of variable A on B is:

β 1 / (1 − β 1* β 2 ) 

(11.6)

And, after a similar derivation, the total effect of variable B on A:

β 2 / (1 − β 1* β 2 ) 

(11.7)

In Table 11.1 we give an overview of the formulae of the different components of a reciprocal relationship and its inherent causal mechanisms. These formulae show that the total effects of A and B on each other are dependent on b1 and b2 in a different way. Although the two b-parameters are taken here as linear themselves, the total effects are not, as will be elaborated in the next section. The same goes for the self-effect and the circular effects. The total effects of A and B are neither symmetric. The same is true for the circular effects. As this table indicates, only the self-effect is symmetric. We want to stress here what the total effect means for the changes involved. The total effect has a similar interpretation as is the case for the direct effect: if there is a change in the (latent) variable A, then this change will be multiplied by the total effect, to bring about the change in the (latent) variable B. So, viewing the total effect is in effect about a strengthening of changes in the variables themselves within the reciprocal relationship. If the total effect is amplifying the change in the variable A, to be taken as a deviation in this variable A, then we may speak about a deviationamplifying effect on B, brought about by amplifying this change in variable A into a change in variable B. The amplifying effect itself is generated by mutual shaping forces. We may speak therefore about such amplifying effects as self-generated effects, operating within the reciprocal relationships (cf. Senge 1990, p. 79). It is of importance to notice that the distinct causal effects cannot be found in the regular textbooks about the causal framework. One may conclude, therefore, that they are not considered to be of importance for analysis in the social sciences as usual. This fact makes our approach of the causal framework an extended causal framework (ECF). In the rest of this book we intend to show the relevance of this

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ECF for thinking in complexity about complexity in a nonlinear complex reality as a new mode of thinking indeed (cf. Follett, in Drucker et al. 1995, p. 63).

Non-Linearity of Reciprocal Causal Effects It may be recognized as rather surprising that in the standard textbooks on structural equation models no figures are presented of a causal effect of non-recursive or reciprocal relationships. Nowadays, they are not difficult to make: see Fig. 11.2 for the total effects. In Fig. 11.2 these total effects of A on B and of B on A can be shown simultaneously in three dimensions, with the values of the two b’s on the x-axis and the y-axis and with the total effect(s) on the z-axis. This figure clearly shows the potential non-linearity of the total effect(s). So, the direct effects on the variables A and B, which are supposed to be linear themselves, may actually produce non-linear total effects on each other within a reciprocal relationship between these variables. As can also be read from Fig. 11.2, the total effects seem to increase

is 10

Z-ax

8 6 4 2 Total Effect

0 −2 −4 −6 −8

−10 −1.50 00 −1. 0.50 0.00 0 is − x a X 0.5 .00 1 B1 1.50

2.00

2 1.5 .00 0.5 1.00 0 0 Y-a −0. 0.00 xis −1. −1.00 50 −2. 50 00 B2

Fig. 11.2  Total effects of variable A and B on each other (symmetric)

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rather linearly, in a pretty large region, for instance when both b’s are smaller than 0.5. However, when the b’s increase, the total effects increase in a non-linear way.

Conclusions About Extended Causal Framework (ECF) relationships are more fundamental than things (Senge 2005, p. 193)

Above, we elaborated on the causal framework-as-usual in the social sciences, by showing the role of reciprocal relationships for the calculation of the total effects within these relationships. This role is essential for understanding the concept of reciprocal causation in causal dynamics. Only then may we be able “to account for realworld processes involving change and reciprocal causation” (Namboodiri et al. 1975). Causal thinking, then, becomes closely connected to processes taking place over time. This opens the link between the fundamental and the practical. We may now link the extended causal framework (ECF) with a different use of modelling causal processes and their effects over time within the scientific realms of our sciences. This means the introduction of the role of time in these processes. We agree with Long (1987) about the detrimental effects of excluding time in modelling processes in science (see also Willett 1997). By taking time into account, we may for instance introduce so-called ‘self-enhanced loop effects’ as potential, nonlinear effects within dynamic loops of relationships (cf. Hayduk 1987, 1996). These effects, with their equations, depending on time, may be expressed as follows (Box 11.1): This very notion of self-enhanced loop effects can be easily linked with the notion of causally generative processes based on generative mechanisms, generative principles and generative structures. We may build a new “relational and interactive view of development” (Wimsatt 1999, p. 173). For practice, this means that we may think of causal relationships as “growth-producing relationships” (Joyce and Showers 1995, p. 182; emphasis added). This corresponds nicely with the description of how geometric progression relates to organic growth, as prophesized by Follett in 1924 (see Drucker et al. 1995, p. 43). She speaks about ‘the law of geometric progression’, which she considers as equivalent with ‘the law of organic growth’ (Drucker et al. 1995, p. 50). She concludes that the social sciences have to reckon with these findings: “The social sciences must learn to … reckon literally

Box 11.1  (Total) Self-Enhanced Loop Effects on B and on A (Below) β 1t i + ∆( β 1t i , β 2 t j )* β 1t i β 2 t j + ∆( β 1t i , β 2 t j )* β 2 t j

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with it” (Drucker et al. 1995, p. 50; emphasis added). In the end, she comes to the fundamental conclusion that “the activity of the relating alters the terms of the ­relating and also the relating itself” (Drucker et al. 1995, p. 51). The notion of independent variable may become different, then, because the equations are constantly changing (Drucker et al. 1995, p. 52). The dependent variable may change as well. Follett gives the example of price in economy: “price is a developing situation; it depends on an interweaving; it is a function not of an independent variable alone but of the relation between it and the independent variable” (Drucker et al. 1995, p. 53; emphasis added). Based on this idea she defines function as follows: “function is the activity of relating, it is the operation, not what results” (Drucker et al. 1995, p. 52). It is of utmost importance to notice that her notion of function turns time into the equation! We may now link this idea of function with the notion of generative function, in which the parameters of the relating may change over time; that is, of the b’s themselves. This change of parameters is very much part and parcel of a dynamic interweaving going on over time. This idea brings us closer to the idea of complexus as “that which is interwoven” (Morin 2001): not only as a result but also as function of a complex activity of dynamic interweaving, that is, as an activity of dynamic relating. We turn to this topic in Chap. 13 on “The Complexity of Complexity”. To recap, we have shown the close connection between our extended causal framework (ECF) and the notion of complexity. We may bring the notion of complexity closer to that of a more dynamic, generative complexity, as linked to causal relationships within networks of reciprocal relationships with dynamic ­interweaving. These networks may be viewed as so-called ‘Augmented Transition Networks’ (Hofstadter 1987). The notion of generative complexity within such kind of ­networks may be taken as a solid kind of foundation for what Rescher has described as “the fact is that complexity is self-potentiating” (Rescher 1998, p. 28; emphasis added). A foundation that not only describes the processes going on but which is also able to become explanatory about the generative processes and the effects involved. This is a fundamental way of connecting explanation of generative complexity as self-potentiating with a causal explanation of the complexity of realworld complexity and its underlying causal dynamics of causal real-world processes (see Namboodiri et  al. 1975, pp. 22–23). Inspired by Follett’s thoughts, we may speak about the self-generative nature of the self-creative processes involved in the complexity of interaction; processes that are related to the notion of autocatalytic processes. This self-generative nature can be linked to what Follett called “novelties” as being very much of “psychologist’s critical moments of evolution” (Follett, in Drucker et al. 1995, p. 50). We think, these critical moments, in turn, correspond with what is going on in Vygotsky’s description of what he has called ‘the transitory child’ (Vygotsky 1987b, p. 91). Both Follett and Vygotsky have put strong emphasis on becoming more explanatory about this kind of phenomena. Follett stated this as follows: “It is impossible to overemphasize this point; it means a new approach to the social sciences” (Follett, in Drucker et  al. 1995, p. 50; emphasis added). Similarly, for Vygotsky, it meant as much as “the building stone that has been rejected by the builders of the science of psychology” (Vygotsy 1987, p. 91).

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With Namboodiri et al. (1975), we think that the complexity of the real world can only be dealt with by an effort “to incorporate as much of this complexity as possible into our models” (p. 20). We fully support their assessment that only by building in this kind of generative complexity in our equations about causal processes of reciprocal causation, based on the interplay of forces exerted within indefinite interactions, we can “allow for nonlinearities” (Namboodiri et al. (1975), p. 20). We like to call our approach ‘a fully generative approach of complexity’. Our approach is a fundamental, overall kind of approach, which is about a new paradigm of complexity. With this new paradigm, based on the extended causal framework (ECF), we may become really explanatory about the fundamental selfpotentiating characteristic of complexity as a fundamentally generative causal power. This being the case, because the total effects of reciprocal causation within reciprocal relationships can be expressed as self-generative functions of the two single b’s involved. It is these kinds of effects that show the causal power that is operating within the scientific realms of study in our sciences. It is a causal power that may operate as a generative power in the real! This turns our approach of complexity into a fully generative approach of complexity, as self-potentiating in principle at least. The generative approach, with the new paradigm of complexity, will constitute the generative foundation of a new science of complexity: see Chap. 13 on “The Complexity of Complexity”. This new science may offer the link between the fundamental and the practical, by enabling a possibility-oriented approach for practice within the social sciences and humanities, which is opening new avenues for understanding (Ruurlo 2006). In the next chapter about ‘the unit of study’ in our sciences, we may address the question that relationships are more fundamental than things (Senge et al., 2005, p. 193); that is, in general but for the social sciences in particular, with human beings as the main focus of study. This has important consequences for the study of human beings in these sciences.

Chapter 12

Rethinking the Unit of Study

… there is never in real life a stimulus followed by a reaction as a distinct unit of study (Mary Parker Follett1)

Introduction After the chapters on rethinking interaction and rethinking causality, we have to make another step before we are able to rethink the concept of complexity in use in the social sciences and humanities. For this ambitious goal, we need to rethink the unit of study as the subject of study in the social sciences. Only then, we can make the step of building a new science with a new focus on complexity as the subject of study in the social sciences. In this chapter we would like to show how, from the basic unit of a simple relationship with interaction between two entities, we may build up the new, larger unit: that of a complex, dynamic network. We may show the characteristics of the dynamics of such a complex network as modelled within the extended causal framework (ECF). It may be shown that these characteristics represent the realworld dynamics, with its real-world processes that are constitutive of the real-world complexity: that is, of the nonlinear, complex reality. We may, then, become explanatory about what Rescher (1998) has described as the fact that complexity is self-potentiating (p. 28). For Rescher himself, this seems a self-evident fact. But it needs explanation. For an adequate description, understanding and explanation of this complex concept of complexity, we have to develop a new way of thinking and modelling that is based on the new unit of study and the new tools, developed in the preceding chapters. These tools are to be derived from the extended causal framework.

Referred to by and in Metcalf and Urwick 1941, p. 15; emphasis added.

1 

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_12, © Springer Science+Business Media B.V. 2011

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Unit of Study The new step, of the unit to be taken, also has a long history in our viewing and doing science and in philosophy as well. The single entity that was a fixed, static entity has been the dominant unit of study in the social sciences and humanities. This was characteristic for the relationship between science and the real(m) in these fields of science. It has led to taking the complexity of reality for granted, evading the notion of ‘real’ complexity that was so much a part of the real-world complexity. Doing so, we have become the victims of blinding paradigms and the prisoners of description, not able to become explanatory of the complexity in our world. We think it is time for de-entifying the way we look at this complex world (cf. Valsiner 1998). The new focus should be on relationships, loops and processes within those loops. This focus is fully in agreement with recent developments in the natural sciences, in the field of fundamental theorizing in physics. The new developments in this field may be demonstrated by a quotation of the theoretical physicist Lee Smolin (1995): Indeed, for me the most important idea behind the developments of 20th century physics and cosmology is that things don’t have intrinsic properties at the fundamental level; all properties are about relations between things (Smolin 1995, p. 289)

His view corresponds with that of Mary Parker Follett (1924), in her book Creative Experience. She stated that human relationships are “the warp and woof of society and industry” (in Metcalf and Urwick 1941, p. 14). She was also clear about so-called ‘things’ in life: “every activity is not a thing in itself, but merely a moment in a process” (Metcalf and Urwick 1941, p. 15). This correspondence in basic attitude of viewing the subject and unit of study in different fields of science demonstrates the significance of the new approach as a full, transdisciplinary approach. We take it as self-evident that the world and life itself is dynamic and complex and we think we should take it that way for our viewing and doing science in the twenty-first century, as ‘the century of complexity’ (Hawking 2000). The world is in fact not static and fixed at all. The subject of study should therefore be a unit that is dynamic. Henceforth, we propose the unit of the ‘dynamic ensemble’ as the new, basic unit of study (cf. Kauffman 1993, on this new unit). This unit comprises the two constituent elements, their intrinsic relationship and the dynamics of the interaction within this ensemble. By taking this inherently complex unit into account, we may start a different adventure in our viewing and doing science, which is based on what Starobinski (2003) so nicely has described as “the adventure of action and reaction”. In the preceding chapter we already gave a different picture of the causal interaction within a (dynamic) unit of two (latent) variables, envisioned as a loop with dynamic, causal influences and effects, operating as mutual simultaneous shaping forces. We showed the nonlinear complexity of the dynamics of effects within this dynamic unit. Our mission for this chapter on the rethinking of unit of study is, to show that the potential, nonlinear dynamics within the loop of this unit, with their self-enhanced loop effects, is the basic building block for studying the complexity of real-world complexity in our inherently nonlinear complex reality. We argue that

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181

this will be the foundation stone that has been disdained in our history of science. This foundation stone is the corner stone for a new science of complexity, with a new focus on the complex dynamics of complexity. Wit this new corner stone, we will be able to show that indeed “nonlinear dynamics is another name for complexity science” (see Davis 2003, p. 42; italics in original). From this notion, we may better realize that the study of this nonlinear dynamics, with its complex, dynamic realworld processes, has been so difficult in our history of the sciences, because of the difficulty of studying such processes in the scientific realms of our sciences (cf. Ruurlo Manifest 2006). Edward Wilson (1975) has given a clear argument of this difficulty in building a theory: “Process is difficult to analyze because the fundamental units are elusive, perhaps nonexistent” (p. 282). In his book Sociobiology, he addressed the problem of building a theory for sociology as a science. It may be clear that his view and that of Lee Smolin (above), about the general problems for theory about the real complexity of reality, illustrates the fundamental difficulty of the problems at stake in building a new theory for the development of a new transdisciplinary approach of complexity in our viewing and doing science. The simple but yet very complex question to address is “how may we go from the simple to the more complex in our viewing and doing complexity science as a field of study of nonlinear dynamics?” How can we become explanatory about the complexity of complexity in the scientific realms of our sciences? Can we develop a new language about complexity for this rather ambitious enterprise? We intend to do so. So, at the end of this chapter, we will be able to speak about complexity as self-potentiating. That is, we may use a new language about the very dynamics of complexity of ‘bootstrapping’, to be conceived as a potentially nonlinear process and of ‘generativity’ as an inherently complex feature of this process; both features can be taken as fundamentally characteristic of ‘self-organization’ in (self-) generative, self-sustaining, self-maintaining, self-realizing complex systems. The new language is about new generative principles and generative mechanisms that may describe and explain the degrees of interactivity, connectivity and generativity of modelling the inherent complexity of the real-world dynamics of our nonlinear, complex reality. Ultimately, the new language of a new science may bring life into the equations of complex systems evolving over time in the real. For a first impression of the complexity involved in this, see the quote from Valsiner (1998) below about the complex dynamics within the new unit of study. …. a hyperdynamic process generates different by-products as it proceeds in its cyclical-helical unity (Valsiner 1998, p. 251; emphasis added)

From the Simple to the Complex For the new thinking in complexity about the nonlinear dynamics of a nonlinear, complex reality, we start with the basic unit of the loop or the ensemble as the essential, constitutive unit. This dynamic unit is the basic unit complex systems are

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made of. We may speak about the dynamic loop picture and about networks of dynamically interconnected loops as the subject of study in our nonlinear, complex reality. We would like to share our excitement with Smolin (1995) about the complex potentiality of that so-called ‘loop picture’ of reality: “What’s wonderful about the loop picture is that it’s entirely a picture in terms of relations. There’s no preexisting geometry for space, no fixed reference points; everything is dynamic and relational” (Smolin 1995, p. 289). The loop picture is fundamental for our viewing and doing science: a science that is based on a new epistemology and thinking about ontology and their relationship with the scientific realms of our sciences, i.e., of the social sciences and humanities. We may connect this potentiality of the loop picture with what Rescher (1998) has described as the fact of complexity – that complexity is self-potentiating (p. 28; emphasis added). In our modelling of complexity as self-potentiating, we start with the basic loop that represents the causal interaction within a reciprocal relationship, already described in preceding Chap. 11: see the picture below. We may abbrevi←. This symbol is ate this reciprocal relationship mathematically by the symbol → in common use within the standard version of the causal framework and described as a reciprocal or non-recursive relationship2 (see e.g., Jöreskog and Sörbom 1993). RA B ß1 A (t)

B (t) ß2 RB A

Actually, we prefer to speak about dynamic bi-directionality of reciprocal interaction within a causal loop. Such a loop is essentially a loop with two different cycles that may evolve over time. This shows already the fundamental complexity of the simple unit of a loop with two cycles between two entities; entities that are not fixed but may evolve themselves over time. The 3-D picture of the potential nonlinear total effects, presented in Chap. 11, shows clearly the complexity of a simple unit of the dynamics within a causal loop. This 3-D picture of the total effects is based on the generative functions that may be conceived as producing potential nonlinear, generative effects within the loop. The causal influences operating within the loop operate as mutually shaping forces. These forces, operating in the course of time through recourse, may develop into a kind of ‘generative

This term is somewhat confusing because recursive is derived from re-cur, which can mean again, or back. See http://dictionary.reference.com/browse/recur The focus here, in this symbol, is on both back and again! For this reason, we prefer the term reciprocal relationship. 2 

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forces’ (Morgan 1997). Henceforth, the dynamic complexity involved is of a ­fundamental generative kind. That’s why we call the complexity ‘generative complexity’. Based on this new idea of a generative kind of complexity, we may build up a new science about the tremendous complexity of a network of such loops (cf. Smolin 1995). The new science is about the (causal) dynamics of this dynamic, generative complexity within dynamic structures. The challenge for this new science is to show the merging of the fundamental, of theorizing about the nature of complexity and the practical of organized complexity in complex, generative ­systems. We may show this organizing of complexity manifests itself in practice. But to do so, “an overturn of the usual way of thinking” is needed (see Smolin 1995, p. 295). Smolin makes a strong plea for a fundamental relational view, thereby referring to the original work of Leibniz (Smolin 1995, p. 290). The response of the entities involved, can be viewed as a response to a relating (cf. Follett 1924, 1995). With Thomas Smith (1992), in his book Strong Interaction, we may speak now of hitherto unknown forces: “forces that produce strong interactions: responsiveness potentiating responsiveness, transference meeting transference” (p. 75; emphasis added). This turns the concept of complexity into that of generative complexity, linked with generative forces. These forces, now, can evolve into really generative forces operating in complexity as self-potentiating through nonlinear effects over time! So, we have turned time into the equations of complexity, conceived as a dynamic, generative, self-potentiating concept with potential nonlinear effects over time. The development of these entities can be viewed as an inherently complex development through interaction within reciprocal relationships (cf. Fogel 1993). The modelling of the reciprocal influences on each other may now be taken as mutually shaping forces exerted on each other as generative forces. The corresponding mutual effects may turn into nonlinear effects on each other over time. This turns the generative complexity involved into a self-potentiating kind of complexity over time. Even more importantly, the notion of generative, self-potentiating complexity brings forth the notion of ‘directionality’. This notion, we think, is fundamental for a theory of life itself (cf. Rosen 2000). It is this very notion of ‘directionality’ that can also be viewed as the cornerstone of a theory of life; that is, of life as a process (cf. Follett, on this concept of life itself; see above). This idea of complexity of entities in causal interaction within a reciprocal relationship between these entities is also our basic stance in dealing with the complexity involved in interaction in general and with communicative human interaction in particular. This is why the causal modelling of this interaction starts with the fundamental relational view of interaction. This brings us to a modelling of the relating itself as a causal, reciprocal kind of relating, which is very uncommon in the social sciences. It demands for a new kind of thinking about interaction and about entities as dynamic, evolving entities. This demand runs parallel with the development in modern physics. For this, we may refer to Smolin’s view about physics, in his plea for new thinking in physics, demonstrating, again, the fundamental transdisciplinary nature of our new approach of the social sciences.

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Networks and Generative Systems By taking the inherent complexity of interaction within reciprocal relationships into account, we need a process view of interaction. In Chap. 10 we started with a simple, general model of interaction: see Fig. 12.1 below. For simplicity time was left out of the model. To model the dynamic and complex process in the real, we need to take time into account in the model. So, we extended the model, as ­represented in Fig. 12.2. In this model the relating between A and B is visualized, as two separate arrows: RAB and RBA. They are distinct relationships because the relating of A to B is not the same as the relating between B and A. This difference in relating also makes a difference in the influencing of the other. For each one’s response “is always to a relating” with the other (Follett 1995, p. 42). The picture in Fig. 12.2 makes the interaction complex, with the potential of change over time. But, again, although time seems to be a variable in the picture, the variables are not dependent of time! They may, however, change with time. The picture also shows that the two b’s may vary over time. Most importantly, it shows that these changes in the two b’s may co-vary with the changes in the relating. In turn, the relating, the RAB and RBA, may vary with the changes in the two b’s as well. So, essentially four variable elements are involved in the dynamics of causal interaction as the new unit of study in thinking in complexity. For the modelling of the interaction, with the potential nonlinear effects over time, we only need the two b’s as parameters in the causal equations. With time included, we may rewrite the equations. The above representation of the causal dynamics brings with it the notion of complexity of interaction as an ongoing process of causes and effects, i.e. that of a generative kind of complexity with effects that are generated in and produced

Fig. 12.1  Simple model of reciprocal interaction

R AB (t)

ß 1 (t) B (t)

A (t) ß 2 (t)

Fig. 12.2  Extended model of reciprocal interaction

R BA(t)

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through the interaction both entities are involved in. In this and in the next chapter, about complexity, we will elaborate on this fundamental, generative notion of ­complexity. We intend to show how we may start new thinking in complexity as a way of thinking in terms of the new concept of generative complexity. This new tool of thinking is fundamental for thinking about the functioning of complex ­systems as generative systems, based on fundamental generative principles and mechanisms. We may connect this new way of thinking with the ‘loop picture’ presented by Smolin (1995) in his alternative thinking for the field of the very small-particles physics. This may show the fundamental transdisciplinary character of the new thinking in complexity. This transdisciplinary new thinking in generative complexity is complex indeed!

A New Unit for Conceptualizing Complexity In this section, we want to connect the representation of interaction as causal interaction with the ‘loop picture’ of such interaction, because the loop can be considered to be a basic unit of study in new thinking in complexity as generative complexity. ← as a loop could be In Chap. 11 we showed that the reciprocal relationship of → represented in three different ways. The last representation is presented below, in ← as a loop, with different states of the latent variBox 12.1. This is the weave of → ables A and B over time. Box 12.1 actually gives a representation of the smallest unit of an ensemble: as a small network between two latent variables. A representation that shows how the causal influences and their causal effects may develop over time, dependent on the strength of the bi-directional relationship. The properties of this network are about the relations between A and B. Both A and B are evolving over time. It is important to notice that these influences and effects on A and B are not dependent of time but take place in time! The subscript t + i denotes the steps to be taken in time in the model, starting from a time point t. The time between the steps may actually be infinitesimal small. As a consequence, the time taken for making all of the steps may be infinitesimal small in the real as well. All of this goes beyond perception.

← with Latent Box 12.1  Representation of the Reciprocal Relationships → Variables A and B At

At+1

At+2

At+3

A

Bt

Bt+1

Bt+2

Bt+3

B

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You do not see what you do not see: that is, the complexity of the processes that are involved. This notion of causal processes ‘producing’ effects over time is very different from the notion of the causal ‘production’ of effects in causal modelling in the social sciences. Mathematically, it was shown in Chap. 11, that the reciprocal causal effects over time develop as a geometric series: β 1* β 2 + (β 1* β 2 ) + (β 1* β 2 ) +…………(β 1* β 2 ) 2



3

n



This geometric function is a kind of generative function, generating the effects over time in a cumulative way. In Chap. 11 we saw that the total effects were similar, generative functions that equal to

b1 / (1 − b1*b2) for the total effect of A on B and



b2 / (1 − b1*b2) for the total effect of B on A

We may bring these formulae to a more significant form, which expresses the notion of a generative function more adequately. Returning to the derivation of these formulae in Chap. 10, we may re-formulate the formulae for the total effects as follows: see Box 12.2. These formulae,3 in Box 12.2, show that the total effect (TE) of A on B and of B on A can be viewed as the basic causal effect increased by function D (bt1, bt2) times the basic causal effect. This function expresses an increase in the basic causal effect of A on B and of B on A. This function, which is only dependent on the values for bt1 and bt2, is the same function for both the TE of A on B and the TE of B on A. It is a symmetric function, based on the two characteristic values of bt1 and bt2 of the loop! Reading the formulas in Box 12.2 carefully, one may notice that the total effects are kind of self-generative effects. The function D (b1ti, b2tj) is the measure of ­generative increase that is ‘produced’ through the mutual shaping forces exerted in the causal interaction (Lincoln and Guba 1985, p. 150). This function D turns the total effect on B and on A into fundamental generative functions. The values of these functions may increase nonlinearly! This means that the total effects on B and on A may increase nonlinearly over time. These total effects can be visualized in a

Box 12.2  Total Effect (TE) of A on B, and of B on A Total Effect (TE) of A on B = bt1  + D (bt1 , bt2) * bt1 Total Effect (TE) of B on A = bt2  + D (bt1 , bt2) * bt2

3  It is not possible to find these formulae in the regular books about the causal framework. Only Hayduk gives a reduced version of these formulae, in Hayduk (1996).

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three-dimensional space, as shown in Chap. 11. This space may be called a ‘transition space’, which shows the amplification of changes in the (latent) variables involved and the potential nonlinear transitions of effects in the changes of these variables (see Holland 1998, p. 240). Henceforth we may speak about ‘transition’ effects that are ‘produced’ in the interaction as an ongoing process. Interestingly, the generative functions in Box  12.2 are potentially nonlinear in their effects over time. These are effects ‘produced within the causal loop of a single causal, reciprocal relationship’. Because of this, we may also speak about ‘enhanced loop effects’ (cf. Hayduk 1996). For the total effects we may introduce, now, the notion of the ‘self-enhanced loop effect’ (Hayduk 1996). In every loop, there are two of such total self-enhanced loop effects. It may be stressed that this means that these functions are generative functions and the effects are essentially generative effects that are brought about, or produced within a loop on the constituent, fluid kind of entities of the loop. The effects may also be considered as self-propagating effects, propagating themselves in and through the loop in time. It is of importance to notice that the two effects are not symmetric within a single loop! We have now developed a new tool for linking causal loops with the functioning of networks; that is, the loop as the smallest network, as represented in Box 12.1. It is hard to over-emphasize this deep but hitherto hidden link for new thinking about complexity: that is, the complexity of networks (cf. Barabási 2003, p. 238). We agree with Lincoln and Guba (1985) that “the universe is an interconnected network” (Table 2.7, at p. 68). We think this, taken together, as intertwined, to be the cornerstone for a new science of complexity. This cornerstone may be considered to be the foundation stone, ‘simply’ disdained by the builders of science (cf. Vygotsky 1987b, p. 91, on the science of psychology). In Fig. 11.2 of Chap. 11, it was shown that the total effects over time may become nonlinear when the two b’s increase, evolving towards the value 1.00. These nonlinear effects may happen in the smallest unit of the loop between two latent variables involved, which may be considered to be a kind of constituent ‘entities’ that may change over time. These entities are ‘fluid’ kinds of entities. So, these fluid entities are fluidly connected through an evolving reciprocal relationship, evolving over time. They are the potential constituents of a fluid network, like fluid neuron networks or networks of ants (see, e.g., Solé and Goodwin 2000, pp. 159–161). It may be concluded that the simplest circuitry, that of a single dynamic loop with interaction, may already be quite complex, because of the potential, generative causal processes and enhanced effects within this loop. This conclusion supports the idea that complexity science is another name for nonlinear dynamics (see Davis 2003, p. 42).

The Complex ‘Work’ of Causal Networks Based on the causal, dynamic loop as the fluid unit of study, we may go on to study more complex units, such as fluid causal networks, built up from this ‘simple’ but complexly fluid unit of study. We may start to build complexity from the simplicity

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of a simple but yet complex circuitry of the dynamics and the potential effects within this dynamic unit. To continue, we may introduce the notions of generative principles and generative structures, to be connected with and operating in fundamental, generative functions. We introduced already the notion of self-propagating of effects within loops, enabled by the generative ∆-functions, presented above. We may speak, then, about the self-generative potential of causal loops. All of these notions are leading to the hitherto rather unknown concepts of generativity, learnability, connectivity and evolvability as characteristic features of dynamic causal networks that operate in generative, complex systems.4

From Simplicity to Complexity – A Transdisciplinary View It is time to introduce the notion of complex networks as unit of study with simple knotted loops. In this section we would like to extend the notion of a single loop to a network system of loops. To be more specific, we may extend the loop picture of a causal reciprocal relationship to a dynamic causal network. Inspired by Wolfram (2002), who shows nicely these extensions in the section ‘Network Systems’ (pp. 193–203), we may think of causal networks with more loops and show how such loops are knotted in complex, dynamic causal networks. His approach may be ­considered as promising for thinking about causal networks and their dynamics in complex generative systems, which can be linked to the fundamental transdisciplinary concept of ‘self-organizing systems’.5 Now, it seems adequate and relevant to think of complex, causal networks of loops in generative network systems. The use of such a concept, we suggest, is enabling for a transdisciplinary approach. We think it makes possible to address the fundamental question: In what way, then, following which kind of principles and what kind of generative structures, can we think of the inherent complexity of the self-organizing processes involved in these systems?

Like Lee Smolin (1995) did for physics and Stuart Kauffman for the problem of self-organization, dealing with the problem of organized complexity, constituting our complex reality, we may better start with putting the seemingly simple but ultimate complex question “What is the complexity involved?” This question may be

Although it goes a little bit far to connect our way of conceiving of complexity, based on causal loops, with that of Wolfram (2002), the parallels with his concept of causal networks and causal interaction and generative functions are exciting but not so easy to understand. But, most importantly, he addresses the problem of the unit of study correctly as a fundamental problem in his approach of physics as a new kind of science. 5  Although we actually prefer another term, instead of self-organization, we use the last concept in order to use the same kind of trans-disciplinary language (see also Kauffman 1995b, p. 181; Morin 2007). 4 

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followed by the next, more difficult question: how can this complexity, which is a dynamic, generative kind of complexity, be turned into an effective kind of organized complexity in the nonlinear, complex reality as the subject of our new thinking in complexity and the founding of a new science? Ultimately, we may find the entry for new thinking in complexity as self-potentiating (Rescher 1998). This new thinking will simultaneously give the opening for making use of this ­self-potentiating power of complexity, with its potential, self-enhanced loop effects. We may call this kind of complexity ‘advantageous complexity’. This will be the new tool of thinking for use in the social sciences and humanities. This new tool of thinking in complexity will be very much part of the retooling of our viewing and doing science. This retooling is very much constitutive of the shift of paradigm towards a new paradigm of complexity, which is so much needed for the reinvention of our social sciences and humanities (cf. Morin 2008). The new paradigm will bring these sciences closer to the real-world complexity of a fundamental, nonlinear complex reality. This notion of complexity of real-world complexity, with its underlying real-world dynamics of complex real-world processes, will enlarge the space of the possible, which are very much the spaces of a new world: the world of the possible (Kauffman 1993).

Explaining Emergent Dynamic Complexity as a Condition for Effective Complexity It is our aim to develop a programmatic view for the study of complexity. Thinking in complexity about complexity will be along the following lines: we think of complexity as complexity that is causally and dynamically interwoven, with equations of enabling generative functions, needed for organized complexity as manifested in self-generated, self-sustaining, self-maintaining, self-organizing and self-realizing systems.6 We may, then, rightly ask the question: “What is the weave?” (Kauffman 1995b, p. 185) The necessary steps will be made from a trans-disciplinary perspective, for the very reason that complexity as described in this way is a fundamental trans-disciplinary concept.

Complexifying Modelling To develop the programmatic view, sketched above, we need to increase the ­complexity of our modelling. The challenge for complexifying our notions of reality is in the enlarging of the space of the possible in our viewing and doing science as activity, fundamentally related to the equally enlarged scientific realms of our ­sciences (see Fig. 7.1 in Chap. 7; cf. Ruurlo Manifest 2006). This goal may be recognized as the study of autopoetic systems, with its origins in the nineteenth century (Kant) and put on the agenda of social (cognitive) science by the original thinkers Maturana and Varela.

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We think a good start for complexifying our modelling of causal interaction for the modelling of generative, causal networks is given in Fig. 12.3 below. It shows a complex, extended version of the simple causal models of interaction, in Figs. 12.1 and 12.2 above. It shows the elements A and B as complex dynamic entities themselves. Everything is dependent of everything in this model. Actually, both the elements and the links between these elements in the modelling are infinite, based on indefinite, long-term interactions (cf. Dewey, in Biesta 2006, on human interaction). Is this dynamic unit, then, the new unit of study for new thinking in and of modelling complexity? Our answer is “yes, it is” and there is nothing to be afraid about. One only needs to become aware that we need new thinking for dealing with this tremendous complexity. This is the path of real innovation in and for a new science. Innovation never happens where one seeks it (cf. Luhmann and Schorr 2000, p. 40). Based on these kinds of reflection about innovation, we may as well realize that they clarify why the paradigms ‘in use’ have been so often blinding paradigms and scientists viewing and doing science, who “have a blinkered view of the world” (Daniel Dennett, in Brockman 1995, p. 331), not able to explain what still needs explanation. We may think, here, of evolution and of life itself. Because of this being stuck in our viewing and doing science, we are still not able “to build a theory that combines self-organization of complex systems and natural selection” (Kauffman, in Brockman 1995, p. 337). For such a theory we need a different kind of thinking and explanation: thinking in complexity and explaining networks or patterns with “a pattern model of explanation” (Lincoln and Guba 1985, p. 206; italics in original). So, we may come to the conclusion that we still do not really know what the ‘motor’ of evolution looks like, or how it operates. But for here, in this book about

Fig. 12.3  A sketch of the complexity of interaction within a simple unit of two entities A and B

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thinking in complexity, the more basic questions are what the role of complexity may be in building an adequate theory for explaining what needs explanation: 1 . How may complexity become dynamic complexity? 2. How may dynamic complexity turn into effective complexity? In what way are we able to open up a new toolbox, to start thinking-out-of-the-box and become more explanatory about the dynamics of complex, generative systems and their inherent complexity? What kind of unit do we have to choose to be able to do so? We think Fig. 12.3 gives a first hint about how to go on in this new thinking in complexity for explanation. It shows the causal interaction as a dynamic, causal network at a certain point in time. Of importance is that we may not only describe the situation of this network as the state of the network but also in terms of the state of the two entities involved as fully connected states. This, we argue, is what the reality of complexity as the subject of study of complexity is really about. It shows the complex and tortuous path that goes from simplicity to complexity in our nonlinear, complex reality. We return to this in the next chapter, Chap. 13, about “the complexity of complexity”. But first, we go deeper in the complex subject of study and the unit of study to be chosen for new thinking in complexity. Ultimately, to be able to deal with the real-world complexity, we have to come to grips with the causal dynamics in causal, dynamic networks as the new unit of study. We intend to show this complex dynamics, manifesting itself as a kind of self-generative dynamics of complex self-causation. For clarity, self-causation is not to be taken here as immediate self-causation, which is a common but very misleading misunderstanding but is actually mediated via other variables or entities. Within this unexplored dynamic causal framework, causality may be taken in terms of “Causes [that] produce effects that are necessary for their own causation” (Morin 2007, p. 14; emphasis added). With this new conception of causality, we may better describe the functioning of complex (adaptive) systems. We intend to show this functioning of complex systems in terms of a causally generative functioning, with causal interaction as self-generative, self-propagating causal processes and their total causal effects over time. We think of such self-propagating and selfgenerating processes “in which the product of the process is necessary for the process itself” (Juarrero 1999, p. 5; emphasis added). We may go somewhat further by considering the causal dynamics of the network and ask in what way the network as a whole is “representing a complexly woven tapestry of functions” (Glick 1997, p. xiii). So, we have a more extended complex unit: that is, of the complexly woven tapestry. Underlying this tapestry of functions is a dynamic structure, consisting in complex, generative structures functioning according to generative principles and mechanisms. How, then, can the functions of the tapestry be linked with the causal, generative functions and the generative structures of a dynamic, causal framework? This is a real complex question, which needs still more steps to be taken in our thinking in complexity and our modelling of complexity. Firstly, we need to extend our unit of study to get grips on the complex dynamic networks being part of the complex tapestry. Then, we may get a better idea of the complexity involved; that is, the complexity of real-world complexity

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with its underlying real-world dynamics of real-world processes. In the end, we may arrive at the fact that complexity is not only self-generative but also selfpotentiating7 (cf. Rescher 1998).

From the Simple to the Complex Unit of Networks ← of a network (a single loop representThe simplest extension of the smallest unit → ing a reciprocal causal relationship with causal interaction), consists in two knotted loops, simply represented as follows: ADBDC This doubling of the basic unit delivers the following picture of the causal network involved: see Fig. 12.4. Although this picture may not look very complex, the total causal effects on A, B and C will show a real increase in complexity. This is easy to recognize for the effects on the (latent) variable B. The causal effects originate both from A and from C. Consequently, the total effects on B will be a complex mix of causal effects from these two entities (conceived as latent variables in the causal framework). Everything is evolving in time and so are the total effects. These total effects are potentially nonlinear, delivering already a rather complex landscape of causal effects. We will not give all the formulae here, because that may be confusing and leading away from the topic in this chapter: that of the unit of study. We may better introduce an important notion about a possibility of extending the circularity of the simple causal sequence A D B D C, with arrows from A to C and from C to A. This gives the next representation of a circular sequence:

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This representation is similar to that given by Stuart Kauffman (in Solé and Goodwin 2000, p. 258). It shows the interconnectedness of the different latent variables or entities involved in the sequence as a representation of complex, dynamic, entwined causal processes. What is of real importance is that the sequence is not just a sequence but has actually a kind of web-like structure: that of a causal network. This may be better shown in Fig. 12.4 below. The reader may realize that innovation never happens where one seeks it (Luhmann and Schorr 2000, p. 40), which closely corresponds with Kuhn’s thought about paradigms and shifts of ­paradigms in viewing and doing science (Kuhn 1970).

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We may, now, easily increase the complexity of the unit of study into a sequence of four elements A D B D C D D with the following extension of arrows, showing the complex interconnectedness of the whole sequence. This sequence is, again, not

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just a sequence but has actually a kind of web-like structure: that of the causal network, with four knotted loops, as shown in Fig. 12.5. This unit and picture of the web-like causal network may be viewed as the building stone of a simple tapestry, which may function as a dynamic kind of tapestry of functions (cf. Glick 1997, on Vygotsky). We may, then, start to find an answer to the still unanswered question “What is the weave?”, which is a dynamic weave. For this we need to think of webs and webbed networks with webbed architecture. This kind of architecture is about dynamic bootstrapping configurations producing bootstrapping processes and corresponding nonlinear bootstrapping effects. What we are aiming for is the building of a tapestry that is a dynamic tapestry with a dynamic weave, corresponding to a tapestry of functions. How, then, can we conceive of the dynamic weaving of such a tapestry? Our first preliminary attempt goes in the direction of building such a tapestry by using our extended causal framework, to be visualized as an emergent, self-ordering, self-enhanced loop picture, of a dynamic network, with causal trajectories of strengthening functions.

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We may conclude that our new thinking in complexity has developed into “a new modelling philosophy” (Barabási 2003, p. 90), about modelling self-causation within complex, dynamically interconnected loop networks. This modelling is integrating complexity thinking with network thinking (Barabási 2003, p. 238), offering a new entry for dealing with the complexity of real-world complexity. All of this means not only a new mode of thinking but it offers a new perspective of the dynamics of networks, with power laws about nonlinear effects, which can describe real networks, with a corresponding “new language of networks as well” (Barabási 2003, p. 91). The reframing of complexity, based on this new framework of a new mode of thinking, may lead us to “a new level of comprehension about our complex interconnected world, bringing us closer than ever to understanding the architecture of complexity” (Barabási 2003, p. 92). We are pretty sure this will be a new kind of understanding that goes beyond that of architecture as we used to know it (cf. the quote below, from Corbusier himself, at the end of his life). The webbed architecture about webbed networks (Kauffman 1993, p. 428; emphasis added) is inviting for a new kind of explanation: that is, of pattern explanation, of evolving networks of interconnected loops, with their patterning of threads and development of effects that can evolve into a kind of functional bootstrapping over time (Kauffman 1993, p. 373). We may speak about such kinds of webs in terms of webs that “govern their own possibilities of transformation” (Kauffman 1993, p. 370). Such webs can be described as self-ordering or self-organizing webs. These kinds of webs are very much like “the webs without a spider”, as described by Barabási (2003, p. 219). This complex notion of a web can become the very building stone for a new science of complexity; a new science that can deal with ‘the problem of life itself’ (cf. Rosen 2000). This promises to be a new science that can deal with Vygotsky’s notion of the ‘transitory’ child (1987a, b, p. 91) and with the complex notion of ‘Augmented Transition Networks’ (Hofstadter 1987). The new science may be

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Fig. 12.6  “Sleeping Beauty”, by Nadine Sterk. © 2006. Atelier NL Photo by P. Scala. Example of weaving of ‘network’ in three dimensions. See Annex 12.1

opening for a new, augmented reality as well; that is, of a ‘new world of the ­possible’ (Kauffman 1993), by enlarging ‘the space of the possible’ (Osberg 2009). The new reality is not static but a fluid reality, about a fluid architecture, with fluid entities and their fluid dynamics, evolving over time, like the reality of life itself. In the next chapter we start with the reframing of complexity by considering the topic of the complexity of complexity, which is very much the real-world complexity, as being part and parcel of life itself. After all, nature is right and the architect is wrong (Corbusier, at the end of his life 8)

We think it is not by chance that he became aware of this at the end of his life. This is a moment that one realizes that “life happens when you are making other plans” (John Lennon).

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Annex 12.1  Information about the “Sleeping Beauty” Sleeping Beauty 2006 | Nadine Sterk Where there is light, there is life. When you switch on the lamp, it provides you with light. You provide it with the generating power it needs to grow. Similar to living organisms, this lamp contains all the essential “mechanisms” that will enable it to develop. All it needs is energy and it starts creating its own lampshade. It knits it slowly around the lamp, pausing only when the light is off. Its growth places it beyond the bare utilitarian necessity of artificial light. The lamp becomes an animate part of space, an existence in its own right. text Theodora Antonopoulou photography Paul Scala collection gallery Kreo

Chapter 13

The Complexity of Complexity

In order to arrive at what you do not know, you must go by a way which is the way of ignorance T.S. Eliot, from “East Coker”1

Introduction This is the core chapter of this book, about the complexity of complexity. After all of the rethinking in the preceding chapters, we think we are able to present a different notion and concept of complexity that can lead to a new way of thinking in complexity. We intend to develop a way of thinking in complexity that goes beyond the complexity as taken for granted in the field of our social sciences and humanities. The notion of complexity we would like to present here is a dynamic, deeply generative notion of complexity. We call this ‘generative complexity’ (cf. Rescher 1998, p. 9). This notion goes way beyond the version of a restricted complexity. We start our thinking in complexity about complexity by exploring generative complexity as the focus for conceiving the notion of general complexity (see Morin 2007). This general notion of generative complexity makes it possible to link the descriptive complexity with that of interactional complexity (Wimsatt 2007, p. 181; italics in original). The key feature of this new notion, however, is the potential nonlinearity of generative complexity. This implies the nonlinearity both in the dynamics of interaction, of interactional complexity and in its temporal effects on the entities involved in the interaction(s). This potential nonlinearity is based on the complexity of interaction within the fundamental, dynamic unit of the causal loop in the preceding chapter. We may speak of the causal power of this new dynamic unit with its fundamental, self-enhanced (causal) loop effects on the entities involved, in the course of time. These effects are based on the fundamental, generative function of total effects of causal interaction that take place in time and space. We may

In Wendell Berry, in Vitek and Jackson 2008, “The Virtues of Ignorance”, p. 37 (emphasis added).

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speak, therefore, about the generative power of causal interaction, enabled by the generative forces exerted in the long-term interaction. Our concept of ‘generative complexity’ for the social sciences is unifying in the approach of the inherent complexities of reality in our sciences in general: that is, for instance, both the reality of physics (see Smolin 2006 2) and that of biology as well (see Wimsatt 2007). That makes our topic of the complexity of complexity a real transdisciplinary topic, of interest for various different disciplines.

The Complexity of the Concept of Complexity The use of the notion of complexity can never be taken for granted (Alhadeff-Jones 2009, p. 68)

This is the final part of this book, about the complexity of the very concept of complexity itself. After having made all of the steps of rethinking in the preceding chapters, we think we are finally able to present a different notion of complexity that leads to a new thinking in complexity; a new thinking that goes beyond the notion of complexity so much taken for granted in different fields of our social sciences (Alhadeff-Jones 2009, p. 68; emphasis added). From this stance, we may show the reader that we really need thinking in complexity to grasp the very complexity of reality; a reality that can better be taken as a fundamental ‘nonlinear complex reality’ (Mainzer 2007, p. 16). Thinking in complexity is not just a kind of philosophy but is taken here as foundational for a new science of complexity as well. This kind of foundational new thinking in complexity will not only be about the discovery and the description of complexity in a nonlinear complex reality but may also be considered to be the foundation for a general theory of complexity: that is the complexity of complexity itself as a fundamental concept linked to the nonlinear complex reality. We do so by making a link with the rather strong opinion about complexity put forward by the philosopher Nicholas Rescher (1998): “The fact is that complexity is selfpotentiating” (p. 28; emphasis added). We fully agree with Rescher and take this notion as a fact of life: of life itself (cf. Rosen 2000). We argue that it is through this link with complexity as a fact, concerning a potential nonlinear complex reality, that we may derive a new ontological status of complexity. This is in line with Goethe’s adage that “if we want to achieve a living understanding of nature we must follow her example and become as mobile and flexible as nature herself”

What are really fundamental and also general in this are causality itself (Smolin 2006, p. 241) and the underlying causal processes and relations of causality (Smolin 2006, p. 244). Interestingly, the importance of causality in this seems similar to understanding the fundamental role of causality in understanding of the new physics of spacetime (see Smolin’s Chap. 15). This makes our approach a real trans-disciplinary one.

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(Goethe, in his book “Morphologie”).3 So, we need a more flexible, new method to be able to harness the living complexity of complex nature herself in our viewing and doing science. We may conclude from the above reasoning about complexity that our common notions of complexity are insufficiently complex. This conclusion has consequences for epistemology too! We may need a new epistemology about complexity, with a rather dramatic change in focus. We agree with Luhmann (2002) that epistemology “can no longer be understood as a theory of the founding of knowledge” (p. 152). He states, quite contrary, that “the opposite is true: it analyzes the uncertainty of knowledge and gives reasons for it” (Luhmann 2002, p. 152). From this stance, we may derive an epistemology of complexity that may bridge to the unknown: the hitherto unknown about complexity. It may be considered to be “an epistemology that recognizes its own ignorance” (Brown, in Vitek and Jackson 2008, p. 168). From this stance, we may view it as a kind of learned ignorance (Nicholas of Cusa, in Luhmann 2002, p. 192). The new epistemology is not only an epistemology of the uncertainty of knowledge. It is as much, or even more so, an epistemology of the possible. So, complexifying reality brings with it the opening of a new reality, of hitherto unknown possibilities. Complexifying can be taken both as opening up and enlarging the spaces of the possible within the scientific realms of our sciences (cf. Ruurlo Manifest 2006).

A New Approach of the Complexity of Reality Die gerade Linie führt zum Untergang der Menschheit 4 (Hundertwasser 2004, p. 79)

Our new, scientific approach may be characterized as complexifying our viewing and doing science. This may be viewed as a shift of paradigm and as a foundational way of seeing the world anew (Senge 1990, p. 68). This shift of paradigm constitutes a way to escape the danger linear thinking and that of linear causality as well. With Senge (1990, p. 73), we are of the opinion that although reality is made up of circles, we seem to see only straight lines, not being fully aware of the dangers it brings with it for humanity and society at large (cf. Hundertwasser 2004; see footnote 5). We take it as a fundamental task of our social sciences and humanities to account for and become more explanatory about “the changing nature of social realities” (Deaux and Philogène 2001, p. 319). We fully agree with Robert Reid that

3  Originally published in 1817. See Craig Holdrege, in Vitek and Jackson 2008, The Virtues of Ignorance, p. 332. 4  “The straight line leads to the end of humanity/mankind” (own translation).

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only with the use of such a fundamental shift, of seeing the world anew, that we might be able to grasp the complex, still confusing reality (see Reid 2007, p. 306; cf. Goethe’s adage above). Based on this shift as a kind of precondition, we may develop a new, explanatory approach of complexity. Traditional forms of explanation are falling short of explaining the complexity of real-world complexity, of real-world systems, as part and parcel of a nonlinear, complex reality. We may better explain this new reality by seeing the complex patterns of change. These are the patterns that are linked with the dynamically interconnected loop networks. To enable the explanation of these complex patterns, we need what Lincoln and Guba (1985) alternatively have called “a pattern model of explanation” (see, p. 206; italics in original). They link the new kind of explanation with a more viable concept of causality: of mutual simultaneous shaping forces (p. 150). This is the kind of explanation we will focus on in this chapter: on explaining the very complexity of patterns within complex networks of dynamically interconnected loop networks. Our approach will bring new complex concepts, as an essential part for the development of “a language for complexity” (Senge 1990, p. 268; italics in original). With this new language we may not only describe but also become more explanatory about complexity. This will be the new language for the description of a new reality; a reality that is composed of networks of dynamically interconnected causal loops, to be modelled within the extended causal framework, as a potentially nonlinear framework (see preceding chapters). We strongly believe, as the history of our sciences has shown, that the use of a new language may overcome “the intrinsic biases toward linear views in our normal everyday language” (Senge 1990, p. 268). A new language for complexity may escape the danger of linear thinking about an inherently nonlinear reality. Complexifying reality in the way as delineated above may not only imply the humanizing of our sciences (Morin 2002) but also be beneficial for humanity and society at large too!

Generative Complexity The notion of complexity we would like to present here is a fundamental, dynamic, generative notion of complexity. We call this ‘generative complexity’. This notion of complexity goes way beyond the version of a restricted complexity (see Morin 2007). We may focus, then, on generative complexity as the focus for conceiving the notion of ‘general complexity’. This general notion of complexity makes it possible to link the notion of descriptive complexity with that of interactional complexity (Wimsatt 2007, p. 181; italics in original) and that of the relational complex. So, the concept of ‘general complexity’ is integrating these diverse notions of complexity. We may think here as well of the fundamental tri-partite relationship between connectivity, as being about the relational complex, interactivity, as being about the dynamics of interaction and generativity, as the ‘product’ of the generative forces exerted within the communicative human interaction. The very concept of ‘generativity’ is a difficult concept. Yet is has been used by different scholars,

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for use in different fields and disciplines (Lord 1994; Sassone 1996; Wimsatt 2007). Generativity can be understood here as a fundamental, creative state of being of human beings, as the (two) entities involved in the interaction (Sassone 1996, p. 520; and Wimsatt 2007, p. 12). Brian Lord (1994) makes mention of achieving collective generativity, as a condition of “knowing how to go on”, based on a full Wittgensteinian perspective (p. 193). This generative state of being, taken individually or collectively, can be taken as strongly linked to the dynamically interconnected loop network of relationships among the entities within the network, with their characteristic (latent) variables. Linked to these states we may speak about generative systems, with generative structures (Wimsatt 2007) responsible for these generative states of being as potential nonlinear being. From the above, we may derive that the key feature of the new notion of complexity is the potential nonlinearity of generative complexity: nonlinearity both in the dynamics and in its effects! This complex nonlinearity is ‘simply’ based on the unrecognized complexity of interaction within the fundamental, dynamic unit of the causal loop in the preceding chapter, conceived as dynamic in both the generative process and in the generative structure. Actually it is about the matrix of dynamic interaction within a dynamic relational matrix (cf. Maturana and Varela 1980, p. 122). The real complexity of this seemingly ‘simple’ dynamic unit has been denied for too long. We agree with Morin (2005) that our common concepts of complexity have had the effect of flattening the real complexity of our complex, nonlinear reality and our ways of thinking about it (cf. Morin 2005, p. 259; Mainzer 2000). We may conclude that we have lived in ‘flatland’ for so long in our viewing and doing science in the scientific realms of our sciences (cf. “Flatland”, the classic by Edwin Abbott 1884, in Wimsatt 2007, p. 386, fn. 22). So, it is time to escape flatland and enter new spaces of possibility and domains of potentiality. These are the high-dimensional spaces, described as so-called ‘hyperspaces’ above. We may escape this domain within flatland by taking complexity as generative complexity to be described within these hyperspaces. So, we do not only describe generative complexity as a philosophical concept but also as the foundation stone for a new science of complexity; a science that takes complexity as generative complexity and thereby as self-potentiating in the real, as a fact (see Rescher 1998, p. 28). With our new concept of generative self-potentiating complexity, we may enter the new, complex spaces of possibilities in the diverse scientific realms of our sciences. These spaces can be shown to be kind of hyperspaces, like in the modelling of the complexity of processes and effects of so-called ‘hypercycles’ in diverse networks of cycles (Eigen and Schuster 1979). This modelling shows an increase of complexity with the increase of the network of hypercycles. The concept of generative complexity can now be introduced as the complexity of the so-called ‘cyclical-helical unity’ (Valsiner 1998, p. 251). This unity has the spiral development of the two elements as a fundamental characteristic. That’s why it is called helical, in relation with cyclical! The cyclical, in turn, is related to the loop between the two entities involved. For Valsiner himself, these entities are human beings in their communicative human interaction. The complex, dynamic nature of the causal loop involved is the focus of modelling; that is of the modelling

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of the generative complexity involved in this loop. The causal dynamics of the cyclical-helical unity is conceived both as a generative process and as a generative structure, with effects that are dependent on a mathematical generative function. In the preceding chapters we have sketched this modelling of total causal effects over time within the extended causal framework. So, the cyclical-helical unity brings not only time into the structural causal equations of this unity but also the generative function for the total effects, generated over time. It is this fundamental and foundational generative function that describes the generative ‘production’ of effects within the causal chains of circular causality (Morin 2005, p. 259; von Foerster 1993, p. 230). These are the chains within the repeated cycles running within the loops of the cyclical-helical unity. The vicious cycle, then, becomes a complex, generative, creative cycle, in which “the cause becomes effect and effect becomes cause” (von Foerster 1993, p. 230). This is the foundation stone of a new “language for complexity” (Senge 1990, p. 268; italics in original). It is the very language we need to create a new reality: that of a nonlinear complex reality (Mainzer 2007, p. 16). This new language for complexity is closely linked to a shift of paradigm and of “seeing the world anew” (Senge 1990, p. 68). We agree with Davis (2004) that realities can be conceived very much as ‘language-effected realities’ (p. 99; emphasis added). With Davis, we believe that “language and thought are inseparable” (Davis 2004, p. 110; cf. Vygotsky 1987a, b). From the above reasoning, we may derive that one of the main tasks for a new paradigm of complexity is to develop a new language of complexity to deal with the complexity of real-world complexity, of a potentially nonlinear complex reality. We strongly believe in a new kind of world; that is, of a world that Kauffman (1993) nicely described as “a world of the possible” (p. 375). It is for this reason that we are deeply convinced that the new language may bring such a world of the possible as an expanding world. It is fundamentally and foundationally “a world conceived as a network of relations” (Smolin 1995, p. 290). It is a new world, composed of a dynamic, relational matrix with interaction. So, it is about the dynamics of interaction within a matrix of relations and their relational interaction. But it is more than that. It is also a world of creative cycles, generating hitherto unknown possibilities of potential, nonlinear effects within the hyperspaces as enlarged spaces of the possible. Reality, then, becomes a richer reality. Not only in our description but also in our way of explaining the patterns involved in the matrices and the effects ‘produced’ within these complex, dynamic networks of relations. This kind of enriching reality, of an expanding world “woven together from loops and knots”, of complex networks of relations, is very much a generative, transdisciplinary approach. This generative approach is also of importance for relevant fields in physics, like quantum gravity (see Smolin 1995, p. 290) or biology with their biological networks of complex systems and their changing relations among elements (Kaneko and Tsuda 1996, pp. 14, 179). Lee Smolin is strongly of the opinion that relationalists like Leibniz were right (Smolin 1995, p. 290). We are of the opinion that the relational perspective is very powerful. The ‘loop picture’ of reality, as advocated by Smolin, however, is lacking in its view of entities and relations being complexly interwoven. In our view, both the entities and the relations are dynamic

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in their development over time, evolving potentially nonlinear over time. To become explanatory about the (causal) dynamics involved, we have to introduce new terms like ‘degree of connectivity’, ‘degree of interactivity’ and ‘degree of generativity’. Only then are we able to describe the generative complexity and degrees of complexity that are involved in the real-world dynamics within realworld systems being so much part of real-world complexity, with its ever increasing complexity as inherently self-potentiating (cf. Rescher 1998, pp. 28, 51). All of this comprises a kind of complexification of reality (Rescher 1998, p. 51; emphasis added). This description and use of language, with new complex concepts, has already the power of evoking a different kind of reality: that is, a fundamental, nonlinear complex reality. For becoming explanatory about this new, complex reality we need a corresponding complexification of our sciences (Rescher 1998, p. 51; emphasis added). Our new focus should therefore be on the enlarging of the world of the possible. To understand this enlarged world, we need to accept it as a causal world (Dennett 1984, in Oyama 2000, p. 183), with causal networks and causal dynamics of interaction (Oyama 2000, p. 183). This implies a new way of viewing and doing science, which goes way beyond the science-as-usual. With Morin (2002), we are of the opinion that such complexifying may imply the humanizing of the sciences. In our view it has even strong implications for the humanizing of the being of the human being. The complexification of our sciences opens the possibility of turning the being of the human being into a kind of potentially nonlinear being (cf. Stanley 2005). We want to argue here that the complexification of concern thrives on the complexification of causality, as causal networks operating in a causal world (cf. Dennett, in Oyama 2000, p. 183). It may imply the empowering of the human being, in terms of considering his/her complexity as fully self-­ potentiating indeed. Based on this notion, we may become more fully aware that the limits of our world, of scientists, “cannot be claimed to be the limits of the world” (Rescher 1998, p. 51). So, complexifying may mean for us, as scientists, the expanding of the complexity of the real in our viewing and doing science. It turns reality into a richer reality indeed (cf. Bohm 2004). But the question remains “how to approach this very complexity of reality?”

A Generative Approach of Complexity Our new generative approach of complexity as generative complexity, which is based on the new paradigm of complexity, may also bring forth an expanding of the knowledge about complexity of real-world complexity. That is, of an expanding nonlinear complex reality, being an essential part of the world of the possible. This world of the possible we take as a causal world, with causal networks (cf. Dennett, in Oyama 2000, p. 183). These networks are dynamic, causal networks evolving over time, with their causal dynamics being part and parcel of these networks. This view about complexity means a real shift in thinking about the world we live in. It is impossible to overemphasize this point. It gives power to the notion

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of directionality; that is, the directionality of complexity, which is linked to the notion of increasing effects and of expanding within new spaces of possibility. We may link this expanding, new (causal) world of the possible with the rather unusual notion of ‘quality of complexity’. With Morin (2005), we may start to speak about the ‘constructive’ and dynamic quality to the (causal) cycling loop and about recursion 5 as “indispensable for the concepts of self-generation, self-constitution, and autos” (Morin 2005, p. 259; italics in original). We may think of the causally generative power of this new dynamic unit with its fundamental, self-enhanced loop effect; an effect that is based on the fundamental, generative function of total effects of causal interaction that take place in time and space. Ultimately, we think our description of complexity is about the complex, generative order of the world we live in (Bohm and Peat 2000). To us this is the generative order that is responsible for the kinds of quality that we see around us, like in evolution in general and human development in particular. This is basically the quality of dynamic causal networks of our world. Our concept of ‘generative complexity’ is unifying in the approach of the inherent complexities of reality. This encompasses both the reality of physics (see Smolin 20066) and that of biology as well (see Wimsatt 2007). That makes our topic of the complexity of complexity a fully transdisciplinary topic, of interest for the different disciplines of our sciences.

New Thinking in Complexity Relation is the essence of synthesis (Maturana and Varela 1980, p. 63; emphasis added)

With our new concept of complexity as generative complexity within causal ­networks, we may start to understand what new thinking in complexity is about. In the next chapter we will show how the generative power of generative complexity may be derived from the causal power operating within the loops of reciprocal relationships. Both powers are fuelled by the generative, causal forces operating within causal loops. It is a power that can be facilitated within the causal networks of our causal world, with their characteristic dynamic, causal loops. We think these causal networks are foundational for understanding so-called ‘network systems’

We may stress, again, that recursion not only has the meaning of repetition but also that of a reversing of effects like in reciprocal interaction with reciprocal influences (see Chap. 11, about the meaning of non-recursive relationships). 6  What are really fundamental and also general in this are causality itself and the underlying causal processes and relations of causality (Smolin 2006, pp. 241, 244). Interestingly, the importance of causality in this seems similar to understanding the fundamental role of causality in understanding of the new physics of spacetime (see Smolin’s chapter 15). This makes our approach a real transdisciplinary one. We return to this topic in the last chapter. 5 

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with their loop-like structures as a building block of such network systems (see Wolfram 2002, p. 193). It is this fundamental foundation, based on a ‘relational’ perspective (cf. Emirbayer 1997, p. 281) and on the generative function of the total effects that were developed within the extended causal framework (ECF), sketched in Chap. 11. Inspired by the work of Herbert Simon on ‘The architecture of complexity’, our new thinking in complexity will be about the generative complexity that is linked to the dynamic architecture of complexity of complex network systems. This dynamic architecture is based on dynamic configurations of causal, interconnected loop networks; configurations that may evolve into ‘bootstrapping configurations’ over time (see Alexander 2002). We will make a link between the fundamental, the new notion of generative complexity and the practical: how it manifests itself in the fundamental generative order in all areas of experience (Bohm and Peat 2000, p. 157), including that of human, creative experience (cf. Follett 1924). We consider this generative order as fundamentally characteristic of our nonlinear, complex reality; a reality that goes beyond the limited segment of reality that is the focus of social sciences, operating as usual. To be more specific, the generative stance taken here is about the generative dynamics of development of this dynamic architecture of complexity, with its focus on generative principles, generative mechanisms and generative structures. They are the basic tools for conceptualizing hitherto unknown generative spaces, as spaces of possibility, with their potentially unlimited possibilities. Based on this kind of conceptualization of complexity, we may understand that complexity can become self-potentiating as a fact (see Rescher 1998, p. 28; emphasis added). This kind of self-potentiating power of complexity, as resultant of a generative power, operative within the dynamics of causal networks, can be called ‘the quality of complexity’. This quality of complexity is essentially a dynamic kind of quality, which is generated through the (causal) dynamics involved in generative complexity! What is brought about in the very process of interaction, with the shaping forces at ‘work’, becomes generative for the next stage of the process. In short, the process has become self-generative, with self-potentiating power. This power has effects on the intra-generative processes that can become self-potentiating too! This self-potentiating nature of intra-­ generative processes may be described as a state of being of the elements involved in interaction. It is a state of being, which can be linked with the notion of generativity. Leslie Sassone (1996) links this state of being to a norm as well: “As a norm generativity is the power of constituting the individual directed by that individual to becoming a being in-and-for-self” (p. 519; emphasis added). This power of ­constituting as a process of becoming, directed by that individual, can now be taken as a self-generative process. Generativity, then, is the cause and effect in this very complex generative kind of process! It is impossible to overemphasize the significance of this contention. It goes way beyond the Central Dogma of science (see Oyama 19897), of a simple one-way flow of influencing (p. 7). We are now able to

Susan Oyama links this dogma here to a publication of Francis Crick (1957).

7 

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afford a new description of the complexity of processes involved in this. The generative forces operating in the self-generative process of bi-directional influences and shaping forces, exerted in the interaction, are ultimately responsible for the generative, self-potentiating power of the elements in the complex, causal dynamics of interaction. Generativity, understood this way, can now be described as a fundamental quality of complexity of the state the elements can acquire by the generative nature of the processes of interaction. By linking this concept to a degree of generativity, we may find a measure of complexity, which is a fluid kind of measure. This kind of new thinking brings us to the problem of language, again! Without the introduction of a new language that encompasses the notions of (degree of) generativity and the notion of degree of quality of fluid complexity, we cannot overcome the hindrance of functioning prejudices upon which our language is based and become really fully explanatory about the complex processes involved (cf. Nietzsche, in Sassone 1996, p. 516). Only with this new language we may start to decode reality and doing so, overcome the Central Dogma still dominating our “science as usual” (Longino and Doell, in Oyama 2000, p. 147). It is time indeed to escape this science as usual and to start delivering a new kind of reality, which is very much a kind of language-effected reality. The new reality takes complexity not for granted but as a serious topic of study. That is, the topic of a nonlinear complex reality, to be taken as a so-called “meeting ground between code and flux” (Sassone 1996, p. 516, referring to Nietzsche, again) for our sciences; that is, for the sciences in general and the new science of complexity in particular. From this stance, we finally arrive at the formulation of a new agenda for our sciences. It is from this new agenda that we may build a new science that transforms our sciences. The transformation we propose here will ultimately transform the “bad” science, the science as usual (cf. Longino and Doell, in Oyama 2000, p. 147), into a better kind of science; that is, of “good” science (Keller 1985, p. 126). This may be described as the good science we need “to help us shape the future in the best way” (see Scheffer 2009, p. 8). Our own focus will be very much on the transformation of the social sciences and humanities, to promote a more productive way of thinking for the sake of a fruitful expanding of our conception of science. That is: a new science that enlarges our vision of both nature and science and, in doing so, contributes to the effectiveness of science in general in shaping the future of humanity and society at large (see Keller 1985, pp. 134, 6). Ultimately, we hope to turn the dominating science as usual into a new science: “a new science that might, by its very nature, better integrate knowledge and wisdom” (Senge et al. 2005, p. 188; emphasis added). Such a science may be integrative for a new view, opening a new window to the world. This will be a window that encompasses not only a new window but also a new culture. We may refer here to Ulanowicz’s proposal for “A Third Window” (Ulanowicz 2009) and the book “The Third Culture” by John Brockman (1995). We may refer as well to the “third-way approach”, sketched by Sotolongo (2007, p. 120). All of this may be opening for a “third discourse”, linking the fundamental with the practical, that of lived experience (see Starobinski 2003, p. 218).

Chapter 14

The Complexity of Human Interaction

complexity enhancement is a fact of life in nature (Rescher 1998, p. 6)

Introduction We may extend the complexity of our framework of causal modelling of interaction by introducing new, more complex entities like those of more complex systems, as a way of modelling complex organisms, instead of latent variables only. Such organisms can be relatively simple organisms or more complex organisms. Because this book has a focus on new thinking in complexity for the Social Sciences and Humanities, we take the human beings as subject of study as complex human organisms. In this section we want to describe, understand and explain human beings in their interaction. We take this interaction as a dynamic process of communicative human interaction; a process with influencing each other and having effects on each other in the interaction. These effects may become beneficial for both partners in this interaction. In its most advantageous description, we may speak about humans “bootstrapping each other” in such interaction, within small (sub) communities (cf. Bruner 1996, p. 21). These communities can be units like dyads or ensembles; these ensembles may also be ‘ensemble systems’ (Ulanowicz 2009, p. 97). This bootstrapping can be taken as a specific example of the more general case, describing how such systems may shape each other in interaction by mutual simultaneously shaping forces (Lincoln and Guba 1985). It shows how “the members of the system collectively make one another” (Kauffman 1993, p. 371; italics in original). To become explanatory about this bootstrapping as a possibility of shaping by human interaction, in terms of understanding the mechanisms involved in this complex kind of interaction, we need to recognize that “a wholly different way of viewing relationships and interactions is required” (Lincoln and Guba 1985, p. 150). Our focus is on making the link between the fundamental and the practical, to open up and enlarge the spaces of the possible within unknown domains, which are so much part of ‘the realm of possibility’ (Rescher 1998, p. xv;

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_14, © Springer Science+Business Media B.V. 2011

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see also Osberg 2009; Jörg 2009). We mean here domains of potentiality, with complexity to be taken as self-potentiating (Rescher 1998, p. 28) and functioning as such, in terms of what Kauffman describes as functional “bootstrapping” (Kauffman 1993, p. 373). All of this can be very relevant for practice in the field of Social Sciences and Humanities, like e.g., in the field of learning and education (Bruner 1996; Barab and Kirshner 2002; Davis 2004; Davis and Sumara 2006; Lemke and Sabelli 2008; Osberg 2009; Jörg 2009, 2010a, b). With Lemke and Sabelli (2009), we may realize that “the education system is one of the most complex and challenging systems for research” (p. 128). A system that we think is so much in need for “a change in the paradigms of our thinking about research on education” (Lemke and Sabelli 2009, p. 128; emphasis added; see Jörg et al. 2007; Jörg 2009, 2010a, b).

Modelling the Complexity of Human Interaction We may start by expanding the simple picture of social inter-action between two human beings A and B by taking their intra-action into account: intra-interaction of elements within the organisms to be studied: see Fig.  14.1 below. With two organisms, we may speak about the inter-action between the two organisms with their intra-action taking place within the two organisms, which is human beings here. This is an extension of the cyclical-helical unity we described before. In Chap. 11 we presented the figure as the one below about the complexity of two complex entities, in their complex inter-action between intra-action: see Fig. 14.2 below, with the complexity of intra-action inside the two separate entities A and B. We may think of A and B as human beings, with their many relevant (latent) variables ai and bj ‘operating’ both inside A and B and between A and B. So, we have the complex inter-dynamics between and the intra-dynamics of interaction within A and B as complex units. The dynamics involved we take as complex, generative, causal dynamics. Together the (three) dynamic complexities constitute the full complexity of A and B in their complex interaction. In Fig. 14.2 we have added the interaction with the environment: both the inter­ action of A and that of B with the environment. This rather complex figure offers the possibility of introducing the notion of ‘bootstrapping’ as a fundamental and complex

Fig. 14.1  Picture of simple human interaction as reciprocal interaction (From Akkerman and Niessen (2011). With permission of the authors)

Modelling the Complexity of Human Interaction Fig. 14.2  A complex representation of human interaction between A and B including their own, specific intra-action

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process for the description and explanation of development of the separate entities A and B. This process can be conceived as being essentially about evolvability, to be conceived as a fundamental capability of both entities in their interaction. We may, thus, develop the terms and the shared terminology of a new language, making it possible to speak about ‘bootstrapping’ in terms of ‘interactive expansion’ and strengthening relationships. Such expansion and strengthening may take place within the complex web of structural dependencies that is involved in the complex picture of Fig. 14.2 This expansion of the model may bring us closer to what bootstrapping can be in its full extension in our complex modelling of interaction: an explanatory tool for understanding the complex, nonlinear reality. Above we defined ‘bootstrapping’, in terms of “use of existing resources or capabilities to raise (oneself) to a new situation or state” (Oxford English Dictionary). We think we are now more able to elaborate on that definition from our new thinking in complexity. In Fig.  14.2, the two entities A and B are pictured to have the opportunity to ‘use’ the environment as a resource. This opportunity has the potential to enable and foster the capability to evolve. Thus, A and B can modify or improve themselves “by making use of what is already present”; that is, present within the given environment for both partners in their interaction. Bootstrapping in this sense has a direct connection with the power to generate through interaction with the other

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partner and with their shared environment. This means that through a high quality of interaction and quality of reciprocal relationship among A and B, both entities may be turned into a state of so-called ‘generativity’, as a complex state of being (Sassone 1996, p. 519). Such a state is in essence a state of potentially generating expansion, in terms of opening spaces of possibility for both A and B. This gets very close to what Bruner (1996) described as “bootstrapping each other in small (sub) communities” like dyads, ensembles and ensemble systems. For Bruner, however, this notion was very much an intuitive notion, for he gave no details whatsoever about the processes involved in his use of the term ‘bootstrapping’. In a more sophisticated terminology, we may also describe the bootstrapping processes involved as “self-generative or self-sustaining processes” (in Webster’s Dictionary). These rather complex descriptions of processes with their generative bootstrapping effects may show the evolvability of the two entities within so-called ‘generative spaces of possibility’. These generative spaces are complex n-dimensional spaces. They can be described as so-called ‘hyper-spaces’, in which many variables can be represented in their co-evolving over time. We may view these variables as well as complex, dynamic landscapes within these hyperspaces of (potential) total effects. We return to this topic below. By understanding more fully and fundamentally the concept of bootstrapping, we may become not only more descriptive but also more explanatory about human beings that may bootstrap each other in their interaction, within a shared environment. Below, we make a start in becoming explanatory about the real complexity involved in these processes as fundamental processes of development and evolvability.

The Need for New Tools for the Description and Explanation of Generative Complexity In this section we want to be more specific, both theoretically and technically, about the new tools for describing and explaining the complexity involved in the development and evolvability of complex, fluid entities like human beings in their interaction. We want to address the theoretical and practical challenge of answering the still unanswered question about the complexity of real-world complexity. How can ‘simple’ complexity become generative complexity in the real? And how does it actually ‘work’ in reality, as part of the complexity of the real? How does this question connect to the concept of evolvability, which is so important in theorizing on evolution? Finding answers to these complex questions may bring us also nearer to the other, more fundamental but also still unanswered question “What is life?”, put forward by different scientists like Kunihiko Kaneko (2006, p. v) and others as well (e.g., Eigen 1992; Rosen 2000; Solé and Goodwin 2006). We interpret this question not only as a question about evolution but also about the dynamics of ‘life itself’ (see title of book by Rosen 2000). Our focus is on the complex dynamics of life of human beings in their complex human interaction over time. How can we become more explanatory about these fundamental but largely ignored questions?

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To find the answers to these complex questions, we are badly in need of more complex tools. There is a basic truth in the statement that we urgently need complexity as a scientific tool to be able to deal with the complexity of the real: that is, of real life. Below we start with developing the new tools of thinking in complexity that is meant to become part and parcel of the new complexity paradigm; a paradigm that can become the foundation for a new science of complexity. This new science we conceive to be a real transdisciplinary science.

What Makes Complexity Generative? Below, in Box 14.1, the basic dynamic relationship between inter-action and intraaction is shown, in terms of the generative processes that may take place in the complex interaction like between organisms in general and the interaction between human beings in particular. We concentrate here specifically on the last. For simplicity we have sketched the interaction with the symbol for cooperative interaction. We may read this interaction as well as the coincidental interaction or with the symbol for the stronger version of cooperative interaction. In Chap. 8 we showed the total effects of the causal interaction between A and B within the extended causal framework. The generative, potentially nonlinear total effects of causal interaction constitute the foundation of the new complexity paradigm.

The Complexity Paradigm In the rest of this chapter, we will build upon the results of the new framework of thinking in complexity, which is essential for the new complexity paradigm. We start with the generative complexity that can be derived from the basic causal interaction within the unit of the ensemble, to be taken as the cyclical-helical unity of two entities in their interaction within a (reciprocal) interactive relationship. Figure  14.3 shows the two functions of the total effects on A (left) and on B (right), which are the two generative functions we developed within the extended

Box 14.1  Schematic View of Generative Processes of Inter-Action Between Intra-Action intragenerative processes

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causal framework for A and for B (see Chap. 8). They show the potential values for the generative functions under the condition that the absolute value of the product b1*b2 is lower than 1. This limits a region within the ground plane of b1and b2. In the 3-D space of the total effects we1 may distinguish different regions: the flat region where the two values b1 and b2 have low values,2 say for example between −.50 and .50. In this region the total effects of the generative functions are low. So, their values are linked with the flat region. The situation becomes different when the values for the two b’s increase in the course of time.3 This may happen in the shortterm (of a split second, like in a neuronal network), in the medium-term (like in human interaction), or in the long-term (of centuries for cultural processes, or even era like in evolutionary processes). In this case, the total effects of the generative functions may go beyond the flat region and may increase nonlinearly over time. In Fig. 14.3, we have pictured a red line in the 3-D function for both A and B as two single so-called ‘latent variables’ within the causal framework. The red lines show the increase of total effects on the latent variables concerned; an increase that depends only on the values of the two b’s involved: of the direct effects of A and B on one another. These b’s may increase or decrease in the course of time: see Fig. 14.3. This shows also what happens in case of increasing b’s. The red lines represent the trajectories of causal strengthening of the effects, that is, of the generative functions for the total effects on A and B, in and through causal interaction over time. This increase happens in general with increasing values of each of the two b’s. For the reasons of such an increase of the two b’s, we turn to the below.  This black line in the print version is somewhat harder to see.  This is commonly based on the low values for correlations between the variables as measured in actual research. 3  We may remind the reader that the generative functions of the total effects on A and on B are not dependent on time as a variable itself but only indirectly through increase of the b-values in the course of time. 1 2

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The red lines show the potential of strengthening that may be engendered (only) through increasing quality of interaction (QoI) between A and B. That means, in general, of the interaction modelled as reciprocal causal interaction within a reciprocal, interactive relationship that may show an increasing quality of the (reciprocal) relationship (QoRR) between A and B. Increasing quality means an increasing value of the two b’s, both reaching to values above 0.70 but less than 1.00. For reasons of simplicity only, we have pictured the same trajectory of the red line for A and for B, as a path in the 3-D space of the generative functions of both (latent) variables in Fig. 14.3. But the interaction, as sketched above, needs not to be symmetric at all, as we saw in Chap. 8. The red path of strengthening is about the generation of effects, described by the two generative functions; that is of the total effects of causal interaction on A and on B, as resulting from their interaction, evolving over time, as we have shown in Chap. 8. From the description above, we may become aware that, although the strengthening is a result of rather simple causal modelling of such reciprocal interaction within reciprocal relationships, this result of modelling affords the tool for showing how complex bootstrapping may actually take place as a process in the real; not only in human interaction but in interaction between organisms in general. We may remind the reader that the path of the red line, as an expression of the total causal effect, is dependent on the two b’s involved in the modelling of the causal interaction. These two b’s, in turn, are numbers whose dimensions are units of change in the dependent variable per unit change in the independent variable (see e.g., Duncan 1975, p. 162). The two b’s express the structural relationships between latent variables (LV’s); in this case, the two latent variables A and B. The underlying individual variables of these latent variables involved (underlying the latent variables) may be qualitative or quantitative (Duncan 1975, p. 162).

Distinctions to Be Made It is important to make a distinction between two single latent variables A and B, as kind of fluid entities in causal interaction and the human interaction between two partners A and B, with their communicative human responses (Stacey 2001, 2003). With symbols we make the distinction as follows: see Box 14.2.

Box 14.2  Two Different Representations of A and B in Interaction A and B as latent variables A and B as human beings

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Box 14.3  Different Representations of A and B in Their Different Kinds of Interaction

intragenerative process of cooperative intra-action

intergenerative process of cooperative inter-action

intragenerative process of cooperative intra-action

Of course, we may also put the two other kinds of interaction, and within this picture in Box  14.3: that is, both for the single inter-action and for the intra-action within A and B . Mostly, however, we shall choose the case of for cooperative action, for reasons of simplicity. With these notations for use, we may show the real complexity of the models of interaction, i.e., that of human interaction, with their complex inter-action between intra-interaction, being both generative kinds of processes. We can easily extend this picture and show more complex forms. Further on, we shall focus on this extension, to show the tremendous complexity we need to model to make the link with the real-world complexity, with their nonlinear total effects over time. These total effects are the foundation for sketching the landscapes of states of being of A and B as dynamic landscapes within hyperspaces, as high-dimensional generative hyper-spaces, with their potential nonlinear total effects over time. Ultimately, all of this enables the description and explanation of what we may call “the enhancement of complexity” (Rescher 1998, p. 6). With Rescher, we are convinced this enhancement of complexity to be “a fact of life in nature” (Rescher 1998, p. 6). So, we finally come closer to what Rescher has called “the complexity of the real”, in his book on complexity (title of Chap. 4). With Rescher, we believe this enhancement of complexity may turn complexity into a dynamic of self-potentiating; not just as a description but as a fact (Rescher 1998, p. 28; emphasis added). With him, we believe this view of complexity enhancement to be “entirely naturalistic and nonteleological” (Rescher 1998, p. 5; cf. Lincoln and Guba 1985, p. 7, on the meaning of their proposed naturalistic paradigm).4 For us, and for the new paradigm of complexity, this means the ultimate challenge for a new generative approach, complexly heading to become explanatory about this complexity, conceived as a kind of ontological complexity of the real. We may only become explanatory  Interestingly, they use descriptions like e.g., postpositivistic, qualitative, hermeneutic and humanistic as alternative aliases for this paradigm (p. 7).

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about this complexity by building a ‘tower of complexity’, as a new tool for use in our new thinking in complexity (Lincoln and Guba 1985, p. xiii); that is, for the understanding and explanation of reality as a potential, nonlinear complex reality (see Mainzer 2007, p. 16, p. 434).

The Enhancement of Complexity The new tools of thinking we developed above, as well as the new metaphors in use, afford the entry for thinking about within-level and between-levels of causation, as forms of multi-level causation, with multiple causes operating between the entities concerned. These forms of causation are considered to be part and parcel of complex, multi-layered networks (see e.g., Rose 1997, pp. 304–305). These new tools of thinking (that is of thinking in complexity) afford the entry for new thinking about the richness of interactions between cooperatively relating organisms (Rose 1997, p. 259) and about complexity enhancement as a fact of life in nature (see quote by Rescher, above). Such thinking may explain the choreography of the causal dynamics involved, as mutually shaping forces (see Lincoln and Guba 1985), operating within the complex, multi-layered networks and their webbed architecture of complexity. This can be architecture of bootstrapping configurations. So, we can finally link this notion with the generative processes of bootstrapping and their potential nonlinear effects over time. We can view this bootstrapping as a kind of dynamic interweaving within a learning net; that is, as a web-like structure with different interdependent levels (Rosen 1970, pp. 242–243). We may speak, then, about organisms as a kind of fluid, dynamic entities, with (self-) generative mechanisms operating within dynamic units, with generativity as potential (new) states of being of these organisms. The dynamics of this operation may play a role in phenomena like morphogenesis and even metamorphosis (Goethe 2009/1790; Vygotsky 1978, 1981). These are considered, now, to be based on the notions of the quality of interaction (QoI) and the quality of reciprocal relationships (QoRR), as well as the degrees of interactivity, cooperativity, connectivity, generativity, complexity, evolvability, plasticity and stability of web-like structures of complex webs with their webbed networks and webbed architecture (cf. Kauffman 1993, 1995a, b): see Picture 14.1. Based on such terms and terminology we may open a new perspective and start to think about such complex kinds of powerful web-like structures. Their power is based on the causal power of complex causal networks, with their causal dynamics and potential nonlinear effects over time. This opens a view of the complex web, in terms of “the web that governs its own possibilities of transformation” (Kauffman 1993, p. 370). We may even start to think about entities that mutually transform one another. This kind of opening and enlarging the space of the possible is opening a new world of the possible: that of a nonlinear complex reality (Kauffman 1993; Mainzer 2007).

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Picture 14.1  Nerves of a leaf by Lu’u Ly, from Wikimedia

Below, we develop the complexities involved in modelling the causal dynamics of interaction, which we think is representative for the interactions that take place between (inter) and within (intra) the human beings in their human interaction, conceived as inter-action. To give an idea, we may speak about the complex interaction between intra-action as that of the dynamics of interactional complexity and intra-actional complexity within each of the two entities involved in this ­inter-action. This kind of conceptualizing the complexity involved in interaction is conceived as the very building stone for the description and explanation of the dynamics of generative complexity of interaction in the real. We think it has the potential of qualitative transformation through processes of spiral development to higher levels, enabling for morphogenetic changes, possibly leading even to the complex process of metamorphosis (see the work of Vygotsky, e.g., 1978, chapter 5; Vygotsky 1981). Doing so, we think we get very close to the wonder of Nietzsche about the complexities of reality. Ultimately, we believe that the use of all of these tools for new thinking in complexity and modelling complexity may be really explanatory of the fabric of what Rescher described as “the complexity of the real” (Rescher 1998, chapter 2). With Ulanowicz (2009), we believe this complex fabric can be conceived as ‘a fabric of causality’ (p. 56). This complex fabric, we argue, has the potential of becoming really explanatory about “the nature of the fabric of nature” (p. 55). With these complex, explanatory tools of thinking and modelling, we may become explanatory about the dynamic interweaving of complexity and the shaping forces exerted by such interweaving; an interweaving that explains the full dynamics of generative complexity as self-potentiating (Rescher 1998, p. 3). With these tools we may become explanatory about the complex phenomena in nature and of the real-world complexity of our inherently complex, nonlinear reality (Rose 1997, p. 164; see also

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Box 14.4  The Challenges to Face for a General Theory of Complexity The theoretical challenge is to become explanatory of life itself: to develop a new way to answer the still unanswered question “What is life?” (Kaneko 2006, p. v; cf. von der Malsburg 2009) The practical challenge is to get closer to “learning characteristics of real organisms” (Rosen 1970, p. 245).

Rosen 2000; Mainzer 2007, p. 16, p. 434). With these tools we may face some fundamental challenges of new thinking in complexity about real-world complexity: see Box 14.4. The ultimate theoretical challenge is to face this complexity and the complexity enhancement as being part of “the complexity of the world” (Luhmann 2002, p. 157), as a fact of life in nature (Rescher 1998, p. 6) and of life itself (Kaneko 2006, p. v). This complexity of the real and of nature, we call ‘real-world complexity’. We take Rescher’s description of this complexity seriously, where he states that “the world’s complexity means that there is, now and always, more to reality than our science is able to dream of” (Rescher 1998, p. 28; emphasis added). It is this complexity that enlarges the space of the possible within an unexplored world of the possible (cf. Kauffman 1993). We think this is very much the complexity, still denied by so many scientists in different fields of science and their various disciplines. With the new paradigm of complexity, of generative complexity, we may obviate the ever-present reductionistic stance, which still dominates our sciences in general and the social sciences and humanities in particular. Our paradigm of complexity aims to be a full transdisciplinary paradigm for all of our sciences! The practical challenge is to get closer to “learning characteristics of real organisms” (Rosen 1970, p. 245): see Box 14.4. To do so, we need the new paradigm of complexity; the new paradigm that leaves behind the misunderstood work of Newton and the Newtonian paradigm (Rose 1997; Ulanowicz 2009), wrongly based on this deep misunderstanding. The paradigm of complexity, we think, is the paradigm long sought for (Rose 1997; Rosen 2000; Kaneko 2006; von der Malsburg 2009; Reid 2007). Becoming more fully explanatory about kinds of complexity as a generative kind of complexity, we may ultimately become able to address the still unanswered question “What is life?” (Kaneko 2006, p. v) We may find the answer by exploring the generative causes of evolution (see Reid 2007, p. xiv), by inventing a causal theory of evolution (Reid 2007, p. 23), thereby replacing Darwin’s causal theory, which was fundamentally wrong (Reid 2007, p. xiv). This is, however, not the topic of this book (see Jörg 2012). But we may learn from this new entry that we may open up a new vista perspective: not only about generative causes but also about the complexity of “causal matrices that are mutually influential” (Reid 2007, p. 322), with their mutually shaping forces exerted in the causal interaction. But for dealing

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with this kind of complexity we urgently need more complex modelling of the complexities involved.

Complex Modelling of the Complexity of Complexity From the information, presented above, we may derive the following presentation of modelling interaction: see Fig. 14.4 below, for the case of two human beings A and B in their different forms and qualities of interaction. The symbol for inter-action between A and B is taken to be for coincidental inter-action, for cooperative inter-action and the symbol for cooperative inter-action within a loop. For the intra-action within A and B , we have the symbol of for coincidental intra-action, the symbol for cooperative intra-action and for cooperative intra-action within a loop within A and B . The pictured forms in Fig. 14.4 are the somewhat extreme, pure forms of interaction. Of course, we may put different forms as mixed forms at these places, such as B

A

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coincidental intra-action

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cooperative intra-action

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cooperative intra-action within a loop

Fig. 14.4  Human beings A and B in their three different kinds of inter- action between the three different kinds of intra-action within A and B

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for example . It is hard to tell in advance if all combinations are realistic. Only practice may tell. Most importantly, we may see in this Fig. 14.4 an increase of strength or quality of inter-action between A and B from top to bottom. We may link this increase of strength with the concepts of ‘strong interaction’ within a loop and that of ‘causal power’ of such interaction within a loop. Consequently, we may also speak about the potential weak form of interaction of coincidental interaction between A and B . The reader may be aware that this has consequences for the nature of complexity involved in these cases, in terms of the quality for what we may call ‘interactional complexity’. This kind of interactional complexity, in turn, is the base for the socalled ‘generative complexity’, mentioned before. We may expect the more complex generative complexity as more applicable for the bottom case in Fig. 14.4 and coincidental complexity for the case at the top of this figure. Now, we may take the steps from viewing complexity as interactional complexity, to more dynamic forms of complexity, such as generative complexity, which are linked to different forms of hyper-structures of latent variables, conceived as networks, evolving over time. We may be able to show that these hyperstructures, with interaction within interconnected loop networks, are evolving potentially nonlinear in their dynamics and also in their effects over time. Doing so, we can extend the language in use in our sciences, of use for the description of the complexities involved in interactional and generative complexity. By using this language, we hope to create a language-effected reality that corresponds as closely as possible with the real-world complexity of a nonlinear complex reality (Mainzer 2007, p. 16, p. 434).

Dynamics of Complexity of Interaction We are now able to connect the different kinds of interaction between A and B and their total effects over time. In Fig.  14.5 the three different kinds of interaction between latent variables A and B are symbolically represented. Based on this kind of representation of kinds of interaction we may derive the much more complex interaction between A and B as human beings with their potentially complex intra- action between latent variables. These kinds of intraaction may have their different quality of interaction (QoI) taking place inside the two human beings with different qualities of reciprocal interactive relationships (QoRR) between latent variables inside each of them: see Fig.  14.6. From the

Fig. 14.5  Symbolic representation of causal interaction between latent variables A and B

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220 Fig. 14.6  Same as above for A and B as human beings with their intra-action

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r­ epresentations in this figure we may derive different kinds of potential effects. These effects may increase from top to bottom, with increasing QoI within increasing QoRR within the loops between the entities involved: both of the latent variables inside and those between the two human beings A and B . Again, we may view an increase in the complexity of interaction from top to bottom. That is, in the qualities of interaction and of the strengths of interactive relationships: both within and between the two human beings in their complex interaction. For the main combinations of interactions we may refer to Annex 14.1. Based on the distinctions of complex interaction we may distinguish different kinds of total effects of the generative functions about different kinds of interactions involved, taking place both inside and between A and B . In Fig. 14.7, below, we have visualized the potential total effects of the interactions inside and between A and B for the common case of cooperative interaction. That is, for the cooperative interaction: both within and between A and B . For reasons of clarity we present only the total effects within A and B . The focus is on the complex dynamics of intra-action between the latent variables X and Y within A and B . Figure 14.7 below we may interpret as follows. Inside both A and B we see the cooperative intra-action between two latent variables, say XA and YA for A and XB and YB for B . We also see the 3-D spaces of the potential total effects for the generative functions of these effects in case of increase over time, expressed as the trajectories of total effects in these 3-D spaces. In case of A two b’s are involved in the modelling of the (causal) interaction inside of A . Similarly, two b’s are involved in the modelling of the (causal) interaction inside of B . But there are also two b’s involved in the modelling of the (causal) interaction between A and B . So, we have six b’s in total, with different values. These values are fluid, evolving over time. With all the complexities involved it is hard to tell what will happen in advance. But potentially strange things may happen. We think of the possibility of complexity as self-enhancing and selfpotentiating, as clear potentialities of the real (see Rescher 1998).

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Fig. 14.8  State hyperspaces for A and B with effects, depending on the internal latent variables X and Y within A and B (Derived from Mainzer 2007, Fig. 9.4b. With permission)

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Landscapes of Effects Within State Hyperspaces We may extend our description of complexity by introducing more complex kind of effects of ensembles of systems with their inter-action on each other. This description is based on the generative functions of total effects, as modelled within the ECF. If two latent variables have nonlinear total effects on each other, as shown by their trajectories (see the red, or black, lines above, in Fig. 14.3), they may have a composite total effect on a third latent variable. This composite effect can have a kind of unitary effect on the system as a whole, e.g., its level of energy: see Fig. 14.8, below. In Globus (1995), an example is given of a state space of bipolar order (p. 94). In Annex 14.2 a representation is given of a complex landscape of states within a state hyperspace; in this case a 3-dimensional space. In Fig. 14.8 below, we have sketched the basic idea about such a state space. It shows a visualization in three dimensions, of a potential landscape in three dimensions (copy of Fig.  9.4b, in Mainzer 2007, p. 429). This picture can be extended to more complex possible landscapes. In Annex 14.2, an illustration is given of the possible complexity of effects for a complex system like the human being, which is derived from the field of psychiatry and brain research. It shows Globus’s visualization of the potential complexity of a landscape of composite effects of relevant latent variables within the state hyperspace. These composite effects are about an energy level that depends on the two latent variables of concern here: the affect variable and the motor activity in the brain (see Annex 14.2). It shows the complex possibilities of states of being, being so much part of the complex system of the living human being, like depression and mania, which are states within the same landscape of effects, in this case only depending on the value for the two relevant latent variables: affect and motor activity. So, the landscape in this picture may be conceived as a complex domain of potentialities of states of being or as a landscape of possibilities of states of being. Of course, the actual landscape is a dynamic kind landscape, which is evolving over time. Again, such a landscape may evolve over time without being dependent on time as a variable! This figure shows only one single, complex landscape of possibilities for only two latent variables, for a single human being B . It is easy to imagine how the picture of the landscapes can be extended to more dimensions and to more (complex) systems, in high-dimensional, so-called ‘state hyperspaces’ (Globus 1995). The landscape in the figure shows that the effects are not linear but sensitive for the values of the latent variables of concern here. It is good to stress that this example from Globus’s work is taken only for illustration, to show the complexities that are possible to think of, when we speak about the complexity of the real (Rescher 1998). In a way, it may illustrate how complexity can become actually self-potentiating in the real, for the good or the bad. The suggestion of the picture of a landscape within a state hyperspace may be one of being evidencebased, thereby supporting Mainzer’s assessment that “neural and psychic forms of illness can be interpreted as complex states in a nonlinear system of high sensitivity” (Mainzer 2007, p. 11). With Rose we are also convinced that “there is not and cannot

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Box 14.5  Excerpts from Sara Maitland’s Book A Book of Silence “And there, quite suddenly and unexpectedly, I slipped a gear, or something like that. There was not me and the landscape, but a kind of oneness: a connection as though my skin had been blown off. More than that – as though the molecules and atoms I am made of had reunited themselves with the molecules and atoms that the rest of the world is made of. I felt absolutely connected to everything. It was very brief, but it was a total moment. I cannot remember feeling that extraordinary sense of connectedness since I was a small child” (p. 63) “For several hours I enjoyed an extraordinary rhythmical sequence of emotions – great waves of delight, gratitude and peace; a realization of how much I had done in the last six weeks, how far I had travelled; a powerful surge of hope and possibility for myself and my future; and above all a sense of privilege. But also a nakedness or openness that needed to be honoured somehow” (p. 77) “For a short while I was absorbed in joy. I was dancing my joy, dancing, and flowing with energy” (p. 77) “[my specific experiences of silence] had begun to teach me better, and now I was finding more and more complexity. The more silences I looked at, the more silent places I went to, the more I became aware that there were dense, interwoven strands of different silences” (p. 186) “I came to feel that it [that is, the choosing to be solitary and the choice of silence] really is about going down (or in/up/through/over) a level internally” (p. 240)

be any straightforward one-for-one relationship between the complexities of our mental experiences and the simplicity of a single biochemical measure” (Rose 2006, p. 237). In the work of the writer Sara Maitland (2008), a nice example is given of her (mental) experiences with exploring the ‘working’ of silence, which showed to be unexpectedly and surprisingly so much different for different circumstances in which silence can be experienced. She speaks about the creative, generative power of silence (p. 126). In Box 14.5 some of her impressions are given about the real effects of her personal experience of this very power of silence. The point of interest here is that they are a nice illustration concerning the complexity of the real (Rescher 1998). She concludes that “we deny the reality of silence, we reduce it to a lack of absence and make it powerless” (p. 130; emphasis added). This reduction, we argue, is very similar to the reduction of complexity in our history of the sciences, making it powerless, where it can actually also be taken as self-potentiating, as a fact (see Rescher 1998, p. 28). This means that it can be taken as part of an essentially nonlinear complex reality (Mainzer 2007, p. 16, p. 434). In the last quotes in Box 14.5 Sara

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Maitland addresses her discovery: that is, her “finding of more and more complexity” (emphasis added), about deeply layered levels of an internal reality. This is of interest because Rescher, as a philosopher, is also describing a kind of philosophical discovery process, one of exploring reality, in which he describes the complexity of the real as a fact. He links this notion of what may be called ‘evidence-based complexity’ with various linked notions of complexity, like ‘descriptive complexity’, ‘generative complexity’ and ‘ontological complexity’ (Rescher 1998, pp. 7–9). Of course there is a difference between “our conception of reality and reality as it really is” (p. 124; emphasis in original). Similarly, it is true that “the world that we describe is one thing, the world, as we describe it is another” (Rescher 1998, p. 124; emphasis in original). In his wonderful book about complexity, he manages to escape the reduction of complexity that has such a long history: both in philosophy and in our sciences. This brings him to a linking of complexity in terms of complexity enhancement being “a fact of life in nature” (p. 6), which needs “a theory of complexity self-potentiation” (Rescher 1998, p. 6). His view of complexity is basically opening new levels of reality, which is fully corresponding to our idea of a layered kind of reality with deeply layered, dynamically interconnected loop networks. We would like to stress that our new thinking in complexity may afford the tools of thinking about our world, which can be conceived as being part of what Rescher (1998) calls ‘a chaotic universe of chance’ (p. 207) and “to see such a world as the stage for the self-generation of order” (Rescher 1998, p. 207; emphasis added). This view about the world can be linked to the notion of creativity and that of ontological creativity. We fully agree with Bohm and Peat (2000) that this notion of a natural kind of creativity in nature can be taken as opening the possibility “for creativity to operate within a causal framework” (p. 97). This original view corresponds with our causal thinking about the causal dynamics operating within the extended causal framework delineated in Chap. 11, which showed the role of the generative functions describing the total causal effects of causal interaction within reciprocal relationships over time. These total effects can also be taken as generative effects, which are ‘at work’ in real-world complexity, with its real-world dynamics in our real world. With Rescher (1998), we are convinced that “complexity cannot emerge and persist without order” (p. 199). We are also convinced that the order of our world is in essence a generative order (cf. Bohm and Peat 2000, p. 202, referring to the work of Goethe; see also Alexander 2002, on the nature of natural order in the world we live in). This process of generation of order can be linked with the notion of “free play5” and that of organisms that may enter “a state of ‘free play’” (Alexander 2002, p. 203). This is the very kind of dynamics of a mental state that Sara Maitland seems to describe in the ‘working’ of silence on her, being at work in her experience of silence over time. Her descriptions in different conditions of silence give the strong impression that the state she gets in is a kind of “promoting its own flow” (Globus 1995, p. 89). This process can be viewed as demonstrating a kind of self-generative,  We may refer here to Freud’s conception of the mental, about mental phenomena as “brought about by the play of forces in the mind”, in his “General introduction to psychoanalysis” (see Globus 1995, p. 109).

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self-potentiating, demonstrating complexity ‘at work’ within the realm of possibility. A realm (of experiencing silence) that seems to be rather unknown and therefore to be in need for exploration (her mission). We may take the complexity involved as kind of hyper-complex processes, integrating network thinking with thinking in complexity. We need to think beyond the linear to be able to think of such complex processes, especially beyond the linear of linear causality. The complex generation of order, now, may be viewed as a ‘creative’ kind of process with unexpected, surprisingly emergent effects. We are of the opinion that our complex causal modelling of real-world complexity is the new tool for understanding and explaining the creativity of such a generative order, which is underlying this real-world complexity and its real-world dynamics, which is a causal, generative kind of dynamics. We hope that our new thinking in complexity shows the generative power of the new thinking in generative complexity, which is so much based on the causal power of the new conceptual framework. But, like Rescher (1998), we may also warn the reader that although “we deeply want and need to grasp the world in straightforward, accessible terms” (p. 199), we need also to be fully aware that “this is something that the complexity of that world’s ways themselves preclude” (Rescher 1998, p. 199).

Implications for New Thinking in Complexity We are now able to present all different kinds of interaction within and between A and B , thereby showing an unlimited kind of dynamic complexity of effects in time and space. They represent the opening of an infinite space of possibilities for complex systems thriving on interaction. They illustrate the very complexity of complex processes of interaction over time and space and its effects over time and space. This complexity, we argue, is to be taken as the very complexity of the real, as proposed in Rescher (1998). It is the complexity of complex processes that is to be considered as potentially self-potentiating within the realm of possibility (Rescher 1998). So, we have finally arrived at real dynamic complexity about the realm of natural reality as being so much part of the nonlinear complex reality (cf. Mainzer 2007). This real complexity, we believe with Kauffman (2009), means “that we must radically alter our account of reality” (p. xv). The nonlinear complex reality, then, becomes the new reality. It is the new reality that is opening the very realm of possibility (Rescher 1998, p. xv). So, we may arrive at a new science of complexity, which focuses on generative complexity, which is closely linked to the ontological complexity of our world. This ontological complexity is very much about an ontological creativity of complexity as self-enhancing and self-potentiating, which is enabled by a generative order. These links may show that our new science of complexity will ultimately be a new science of the possible; that is, about the possible within the realm of possibility. A realm that we can take as an expanding realm, closely linked with the concept of a nonlinear complex reality (Mainzer 2007, p. 16, p. 434). The new science of complexity, then, implies the possibility of a new

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kind of epistemology: the epistemology of the possible. With this new epistemology we may develop new knowledge about the complexity of the real; that is, of hitherto unknown generative mechanisms and new concepts like interactivity, connectivity and generativity, of use for the description and explanation of phenomena like bootstrapping, the Snowball phenomenon, as processes in which small changes can be turned into large effects. These phenomena can now be described and explained within hitherto unknown high-dimensional state spaces of possibility, also known as ‘state hyperspaces’ (Globus 1995). From this kind of understanding and explanation of complexity as dynamic, generative complexity, operating within such hyperspaces of the possible, we may derive the rather unknown notions of effective complexity and advantageous complexity as unexpectedly practical notions within the hitherto unknown realm of possibility. These are notions we are now ready to understand from the causal power exerted within processes of dynamic interweaving within dynamically interconnected causal loop networks. These notions are bridging our new thinking in complexity with the unknown. These kinds of nested networks can be considered as complex layered networks of the real, being operative in the real, with potential nonlinear effects over time and space within a nonlinear complex reality. These causal networks are fluid networks with dynamic, fluid effects; effects that are not dependent on time and space itself but only on the dynamics of changes within the network. It is the self-generative dynamics of the webbed networks within the webbed architecture of dynamic configurations that is responsible for the complexity of a nonlinear complex reality. We may conclude that our new thinking in complexity may not only describe but also explain complexity as generative complexity that is possibly self-potentiating, as a fact in reality (Rescher 1998, p. 28). This, we argue, is the very complexity of the real that really bridges to the hitherto unknown. With Kauffman (2009), we are of the opinion that this kind of new thinking in complexity, linked with new thinking about dynamically interconnected causal loop networks, shows that we may “radically alter our account of reality” (p. xv). We may start to think of a reality that should be taken as a potentially nonlinear complex reality (cf. Mainzer 2007). Of course, this expanding of reality as a deeply layered kind of reality may have a significant effect on our viewing and doing science. Based on this new scientific outlook, we may start to build a new science of complexity. This will be a science that may surprise us, as stated by Solé and Goodwin (2000): “Complexity shows us that we live in a fascinating but counterintuitive universe, a nonlinear and unpredictable world operating by rules still to be discovered” (p. 303). So, new thinking in complexity has the potential of generating a new world as subject of new study: that of dynamic, generative complexity about the deep generic or generative order underlying our new reality as a nonlinear, deeply-layered complex reality. This very generative kind of complexity, although very complex indeed, is very much about an ordered complexity, generated through different qualities of interaction within different qualities of reciprocal relationships. Below, we go a little bit deeper into this possibility for generating a new tradition in our sciences in general and the social sciences in particular. This view finds strong support in Solé and Goodwin (2000): “The sciences of complexity show us that we

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are embedded in a world fundamentally different from that which has previously characterized modern science, with its emphasis on prediction and control” (p. 28; emphasis added). This brings a new scientific outlook and focus on the subject of study: the realization of systems as a kind of complex, self-generative system, with their characteristics of performance in a nonlinear complex reality. Ultimately, we want to argue, we may not only become able to describe ‘the intrinsic creativity of nature’ (Solé and Goodwin 2000, p. 20) but also become more explanatory about how this complexity of creativity may be really ‘at work’ in nature: for instance in the functional bootstrapping as a mechanism in evolution (see e.g., Kauffman 1993). For a more extended view on the expanding of our sciences, in particular the social sciences and humanities, we may refer to a future publication (Jörg 2012). This describes the foundation of a new science, with a new scientific outlook that is based on the new tools of thinking in complexity that is delineated in the present book. We would like to stress here that this opening for a new science will demand for a new language for description and explanation of what may be called ‘the dynamic hypercomplex’ as being part of and constitutive of a nonlinear complex reality, with complexity as self-generating within self-generative systems and with complexity and the power of self-potentiating. The proposed new science of complexity fully integrates the complexity thinking with network thinking in a hitherto unknown way. We could not escape being immersed in a tradition, but with an adequate language we could orient ourselves differently and, perhaps, from the new perspective generate a new tradition (Maturana, in Maturana and Varela 1980, p. xvii; emphasis added)

Steps Towards a New Science of Complexity The world’s complexity means that science is limited by the very fact of being our science (Rescher 1998, p. xiv; italics in original)

Our new thinking in complexity is not only bridging to the unknown in a theoretical way but can also be taken as linking the fundamental with the practical. By escaping the old ways of thinking about the complexity of the real and by developing the new tools of thinking in complexity of the real, we are able to discard the limitations of our normal science as a science-as-usual. We are fully aware that you cannot find a new science. Almost a century ago, Vygotsky already made clear that for enabling a new science, you have to invent it (Vygotsky 1997a). We have the hope and intention to invent a new kind of science: that is, a new science of complexity that is founded on the rethinking of the basic concepts in use in our science-asusual. Doing so, we may orient ourselves differently and “generate a new tradition” (Maturana 1980, p. xvii). Our aim is not so much a shift of paradigm but more that of a complementary way of seeing and thinking about complexity of the real. The main focus is on the realization of complexity in a nonlinear complex reality.

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We now also better recognize the truth of Kuhn’s assessment that you cannot create novelty and innovation if you keep within the limits of what he called ‘normal science’; that is, the science-as-usual. All of this is strongly related to what Rescher describes as “the very fact of being our science” (Rescher 1998, p. xiv; italics in original). The role of language is of special importance for the building of a new science about the world. We fully agree with Wittgenstein (1954) that the limits of our language are the limits of our world but that does not mean that these limits are the limits of the world. Rescher (1998) fully recognized that philosophy had not developed a language for complexity in its long history. It is because of this that we may recognize that the limits of our language represent not only the limits of philosophy but also the very limits of our science. It is only by rethinking and developing a new language about the complexity of the real that we might be able to escape the limits of language in use in our thinking about complexity. This is not just a theoretical exercise but has great practical value by opening up and enlarging spaces of the possible within the realm of possibility.

Linking the Fundamental with the Practical The ultimate challenge for a new science of complexity is to link the fundamental with the practical. This link offers a new scientific outlook for the study of complex systems. We think this new outlook is of utmost importance for our view of complex systems evolving over time. The new science is aiming at showing the power of complexity in its unexpected role of self-potentiating in the real, showing its potential within the realm of possibility. This role is about opening up and about enlarging spaces of the possible (see Osberg 2009). We may formulate new questions about how to enlarge these spaces of the possible and about how to create and generate the possibilities within these spaces, thereby showing the realm of possibility within these spaces. These spaces can be shown to be generative hyperspaces. The states of being of the complex systems involved are complex, fundamentally generative states of being. The subject of study, then, is about the realization of these complex systems as living systems: how they are generated and how they evolve over time and space. Our focus is on the study of human beings as complex, living systems: about their potential of realizing themselves over time as selfgenerative living systems. The new scientific outlook describes and explains how complexity can become self-potentiating and generate new possibilities over time and space within complex generative hyperspaces. It may show the possibility of what Sara Maitland described so nicely as “freeing up space in the brain” (p. 280), in her deep exploration of silence.6 The new outlook is a cognitive outlook that bridges to the hitherto unknown. This scientific outlook and perspective can be shown to be the link between the fundamental and the practical.

6

 See her wonderful book (2008) with the title A Book of Silence.

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Enlarging the Space of the Possible With the new tools of thinking in complexity and the new terms and terminology sketched above, we may finally become able to enlarge the space of the possible and open up new vistas of possibility within these spaces, made possible by our complex new thinking in complexity. With these tools we may create the power “to view systems with new eyes”, such as educational systems (see Lemke and Sabelli 1998, p. 128). We may not only view systems like educational systems with new eyes but also start to view the new landscapes and spaces of new possibilities that are linked to these inherently complex systems. We may, then, discern different kinds of new spaces of the possible with their different possibilities.

Spaces of Possibility We may distinguish different spaces of possibility for our modelling of causal interaction between latent variables and between complex systems like human beings. We may think of such systems in terms of generative systems in general and conceive them as well as operating in terms of self-generative processes. This makes such systems self-generative or self-reinforcing systems. But for new thinking in complexity about such systems, we may better think of the dynamics of inter­action between such selfgenerative systems. We argue that this kind of new thinking opens up new vistas of possibility: of complex, dynamic landscapes of effects evolving over time, which are representative of the new spaces of the possible for the complex self-generative systems of concern for the social sciences: human beings. We may then be able to think of such beings as potentially nonlinear human beings with their acquired potential state of complex human being. A complex state that is acquired by thriving on inter-action with other human beings and on the complex processes of intra-action. Based on our new generative approach we may better understand and explain how learners may become able to “bootstrap each other” in small (sub-) communities of learners (Bruner 1996, p. 21; emphasis added). This process of bootstrapping is a complex process within an architecture of loop networks with dynamic configurations that thrives on strong, reciprocal interaction within all kinds of complex hyperloops, as kinds of causal loop networks of strong reciprocal relationships. We may open up new vistas of possibility by thinking of boot­ strapping processes in which learners may bootstrap each other into complex, dynamic, generative states of being, with their inherent capability to generate possibilities. It is the generativity of living systems that thrives on reciprocal interaction, in which social, generative forces are exerted on each other, operating as mutually shaping forces, which generate total effects over time and space. So, we agree with Solé and Goodwin (2000) that interactions are the key ingredients of behavioural complexity of the entities involved, like systems, organisms or individuals (p. 176). The complex, self-generative systems may operate, then, as a kind of bootstrapping system, which is characterized by so-called ‘functional

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bootstrapping’, in a similar way as is the case for evolution (Kauffman 1993). These are complex, self-generative systems, with their hitherto unknown characteristics of learnability and evolvability (Kauffman 1995a, b). Actually we may discern, now, different kinds of learnability and evolvability: two kinds linked to each of the two individual human beings and one, more general, linked to the unity as a whole; of what Kauffman called the unit of ‘the ensemble’ for the science of biology and what Luhmann and Schorr (2000) called the ‘twosome’ for the field of learning and education. The real complexity to address is how these learnabilities and evolvabilities and their dynamics are intertwined and mutually transform each other over time (Ulanowicz 2009). Our approach is a deeply generative approach that can be equated with the potential of a fundamental, possibility-oriented approach. Such an approach has been described for the field of education, as one that enlarges the space of the possible and opens up new spaces of possibility (Osberg 2009). This possibilityoriented approach means the end of a ‘things-oriented’ approach for our sciences in general and those of the social sciences and humanities in particular. Elsewhere (Jörg 2010a, b), we argue that this possibility-oriented approach may replace the idea of required learning for education, to turn this into that of real learning (cf. Gagnon and Collay 2001, p. xix), with hitherto unknown effects such as bootstrapping each other as learners within small (sub) communities; effects that have also been described as ‘explosive possibilities’ in communities of learning (Barab and Kirshner 2002). Education, then, may be conceived anew as the creation of a context, like a niche in the evolution of species, to enable the functioning of living human systems and their coming into presence as a way of realization of learners as human beings through their optimal functioning as self-generative systems. This kind of new thinking in complexity shows how complexifying the subject of study may offer the possibility of a kind of humanizing the social sciences and humanities: by the opening and enlarging new spaces of the possible. Our approach may also replace the discussion about the role of emergence, of emergent processes and emergent effects: not only for the complex topic of evolution and life in the field of biology but also for the field of learning and education. We propose to turn emergent into generative; that is, into generative processes and generative effects, described and defined by the generative functions of the extended causal framework, delineated in Chap. 11. We argue that the generative is not only better descriptive of what happens in the real but the generative is also more explanatory about the processes that play a role in the complex processes of interaction and development within systems as living systems and their actual realization through complex, generative processes of self-potentiation. Our concept of generativity is more characteristic of the whole system than single emergent effects. This, we think, is what complexity of the real is really about as the subject of study in our complex, generative, trans-disciplinary approach of complex living systems and their realization in the world of real-world complexity. Our science of complexity, which is in development, is to be taken not only as a science of hitherto unknown possibilities but can be considered to be a science of

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hope, because it makes an end to the reductionistic stance that dominates our sciences and which we take as responsible for a deprivation of our culture in general and that of the culture of education in particular. We mean here the trivialization of the inherent complexity of the human being, in its standard reduction of complexity in the social sciences. This trivialization can be ascribed to the learned incapacities of dealing with the complexity of complexity of our real-world complexity with its real-world dynamics, which is fundamentally a causal dynamics. We need a shift of paradigm to enable a new way of seeing and thinking about the generative nature of this kind of real-world complexity. The new science is about the generative nature of complexity, which links to the generative order of our world. The new thinking about the generative complexity, responsible for the generative nature of this world’s complexity, is based on a new conceptual framework. With this new thinking in complexity, based on a fundamental reframing of complexity, something radically new has appeared: “the possibility is opened for creativity to operate within a causal framework” (Bohm and Peat 2000, p. 97; emphasis added). From our new scientific perspective on (reframing) complexity this is a causal framework that is based on the extended causal framework that has remained ‘hidden’ in our social sciences for so long (Bohm and Peat 2000, p. 202). Because of this ‘hidden’ position of ‘real’ causality, the possibility of bootstrapping processes and their bootstrapping effects has been suppressed, in a way that compares with the suppression of the possibility of the so-called ‘butterfly effect’ (Mainzer 2007, p. 11). The new conceptual framework starts with a more viable concept of causality (cf. Lincoln and Guba 1989). This turns our framework into a new framework that links causal thinking with network thinking (Barabási 2003); a link between a theory of complexity and network thinking that has been deeply overlooked according to Barabási (Barabási 2003, p. 238). We are convinced that this new link, made in our new conceptual framework of a reframed notion of complexity, is finally opening up new vistas of possibility within the realm of possibility. It is a complex conceptual framework that can be taken as ‘really’ opening for analyzing the complexity of real-world complexity; a complexity that seemed almost un-analyzable (cf. Bohm and Peat 2000, p. 219). The new framework shows the power to deal with generative principles, of generative processes, based on the causal, generative functions of the extended causal framework (ECF), delineated in Chap. 11. These generative functions, in turn, are based on the social, mutually shaping, generative forces exerted in strong interaction within strong reciprocal relationships. This new framework, with the newly developed tools, shows the ‘unlimited creative potential’ (Bohm and Peat 2000, p. 134) of a complex, dynamic interweaving within webbed networks, with their webbed architecture of dynamic, evolving configurations, which are based on the causal dynamics of strong interaction with potential nonlinear total effects, taking place over time and space. See Picture 14.2. The framework we have developed for analyzing the complexity of real-world complexity is also enabling for the development of a new language with new terms and concepts, never used before to deal with complexity. This book is an invitation to the reader, to get more familiar with this new language and to become ready to use this language, for the sake of going beyond the limits of our world (Rescher

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Picture 14.2  A webbed network with specific 3-dimensional architecture (Foto made by Teun Spaans)

1998, p. 51; emphasis in original; see also Wittgenstein 1921/1961, proposition 5.6, about the limits of my language being the limits of my world); that is, the world as we view it in our science-as-usual. Only by learning the new language we may become better able to extend these limits and to dis-cover that “these limits cannot be claimed to be the limits of the world” (Wittgenstein 1921/1961, p. 51). With Wittgenstein (1921/1961), we may be aware that “whatever we see could be other than it is” and “whatever we can describe at all could be other than it is” (both part of proposition 5.634). So, reality may be different and be taken as a nonlinear complex reality (Mainzer 2007, p. 16, p. 434). The new language will make our thinking different. With Bohm (2004), we may become aware that “thought is part of this reality and that we are not merely thinking about it, but that we are thinking it” (p. 140; emphasis in original). It is in this perspective that we may think of ‘reality as a choice’ (see Jörg 2009). With our new thinking in complexity we may become able to think reality as a different kind of reality: a fundamental nonlinear reality. From this perspective, we may become finally able to describe and explain “physical, social and mental realities” (Mainzer 2007, p. 14). This is in essence the mission of this book: to open up a new kind of reality; one that integrates the linear with the nonlinear. This, we think, is the reality that has remained hitherto unknown in our social sciences and humanities (cf. Luhmann 2002) (Picture 14.3). We may also become more aware that our science may become a different kind of science: not one of perfecting our science, by being in control but one of opening new vistas of possibilities that are hitherto unknown: new possibilities of complexity, with the power of self-potentiating and bootstrapping, thriving on strong interaction within dynamically interconnected loop networks of reciprocal relationships. The new science will escape the traditional binary oppositions, like nature-nurture, mind and brain and the split between system and environment, all of which have done so much damage to our sciences. The new science will escape the danger of instructionism and constructivism that have dominated the social sciences. The new science will be fundamentally possibility-oriented and replace an ends-oriented

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Picture 14.3  “Time Writer” by Lonny van Ryswyck. Atelier NL, The Netherlands. See Annex 14.3

approach. Each entity can be linked to a hitherto unknown space of possibilities; a space that Wittgenstein has described as “a space of possible states of affairs” (Luhmann 2002, proposition 2.013). From this idea we may start to think of “freeing up space in the brain, more commonly suppressed by language and linear thought” (Maitland 2008, p. 280; emphasis added). This view, supported by our new thinking in complexity, can be taken as bridging to these unknown spaces of possibilities of possible states and as enriching for humanity and society at large. It turns reality into ‘a much richer sort of reality’ indeed (Bohm 2004, p. 140).

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Annex 14.1  Main Possibilities of Combinations of Interaction Entities Ensembles of latent variables in their cooperative intra-action, showing coincidental inter-action

Hyperloops

Symbolic form

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Ensembles of latent variables in their cooperative intra-action, showing cooperative inter-action

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Ensembles of latent variables in their cooperative intra-action, showing cooperative inter-action within a loop

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Ensembles of latent variables in their cooperative intra-action within a loop, showing coincidental inter-action

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Ensembles of latent variables in their cooperative intra-action within a loop, showing cooperative inter-action

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Ensembles of latent variables in their cooperative intra-action within a loop, showing cooperative inter-action within a loop

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Annex 14.2  State Hyperspaces for and with Composite Function of Effects, Depending on the Variables Affect and Motor Activity of the Brain

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Annex 14.3  Information About “Timewriter” by Lonny van Ryswyck, Atelier NL, The Netherlands Timewriter 2006 | Lonny van Ryswyck Time seems to move on a circular, repetitive, infinite path. 360º a minute, 360º an hour. The future becomes present, the present becomes past, the past becomes future. Constantly replacing each other on the clock, the three states of time become indefinable. The Timewriter is a mechanical instrument made to measure and register time. Using four numerical stamps it imprints time, tracing it, on paper every minute. Time is described and recorded as a continuous linear progression. text Theodora Antonopoulou photography Paul Scala

Chapter 15

Summary and Conclusions

I think the next century will be the century of complexity (Stephen Hawking 2000; see Davis and Sumara 2006, p. 3)

Introduction The more concrete aim of this book is to reframe what Rescher (1998) described as “the complexity of the real” (in his chapter 2). We are of the opinion that this should be done from the bottom up, all for the sake of truly opening the social sciences and humanities (cf. Wallerstein et  al. 1996). We tried to convince the reader that we needed a shift of view, of new thinking in complexity about the complexity of our world. We were convinced that only through such a shift we might be able to bridge to the unknown; that is, to a world that can best be described as the hitherto unknown ‘world of the possible’ (see Kauffman 1993, p. 371). Actually, we needed a shift of paradigm towards what Morin has called ‘the paradigm of complexity’ (Morin 2008). We took this paradigm as a scientific paradigm. For complexity is not a philosophical problem but a real scientific problem. So, the topic of complexity, although complex indeed, needs to be taken as a scientific concept1: as embedded in a new conceptual framework. We are of the opinion that this new framework might have the power to integrate the many different notions of complexity in our sciences and make an end to the confusion on the topic of complexity; of a situation around the use of the term complexity, which has been described as ‘chaoplexity’ (Horgan 1996, p. 191). Most of the used terms of complexity are descriptive and not very explanatory of nature. Others are very mathematical of nature, such as the chaos theory and catastrophe theory, or dynamical systems

Interestingly, it was the philosopher Nicholas Rescher (1998) who convinced me of this stance to be taken for the study of complexity as a science, with his view of complexity as self-potentiating, being very much part of the complexity of the real.

1 

T. Jörg, New Thinking in Complexity for the Social Sciences and Humanities: A Generative, Transdisciplinary Approach, DOI 10.1007/978-94-007-1303-1_15, © Springer Science+Business Media B.V. 2011

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theory; theories that seem to lack a clear relationship with the very complexity of the real (see e.g., Oyama 2000; Fleener 2002; Scheffer 2009). To us they seem indicative of a kind of rhetoric in use in different fields of our sciences and their various disciplines. We hope to have shown that our scientific concept of complexity has a potential for making the link between the fundamental and the practical and may end the rhetoric of the language in use about complexity, like in the field of education (see Jörg 2009, 2010a).

Elaborating on the General Aim of the Book Summarizing this book, the reader may wonder what this book is really about and what this book is actually heading for in our new century. We may ask ourselves if this century can really become the century of complexity, as prophesized by Stephen Hawking. We may notice that there is quite a bit of confusion about the definition and use of the term complexity. The same confusion seems to be the case for what one may call ‘complexity science’ (cf. Davis and Sumara 2006). Complexity is very much a contested concept in the different disciplines of our sciences. It is therefore of utmost importance, for our viewing and doing science from a complexity perspective, that we become more scientific about the use of the concept of ‘complexity’ in our sciences. In general there seems no recognition of the complexity of complexity as the subject of study in the common scientific approach of complexity. It is our impression that the discourse on complexity is mostly about the use of complexity in a metaphoric sense, thereby leaving out any kind of explanation of how complexity may be ‘at work’ in the real from a scientific perspective. This brought us to the topic of the necessity of reframing complexity and thinking about complexity in a different, more scientific way. Henceforth, the main topic of this book is the topic of complexity, with the open questions “What is complexity really about?” and “How can we learn to think the new way: that is, think in complexity?” And, most importantly for the opening of our sciences and the building of a new science: can we become really explanatory about this complexity as complexity of the real? These are open, still unanswered questions in our sciences, which are waiting for an answer. Although we think that we have found some kind of answer on these questions, we are also sure that it is not the final answer. We have to stay somewhat modest in our final goals because there are no simple answers for these questions. Complexity remains a complex concept and a complex subject of study for our sciences as well. But, based on all the rethinking done, about what mainly has been taken for granted in our viewing and doing science, we feel pretty sure that we have finally discovered a new path for viewing science. We think it is the path of novelty and development, the path for exploring a new entry to the opening of our social sciences; with the path being a rather tortuous path (Kuhn 1970; Wallerstein et al. 1996; cf. Reid 2007, pp. 5, 7). It is the path that goes beyond the science-as-usual, as a science that shows its inherent inability to produce novelty (Kuhn 1970). We only could tread this new

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path by taking the possibility of a shift of worldview not only as possible but also very much needed for the opening of our sciences in general and the social sciences and humanities in particular. We found profound support for our stance from the basic way of thinking about scientific revolutions by Thomas Kuhn (1970).

Learning to Think in Complexity This book is about new thinking in complexity for the social sciences and humanities, for the sake of engendering a different view for viewing and doing science within this broad field of our sciences. To enable the new thinking in complexity, we had to escape old thinking about the basic concepts in use in our sciences and humanities. We were fully aware that we had to learn to think in the new way. With Lev Vygotsky, we wanted “to find out how science has to be built” (Vygotsky 1978, p. 8). With Vygotsky, we were convinced that you cannot find a (new) science; you have to invent it. This is very much what this book is about: the invention of new thinking in complexity, as a foundation for the building of a new science. The focus has been on the basic concepts of our sciences. We formulated a challenge to rethink these basic concepts. In Box 15.1 the steps of new thinking are recapitulated.

Box 15.1  Steps of Rethinking the Basic Concepts of Our Social Sciences 1. The first step concerns the need to become reflective. Reflection is needed to become aware of the crisis, to analyse the crisis we are in, in general and for the social sciences in particular and to learn how to overcome the crisis. This step may be described as the hardest part of reinventing our common ways of viewing and doing science. It means recognizing the possibility of imprisonment in viewing and doing science, with its concomitant possibility of myopia and the phenomena of developing blind spots. In this sense it is decisive in opening “a new way of seeing” and more importantly, “the will to transform the whole intellectual scene” (Wittgenstein, in Fleener 2002, p. 127). In practice, the consequences are that we need to overcome the resistances in our view of the world and our viewing and doing science from our acquired ways of knowing. This may entail opening new frameworks or new approaches. We may only be able to make this step by thinking of a different future, about a different world to work in: a world that may encompass a richer sort of reality. History may tell the worth of making such a shift in thinking: of new thinking in complexity as a promising approach. 2. The second step of rethinking, of rethinking reality, brings forth an enlarging of our worldview that goes beyond our commonly assumed notion of reality, enlarging the space of the possible by taking complexity of reality into (continued)

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Box 15.1  (continued) account as the object of study, with a focus on the potential nonlinearity of complexity. After making this step, we may be able to ‘deliver’ a different reality as social scientists; that is, ‘a nonlinear complex reality’ (cf. Mainzer 2007, p. 16, p. 434). 3. We may state that our proposed new thinking in complexity is not only opening for a new way of seeing ….. but is also transforming the whole intellectual scene (see above). Taking the complexity of a different, more complex reality into account is considered as foundational for new ways of knowing about the complex, nonlinear reality. It will be transformative for our way of describing, understanding and explaining the object of study of the social sciences. If reality is of a generative order, as Bohm and Peat (2000) have stated, we believe reality ‘really’ is a complex, nonlinear reality. Based on this thinking in complexity about this complex, nonlinear reality, we need different principles and mechanisms to become explanatory about this fundamental, generative order. 4. One of the new steps to make was the rethinking of interaction. We had to become aware that, surprisingly and somewhat unexpectedly, interaction was not a standard term in our history of the sciences: not in the natural sciences and neither in the social sciences. The interpretation it got was in the second half of the nineteenth century and has been a very mechanistic, law-like version of action and reaction since, inspired by the Newtonian paradigm. Like reality, this was the notion of interaction, simply ‘delivered’ by science and their practitioners. This may be viewed as a result of a misguided paradigm. It implied a linear view of interaction, with a chainlike structure of action and reaction taking place in time. But interaction is much more complex than commonly assumed in our sciences. The linear should be turned into a nonlinear view of interaction. 5. We think causality is still the corner stone for understanding reality because our world is a causal world. But the central question is how one may take causality to be the key for understanding reality anew. We think the traditional causal framework, which is based on the ‘Central Dogma’ of a one-way flow of causation, is not very satisfactory for this (Oyama 1989, 2000). The focus is too much on simple action and reaction, with dependent and independent variables and just that. And not on how the independent variable may be generating in its influence or effect on the dependent variable, conceived as a non-standard reaction. More seriously, time is left out of the equation in structural equation modelling (SEM). This happens even without noticing, which makes this assumption a kind of inherent myopia or blind spot. Becoming aware of this (step 1) made clear that thinking-out-of-the-box was badly needed. We argued that we need an (continued)

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Box 15.1  (continued) extended causal framework that takes causal processes seriously as an object of study in our social sciences. We may better not only focus on recursive, simplistic causal chains but also on non-recursive, reciprocal relationships with their causal loops, showing their inherent but hidden potential of nonlinearity of total effects over time. 6. The new unit of study is the unit of the ensemble or ensemble systems. This unit is actually the unit of the dynamic ensemble that takes time into account. Both the entities and the relationship between the entities are potentially dynamic and fluid. The modelling of this dynamic unit within the extended causal framework of SEM, as a causal loop of reciprocal interaction with cycles of causal influences taking place over time, shows the hitherto unknown potential of the ensemble of two entities connected as a dynamic unit of study. The total effects of the causal interaction are based on the generative functions of the total effects on the entities involved in the ensemble. These can be nonlinear over time. The dynamic unit of the ensemble, of the causal loop, shows a complexity that has ‘simply’ been discarded as the corner stone for the building of the social sciences.

Elaborating on All the Steps Made The duration of childhood basically depends on the complexity of an organism, its conduct, and the complexity and variability in its surroundings. The fundamental symptoms of childhood are development and plasticity (Vygotsky 1993, p. 298; emphasis added)

Reading all the preceding chapters, it may have become clear to the reader that formulating a general theory of general complexity is not (only) a philosophical but a real scientific endeavour (cf. Morin 2007, p. 24; and Vygotsky’s effort of building a new science by invention). This, we think, is of fundamental relevance for “radically altering our account of reality” (Kauffman 2009, p. xv). This implies a kind of reclaiming of reality, which is of fundamental relevance for the social sciences and humanities. This made us speak about the challenge of building a foundation for a new science of complexity as a transdisciplinary approach of a fundamental, complex, nonlinear nature of reality. That’s why we developed the tools for delineating all of the complexities involved in describing, understanding and explaining complexity, as part and parcel of our nonlinear complex reality. We developed the new tools of thinking for becoming more reflective on our ways of knowing about the ‘real’ complexity of reality, on a new concept of interaction, on an extended causal framework and on the choice of the unit of study. These are the basic tools for a shift of mind, concerning a transition to a new transdisciplinary approach of our viewing and doing

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science. With the new tools, we aim to build up a new language for our new thinking in complexity, as a scientific way of thinking, which is opening for a different discourse about a new reality. We are of the opinion that we need a different, more scientific language for complexity, to end the rhetoric about complexity in our world and better strive for a scientifically informed philosophy of complexity (cf. Wimsatt 2007, p. 26). With this new thinking we will be better able to describe, understand and explain a nonlinear complex reality. By speaking differently about the complexity of reality, this complex reality will become different itself. Delivering reality is a very basic part of viewing and doing science by scientists. Henceforth, our enterprise is a scientific enterprise about ‘delivering’ a new reality with the use of a new paradigm: the paradigm of complexity. We do so by taking complexity of our world as real; about what Oyama (2000) ‘simply’ calls “really real” for the field of biology (p. 207). We fully agree with Rescher (1998) that “the world’s complexity means that there is, now and always, more to reality than our science ….. is able to dream of” (p. 28). This is our basic starting point for new thinking in complexity about real-world complexity in a nonlinear complex reality. It is constitutive for the invention and the building of a new science, which takes a fully trans-disciplinary perspective on complexity, for actual and factual use in all different kinds of disciplines. With the new paradigm of complexity, we may better be able ‘to harness complexity’ (Axelrod and Cohen 1999) and become able to turn our common notions of complexity into effective and, ultimately, advantageous forms of complexity. We may develop and make use of complexity as self-potentiating, to be taken as a fact, thereby linking the fundamental with the practical in a deep sense (see Rescher 1998, p. 28). In this sense, the complexity theory is a deep theory indeed (cf. Kauffman 1993, p. 298). It is therefore our deep hope that we can make the twenty-first century ‘the century of complexity’ (see Barabási 2003, p. 226; cf. Stephen Hawking 2000). Ultimately, we hope that adopting the new way of thinking in complexity may bring scholars “practicing their trades in a different world” (cf. Kuhn 1970, p. 150). This is actually and factually the world of complexity: that is, of complexity as self-potentiating. Taking the new thinking in this kind of potentiating complexity seriously means for us “exploring the world of the possible” (Kauffman 1993, p. 375; emphasis added). So, complexity is directly linked to enlarging spaces of the possible and opening new spaces of possibilities. From the perspective of a new method of viewing and doing science, the new thinking in complexity fosters a kind of network thinking about the causal dynamics of generative systems like the so-called ‘self-organizing’, ‘self-(re)producing’, ‘self-generative’, ‘self-amplifying’, ‘self-propagating’, ‘self-potentiating’, ‘selfsustaining’, and ‘self-maintaining’ systems as characteristic functions of complex, generative systems (CGS). These are conceived as a new kind of dynamic systems, evolving over time through processes of evolution, with their characteristics of bringing “evolvability into existence, pulling itself up by its own bootstraps” (Kauffman 1995b, p. 185; cf. Buckley 1967, p. 35). These functions comprise the self-potentiating power within complex, generative systems, operating by a functional, generative ‘bootstrapping’ function (Kauffman 1995a, b, p. 288; cf. Kauffman 1993, p. 373; Wimsatt 2007, p. 139). It is this opening of a hitherto unknown generative bootstrapping function, responsible for the self-potentiating

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power within complex systems that is the foundation stone for the building of a new science by invention. This is the very corner stone for a new description and explanation of a nonlinear complex reality within the new conceptual framework of a new science of complexity. With this stone we are able to view the generative foundation for a new science of complexity. This new science goes way beyond what Rescher (1998) has described as the ‘cognitive domestication of the real’ (in his chapter 2), by taking account of what he calls the very fact of complexity as selfpotentiating. So, we should better take this complexity not for granted but as really real! This implies an ever-expanding notion of the real: “It means that there is always more to be said here – that the complexity of the real as science reveals it to us is ultimately unfathomable” (Rescher (1998), p. 51; emphasis added). This notion gives a better insight into complexity of the real as really real. It also makes clear that knowledge about complexity is always provisional indeed (cf. Cilliers 2009). To become more explanatory about the nonlinear complex reality we need the tool of a self-potentiation theory (Rescher 1998). Such a theory is in need for a new type of explanation, which we have called ‘a pattern model of explanation’ (Lincoln and Guba 1985, p. 206; italics in original). Further on, we go deeper into the problem of explanation. All of the new thinking in complexity, delineated in this book, has consequences for our ways of knowing about the complexity of real-world complexity. It is for this reason that we favour a new epistemology: an epistemology of the possible, about a new world of the possible, which finds its base in uncertainty, in our ignorance, or in what we do not know about this world (Luhmann 2002, p. 152). We support the notion that the new epistemology “analyzes the uncertainty of knowledge and gives reasons for it” (Luhmann 2002, p. 152). This notion is in agreement with the idea that knowing about complexity of real-world complexity is always a provisional way of knowing about real complexity (cf. Cilliers 2009). Put in a different, more optimistic way, we may state that the new epistemology, in use in the new science of complexity, can be linked to a new, possibility-oriented approach in our sciences. It can be used for explaining directionality as an inherent characteristic of generative complexity as self-potentiating. With this tool of explaining directionality, we may become more explanatory about so-called ‘self-directing systems’, already conceived as possible within a causal framework by Walter Buckley, based on what he describes as ‘circular causal chains’ (1967, p. 69). This very notion of directionality of generative complexity can be linked to the very notion of quality. Taking these two together brings us to the important concept of what we prefer to call ‘the quality of complexity’. We may, then, not only distinguish the degree of complexity, as linked with the degree of interactivity and the degree of connectivity but also link this degree of complexity with generativity as part of state of being, with an inherent capability of generating new possibilities within hitherto unknown spaces of possibility. These are themselves spaces within the realm of possibility. We may now think of this quality of complexity in terms of its self-potentiating characteristic (see Rescher 1998, chapter 2). With Brian Goodwin (1994), we may speak about the possibility of “a science of qualities rather than one of quantities” (Rose 2006, p. 190), opening for a science that may focus on the question about life itself, as a still unanswered question (see e.g., Rosen 2000; Kaneko 1996). This very idea of the quality of complexity cannot only be

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taken as bridging to the unknown but may also finally bridge the gap between the natural sciences and the humanities (Snow 1959). Ultimately, thinking in terms of the quality of complexity, of complexity as self-potentiating, may bring the important idea of a “Third Culture” more close to the opening up of new vistas of possibility (see Brockman 1995; cf. the view in “The Third Window”, by Ulanowicz 2009). We are very much aware and optimistic about it in the sense that this may become a different culture or window in our viewing and doing science. This new culture may really bring about the humanizing of our sciences. This is the humanizing generative approach that we need to overcome the limited knowing of our world; a world that is actually and factually so much a world of the possible, of the hitherto unknown (Morin 2002; see also Vygotsky 1993, pp. 13, 65, about realizing ‘unrealized potentials’ of children, in his new psychology). We think this world of unrealized potential, of new spaces of possibility and domains of potentialities, is so much more a world of the possible than we have ever thought before (cf. Bohm, in Morgan 1997). So, we may speak about “the realization of the living” (Maturana and Varela 1980); that is, about the realization of the living of living human beings. This human and humanistic perspective is in essence very much a Vygotskian perspective. The new science of complexity with a possibility-oriented way of knowing about this world of the possible is deeply human by enlarging and opening new spaces of possibility within a world that is still dominated by our ignorance. But in the end we may come to the conclusion that we have become deeply aware that the way of ignorance is the way we must go to arrive at what you do not know (see T. S. Eliot, in “East Coker”). It is such deep thinking that is so much part of a third culture. Some of our great poets, like the American poet Ralph Waldo Emerson, were of d of science itself: “For poetry is science”, according to Emerson (in Blasing 1987, p. 74). For poetry, like novels, ‘really’ has the ‘creative, generative power’ (Maitland 2008, p. 126) of opening the spaces of the possible, which are possible within the world of the possible: of what has been nicely described by Sara Maitland as a complex process of “freeing up space in the brain” (Maitland 2008, p. 280). From this opening perspective, poetry is similar in its power to generate as the self-potentiating capacity of complexity, described by Rescher (1998) as a fact (at p. 28). We may also refer to what has been described as ‘the Vygotsky space’, that is, as a kind of ‘potential space’: “the potential space is the area that is neither what the child nor the mother knows” (Winnicott 1971, in Litowitz 1993, p. 190). Maturana and Varela (1980) use the concept of ‘autopoietic space’, to describe this potential space as a space of realizing. Like we have done implicitly in this book, they use the concepts of ‘a matrix of interaction’ and that of ‘a relational matrix’, to build such a potentially autopoietic space (p. 122). We are now able to link such a space with the learning and development of children, in their realizing their life as a human being. It is the very space that relates to the potential development of children in their communicative human interaction with others, also described as “a conversation in the Vygotsky space” (see Palincsar et al. 1993, p. 51). Both poetry and complexity can therefore be characterized by variability and plasticity as fundamental, generative characteristics (see Vygotsky 1993, p. 298; see quote above). Reading about this similarity between poetry and complexity, one

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may, then, be not surprised that Lev Vygotsky was close to the world of poets (like Mandelstam), which was of significance for his original new way of thinking.2 We think this may be the real source for his becoming a genius of his time and still is for our time, opening up new spaces for new thinking. He may still be considered to be “a visitor from the future”, as recognized by the famous cognitive psychologist Jerome Bruner (1987), in the foreword of the first volume of his collected work (in English). He was, for instance, very much aware of the fundamental significance of complexity for new thinking about childhood: see the quote above and the one below, which both fully take account of complexity as really real. His view of the concept of childhood shows him to be a visitor from the future indeed: a visitor from what has been called “the Century of Complexity” (Barabási 2003; Hawking 2000). It is by standing on his shoulders that we may become inventive of a new science; a new science that we badly need to overcome the crisis we are in. In our view it is still the very same crisis that Vygotsky recognized as characteristic of psychology at the start of his unusual scientific career (Vygotsky 1997a). Based on his fundamental, creative ideas, we may start building a theory of complexity as a general, trans-disciplinary theory of complexity. This general theory, enabled by a shift of paradigm towards the paradigm of complexity, is of use for all disciplines, studying the topic of complexity of subjects within the diversity of scientific realms of our sciences (Ruurlo Manifest 2006). What is of utmost importance here is that we may link the fundamental of new thinking in complexity with the practical; that is, the practical, which Vygotsky linked so eloquently to the introduction of the child to real life3 (Vygotsky 1993, p. 65; emphasis added). That which is impossible on the level of individual development becomes possible on the level of social development (Vygotsky 1993, p. 219; emphasis added)

The Significance of Generative Complexity In this section we would like to show how we may turn the general notion of complexity into that of dynamic complexity and of generative complexity. This notion is to become the generative foundation for a new kind of science, i.e., of evolution, which is not only descriptive but also explanatory about complex generative systems 4 (CGS) as the subject of study in the field of evolution (that means CGS, instead of CAS, as complex adaptive systems; cf. Wimsatt 2007,

In several places he quotes a poem to elucidate what he means in his text. Although we can link this notion nicely with the concept of autopoiesis delineated in Maturana and Varela (1980) and the concept of metamorphosis in Vygotsky (1978) and the theory on morphology and metamorphosis by Goethe, we will not do so here. 4  We use the term ‘complex generative systems’ on purpose here, instead of complex adaptive systems, because it is a more encompassing term for the new science of complexity. 2

3 

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p. 135). With Susan Oyama (2000), we are critical about the concept of system, with its common link to the stability of systems (p. 182). The ultimate challenge is to turn generative complexity into a form of selfpotentiating complexity. In a deep sense, this challenge links the fundamental with the practical. We think it is closely related to the all-important, fundamental question “How to generate coherent wholes?” (Solé and Goodwin 2000, p. 61; cf. Eigen and Schuster 1979, p. VII) We may also put this general question somewhat differently, as follows: “What is the weave?” (cf. Kauffman 1995a, b), or in terms of dynamic webs as complex systems that “govern their own possibilities of transformation5” (Kauffman 1993, p. 370). These are the questions that are still very much unanswered questions (Simon 1996). We are of the opinion that by finding the answers to these questions, we may find the entry for enlarging the space of possibilities in the social sciences. This is the challenge that may be considered as similar to the one put forward by Stuart Kauffman (1993) for the biological science. So, the challenge is a real trans-disciplinary one. Taken together, the finding of answers may be considered to be the entry of “a much richer sort of reality” (Bohm 2004, p. 140), with new spaces of possibility, of ‘a vast dimensionality’ (Bohm 2004, p. 140; cf. Kauffman 1993, p. 33). With David Bohm, we take our approach therefore as a literal approach; one that aims to give “a literal representation of reality as it actually is” (Bohm 2004, p. 140). But of course, we recognize that reality is not static; reality should therefore be taken as ‘reality-in-process’ (Sandywell 1996, p. 423). With Whitehead (1925/1967) we may therefore state the following: “Thus nature is a structure of evolving processes. The reality is the process” (p. 72; emphasis added). This is also the entry for the description and explanation of “a richer sort of life”, such as those of complex living systems. The understanding of living of these living systems is not ‘ends-oriented’ but more ‘possibility-oriented’; an understanding that is both opening and enlarging spaces of possibilities (see Follett 1924, in Drucker et al. 1995, p. 58; Kauffman 1995a, b, p. 188; Osberg 2009; Jörg 2009). The general entry, described above, turns the approach of enlarging the space of the possible, as a fundamentally generative space, into a general, trans-disciplinary approach.6 It is therefore also opening for a new approach of the social sciences: a new approach, with a new methodology to reinterpret social reality (Wallerstein et al. 1996, p. 76; emphasis added). It is opening as well for dealing with the complex systems of biology, in terms of self-generative systems, with their dynamics of living processes as creative processes (see Solé and Goodwin 2000, p. ix; cf. Mayr,7 1988, p. 1).

We would like to stress here that these are the questions already formulated by Vygotsky, as a visitor from the future, be it in somewhat different terms but was unable to answer in the beginning of the twentieth century. 6  See http://www.paralimes.org/; see also the Report of the Gulbenkian Commission on the Restructuring of the Social Sciences (Wallerstein et al. 1996, p. 79); and the mission of CIRET. 7  Ernst Mayr himself seems to have been quite confused about methodology, such as about the concept of causality in the prediction of future events, in his chapter “Cause and effect in biology” (Mayr 1988, cf. p. 24 with p. 36). 5 

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We fully support Solé & Goodwin, in their view of the role of the sciences of complexity in the new century of complexity: The sciences of complexity show us that we are embedded in a world fundamentally different from that which has previously characterized modern science, with its emphasis on prediction and control of nature (Solé and Goodwin 2000, p. 28; emphasis added)

We know, for sure, that the study of complexity is very much focused on the very complexity of the object of study. All of us may be convinced of the complexity of complexity. But, starting from all the rethinking in the preceding chapters, we may now argue that the study of this complexity of complexity should be better defined by its method and methodology than by its object of study (cf. Davis et al. 2005, p. 2; emphasis added; cf. Vygotsky 1978). The method of study is even more basic than the object of study, for building of a new science: that is, the new science of complexity. For this method of viewing and doing science, with its concomitant methodology, is based on a shift of paradigm that brings scientists to a different worldview, with a different ontology and epistemology, all of which are essential for their viewing and doing science. The new science of complexity will be about transition processes of transitory objects like Goethe’s notion of transition that he linked to the study of the ‘transitory’ child and taken by Vygotsky as the foundation stone (of study) in the building of a new science (see Vygotsky 1987b, p. 91; cf. Vygotsky 1997, p. 117; cf. Maturana and Varela 1980, on transitory individuals). The method for describing and explaining the transitory processes that account for the transitory nature of the child as object of study was for him the foundation stone for the invention and building of a new science (Maturana and Varela 1980, p. 91; see also Vygotsky 1978, p. 8). This is as much for him as it is for us the corner stone of a new science of complexity about the transitory objects within complex, dynamic networks, to be conceived as regulatory transition networks, rich in dynamically interconnected loops (see Kauffman 1993, p. 428). Inspired by Stuart Kauffman, we argue that it is this dynamic complexity of loop networks, with their webbed nature of richly interconnected loops and the “the intricate web of interactions” (Barabási 2003, p. 238), as fundamentally constitutive of the webbed architecture of complexity that we want to focus on in the next part of this chapter (all emphasis ours). So, in building a new science of complexity, we may start to ask “What is complexity?” to be able to study the real-world complexity of real-world systems being part of our nonlinear complex reality. Our focus here is on the quality of complexity for understanding this complex reality as a much richer sort of reality (see Bohm 2004, p. 140; emphasis added). We fully agree with Wallerstein et al. (1996) that this will be a reality that goes way beyond the limited segment of reality that has been taken as real for so long (see Wallerstein et al. 1996, p. 62; emphasis ours). From this view, we may derive that we need to find a new way of thinking, of thinking in complexity, to discover what we do not know, to escape our ignorance on reality, which is actually and factually so much a nonlinear complex reality (Mainzer 2007, p. 16; cf. quote of Eliot, in “East Coker”, quoted above).

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For the building of a new science of complexity we conclude that to escape our ignorance of real complexity, we need a new scientific, explanatory approach that can explain much more of the complexity of real-world complexity. With Albert-László Barabási (2003), we may wonder why it has taken so long to find a new mode of thinking and a new scientific approach to deal with the very complexity of our real-world complexity (p. 227). We think the problem of complexity, as defined here, in connection with the problem of causality, remained “a hardy perennial of social science” (see Buckley 1967, p. 71). Henceforth it remained an unanswered problem. The problem was the difficulty to learn to think the new way, that is “to have a new way of thinking and perceiving which brings everything together” (Bohm 2004, p. 140; cf. Bateson 1972; Maturana and Varela 1980). So, deep theorizing on the complexity of reality was too hard for those scientists operating within the science-as-usual. It was even too hard for those scholars who wanted to go beyond it, like Buckley, Bateson and Maturana & Varela. There are actually and factually too much blinding and misguiding paradigms in use in our social sciences and humanities. That’s why we needed to take so many steps to become aware of the real problem, which is our ignorance on the ‘real’ complexity of real-world complexity and to start new thinking in complexity. We needed to make the link between causal thinking, network thinking for making thinking in complexity possible. Finally, we are fully aware that only by making all of these steps together that the new thinking in complexity can be taken to be sufficiently complex to foster a different kind of approach of the study of our reality; a reality that is fundamentally a nonlinear complex reality indeed (cf. Mainzer 2007, p. 16).

How Far Have We Come? Thinking in complexity is essentially thinking about our way of viewing reality and also very much about our way of ‘delivering’ reality, as we actually always do as scientists, unwittingly or not. That’s why we started with rethinking of the concept of reality itself and to think of reality in a different way. We did so by linking new thinking about causality with network thinking, to enable the new kind of thinking in complexity. This enabled a discussion about webbed networks of dynamic loops, with their webbed architecture of potentially generative structures, operating on social, potentially generative forces over time. The study of a complex reality, then, turned into the study of a kind of layered reality with webbed networks of causal networks (Oyama 2000, p. 161, p. 183). These constituent elements of our reality, with entities being connected in and through the causal networks, showed clearly their “embeddedness in a causal world” (Oyama 2000, p. 183). It is a world “in which causes and effects are not ultimately distinguishable” (Oyama 2000, p. 183). Ultimately, reality, then, becomes a fluid kind of reality. This gets very close to how we experience reality in the real. More importantly, the elements/entities show a kind of embeddedness, which is a complex, generative kind of embeddedness in our world. We hope to have shown that this world is still an unexplored world, about the complexity of the real (Rescher 1998).

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In the different chapters of this book we developed a new way of seeing and thinking about the complexity of the real. We developed the new tools of thinking in complexity to be able to deal with that complexity of the real, as a nonlinear complex reality indeed (Mainzer 2007). For the main message of dealing with the complexity of the real is that you need complexity of thinking to be able to deal with the complexity of real-world complexity. We showed how it is possible to think about these new tools by making use of new terms and a new terminology. We are now able to speak about so-called ‘generative spaces’, with dynamic, potential landscapes, showing complex states of (human) being, of entities evolving within high-dimensional spaces, to be conceived as complex, state hyperspaces (cf. Mainzer 2007, pp. 428–429). It is hard to over-emphasize that our paradigm of complexity is about real-world complexity. Our paradigm of complexity is close to what Lincoln & Guba described as a ‘naturalistic’ paradigm, with different aliases, such as post-positivistic and humanistic (Lincoln and Guba 1985, p. 7). They and others like Buckley (1967,) inspired us to think about a more viable concept of causality. One that takes causality not for granted. This brought us to the notion of an extended causal framework that could deal with nonlinear effects of causal processes of causal interaction. This enabled thinking about nonlinear causality as a tool for thinking in complexity. The next link to be made was the link with the deeply overlooked link between thinking in complexity and network thinking (see Barabási 2003, p. 238). They are foundational for new thinking about explanation in terms of so-called ‘patterns models of explanation’ (Lincoln and Guba 1985). This kind of thinking, in turn, is opening for new thinking about dynamic landscapes of complex states of being of entities within generative state hyperspaces. These entities can be network-like entities composed of latent variables, linked with modelling organisms or human beings. Their complex, dynamic states of being are conceived as thriving on interaction within dynamic networks of interconnected loops. By becoming integrative of all these new ways of new thinking in complexity, about complex networks with nonlinear effects about generative states of being within high-dimensional spaces, we believe to have found the key for opening the world of real complexity. We may finally understand the real fabric of nature by understanding the fabric of causality and the fabric of networks operating in the real. Based on this, we may open ‘the spaces of the possible’, to be taken as real ‘spaces of possibility’ that we may view as complex, generative spaces and as domains of potentialities within ‘the realm of natural reality’, which is taken as much as ‘the realm of possibility’ by Rescher (1998, p. xv). These spaces within the realm of possibility can be taken as spaces to be enlarged (Rescher 1998, p. xiv). These are spaces with potentially explosive possibilities, of explosive growth, produced by what Rescher has called ‘explosive processes’ (Rescher 1998, p. xiv). We may think of such possibilities like ‘the Butterfly Effect’, or ‘the Snowball Phenomenon’ as nonlinear effects of amplifying within the new conceptual framework of complexity with its extended causal framework as a new tool for understanding and explanation. We strongly believe these spaces of possibility can be linked to the world of human beings as

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complex human beings. We think the new tools of think anew may be opening for understanding and explaining the complexity of these complex human beings in the realm. Our new understanding of complexity is rather broad and opening new dimensions. We made links with time and space and the nonlinearity of interaction and the modelling of that interaction. We also made a link with ontological complexity, generative complexity and social complexity. We showed how our modelling of the complexity of interaction encompassed the known Matthew Effect and the less known effect, ‘the Comenius Effect’, described by Jan Comenius, in his work as a pedagogue. These kinds of concepts are not only new concepts, of a new terminology but also tools for new thinking and new understanding of the complexity of the real, which is very much part of our real-world complexity. By linking our modelling of complexity with the modelling of networks as dynamically interconnected loop networks, we have developed the tools to describe complexity as the dynamic complexity of dynamic interweaving, which is involved in real-world complexity, with its underlying real-world dynamics. With the use of our ECF we could model this complexity of dynamic interweaving by dynamic networks of loops and the generative spaces of development, linked with these dynamic networks, with effects over time that can evolve nonlinearly. These effects could be visualized within high-dimensional spaces, as dynamic landscapes within such hyperspaces, evolving over time. We hope to have contributed to the elucidation of what has been called ‘complexity theory/science/thinking’ (Davis and Sumara 2006). We have delineated an integrative account of these terms. The reader may decide for her/him-self “whether it should be called a field, a domain, a system of interpretation or even a research attitude” (Davis and Sumara 2006, p. ix). We hope the reader may view it as a new way of viewing the complexity of the world with new eyes, able to see the world anew, enabling for exploring for what Stuart Kauffman described as the challenge of “the exploration of the world of the possible” (Kauffman 1993, p. 375). We take this challenge as the beginning of a new science: the science of complexity (see Jörg 2012). We think this may contribute to elucidate the dilemmas, the unsolved problems, the “great issues” (Oyama 2000, p. 57) and unanswered questions, posed by the evolution theory. The goal is to use the new thinking in complexity as a building stone for a more adequate theory of evolution; one that goes not only way beyond the idea of transmission and simplistic determinism but also way beyond the views of instructionism (Edelman and Tononi 2000, p. 81), of construction (Oyama 2000, p. 28) and of constructivism (Luhmann 2002). Our thinking in complexity replaces the failed notions of interaction and misguided interactionism (Oyama 2000, p. 47; emphasis added) and the failure of what Oyama has described as the Central Dogma of one-way thinking about causality and causal flows of information and influencing (Oyama 2000, p. 50; cf. Ulanowicz 2009, p. 9, about flows as causes).

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Theorizing on Complexity for the Social Sciences and Humanities We take our new approach of reality in the social sciences and humanities as a fundamentally different choice, by taking the complexity of reality not for granted (Bak 1996). Complexity is definitely not ‘simply’ complex. Complexity is ‘really’ complex: both in fact and as a fact! As the philosopher Nicholas Rescher (1998) was also clearly aware of in his book on complexity: “the fact is that complexity is self-potentiating” (p. 28). This simple but yet complex fact about complexity is also the very reason why we argue not to take complexity as a restricted complexity but as general complexity (see Morin 2007). Consequently, we may formulate the general challenge of new thinking in complexity for the social sciences in terms of “A general theory of complexity” (Barabási 2003, p. 237). This theory of complexity, we argue, is a general theory that will be able to address Stuart Kauffman’s fundamental question “What is the weave?” (Kauffman 1995a, b, p. 185) His focus was the complexity of complex systems like living systems, with their characteristics of life itself (cf. Rosen 2000). According to Kauffman it is clear that “no one yet knows” (Rosen 2000, p. 185). Kauffman’s question about the weave seems to be one of the still unanswered questions Herbert Simon (1996) spoke about in his book The Sciences of the Artificial. Considering this state of art in the field of concern, we may wonder why it takes so long to arrive at a general theory of complexity. We believe one of the main reasons is that we tend to be prisoners of description, taking a descriptive approach as the method of study rather than trying to become explanatory in our method and methodology. This is the lesson we have learned from Vygotsky (1978), in Mind in Society8: especially in his chapter 5 on method. For him the crisis in the science of psychology was a methodological crisis. It may be stated that the crisis in method and methodology was the main reason for the crisis in psychology (Vygotsky 1926/1997). Surprisingly, this fundamental lack in our viewing and doing science in the discipline of psychology has not been recognized by the followers of his ideas. In his basic work “Speech and Thinking”, he related his view to the problem of the study of the transitory child, which he borrowed directly from Goethe9 (see Vygotsky 1987a, b, p. 91). In this fundamental passage, at the end of this text, he made the fundamental remark about the foundation stone of psychology that has been disdained by the builders of science. We argue that this fundamental idea about science has been misunderstood or simply neglected by most readers of Vygotsky. This lack of understanding is, however, not hard to explain, because his message was formulated as the last line of a whole text, as a kind of conclusion. So, he was not very clear about the reasons for the disdaining of the corner stone. So, the fundamental reasoning behind this line, with its foundational meaning for science, 8   This is a rather composed kind of text, not composed by Vygotsky himself but by others (see introduction to this book). 9   See footnote 1 in this text.

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remained rather hidden. As a reader you may only understand this meaning by reading all of his work and especially in his text on the crisis in psychology. The problem, however, is that this text remained un-translated until 1997. Many of his followers simply seem not to have read this text, as can be derived from the references in their contributions. So, the question about the transitory child still remains very much an unanswered question. We believe, with Vygotsky, that we need a different method and a new framework for our science to be able to give an answer to this unanswered question. We argue here that we need a shift to the paradigm of complexity for new thinking in complexity to become not only descriptive but also more fully explanatory about the complex problems involved in these unanswered questions. With Vygotsky, we believe that we need to become explanatory about the causal dynamics involved in the dynamics of complexity of real-world complexity, being a fundamental part of the transitory child as a general object of study. To do so, we need quite a bit of rethinking, as demonstrated in the chapters above. Only after all of this rethinking we may be able to think in complexity about what is in fact complex. We may refer here, again, to Rescher (1998) and his idea about complexity: “The fact is that complexity is self-potentiating” (p. 28). If we can become explanatory about this fact, by following the new paradigm of complexity, with new thinking in complexity, then we are on the right track in our viewing and doing science. For then we may find our way through the world, which is a world of real-world complexity; a world of complexity that offers the perspective on a new ‘world of the possible’ (cf. Kauffman 1993, p. 371). This is a world of complexity, to be conceived as self-potentiating. It is a world that enlarges the spaces of the possible, with openings to new spaces of possibilities (see Osberg 2009; Kauffman 1995a, b; Davis 2004; Jörg 2009). Although we do not pretend to give a full answer to the simple but fundamental question, formulated by Kauffman above, about “what is the weave?”, we are pretty sure that the new, more complex answer will be about causal weaving within complex, causal networks of interconnected loops, with their dynamic forcing structure of forcing loops. These complex networks, we think, are constitutive of real complex systems (cf. Kauffman 1993, pp. 496–497). It is the weaving of these forcing loop structures with the intricate web of interactions that must be the focus for our theorizing and study of complex, living systems. So, we may strive for a general theory of general complexity, which is about the nonlinear complex nature of reality (Mainzer 2007, p. 16). We argue that it will be and should be, a general, scientific theory for viewing and doing science from a new transdisciplinary approach. We fully agree with Kauffman (1995a, b), who ended his book with the observation that “we have only begun to invent the science” (p. 304). One may wonder, then, not only why this is being the case but also how we may go on in our viewing and doing science for the sake of the invention of this new science. This is still not very clear. It is, however, for sure that we need a new language for complexity to deal with complexity and be creative of a new reality: that is, a much richer, language-effected sort of reality (Bohm 2004; Davis 2004; emphasis added). For it is very true that “one can only say with a given language what the language permits” (J. Z. Young, in Maturana 1980, p. xiii). Only with a new language, with its linguistically generated

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states, we may be able to generate a new reality,10 which is in essence always linked to a cognitive reality (cf. Maturana and Varela 1980, p. 121; Rescher 1998, p. 28, on expanding the space of reality). Similarly, theorizing on generative complexity, with its new epistemology of uncertainty about the possible, is always linked to ontological complexity; that is, the ontology of generative complexity, which is a dynamic sort of interactional complexity that may develop into a self-potentiating kind of complexity via generative processes and self-amplifying effects within generative structures of webbed, causal networks. These are the foundational networks with their webbed architecture of circular configurations, of causal loops, which may evolve into bootstrapping configurations over time, with processes of functional bootstrapping, based on self-enhanced total causal effects over time. These total effects may take place in a world, which we take as a causal world.

Fig.  15.1  “Sleeping beauty” (hanging) by Nadine Sterk (© 2006. Atelier NL. The Netherlands. Photo P. Scala. See Annex 15.1 for information)

10   We must however always keep in mind that “no description of an absolute reality is possible” (Maturana and Varela 1980, p. 121).

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Conclusions [The big questions are about] causes, strengths of causes, levels of causes and contingency (Gould 1996, in Horgan 1996, p. 124)

Thinking in complexity, we may conclude, becomes very much a kind of thinking in terms of possibilities: that is, of coming into existence, of realizing the living of systems within the hitherto unknown generative spaces of the possible. We are now able to propose a generative theory of evolution, based on the notion of generative complexity as a dynamic form of complexity and on a webbed network with a weblike architecture of circular bootstrapping configurations that may produce the effects we know from the complex phenomena of evolution (cf. Oyama 2000; Rosen 2000; Wimsatt 1999; 2006; Reid 2007; Ulanowicz 2009). With the new way of thinking in complexity, based on the new paradigm of complexity, we come to the main conclusion of this book. We do believe that our new thinking in complexity is opening for a new window on the world; one that goes beyond the Newtonian worldview as the first window and the Darwinian as a second window on the world. We argue for a third window on the world that is opening new spaces of the possible within a very much unexplored world of the possible (cf. Ulanowicz 2009, in his book on the third window and Kauffman 1993, p. 375 and Kauffman 2009, p. xii). It is a window that makes use of a new way of approaching complexity of the real and helps to view the world with new eyes. With Ulanowicz (2009), we think this window is really opening “a new window upon reality” (p. 4). With this third window, we may ultimately become able to describe and explain the ‘fabric of nature’, by the use of the extended causal framework (ECF) as the ‘fabric of causality’, with its hitherto unexplored generative functions. This fabric, then, takes place in a world to be taken as a causal world (Dennett 1984, in Oyama 2000, p. 183), with causal networks and their matrix of interaction within relational matrices (Maturana and Varela 1980). This description is about the interactive complex within the dynamic architecture of circular configurations of relations that may evolve through strong interaction within potential, circular bootstrapping configurations. So, for us this fabric of causality is not a metaphor (Ulanowicz 2009, p. 56) but should be taken as ‘really real’ (Oyama 2000, p. 207), being very much about a layered kind of (network) reality, of living beings realizing themselves through a ‘constructive’ kind of (strong) interaction within these relational matrices of the networks involved (Oyama 2000, p. 161, p. 105). We think this fabric of causality, of networks with dynamically interconnected causal loops, is very much part of the causal world we live in. It is the unexplored nonlinear causality within the new extended causal framework, delineated in this book. This is a framework that goes beyond the Central Dogma of one-way causation, of what has been described as the “canonical causes” (in Oyama 2000, p. 104), which are still dominating in our sciences (Oyama 1989, 2000). This fabric of nature is about the realm of natural reality, now conceived as a nonlinear complex reality. So, we have opened a new window upon reality (Ulanowicz 2009, p. 4). It is a reality that includes the space of the actual within the hitherto

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unknown space of the possible. We take these actual spaces as really real within the realm of possibility. So, the new paradigm of complexity is opening up new spaces of the possible as actual spaces of possibility within a nonlinear complex reality (Mainzer 2007). With the new tools of thinking in complexity we may become able to turn complexity into effective complexity. We may, then, make use of this effective complexity, by turning it into advantageous forms of complexity. Ultimately, we believe we may become able to understand and explain the complexity of complexity, to enhance complexity and become able to turn complexity into hitherto unknown states of self-potentiating within hitherto unknown generative spaces of possibility. We think this opening of the reality is not only opening for new thinking in complexity and modelling of the real but also for new thinking about the realm of possibility (Rescher 1998, p. xv). With Rescher, we may think about ‘the realm of natural reality’, as closely connected with “the real world of human experience” and link the complexity of dynamic interweaving of complex processes with ‘laws of nature’ (Rescher 1998, p. xiv). It is the dynamic and generative complexity that is ‘at work’ within these complex processes of dynamic interweaving. We think they are foundational for the dynamics of self-potentiating processes, such as ‘functional bootstrapping’, described by Stuart Kauffman as being very much part of the fabric of nature (Kauffman 1993; cf. Ulanowicz 2009). We may argue that the fabric of nature can be founded on what may be called ‘the fabric of causality’: that is, a nonlinear fabric of causality with potential nonlinear effects within a new, extended causal framework (ECF). We have developed a complex toolbox, full of complex tools for new thinking and modelling of the complexity of the real. This complex fabric can be conceived as being constituted on ‘a fabric of causality’ (Ulanowicz 2009, p. 56). With Ulanowicz, we believe that “causality in nature is necessarily a two-way conversation between top-down and bottom-up agencies” (p. 103; cf. Oyama 1989, 2000). We mean here a kind of circular or reciprocal causality, linked to and operating within causal loops and networks of causal loops in different high-dimensional spaces. We believe that it is the fundamental process of reciprocal causation as a kind of generative process of causation that is foundational for living systems in general and for life itself. But it is not just the processes that are foundational; it is the self-generative processes that create and turn the living processes into qualitative transformation, unevenness and even metamorphosis (see Goethe 1790; Vygotsky 1978, 1987a, b). It is through the patterns created within and through the dynamically interconnected loop networks that we may view how generativity is enabled, with the inherent, natural capability of “‘knowing’ how to go on” by the operation of generative complexity of the real within the realm of possibility. It is like the very powerful kind of patterns of processes Ulanowicz refers to in his book (2009, p. 148), referring to Mark Bickhard and Donald Campbell (2000), with their emphasis on patterns of processes: “it is patterns of processes all the way down, and all the way up” (p. 331; cf Whitehead 1925/1967, for a similar view, about nature, above). Our own concept of a dynamic, generative kind of causality, then, is a different kind of two-way causality within dynamic loops of networks, with their configuration of processes and reciprocal, interactive, causal relationships, with their power to become self-generative, enabled by the matrix of interaction within relational

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matrices of loops within reciprocal relationships. This power is the very power of the complexity to become self-potentiating, with potential nonlinear effects. This demonstrates the very complexity of real-world complexity of the real within the realm of possibility, as conceived by Rescher (1998). These nonlinear effects within the realm of possibility are corresponding with the nonlinear complex reality, which we take not for granted but as ‘really’ real. With the causal power of our extended causal framework we become more truly explanatory about “the nature of the fabric of nature” (Ulanowicz 2009, p. 55). Our complex, causal, generative approach, then, gets not only close to the realworld complexity of the real but also may get us close to what we take as the generative order of the nonlinear complex reality, showing the hitherto unknown path of how this reality may become nonlinear. In the same way as complexity can be taken as self-potentiating, which is a fact (Rescher 1998, p. 28), this kind of nonlinearity of reality can become a fact, which is generated in the real. From this shift of view and of thinking about the real we may develop a different view of reality: as one that is organized in the real within the realm of possibility. This kind of view is really opening a different view: that of a third window on the world. This window, based on the reframing of complexity within a new conceptual framework, is not only the new window upon reality but at the same time a window on the world of the possible. This world of the possible will be shown to be a world of novelty and innovation; one that departs from the reality as delivered by scientists viewing and doing their science as usual. With Wallerstein et al. (1996), we believe the opening of such a third window on understanding and explaining the nonlinear complex reality will be really opening the social sciences and humanities. The new window may open up new vistas of possibility that are hitherto still unknown and very much in need for exploration. We believe this window, linked with our new paradigm of complexity, may be opening for a new science, with new tools and a new language that affords the explanation of the complex processes underlying the ‘realization of the living’ of living systems (cf. Maturana and Varela 1980). With these tools, we might become explanatory about the potential enhancement of complexity, with different degrees of complexity, to be linked with the quality of the (causal) dynamics involved. This view diverges from Mainzer’s view about the question “what life is?” He is less optimistic about the complex systems approach (Mainzer 2007, p. 437; emphasis in original). Below, we go somewhat deeper into the possibilities for opening a new window for our sciences and the building of a new science. In a next publication we go deeper into the possibilities of building a new science of complexity (Jörg 2012).

How to Understand the Building of a New Science? Although we do not go all the way in sketching the foundation of a new science, we will give some basic preliminary considerations about the building of a new science. Elsewhere, we will go deeper into this fundamental thinking about

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reinventing science-as-usual for a new kind of science, with a different way of knowing about the complexity of our real world (see Jörg 2012). This will be about the generative foundation of a generative approach on the fundamental dynamic, generative complexity of our real-world complexity, which is a self-potentiating kind of complexity, opening up a new world of the possible. What is very fundamental for the new science is that time plays a central role in this. That is, in accounting for and explaining the complexity of real-world complexity and the power of complexity as self-potentiating in expanding our reality into a nonlinear complex reality (Mainzer 2007, p. 16). We may start our thinking about the invention of a new science by thinking about the relation between the classical science and the new science; that is, the science to be invented. All of this is meant for what Rescher (1998) describes as “the complexification of science” (p. 51; emphasis added). The new science will be and should be the new science that is able to deal with a new kind of reality, sketched above. This new reality, which refers to a fundamentally augmented kind of reality, actually becomes a new reality by the use of a new language. It is impossible to overemphasize the significance of the use of this new language to effect new realities in our viewing and doing science (cf. Davis 2004, p. 99). We take it as our point of departure that “the limits of our world …. cannot be claimed to be the limits of the world” (Davis 2004, p. 51). This has strong implications for our ways of knowing about a complex world. It changes our epistemology into an epistemology of the possible, which is as much about uncertainty and ‘the imperfectability of knowledge’ as about the complex world (Davis 2004, p. 45; emphasis added). Although one may wonder if the new theory of complexity will be a reconstruction rather than a deconstruction of the classical science (see Price 1997, p. 4), the general aim of our building a new science of complexity is to link the fundamental and the practical of complexity, which is very much the practical of a new method and methodology as a new tool for the study of nonlinear complexity in the real (cf. Turner 1997, p. xxv). Thinking in complexity for the social sciences is to be considered as mediating in an ever-increasing comprehension of itself (see Bell 2006, p. 16). This basic idea is linking the fundamental with the practical, in the following way: we need complexity for dealing with complexity. We need a web of thinking in complexity to deal with the complexity of the weave of complex systems being part and parcel of our nonlinear complex reality. These complex systems are the systems with their webbed networks of richly interconnected, dynamic loop structures and their webbed architecture of circular bootstrapping configurations, enabling for what Kauffman describes as ‘functional bootstrapping’ processes (see Kauffman 1993, pp. 428, 373). The relevant question, then, is “How to find the complex path in developing such a general theory of complexity, as fundamental and foundational for a new science of complexity which is of use for the practical?” This new path of new thinking in complexity will enable thinking about the scientific link between complexity as a general concept and complexity as dynamic complexity in practice. This linking may lead us to the notion of effective complexity as an important theoretical and empirical notion of new thinking in complexity for the social sciences. In taking

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this effective complexity into account, as a fundamental scientific concept, we may escape the confusion that Edgar Morin (2007) has described as “the illusion that complexity is a philosophical problem and not a scientific one” (p. 24; emphasis added). We strongly believe that this confusion is responsible for a large part of the rhetoric about complexity in the field of the social sciences and humanities. This confusion is very much a part of the crisis we are in; that is, in our viewing and doing science-as-usual. To escape this crisis we need to escape the dangers of linear thinking, as for example about linear causality, which is characteristic for a classic science-as-usual, operating with its blind spots and prejudices, which can be viewed as brought about by blinding paradigms and ultimately resulting in a kind of cul-de-sac or psychic prison, with scientists, for instance, being ‘prisoners of description’ (Edelman and Tononi 2000, p. 207).

The New Science The new science is about a kind of generative science with a strong focus on the generative nature of the complexity of reality with its fundamental, complex, generative order (Bohm and Peat 2000, p. 157). It is our mission to open up a new toolbox for thinking-out-of-the-box, for a better understanding of novelty and emergent order; a topic with questions whose answers are still unknown. We have to make a rather dramatic step: of rethinking the foundations of our social sciences and by taking a fresh look to the building stones that has been disdained. For enabling this mission, we have to go beyond the ‘poverty of reductionism’ or what has been called ‘the reductionistic dream’ (see Rose 1997, p. 272; Dennett 1993, p. 464). We need to take a rather radical process view of reality within the framework of multi-level order (Rose 1997, p. 225). The whole mission is to be conceived as a process of reinvention of our viewing and doing science. The complexity of our reality is not taken for granted but as a complexity that is fundamentally unlimited. Because of this, our knowledge of this unlimited complexity is always provisional. But this does not mean that we cannot tame, harness or ‘simply’ better understand this unlimited complexity. The crises we are in, demonstrate that “no one can afford not to understand the basic principles of how complex systems work” (Gall 1978, p. 17; emphasis added). It is the malfunction of how complex systems actually ‘work’ that we need to focus on (Gall 1978, p. 84), for better or worse. The critical mission of this book is about becoming more reflective about our viewing and doing science: about our assumed reality and our ways of knowing about a different, complex, nonlinear reality. This may lead to new thinking, i.e., about the need for a shift of paradigm. This, in turn, will bring forth the need for a new language to enable a different discourse about the new reality and the new object of study. The conceptual mission is about the need for rethinking our ontological and epistemological foundations and their interrelatedness with method and the methodology in use for dealing with the world. All of this has diverse consequences for the ways of thinking and the concepts in use in viewing and doing

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science. The activist mission is about the use of the newly developed tools as the result of all the new thinking in complexity for practice, for the enabling of a transdisciplinary approach.

The Architecture of a New Science of Complexity We will sketch below how thinking in complexity may foster our thinking in dynamic complexity as a building stone for a new science, which is about generative complexity. This kind of new thinking in generative complexity for a new science focuses on the role of causally generative processes and causal, generative structures from a full scientific endeavour to understand the role of them in enabling the development of self-producing, self-constructing systems in web-like networks. To recap the preceding chapters, we may turn the problem of complexity into a real scientific problem, by recognizing the need to rethink our common ways of thinking and start to rethink complexity by rethinking both interaction and causality, operating within the new unit of study, consisting in more fluid types of entity. We intend to show how the new thinking about complexity is linked to dynamic and to effective complexity, as stages of our new notion of generative complexity: see Box 15.2. The distinction between these forms of complexity as stages can be linked to the distinction between the different powers involved in the building of a new science of complexity: see Box 15.3. It now becomes possible to explain how they differ in power and quality.

Box 15.2  Distinction Between Different Kinds of Complexity Complexity ↓ Dynamic Complexity (DC) ↓ Generative Complexity (GC) ↓ Effective Complexity (EC)

Box 15.3  Different Kinds of Power of a New Science Causal power ↓ Generative power ↓ Bootstrapping power

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Conceived as different powers, with different qualities, they are part of the agenda for a new science. Based on these powers we may better explain the very complexity of reality: how the distinctive versions of complexity in Box 15.2 may actually ‘work’ in our scientific realms as realms of possibility. More importantly, we may describe and explain how these different forms of complexity may turn into a kind of advantageous complexity.

Causality and Explanation With the new conception of causality, based on the rethinking of causality, we may also present a different link between causality and explanation. We would like to propose here that thinking in complexity means thinking explanatory about complexity. Only then, we may be able to build a new, explanatory framework for a new theory of complexity, which may explain, within the extended causal framework, how complexity may be turned into dynamic complexity and how this dynamic complexity can be turned into effective complexity. With this new framework, we think, we might be able to link our fundamental theorizing about complexity with the practical of our inherently complex, nonlinear reality. It is our strong conviction that only such a new theory of complexity may afford the new language to explain what complex reality looks like and can tell how complexity at all levels may be ‘tested’ in the scientific realms of our sciences, in experimental settings or by simulation. With the new framework we may escape, in the field of biology, of what Reid (2007) describes as “the black hole of reductionism, which is still so much at its center” (p. 11). This kind of escape we may consider as essential, constitutive of a paradigm shift. This shift of paradigm may contribute to ‘solve’ “the perennial quest for explanations of evolutionary genesis” (Reid 2007, p. 5). Reid makes the link with what he describes as ‘evolutionary causation’ (Reid 2007, p. 5). We think he rightly does so! His view, however, diverts strongly from scientists, like Maturana and Varela (1980), who try to become explanatory about complex systems like living systems but seem to reject the notion and role of causality right from the start for this purpose. We think these scientists are therefore still very much the victims of blinding, misguided paradigms. As we may know from our history of science, causality and explanation have always been considered as strongly connected concepts. For Vygotsky, it was a plain truth that “For science to explain means to explain causally” (Vygotsky 2004, p. 234). But, of course, this doesn’t tell you how things might be explained causally. For in his time, there was not yet a causal framework available for the social sciences, like that of structural equation modelling (SEM). Actually, explanation, which is so much causally based and almost always thought of as a kind of law-like explanation, is actually not so much linear, law-like at all. What happens in the real, e.g., in the development of living beings as complex systems, it may be viewed more like causal tinkering through causal processes, operating as a kind of causal shaping by force within loops, ‘producing’ the kind of regularities one sees in the real.

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The complexity of these processes may be dealt with from a new, extended causal framework that takes the dynamic, generative processes and generative structures seriously, with their operation based on generative principles and generative mechanisms. We may speak, then, of the causal power of these causal networks. Their causal power may lead us to the notion of generative power of the causal processes of causal interaction within complex causal networks, with “richly interconnected loop structures” (see Kauffman 1993, p. 428), with their generative processes and generative structures operating in living systems in the real. The generative processes are bootstrapping processes with self-enhanced loop effects. The complex, causal networks of complex systems can be characterized by their different degrees of interactivity, connectivity and generativity, as dynamic states of (living) being, which may be linked with their evolvability (Érdi 2008; see also Kauffman 1993, 1995a, b; Solé and Goodwin 2000; Wimsatt 2007; Reid 2007). This sort of evolvability corresponds with the notion of novelty, how novelty is generated in the real. Finally, this shift of paradigm to “a causal theory of evolution” (Reid 2007, p. 59), to a more explanatory causal framework, is the shift to “unexplored potential for emergent order” (in Kauffman 1993, p. 367), in this case in complex biochemical systems. Actually, this is the generative potential exerted by force that shapes, which, we think, is a promising path for what may be called “the re-invention of Darwin” (Reid 2007, p. 27). This new path is the explanatory path of selfcausation that opens up a new explanatory mode and methodology for use in explaining the as yet unexplained. We think this is the framework that Stuart Kauffman may recognize as the framework that we are seeking: “the new conceptual framework that does not yet exist” (1995a, b, p. 185). This is the very framework with theories that are able to explain and show how generative processes can be enforced through hitherto unknown generative mechanisms in which “connected hypercyclic webs will emerge” (1993, p. 366). These webs may emerge in and through generative causation, thriving on (strong) interaction within web-like structures of (strong) reciprocal, causal relationships. Speaking about such a new framework, he clearly states that “We want such theories to be testable, we want them to be explanatory” (Kauffman 1993, p. 367; emphasis added). As a consequence, we may start to think of a new Darwinian paradigm that takes ‘the causal paradigm’ seriously (Reid 2007, p. 28); a paradigm that can be characterized by its inherent causal hypothesis. A causal paradigm that takes into account ‘causal agents’ and ‘generative causes’, conceived as generative evolutionary pressures with their (generative) effects, as constituent elements of the generative power of causality (see Reid, chapter 1). They are the explanatory tools for explaining novelty and innovation: another perennial quest for our sciences. They are also the tools for studying the mechanisms of so-called ‘proximate causation’ (Reid 2007, p. 58). We agree with Ernst Mayr that studying causation, with all its complexity of inherent, proximate causation, “has never been the job of the evolutionary biologist” (Mayr, in Reid 2007, pp. 58–59; emphasis added). So, with Kauffman, we may come to the conclusion that “we shall have to come to understand what ‘explanatory’ might mean in this context” (Kauffman 1993, p. 367). This is what our

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extended causal framework may afford for explaining what is part and parcel of our complex, nonlinear reality. A framework that is different from more common frameworks of dynamic causal modelling that are based on differential equations with time in its equations (cf. Érdi 2008, p. 272; Solé and Goodwin 2000, e.g. at pp. 86, 134, 229).

Complexity, Causality, and Novelty The question of novelty and innovation is another old question that still has no adequate answer, in fields like biology. This is very much true for the processes described by Darwin; processes that only later got the term evolution added to them. There is ‘simply’ no theory of evolution that is explaining the generative synthesis of new forms in evolution. This has been correctly recognized by Robert Reid (2007), in making the following statement: What we really need to discover is how novelties are generated, how they integrate with what already exists, and how new, more complex whole organisms can be greater than the sum of their parts (p. 9; emphasis added)

This is maybe the most basic question about evolution: “how innovation is generated?” (Reid 2007, p. 15; emphasis added). This question basically deals with the link between the fundamental and the practical. We fully agree with Robert Reid that the theory needed for this is “a causal theory of evolution” (Reid 2007, p. 15; emphasis added). His view about the role of causality corresponds strongly with Vygotsky’s (see Van der Veer and Valsiner 1991, p. 311). To become really explanatory about novelty in practice, we need a causal system of thinking and a causal framework for practice. To find the path of discovery, of generation of novelty, we may need to reinvent our way of viewing and doing science. This is in accordance with the tradition of our sciences; how they operate in their conventional scientific realms. The new extended causal framework may offer such a possibility for the reinvention of our sciences. A reinvention that is based on what may be called ‘the new causal paradigm’ (Reid 2007, p. 28). We think this new paradigm has the potential of using the new concept of ‘generative causes’ (Reid 2007, p. xiv). The concept of causality may be conceived as ‘shaping by force’, which is “a more dynamic active (causal) force that molds and shapes organic form as time goes by” (Eldredge 1995, in Reid 2007, p. 27). It is through the generative function of the total effects, linked to the causal loop that small changes in the values of the agentive entities may become enhanced through the causal dynamics taking place in the causal network, in the matrix of interaction within relational matrices. It is the interactivity and the connectivity of these networks that determine the generative power of the total effects. Effects that can be expressed as the generativity of the whole system, operating as a generative system with generative forcing structures (Wimsatt 2007, pp. 137–138; Kauffman 1993, p. 495), which in turn may express itself as evolvability; this equals the power to evolve

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with time (Kauffman 1995a, b). All the small changes may enforce a generative process of self-propagating influence or force that is shaping of a dynamic process of interweaving, which is self-generative and self-producing by an autocatalytic process: that is, a self-reinforcing process of ongoing self-cause in which effects are produced that are necessary for their own causation, to enforce their continuation by shaping forces over time. The link with the reality of complex, living systems, with their emergence of complexity in the real, remains largely an unanswered question. This is a reality that is of a fundamental generative order (Bohm and Peat 2000). We need to learn to think in generative complexity. Thinking in generative complexity fundamentally means thinking in terms of processes of dynamic interweaving through the causal dynamics operating within dynamic causal networks. Thinking in complexity implies the modelling of the dynamic interweaving within these networks. This can be done within the new causal paradigm, with loops and self-enhanced loop effects that show themselves in pictures of dynamic landscapes within state hyperspaces, which are closely linked to hypercyclic webs (Kauffman 1993). Modelling so may be a good start to think about complex, living systems and of the realization of the living in these systems. But to think in complexity about life itself, we need more complexity to become really explanatory of the complexity of living beings as the object of study. We need to become explanatory about novelty and innovation of life itself, in a way that goes beyond the poverty of reductionism. We need the fundamental principle of causality that is generative to be able to do so. It connects a holistic, web-like notion of causality with the fundamental fluidity of reality: see picture above. We may call this a real kind of Darwinian step in our viewing and doing science. This approach demands for a new holistic methodology about weblike structures and organisms as agents operating as weavers that are both the weavers and the patterns woven. We think that only by making such a fundamental step in our thinking, we may become really explanatory about the generative order that is so characteristic of all the patterns of life evolving over time. Becoming explanatory about these patterns we need to replace the common notions about explanation and take an alternative model and a new way of modelling that is based on a ‘pattern model of explanation’ (Lincoln and Guba 1985, p. 206), based on a viable concept of causality. This should be a kind of modelling that links “ideas of causality with possibility, so central to our developmental theories” (Oyama 2000, p. 184). This modelling is made possible by our new conceptual framework, which is an extended causal framework (ECF), with generative functions, which may explain the nonlinear total effects over time. We agree with Edgar Morin (2007) that the dominant view of complexity is still very much a restricted view of complexity. We may extend this notion of restricted complexity, to be able to speak about the quality of a dynamic complexity that has a link with the quality of life itself. We really need to go beyond the preconceived limits of the possible,11 to build a new science.

Mission of Para Limes (see above).

11 

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15 Summary and Conclusions

Picture 15.1  Guggenheim Museum Bilbao (Photo by Myk Reeves)

Annex 15.1

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Annex 15.1  Information About the “Sleeping Beauty” by Nadine Sterk, Atelier NL, The Netherlands Sleeping Beauty 2006 | Nadine Sterk Where there is light, there is life. When you switch on the lamp, it provides you with light. You provide it with the generating power it needs to grow. Similar to living organisms, this lamp contains all the essential “mechanisms” that will enable it to develop. All it needs is energy and it starts creating its own lampshade. It knits it slowly around the lamp, pausing only when the light is off. Its growth places it beyond the bare utilitarian necessity of artificial light. The lamp becomes an animatepart of space, an existence in its own right. text Theodora Antonopoulou photography Paul Scala collection gallery Kreo

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Index

A Academic framework, 127 writing style, 127 Academic world specialization in our, 128 Acquiring new ways of knowing, 129 Acquisition of knowledge provincial, 118 Action inter, 208, 211, 214, 216, 218, 219, 222, 233, 234 intra, 211, 219 traditional, 98 Activity (ies) real-time, 163 self-organizing, 28 Adaptation new method of, 37 Adapting, 95 Adventure of action and reaction, 180 uncertain, 116 Affair(s) complicated, 47 state of, 87, 101, 106, 112, 113, 233 Agency bottom-up, 255 discarded, 40 of the human being, 40 role of, 36, 40 top-down, 255 Agenda hidden, 20, 25, 30, 39, 43, 48, 70, 71, 76, 107 new, 43, 45, 48, 53–69, 71, 96, 116, 117, 130, 206 new kind of, 37

for a new science, 44, 46–47, 139–141, 260 of our sciences, 9, 37, 206 Agent(s) active, 66, 104 human, 55, 60, 62, 66 in interaction, 62 social, 61 Alternation of rest and movement, 60 Amplifying small differences, 154 through recurrent processes, 168 Analysis causal, 31, 106, 159–161 dominant modes of, 20 new methods of, 24 Antagonistic, 110 Appearances, 62, 89, 92 Approach critical constructivist, 117 critical realist, 117, 129, 130 ends-oriented, 122, 153, 162, 168 foundational, 9, 57, 159 fully generative, 177 fully integrative, 47 morphogenetic, 216 new, 3, 5, 45, 46, 57, 64, 130, 137, 140, 153, 156, 159, 176, 180, 183, 199–200, 239, 246, 251 ontological, 103 possibility-oriented, 66, 122, 168, 177, 230, 243 programmatic, 110 serious, 132 solid, 65 third-way, 206 trans-disciplinary, 12, 13, 47, 65, 104, 110, 165, 230, 246 281

282 Archer, M., 19, 36, 38, 40, 91, 99, 111 Architecture of (circular) bootstrapping configurations, 254, 257 of complexity, 97, 194, 205, 215, 247 of dynamic configurations, 205, 226 of loop networks, 229 understanding the, 194 webbed, 83, 101, 113, 193, 215, 226, 231, 247, 248, 253, 257 web-like, 4, 101, 116, 192, 193, 215, 259, 261 Arcs organization of (reflex), 58 reflex, 58 Assimilate, 95 Assumptions taken for granted, 35 Attitude empirical, 109 Autocatalysis as a generative process, 148 notion of, 148, 153 Autocatalytic loops, 146 processes, 113, 146, 163, 176, 263 Autostimulation, 36 Avenues (opening) new, 41, 112, 119, 122, 134, 177 for understanding, 119, 122, 134, 152, 177 Axelrod, 36–38 B Barabási, A.L., 194, 231, 248 Bateson, G., 47, 49, 66, 78, 82, 119, 158, 248 Becoming being through, 14, 39, 40, 54, 55, 86, 88, 123, 140 complexly, 145 Behavior future, 107 present, 107 Being becoming a, 14, 205 distinction between knowing and, 126 (complex) human, 1, 5, 11, 13, 14, 23, 29–32, 34, 36, 38, 40, 46, 51, 60, 61, 63, 64, 66, 67, 81, 86, 88, 93, 98, 105, 110–113, 126, 157, 177, 201, 203, 207, 208, 210, 211, 213, 216, 218–222, 228–231, 244, 249, 250 in-and-for-self, 205 more complex, 40, 46

Index new vision of human, 46 new way of, 46, 81 nonlinear, 14, 40, 67, 81, 110, 157, 201, 203 processes of, 55, 145 self-organizing, 145, 146 social, 14 the very nature of human, 40, 46 Belief(s) common, 105 paralyzing, 32, 36 Betrayal, 37 Bhaskar, R., 72, 85, 89–91, 93, 95, 96, 98, 99, 101–103, 107, 111 Biases intrinsic, 200 Bickhard, M.H., 255 Bi-directional influences, 206 shaping forces, 206 Bi-directionality dynamic, 182 of reciprocal interaction, 182 Biology scientific realm of, 39 Birth, 41, 43–51, 58, 69, 71, 81–83, 96, 99, 105, 116, 117, 121, 130 Black hole(s) in every totality, 141 of reductionism, 18, 21, 24, 30, 260 Blind (danger of) becoming, 40, 41 Blind alleys escape the, 41 Blinding (of) paradigms, 20, 25, 30, 39, 72, 75, 76, 142, 180, 190, 248, 258, 260 Blindness conceptual, 14 Blind spots, 25, 30, 39, 71, 72, 76, 82, 125, 141, 239, 258 Bohm, D., 33, 66, 224, 232, 240, 246 Bohr, N., 92 Bootstrapping configurations, 113, 193, 205, 253, 254, 257 dynamics of, 147, 181 each other, 150, 163, 207, 210, 229, 230 effects, 4, 113, 143, 193, 210, 231 into existence, 113, 242, 254 functional, 113, 194, 208, 227, 230, 242, 253, 255, 257 as a generative process, 148 over time, 194

Index power, 232 processes of, 32, 113, 163, 261 ‘productive’ of, 143 system, 79, 229 Bootstrapping processes ‘working’ of, 147 Borders cross the, 35 Brain freeing up space in the, 228, 233, 244 motor activity of the, 234 Breakdown of disciplinary modes, 125 Bridge the gap, 119, 132, 244 to the hitherto unknown, 45, 118, 119, 228 Brockman, J., 206 Bruner, J., 210, 245 Buckley, W., 159, 243, 248, 249 Building agenda for, 54 a new science, 11, 12, 14, 21, 22, 40, 47, 87, 103, 105, 109–111, 137–139, 147, 159, 179, 241, 247, 256, 257 Building block(s) basic, 180 for studying the complexity of real-world complexity, 180 Building stone for a new science, 86, 89, 138, 139, 163, 165, 181, 194, 201, 259 Bumblebee airborne, 128 flying, 128 Butterfly effect, 4, 135, 150, 231, 249 C Calculable the notion of the, 160 Campbell, D., 255 Capability of knowing how to go on, 255 natural, 25 Capacity to change goals, 68 enlarging, 2 Capra, F., 27, 129, 133, 134 Captive(s) of the blind spots, 125 of myopia, 25 of old thinking, 3 Carroll, J., 20

283 Causal agents, 62, 64, 261 Causal analysis traditional, 159 Causal chains of circular causality, 202 Causal dynamics, 4, 31, 57, 59, 61, 62, 64, 67, 97, 100, 112, 135, 138, 142, 144, 145, 148, 149, 153, 157–159, 161–168, 175, 176, 183, 184, 191, 202, 203, 205, 206, 208, 215, 216, 224, 231, 242, 252, 256, 262, 263 Causal events, 64 Causal hypothesis, 261 Causal influence, 7, 153, 162, 180, 182, 185, 241 Causality alternative metaphor of, 162 circular, 157, 158, 164, 202 complexification of, 203 complexifies, 142 complex role of, 142 concept of, 31, 61, 153, 157, 160–162, 168, 200, 231, 246, 249, 262, 263 construction(s) of, 159 creative, 164 different kind of, 149 dynamics involved in, 142 explanatory about, 143 fabric of, 216, 249, 254, 255 generative concept of, 168 generative power of, 64 ideas of, 263 interactive, 61 linear, 12, 80, 104, 158, 160, 199, 225, 258 in nature, 255 nature of, 158, 160, 161 needs time, 170 network, 158 new kind of, 162 new thinking about, 48, 61, 156–158, 248 nonlinear, 7, 9, 61, 156, 157, 249, 254 nonlinear reality of, 159 one-way (flow of), 3, 21, 156 paradoxical, 158 perennial of, 159 principle of, 61, 263 problematic concept of problem of, 3, 83, 106, 159, 160, 248 reciprocal, 61, 62, 255 rethinking, 139, 155–177, 179

284 Causality (cont.) role of, 142, 156, 159, 204, 260, 262 in social theory, 159, 160 (fundamental) stance about, 61 theory of, 149 (different) theory of, 62 (new) thinking about, 48, 61, 156–158, 248 thinking in terms of, 12, 61 topic of rethinking of, 159 trivialization of, 143 two-way (conversation), 255 (old) version of, 149 viability of, 161, 162 viable concept of, 162, 200, 231, 249, 263 web-like notion of, 263 Causal loop(s) reciprocal interaction within a, 135, 182 self-generative potential of, 188 unit of a, 182 Causal matrices, 217 Causal mechanism generative, 7, 63, 99, 168 reciprocal, 170 Causal modeling unexplored part of, 31, 161 Causal networks dynamic, 188, 204, 263 self-maintenant, 167 Causal paradigm, 261–263 Causal pathway compound, 171 of repeated cycles, 171 Causal power generative, 99, 129, 177 Causal process cyclic, 172 Causal relationships dynamic patterning of, 167 fluid, 161 reciprocal, 63, 135, 261 Causal sequence circular, 192 circularity of the, 192 simple, 192 Causal system reconstruct the, 24 Causal theory Darwin’s, 217 of evolution, 217, 261, 262 Causation between-level, 215 creative process of, 164 downward, 62 evolutionary, 260

Index functional theory of, 164 generative (self-), 150, 261 mult-level, 215 own, 143, 147, 149, 164, 191, 263 proximate, 261 self-, 146, 150, 191, 194, 261 social, 164 upward, 62 within-level, 215 Cause(s) canonical, 254 generative, 217, 261, 262 play of, 60 produce effects, 143, 147, 149, 164, 191 Causing mutually, 62, 149 themselves, 62, 149 Celebration of complexity, 19, 38 Central Dogma of one-way flow of causality, 3, 21, 156 Century of complexity, 180, 237, 238, 242, 245, 247 21st, 14, 19, 22, 71, 123, 137, 180, 242 20th, 13, 14, 21, 64, 99, 110, 156, 160, 161, 180, 246 Certainty contradictions of, 125, 139 deceptive, 125, 139 inadequacies of, 139 Certainty-driven, 99 Chain(s) of cause and effect, 143 Challenge of acquiring new ways of knowing, 129 methodological, 134 for new thinking, 134 practical, 210, 217 real, 18, 38, 78, 100, 113, 121, 139 theoretical, 217 ultimate, 7, 94, 140, 214, 228, 246 Chalmers, A.F., 111 Chance, 37, 72, 80, 100, 120, 195, 224 Change(s) amplification of, 162, 187 explaining, 39 fundamental, 69, 82, 138 morphogenetic, 216 paradigmatic, 138 qualitative, 14 theory of, 18, 40, 74 Characterization(s) qualitative, 132 quantitative, 132

Index Children trivialization of our, 18 Choreography of the causal dynamics, 215 Churchman, 120, 124, 132 Circuitry simplest, 187 Circular chains, 162 Circular fashion, 156 Circularity the idea of, 169 between variables, 170 Circuli vitiosi, 156 Clarion call to pursue Enlightenment, 23 Clark, M., 20, 38 Clash of doctrines, 27 Closure of the system, 22 Coefficients linear, 171 Co-evolving over time, 210 Cognition ‘real,’ 12, 44 theoretical account of, 44 Cohen, 36–38 Coherence creating, 163 self-creating, 163, 164 self-creative, 167 self-generative, 167 synthesis for, 167 Coherent whole, 68, 246 Collective level in our society, 38 Collectivities field of complex, 51 healthy, 46 Colonization of life world, 111 Comenius, J., 250 Communication problem of, 46, 47 Communicative interaction, 5, 32, 55, 56, 60, 66, 183, 200, 201, 213, 244 Communities of learning, 46, 51, 150, 230 Complex relational, 200 Complexification of causality, 203 of our sciences, 203 of reality, 203

285 Complexifying is humanizing, 4, 19 the process of, 38, 154 the subject of study, 113, 230 the urgency of, 38 Complexity (ies) advantageous (forms of), 7, 189, 226, 242, 255, 260 at all levels, 260 architecture of, 97, 194, 205, 215, 247 basic notion of, 57 behavioural, 229 broader scientific view of, 128 as a building stone, 138, 259 celebration of, 19, 38 complexity of, 1, 2, 19, 34, 40, 50, 74, 131, 142, 145, 176, 177, 180, 181, 189, 191, 194, 195, 197–206, 210, 218–219, 231, 238, 248, 249, 256, 257 complex notion of, 138 conditions for understanding, 57 cybernetic-based, 111 dealing with, 37, 119, 127, 142, 165, 183, 194, 231, 249, 257 definition of, 131 description of, 53, 198, 204, 222 descriptive, 197, 200, 224 different views about, 132 dynamic (forms of), 219 dynamics of, 12, 14, 53, 57, 59, 100, 102, 138, 139, 167, 181, 219–221, 252 effective, 7, 55, 57, 59, 65, 122, 138, 139, 165, 167, 189, 191, 226, 255, 257–260 enhancement of, 214–218, 256 of the entities involved, 229 exact meaning of, 141 explanation of, 57, 63, 135, 138, 141, 176, 238 extended notion of, 154 field of, 12, 60, 132, 141, 165 flattening real, 201 fluid, 206 forms of, 121, 219, 242, 255, 259, 260 fundamental problem of, 153, 154, 159, 166 fundamental processes of, 37 general, 64, 154, 197, 200, 241, 251, 252 generalized, 153 general science of, 120 general theory of, 198, 217, 241, 251, 252, 257 generative (nature of), 3, 21, 112, 231, 258 generative approach of, 177, 203–204, 257

286 Complexity (ies) (cont.) generative kind of, 146, 183, 184, 189, 217, 226 generative notion of, 185, 197, 200 for granted, 12, 21, 37, 180, 197, 198, 206, 238, 243, 251, 258 greater, 49 grounded theory of, 7 harness, 19, 36, 38, 131, 142, 242 higher level of, 167 inherent, 11, 30, 81, 87, 101, 106, 109, 112, 129, 157, 181, 184, 188, 191, 231 interactional, 112, 197, 216, 219, 253 intra-actional, 216 kind of, 37, 74, 100, 143, 146, 183, 184, 189, 217, 218, 226, 253, 257 living, 199 as method of thought, 143 natural, 6 neglected, 124, 144 new conception of, 46, 121 new epistemology about, 118, 199 new landscape of, 34 new language of, 50, 202 new paradigm of, 44, 177, 189, 202, 203, 214, 217, 242, 252, 254–256 of the new real(m), 140 notion of, 11, 19, 55, 57, 110–112, 138, 146, 152, 154, 176, 184, 185, 189, 197, 198, 200, 231, 245 ontological, 125, 214, 224, 225, 250, 253 ontological creativity of, 225 ontological status of, 198 organized, 79, 183, 188, 189 of our knowing, 133 (self-potentiating) power of, 21, 189, 205, 228, 257 for practice, 51, 165, 259 in practice, 117, 132, 257 problem (for), 121, 142 the problem(s) of, 7, 44, 46, 55, 132, 165, 248, 259 (is a) quality, 67, 205 quality of, 55, 205, 206, 243, 244, 247, 263 real, 1, 5, 12, 36, 117, 121, 126–130, 135, 138–140, 157, 180, 181, 201, 210, 214, 225, 230, 238, 241, 243, 248, 249 as real, 43, 117, 124 of the real, 1, 2, 8, 9, 44, 45, 59, 73–75, 90, 93, 95, 98, 100, 101, 103, 104, 111, 121, 139, 145, 157, 168, 191, 202, 203, 210, 214, 216, 217, 222–228, 231, 237, 238, 241, 243, 248, 249, 254–257

Index of reality, 30, 34, 36–38, 40, 45, 46, 48, 49, 58–59, 62, 72, 74, 87, 89, 93, 95, 100–103, 105, 107, 109–111, 115–136, 138, 141, 148, 155–157, 159, 165, 180, 181, 199–200, 203, 239, 241, 242, 248, 251, 258, 260 a really complex concept, 46 real-world, 1, 2, 5–7 of real-world complexity, 1, 2, 5–9, 19, 21, 34, 37, 40, 46, 50, 61, 65, 74, 116, 131, 134, 142, 180, 189, 191, 194, 200, 202, 203, 210, 231, 243, 248, 249, 252, 256, 257 re-describing, 21 (unduly) reducing, 13, 102, 142 reduction of, 1, 223, 224, 231 reframing, 2, 5–8, 48, 83, 98, 194, 195, 231, 238, 256 relevance of, 105 restricted (view of), 129, 154, 197, 200, 251, 263 as a result of weaving, 45 as science, 237 (new) science of, 1–3, 5–9, 34, 41, 47, 48, 83, 113, 115, 121, 130–132, 137, 138, 145, 153, 177, 181, 187, 194, 198, 201, 206, 211, 225–228, 241, 243–245, 247, 248, 250, 256, 257, 259–260 scientific approach of, 167, 238 self-generative, 21 self-potentiating, 2, 3, 9, 19, 181–183, 189, 201, 225 single science of, 130 social, 55, 250 the study of, 100, 142, 189, 237, 247 subsequent, 37 as that which is woven together, 45 theorizing about, 7, 183, 260 tower of, 215 un-analyzable, 231 (true) understanding of, 2, 3, 6, 7, 14, 21, 24, 31, 36, 38, 50, 62, 63, 65, 66, 128, 129, 132, 250 unexpected, 72, 134 unfathomable, 5 use of, 105, 139, 238, 242 versions of, 260 as the very process of dynamic weaving, 45 of the whole human being, 30 (the) world’s, 1, 19, 73, 217, 227, 242 as worldview, 143, 254

Index Complexly explanatory, 129 Complex notion of complexity, 138 Complex process of self-potentiating, 138 Complex role of causality, 142 Complex systems functioning of, 9, 70, 164, 185, 191 generative, 70, 183, 188, 191, 242, 245 Complexus to deal with, 65 Complication leaving out, 128 Complicity ontological, 61, 126, 129, 133, 140, 145 Concept(s) of complexity of (human) agents, 55 core, 137, 147, 162, 168 entangled web of, 47 fruitful, 139 generative, 139, 168 trans-disciplinary, 101, 163, 189 Conceptions of causality, 55 of (dynamic) complexity, 121 of interaction, 56, 168 of a real world, 44 Conceptual deadlocks, 21, 41 Conceptualizing the complex unity, 59 (the) impossibility of, 59 Conceptual quicksand, 127 Concern for the epistemological foundations, 125 Conditions sufficient, 57 for understanding complexity, 57 Configurations architecture of, 215, 226, 231, 253, 254 bootstrapping, 113, 193, 205, 215, 253, 254, 257 dynamic, 205, 226, 229 Confusion escape the, 138, 165, 258 Connectedness fundamental, 2 sense of, 64, 223 Connection(s) causal, 167, 170 between complexity and causality, 142 with interaction, 143

287 Connectivity degree of, 81, 203, 243 of networks, 188, 262 Constituted dialectically, 57 by social relations, 57 Constitution human, 37 Construction novelty, 21, 24 theory, 129, 132 Constructivism danger of, 96 social, 232 Context creation of a, 230 Control emphasis on, 50, 227, 247 Copernicus, 26 Core concepts rethinking of the, 137 Core of theorizing, 139 Cornerstone disdained, 105, 187 new, 105 Correlations fluid, 161 Correspondence between thinking and being in science, 89, 140 Couplings hypercyclic, 4 nonlinear, 4 Courage a kind of, 116 lacking, 116 Co-vary, 184 Creating novelties, 153, 164 Creation of a context, 230 Creative experience, 56, 68, 180, 205 Creativity of complexity, 225 fundamental nature of, 46 intrinsic, 157 key for, 66 of nature, 157, 227 ontological, 133, 134, 136, 138, 140, 143, 144, 157, 158, 224, 225 real, 40 topic of, 66 Crick, F., 205

288 Crisis contemporary, 17, 20, 103 as a crisis, 28 denied, 22, 28 dimensions of, 127 emergent, 26 growing, 26, 27 at hand, 22, 28, 33 inability to deal with the, 28, 29 incapacity to reflect on the, 18, 25 manifestations of, 19 methodological, 14, 29, 35, 77, 87, 91, 121, 251 multiple, 20 in the natural sciences, 22 neglected, 28 notion of, 22 phenomenon of, 26 as a problem, 22 problem of, 27, 29 profound sense of, 64 in psychology, 14, 25, 29, 30, 45, 76, 77, 85, 91, 93, 98, 121, 251, 252 recognize the, 18, 28 reflecting on the, 18, 22–24 role of, 14, 22 scientific, 14, 19, 20, 35 scientific problem of the, 29 of (our) society, 35 solving the, 33–39, 71, 91, 133 state of, 26 (develop) theory of the, 18, 21, 28–32, 87 topic of, 20 of Western Reason, 20, 103 Critical moments of evolution, 176 psychologist’s, 176 Critical stance toward psychology as a science, 29 Crossing complex, 95 Cul-de-sac, 1, 86, 87, 258 Cultivating humanity, 13, 34, 38 Culture based on dialogue, 66 coherent, 66 deprivation of (our), 13, 20, 231 deprived, 19 disastrous for (our), 13 of education, 231 first, 13 in general, 231

Index perpetuation of, 66 perversion of, 19 richer, 12, 13, 104 second, 13 third, 13, 68, 206, 244 two, 13 Cumulate, 4 Cycle(s) complex, 202 couplings of, 4 creative, 202 cycle after, 171 hyper, 201 network(s) of, 201 ongoing, 171 repeated, 171, 202 vicious, 202 Cyclical-helical unity (C-H U) (causal) dynamics of, 202 as a generative process, 202 as a generative structure, 202 loops of the, 202 D Danger of closure in science, 128 of constructivism, 96 escape the, 12, 40, 48, 87, 104, 139, 150, 155, 156, 199, 200, 232, 258 of instructionism, 232 of linear thinking, 26, 33, 40, 48, 75, 87, 95, 104, 139, 150, 155, 200, 258 of lock-in, 126, 128 Darwin, C., 34, 39, 51, 109, 261, 262 Darwin’s causal theory, 217 Davis, B., 127 Dealing with complexity a new method about, 37 a new methodology about, 37 Decomplexifying, 154 De-entifying, 180 Deepening, 8 Definition (generally) agreed on, 131 of complexity, 131 Degeneration of culture, 19, 231 Degree of complexity, 203, 243, 256 of connectivity, 81, 203, 243 of evolvability, 261

Index of generativity, 81, 203 of interactivity, 81, 166, 181, 203, 215, 243, 261 plasticity, 215 quality, 206, 256 stability, 215 De-humanizing, 20, 111 Delusion, 37 Delusive society, 35 Demarcation (old) line of, 156 Dennett, D., 20, 30, 76, 107, 126–128, 133 Departure point of, 20 Deprivation of our culture, 231 signaled, 13 Description(s) metaphoric, 54 prisoner of, 125, 145 Design, 37, 100 Determining a process of, 164 Determinism as-usual, 164 fluid (version of), 4 humanize(d), 3 mechanistic (version of), 5 Deterministic, 80, 106, 160 Developing into potentiality, 60 Development complexity of, 47, 95 equations of, 167 human, 5, 14, 21, 98, 204 interactive view of, 168 of a new language, 33, 47, 70, 135, 137, 181, 202, 228, 231 processes of, 31, 97, 98, 125, 129, 157, 160, 163, 210, 216, 230 recursive, 95 relational view of, 183 self-referential, 95 spiral (processes) of, 216 of tools, 36, 137, 138, 215, 227, 241, 249 trajectories of, 97, 125 Developmental theories, 263 Dichotomy traditional, 156 Dictionary, 127, 148, 149, 209, 210

289 Differential equations linear, 132 nonlinear, 132 Directionality notion of, 183, 203–204, 243 unknown, 116 Disciplinary framework, 125 modes, 125 Discipline(s) of concern, 26, 27 different, 1, 3, 6, 12, 27, 32, 44, 64, 73, 75, 104, 125, 130, 163, 164, 198, 204, 238, 242 field of, 9, 13, 47, 49, 55 realm(s) of our, 1, 3, 141 related, 27 separate, 13, 37, 59, 72, 106, 121, 124, 129, 132, 137, 140, 141 variety, 7 various, 9, 27, 75, 198, 217, 238 Disclosure, 103 Discourse academic, 14, 25 development of, 128 invention of, 128 new, 12, 128 ready-made, 12, 128 (a) third, 206 Dis-covering, 109 Discovery, 11, 92, 128, 198, 224, 262 Disdain, 8, 21, 86, 94, 105, 123–125, 144, 153, 181, 187, 251, 258 Disentanglement analytical, 22 Diversity as a resource, 66 (unknown) role of, 67 Doctrines clash of, 27 Dogma central, 3, 21, 24, 156, 205, 206, 240, 250, 254 Doll, 158 Domain(s) of knowledge, 28 of potentialities, 54, 66, 67, 121, 222, 244, 249 of (creative) potentiality, 35 of the unknowable, 28 unknown, 121, 207 Dominance of linear thinking, 1 Dutch committee of the PPCCS, 44

290 Dynamic(s) biological, 66 of bootstrapping, 4, 147, 148, 152, 181, 215 (mutual) causal, 162 complex, 121, 129, 181, 191, 210, 220 of complexity, 12, 14, 40, 44, 45, 50, 53, 55, 57, 59, 61, 63, 65, 100, 102, 104, 107, 116, 121, 130, 138, 139, 167, 181, 219–221, 225, 245, 247, 250, 252, 255, 259 generative, 63, 191, 205, 226 historical, 49, 66 hydraulic, 162, 164 landscape(s), 54, 135, 210, 214, 222, 229, 249, 263 of life itself, 210, 263 of living phenomena, 129 modeling of, 7, 57, 98, 161–162, 165, 183, 250, 255, 263 nonlinear (in), 100, 114, 180, 181, 187 of non-living phenomena, 129 quality of the, 55, 204 real-world, 44, 45, 51, 54, 59, 61, 62, 65–67, 72, 73, 89, 93, 104, 116, 117, 121–124, 126–129, 134, 135, 145, 148, 164–166, 168, 181, 189, 192, 203, 224, 225, 231, 250 of self-potentiating, 214, 255 social, 49, 66 tri-angular, 126 unity of the, 129 Dysfunction severe, 35 Dysfunctionalities, 125 E Ecologist, 41 Edelman, G., 125 Education ambiguity of, 36 field of, 1, 5, 18, 46, 47, 51, 66, 75, 93, 98, 113, 165, 208, 230, 238 for the future, 18, 32 lessons of, 18 new type of, 51 system of, 1, 98 Effect(s) amplifying, 70, 173, 253 asymmetrical, 57 beneficial, 207 bootstrapping, 4, 113, 143, 147, 193, 194, 210, 231

Index butterfly, 4, 135, 150, 231, 249 causal, 4, 62, 70, 135, 144, 149, 153, 157, 158, 162, 168, 170–175, 185, 186, 191, 192, 202, 213, 221, 224, 253 circular, 171–173 Comenius, 135, 148, 250 components, 171 composite (total), 222 concomitant, 13, 57, 149, 150 cumulative, 55, 57, 171, 172 damaging, 111 dehumanizing, 20, 111 detrimental, 175 devastating, 111 deviation-amplifying, 70 direct, 170–174, 212 distinct causal, 173 emergent, 138, 225, 230 generating the, 186 generative, 182, 186, 187, 224, 230, 261 Jörg, 7, 135 Landscape of causal, 192 loop, 142, 143, 146, 158, 164, 175, 180, 187, 189, 197, 204, 261, 263 Matthew, 7, 135, 148, 250 multiplied, 171, 173 multiplier, 4, 164 non-linearity of, 174–175, 241 non-linear transition of, 187 non-symmetric, 171, 172 ontological, 103 over time, 4, 39, 55, 57, 62, 135, 138, 143, 144, 149, 150, 160, 161, 163, 164, 167, 170–175, 183, 184, 186, 187, 191, 202, 214, 215, 219, 225, 226, 229, 241, 250, 253, 263 over time and space, 225, 226, 228, 229, 231 perverse, 24 play of causes and, 60 reciprocal, 4, 152, 156, 169, 171, 174–175, 186 role of emergent, 230 self-, 170, 171, 173 self-enhanced loop, 142, 146, 158, 164, 175, 180, 187, 189, 204, 261, 263 self-generated, 173, 186 self-propagating, 187, 188, 191 symmetric, 172, 174, 187, 213 transition(s) of, 162, 163, 187 transmit, 171 Einstein, A., 18, 92, 102 Elaborate, 93, 115, 166, 167, 185, 209

Index Elements of change constructive, 27 destructive, 27 El-Hani, 167 Elias, N., 138, 158 Eliot, T.S., 24 Elliott, 131 Emergence of functions, 64, 100 of novel theories, 43 phenomenon of, 36, 84 process of, 138 role of, 230 of structures, 64, 101 Emergent spiraling nature of processes, 98 Emerson, R.W., 244 Empirism blind, 77, 99, 110 Enchantment of complexity, 11, 19, 23 of humanity, 19 of humankind, 11, 19 Endeavour human, 122 Enforce a generative process, 263 Engagement active, 107 Enlightenment motto of the, 23 topic of, 23, 116 Enriching for humanity, 74, 233 for society, 233 Ensemble dynamic, 7, 180, 241 systems, 7, 207, 210, 222, 241 unities of, 4 unit of an, 185 Enterprise (truly) scientific, 29, 41 Entity(ies) agentive, 262 complex, 62, 210 complexity of, 167, 259 dynamic, 62, 167 evolvability of, 210 fixed, 81, 162, 167, 182 fluid kinds of, 161, 187 fluidly connected generate, 143 (fluid) generative, 168 (potentially) nonlinear, 62 (fluid) type of, 259

291 Entrainment mutual, 166 Entrapped, 1 Entrenchement generative, 165 Environment context of, 5 cultural, 128 dynamic, 61, 107 fluid, 217 political, 128 pre-specified, 30 shared, 210 technological, 128 Epistemic fallacy, 91 Epistemological angle, 136 Epistemological basis, 144 Epistemological beliefs, 117 Epistemological consequences, 142 Epistemological difficulty, 136 Epistemological problem broader, 116 the very complexity of the, 116 Epistemological question general, 117 Epistemological stance, 123 Epistemology constructivist, 103 dominant, 106 emerging, 118 of the possible, 5, 6, 118, 129, 199, 226, 243, 257 standards of, 106 of the uncertain, 107, 199 Equation(s) bring life into the, 181 causal, 177, 202 of complex systems, 181 of development, 167 differential, 132, 262 rewrite the, 184 structural (causal), 143, 156, 161, 202 with time, 184, 262 turning time into the, 125 Escape the confusion, 138, 165, 258 the danger, 48, 87, 95, 104, 139, 150, 155, 199, 200, 232, 258 old notions of the real(m), 125 Escaping imprisonment, 132 the orthodoxy, 156 Escher, M.C., 108, 131, 144, 151

292 Evolution causes of, 217 conception of, 39 (psychologist’s) critical moments of, 176 engine of, 66 generative theory of, 254 ‘motor’ of, 190 of species, 230 theorizing on, 210 (causal) theory of, 261, 262 Evolutionary causation, 260 genesis, 260 Evolvability characteristics of, 242 concept of, 210 different kinds of, 230 of entities, 210 of life, 65 processes of, 210, 242 Expanding of our sciences, 227 view on the, 227 Expansion interactive, 209 Experience creative, 56, 68, 180, 205 human, 20, 24, 255 (human) lived, 59 progressive, 153 Explaining innovation, 261 novelty, 261 Explanation different logic of, 155 new kind of, 194, 200 pattern model of, 190, 200, 243, 263 scientific, 53 Explanatory complexly, 129 of the dynamic complexity, 63 (causal) framework, 62, 63, 256, 261, 262 methodology, 36 the need to become, 36 (become) really, 133, 177, 206, 238, 262, 263 tool for becoming, 62 truly, 256 Extended Causal Framework (ECF), 9, 173, 175–177, 179, 205, 231, 254, 255, 263 Extended model, 184 Eye(s) metaphor of the, 17, 35 new, 6, 229, 250, 254

Index F Fabric of causality, 216, 249, 254, 255 complex, 216, 255 of nature, 216, 249, 254–256 nonlinear, 255 Fact self-potentiating, 19, 21, 23, 34, 71, 88, 112, 118, 138, 140, 176, 179, 182, 192, 201, 205, 214, 223, 226, 242–244, 251, 252, 256 vexatious, 37 Fay, B., 110, 126 Field of biology, 31, 230, 242, 260 of complex collectivities, 51 of learning and education, 1, 5, 18, 46, 51, 93, 113, 165, 208, 230 of learning organizations, 46 of learning within the unknowable, 12 of methodology, 142 of social sciences, 11, 12, 34, 39, 40, 54, 55, 58, 130, 149, 209 of the still unknown, 12 Fitness landscape, 135, 161 Fix for (such) a new framework, 65 quick single, 65 Flatland domain within, 201 escape, 201 Flood, R., 28 Flow one-way flow, 3, 21, 156, 205, 240 promoting its own, 224 Fluid mixing, 56 Fly in the bottle, 103 Follett, M.P., 26, 56–58, 61, 66, 138, 150–153, 163, 168, 169, 171, 175, 176, 180 Force(s) causal, 4, 7, 162, 204, 262 driving, 7 exerted, 7, 32, 138, 165, 177, 183, 186, 198, 200, 206, 217, 229, 231, 261, 2216 impelling, 4, 32, 80, 145, 153, 162, 170 (fluid) interplay of, 4 mutually shaping, 182, 183, 215, 217, 229, 231 in practice, 130 repressive, 130 self-propagating, 263

Index shaping, 4, 7, 138, 144, 145, 153, 167, 170, 173, 182, 183, 186, 200, 205–207, 215–217, 229, 263 social, 229, 231 unknown, 105, 183 Form innovated, 14 social, 95, 148, 158 Formula methodological, 36 Formulations mathematical, 105 Foundation the creation of a new, 34 evolutionary, 163 generative, 163, 177, 243, 245, 257 ontological, 120 re-describe the, 1 of a science, 91 stone, 18, 21, 23, 87, 94, 123, 124, 181, 187, 201, 202, 243, 247, 251, 1221 Founded wrongly, 102 Framework abundantly opening, 67 academic, 127 analytical, 37 as-usual, 166, 167, 175 build new, 2, 65 (extended) causal, 7, 9, 135, 173–177, 179, 193, 200, 202, 205, 211, 222, 224, 230, 231, 241, 249, 250, 254–256, 261–263 (new) conceptual, 37, 65, 75, 100, 101, 103, 132, 225, 231, 237, 243, 249, 256, 261, 263 current, 124 (short) description of our new, 63 disciplinary, 125 explanatory (causal), 7, 62, 63, 134, 145, 261 extended, 7, 9, 135, 173–177, 179, 193, 200, 202, 205, 211, 222, 224, 230, 231, 241, 249, 250, 254–256, 261–263 new, 2, 5, 11–13, 19, 28, 34, 37, 41, 63–66, 99, 104, 124–126, 135, 136, 143, 150, 161, 164, 194, 211, 231, 237, 239, 252, 260, 261 solid, 37 stepping outside of the, 124 that does not exist yet, 11, 13, 19, 28, 37, 41, 65, 75, 100, 101, 104, 132, 261 trans-disciplinary, 98 Frontiers of science, 136

293 Function(s) complex, 176, 242 complexity of, 100 developing, 100 development of, 100 emergence of, 100 emergent, 99 generative, 97, 172, 176, 177, 182, 186–189, 191, 197, 202, 204, 205, 211–213, 220, 222, 224, 230, 231, 241, 254, 262, 263 self-generative, 177 Functioning of living (human) systems, 230 as self-generative systems, 230 Fundamental General psychology, 88 Future challenge for the, 22 different, 23, 59, 126, 239 hope for the, 2, 22, 134 landscape of the, 34 of the new science, 134 under perpetual construction, 149 shape the, 3, 9, 41, 70, 206 shaping the, 9, 89, 122, 128, 140, 206 of the social sciences and humanities, 14, 17, 72, 83, 84, 88, 89, 126 of the 20st century, 246 G Galileo, 26 Gap(s) bridge the, 119, 132, 244 in our understanding, 119, 132 Gehry, F., 102, 109 General complexity notion of, 154, 197, 200 Generate novelty, 30, 50, 93, 261 power to, 144, 209, 244 self-change, 61, 63 spaces, 7, 205, 210, 246, 249, 250, 254, 255 unpredictability, 30, 93 Generating influences, 61 process, 145, 163, 191 self-growth, 63 of this world, 67 Generation of effects, 213 of novelty, 262

294 Generative complexity, 3, 9, 21, 101, 112, 146, 176, 177, 183, 185, 197, 198, 200–205, 210–211, 216, 217, 219, 224–226, 231, 243, 245–248, 250, 253–255, 257, 259, 263 effects, 182, 187, 224, 230, 261 forces, 183, 198, 200, 229, 231, 248 foundations, 163, 177, 243, 245, 257 function, 97, 176, 177, 182, 186–189, 191, 197, 202, 204, 205, 211–213, 220, 222, 224, 230, 231, 241, 254, 262, 263, 272 kind of complexity, 146, 177, 183, 184, 189, 217, 226 mechanisms, 7, 32, 61, 64, 67, 90, 97, 99, 104, 136, 139, 144, 147, 148, 165, 166, 168, 175, 181, 205, 215, 226, 261 power, 7, 9, 32, 64, 104, 105, 165, 168, 177, 198, 204, 205, 223, 225, 244, 259, 261, 262 principle, 60, 97, 104, 129, 130, 139, 153, 166, 168, 175, 181, 185, 188, 191, 205, 261 states, 112, 113, 201, 228, 229, 249 structures, 146, 163, 168, 175, 188, 191, 201, 202, 205, 248, 253, 259, 261 Generative complexity description of, 201, 203, 210–211, 216, 219, 224 explanation of, 176, 210–211, 216, 226 exploring, 197 general notion of, 197 generative power, 9, 204 nonlinearity of, 197, 201 Generative forces, 183, 198, 229, 231, 248 Generative forcing structures, 262 Generative function of total effects, 212, 220, 222, 241 Generative power of generative complexity, 9, 204 Generative system, 70, 79, 160, 163, 164, 168, 183–185, 188, 191, 201, 227, 229, 230, 242, 245, 246, 262 Generativity achieving, 201 collective, 201 degree of, 81, 203, 206 dynamics of, 66 of living systems, 229 of new life, 64, 65 as a norm, 98, 205 as a state of being, 98 of the whole system, 230, 262

Index Genesis evolutionary, 260 Genius recognized as a, 145 Geometric series infinite, 171 Geometry pre-existing, 182 for space, 182 Gergen, K., 104 Giants in the field of our social sciences, 55 Gibbons, 124, 125 Glick, J., 94 Globus, 222 Goals capacity to change, 68 Goal-seeking (great) complexity of, 68 vast extent of, 68 Goethe, W., 198, 245, 247, 251 Goodwin, B., 61, 62, 64, 158, 229, 243, 247 Grammar new, 114 Grounding of simplicity, 119, 142 of systematicity, 119, 142 Guba, E.G., 49, 161, 162, 187, 200, 249 Guide to the future, 98 unreliable, 98 Gulbekian, 49 H Habitat, 61 Habits of thought escaping (dear) old, 33, 46, 55, 72, 98, 110 traditional, 46 Hawking, S., 71, 238 Hayduk, 186 Hayek, F., 116, 126 Hebb-like learning rules, 113 learning strategies, 113 Heuristic scheme for constructing models, 39 Higher behavior human, 37 specific uniqueness of, 37 Historical overview, 145

Index Hofstadter, D., 63 Holistic methodology, 263 notion of causality, 263 Homo complexus, 63 Human complex unity of the, 59 sufficiently, 20 Human being actual, 60 agency of the, 40 complexity of the (whole), 30 evolving complexly over time, 60 generative development, 67 living, 222, 244 neglected states of the, 126 new vision of the, 46 new way of, 66 potentially nonlinear, 40, 46, 229 (the) proximal zone of, 67 role of the, 29 (inherently) social, 31 (radically) social, 32 states of, 40, 86, 126, 249 system of the (living), 222 through becoming, 40 totality of the, 51, 60 understanding of the (individual), 31 Human experience dialogical (dimensions of), 19, 20 reflexive (dimensions of), 19, 20 temporal (dimensions of), 19, 20 Human interaction the dynamic complexity of, 57 as a process, 57, 152, 168 the unforeseen of, 67 the unpredictable, 67 the very complexity of, 57, 60 Humanism the perverse of, 24 state of art of, 20 Humanity(ies), 1, 2, 5, 9, 12–14, 17, 20, 23, 24, 32, 37, 41, 43, 45, 46, 48–50, 54, 70, 71, 75, 78, 81, 83, 84, 88, 89, 98, 100, 103–105, 109–114, 116, 118, 125, 126, 132, 134, 140, 152, 160, 166, 177, 179, 180, 182, 189, 197, 199, 206–208, 217, 227, 230, 232, 237, 239, 241, 244, 248, 251–253, 256, 258 benefit of, 7 cultivating, 13, 34, 38 enriching for, 233

295 enrichment, 23 foundation of, 18 real, 13, 24 reclaiming, 23 Humanize the sciences, 13, 105 Humanizing determinism, 5 of our sciences, 200, 244 Humankind enchantment of, 11, 19 enrichment of, 23 Human nature dynamic conception of, 38 in search of, 38 Human sciences liberating the, 14 Humility cultivation of, 13, 24 Hypercomplex dynamic, 227 processes, 225 Hypercycle, 79, 201 Hyperloops complex, 229 Hyperspace(s) of (total) effect(s), 210 generative, 228 landscape(s) within, 210, 222–225, 249, 250 of the possible, 202 Hyper-structure(s) forms of, 219 of latent variables, 219 I Ideas of causality, 162, 263 of possibility, 263 Identities, 99 Ignorance learned, 199 the way of, 244 Illusion, 25, 138, 165, 258 Images, 105 Immaturity Kantian topic of, 23 self-imposed, 23 Implicated concept, 147 Imprisonment escaping, 132 Inability natural, 130

296 Incapacity to create novelty and innovation, 25 for creating novelties, 20, 33 learned, 93 Individual(s) character of the, 66 forms of behavior of the, 66 isolated, 13 (radically social) understanding of, 38 value of the, 66 (as) weaver in the web, 63 Individualism methodological, 31, 41, 79 Influence(s) generating, 61 reciprocal, 32, 56, 153, 183, 204 self-propagating, 263 Influencing causal, 162 each other, 56, 57, 152, 207 Initial kick, 142, 149 Innovation creation of, 60 (social) development of, 63 fundamental nature of, 46 generated, 262 of life, 263 path of, 190 possibility of, 29 question of, 262 radical, 14 world of, 256 Insecurity eliminate, 28 Inspiration source of, 110 Integrate knowledge and wisdom, 206 Integrative for a new view, 206 Interacting, 31, 107, 162 Interaction(s) between (human) agents, 55, 66 appearance of, 62 to be taken as real, 138 bi-directionality of (reciprocal), 182 causal, 7, 31, 101, 143–145, 147, 148, 153, 161–163, 167–170, 180, 182–186, 188, 190–192, 197, 198, 204, 205, 211–213, 217, 219, 220, 224, 229, 241, 249, 261 causal power of, 7, 164, 198, 219 circular, 56 coincidental, 211, 219

Index communicative human, 5, 32, 55, 60, 66, 183, 200, 201, 244 (the very) complexity of, 60 (new) concept of, 61, 135, 241 constructive kind of, 254 cooperative, 211, 214, 218, 220, 233, 234 development through, 40 dialogical, 56, 66 different kinds of, 214, 218–220, 225 dyadic, 4, 5 dynamic, 60, 138, 201 dynamical nature of, 138 dynamic(s) of, 62, 135, 138, 149, 162, 165, 197, 200, 202, 203, 206, 208, 216, 220, 229 effective, 55 emergent kind of, 4 with the environment, 208 evolving over time, 4, 169, 213 forms of, 218 general model of, 184 human, 4, 5, 32, 55–58, 60, 61, 63, 66, 67, 98, 138, 147–153, 158, 168, 169, 183, 190, 200, 201, 207–235, 244 indefinite, 21, 172, 177, 190 inherent complexity of, 184 learning through, 60, 149 linear concept of, 149 long-term, 190, 198 within a loop, 218, 219, 234 loop picture of, 185 matrix of, 244, 254, 255, 262 mutual, 62, 81, 162 (generative) nature of, 60, 81, 138, 205 new thinking of, 60 notion of, 21, 60, 148, 149, 152, 153, 240 processual nature of, 138 process-view of, 149 quality of, 55, 210, 213, 215, 219 within relational matrices, 254, 262 relational view of, 183 representation of, 185, 219 richness of, 215 (as a) scientific concept, 60 strong (form of), 219 theorizing on, 149 (adequate) theory of, 60 (new) theory of, 60 thrives on, 138 through time, 138 unrecognized complexity of, 201 weak (form of), 19 webbed, 4 works in practice, 56

Index Interactivity degree of, 81, 167, 203, 243 Interconnectedness full, 49, 56 fundamental, 109, 155 in nature, 136 realities of, 136 Interdependency(ies), 5, 6, 8, 100, 117, 119 reciprocal, 6, 8 tri-angular, 6, 8 Inter-disciplinary, 39, 156, 158, 161 Interfacing, 107 Interleaving, 37, 100 Interpenetrate, 4 Interplay of impelling forces, 32, 145 Interrelated fundamentally, 55 Intertwined, 49, 55, 100, 120, 187, 230 Intertwining of internal and external factors, 51 intimate, 66 Interweaving (process of) dynamic, 4, 34, 36, 57, 66, 113, 152, 176, 215, 216, 226, 231, 250, 255, 263 intimate, 66 in the relationships, 56 through the relationships, 56 Interwoven causally, 101, 189 complexly, 49, 74, 202 dynamically, 99, 101, 189 radically, 13 Intra-action coincidental, 218 cooperative, 214, 218, 220, 233, 234 within a loop, 218, 234 between (latent) variables, 220 Invent, 14, 24, 26, 45, 53, 54, 63, 68, 75, 78, 82, 85, 89, 91, 92, 96, 102, 121, 149, 227, 239, 252 Inventing a new science, 14, 55, 63, 78, 85, 94, 127 possibility of, 85 power of, 14 Invention contextual, 103 the whole process of, 119 Inventive of a new science, 77, 102, 245 Investigation new methods of, 24 Involution, 40, 95, 99, 129, 130

297 J Jardine, D., 24, 64, 65 Jargon, 13 Jaspers, K., 156 Jöreskog, K., 161 Juarrero, 158 K Kaneko, K., 210 Kant, 21, 23 Kantian fisherman, 128 Kauffman, S., 37, 65, 83, 100, 113, 188, 192, 202, 208, 225, 226, 230, 246, 247, 250–252, 254, 255, 257, 261 Key factor, 138 of new thinking in complexity, 43, 46, 142 Keynes, J.M., 76 Kick initial, 142, 149 Kiel, 131 Know learn to, 121, 132 Knowing different kind of, 110 how to go on, 62, 112, 201, 255 ignorance of, 14 new, 125, 135 new mode of, 118 new ways of, 5, 48, 59–60, 115–136, 139, 168, 240 old elements of, 124 old ways of, 124 as a process, 115, 117, 118 structures of, 117 Knowledge about real-world complexity, 146 acquisition of, 118 advancement of, 117 certainty of, 5 degree of, 120, 122 de-trivialize our, 157 founding of, 199 general theory of, 121 for granted, 258 humanitarian, 101 integrating, 101 of the living, 136 natural, 101 possibility of, 120 precondition of, 61 production of, 118, 125, 126, 128 provisional, 146

298 Knowledge (cont.) social, 101 sources of, 30 status of, 120, 121 uncertainty of, 86, 199, 243 Knowledgeable, 7, 22, 40, 103, 115, 124, 129 Knowledge management process, 126 Knowledge production fluid mode 2 of, 126 new mode of, 126 richness of, 126 Kuhnian boundaries, 68 Kuhnian sense, 44 Kuhn, T., 8, 14, 20, 22, 25, 26, 29, 33, 43, 46, 47, 55, 69, 71, 75–78, 82, 84, 86–88, 102, 105, 106, 159, 192, 228, 239 L Landscape(s) actual, 222 of causal effects, 192 complex, 41, 192, 222 of complexity, 34 complexity of a, 222 of composite effects, 222 dynamic, 54, 135, 210, 214, 222, 229, 249, 263 dynamic kind of, 222 of effects, 222 ever-evolving, 54 evolve over time, 222 fitness, 135, 161 more complex, 222 for our social sciences, 34 picture(s) of (the), 34, 222 of poorly known elements, 41 of possibilities and potentialities, 222 of possibilities of states of being, 222 possible, 34, 41, 229 potential, 210, 222, 249 of states of being, 214, 222, 249 of unknown dimensions, 54 vast, 41 Language (the) choice of, 47, 158 cleansing of the common, 128 for complexity, 200, 202, 228, 242, 252 of complexity, 202, 228 extended, 135 foreign, 127 the need for a different, 47 of networks, 194

Index a new, 7, 12, 14, 33, 34, 47, 70, 84, 114, 127, 135, 137, 158, 181, 200, 202, 206, 209, 227, 228, 231, 242, 252, 256–258 trans-disciplinary, 188 Language-effected reality, 7–8, 34, 47, 70, 127, 202, 206, 219, 252, 257 Law(s) about non-linear effects, 194 of geometric progression, 169, 175 of nature, 123, 128, 140, 255 of organic growth, 175 power, 194 of social relations, 171 Leaps sudden, 61 Learnability characteristics of, 230 different kinds of, 230 Learner(s) bootstrap each other, 150, 229 as human being(s), 230 realization of, 230 Learning complex, 51, 64, 66, 95, 113 (surprising) efficiency of, 32 field of, 1, 5, 12, 18, 46, 51, 93, 113, 149, 165, 208, 230 generative, 60, 64, 230 within the hitherto unknown, 54 net, 215 new concept of, 28 organization, 28, 46, 51 real, 230 required, 230 within the unknowable, 12, 28, 30, 35, 105, 110 Learning organization(s) healthy, 46 Learn to think, 33, 47–49, 55, 59, 65, 78, 95, 103, 107, 119, 129, 157, 238, 239, 248, 263 Leibniz, 183, 202 Lemke, 208 Lenneberg, E., 158, 168, 169 Lens new, 6 Level(s) of an internal reality, 224 of energy, 222 going down a, 223 higher, 5, 167, 216 (deeply) layered, 224 physiological, 150 practical, 105

Index psychological, 58, 150 social, 58, 150 theoretical, 105 Lexicon new, 46 old, 46, 47 Life complexities of, 59, 130, 132, 157, 167 dynamic complexities of, 130, 132 dynamics of, 210 evolvability of, 65 generativity of new, 64, 65 has a place, 129, 144 innovation of, 263 is impossible, 129, 144 nature of, 129 navigate, 65 new conception of, 144 novelty of, 60 origin of, 129 as a process, 183 as self-organized being, 144 study of, 129 tapestry of, 65, 136, 144 theory of, 183 Life course, 98 Limitations provincial, 13 Limits of my language, 232 of my world, 232 of our world, 203, 228, 231, 257 of the possible, 263 preconceived, 263 of the world, 203, 228, 232, 257 Lincoln, Y.S., 49, 161, 162, 187, 200, 249 Linear, 1, 4, 12, 13, 26, 32, 33, 35, 40, 45, 48, 54, 58, 68, 75, 80, 84, 87, 95, 96, 104, 116, 132, 135, 139, 149, 150, 155–158, 160, 161, 166, 171, 173, 174, 199, 200, 214, 222, 225, 231–233, 235, 240, 247, 254, 258, 260, 400 Link tri-partite, 36, 38, 119 Liquefying, 34, 39, 109, 159 Literatures on the topic of complexity, 141 Living realization of the, 244, 256, 263 Living beings realizing themselves, 228, 254 Living reality, 130, 132, 133 Living systems realization of, 228, 256, 263

299 Lock-in situations in doing science, 126 in viewing science, 126 Logic different, 155 of explanation, 155 Long, 163, 165, 168 Longitudinal database, 170 Loop(s) autocatalytic, 146, 164 causal, 4, 61, 63, 80, 135, 142–144, 146, 148, 182, 187, 188, 197, 200, 201, 204, 226, 229, 241, 253–255, 262 cycling, 204 (fluid) entities of the, 187 force within, 260 generative, 63, 175, 182, 183, 187, 188, 201, 202, 204, 248, 250, 255, 261, 262 (dynamically) interconnected, 4, 97, 182, 194, 200, 224, 226, 232, 247, 250, 254, 255 knotted, 188, 192, 193 network system of, 188 of reciprocal relationships, 143, 157, 204, 232 of self-and-other, 63 self-enhanced, 193 Loop effect(s) self-enhanced, 142, 143, 158, 164, 175, 180, 187, 189, 197, 204, 261, 263 Loop picture dynamic, 182 potentiality of the, 182 of reality, 182, 202 in terms of relations, 182 Lord. B., 200 Luhmann, K., 1, 5 Luhmann, N., 73, 93, 118, 121, 122, 127, 199, 230 Lyell, 133 M Mainzer, K., 106, 113, 115, 117, 155, 222 Maitland, S., 223–224, 228, 244 Man actual, 36 real, 36 Map complex, 65 fluid, 65 Maruyama, M., 142, 143, 149 Mastered, 32, 36 Mathew effect, 7, 148, 250

300 Matrices causal, 217 Matrix generative, 97 of interaction, 244, 254, 255, 262 Matthew, 148 Maturana, H.R., 188, 244, 245, 247, 248, 260 Mayr, E., 246, 261 Meaning imprisonment of, 13, 132 Measure fluid kind of, 206 Mechanisms ‘at work,’ 7, 60 causal, 63, 147, 173 generative, 7, 32, 64, 67, 90, 97, 99, 104, 136, 139, 144, 147, 148, 165, 166, 168, 175, 181, 205, 215, 226, 261 of inertia, 30 of nature, 90 Meeting ground between code and flux, 206 Mentality scientific, 13 separate, 13 Merging complex, 95 Metamorphosis, 39, 51, 63, 130, 134, 215, 216, 245, 255 Metaphor to be invented, 12 generative, 7 guiding, 3, 21 machine, 5 scandal of, 111 Meta-theory, 87, 88, 93 Metcalf, 179 Method application of scientific, 116 complementary, 9 of doing science, 95 research, 37, 123 of thought, 118, 138, 143 of viewing science, 64, 247 Methodological crisis, 14, 29, 35, 77, 87, 91, 121, 251 Methodological individualism, 31, 79 Methodological principles, 29 Methodology adequate, 120 alternative, 38 cognitive, 130 of the crisis, 85 different, 129, 130, 140

Index of doing science, 133, 139 explanatory, 36 holistic, 263 interdisciplinary, 156 new, 34, 35, 37, 85, 138, 140, 145–146, 246 (the) principles of, 29, 39 of reality, 88, 89, 122 of reasoning, 29 of viewing science, 133, 139 welcome role of, 119 Midgley, M., 20 Miller, G.A., 158 Mind(s) scientific, 157 Mindset prison, 43 Mission impossible, 12 of inventing a new science, 127 Misunderstanding deep, 217 Mixing fluid, 56 Möbius Band (graphic by M. C. Escher), 108, 120 Mode(s) of description, 132 of knowledge production, 118, 125, 126, 128 multi-dimensional, 132 one-dimensional, 132 self-critical, 55 of thought, 55 Model(s) constructing, 9, 39 mathematical, 145 mechanistic, 3 Newtonian, 126 non-recursive, 170 real complexity of the, 214 structural equation, 143, 156, 161, 174, 240, 260 tri-angular, 5 Modeling adequate, 57 becoming explanatory (in our), 57 of the causal dynamics, 165 of the causal processes, 7 (more) complex, 218 complexifying our, 190 of the complexities involved, 218 complex organisms, 207 cumulative effects, 57 of the dynamic complexity, 57

Index inventing (adequate), 57 main roads of, 9 possibility of, 57, 229 Modeling philosophy new, 194 Mono-causality the idea of, 155 Morin, E., 4, 18, 25, 38, 66, 76, 115–117, 120, 121, 124, 129, 131, 132, 136, 138, 165, 201, 203, 204, 237, 258 Morphogenesis notion of, 143 process of, 98 Morphostasis, 79, 143 Motor activity of the brain, 234 Movement spiraling, 98 Multidimensionality, 132, 152 Multiplication rule, 171 N Namboodiri, N.K., 157, 177 Naturalistic, 161, 214, 249 Natural sciences development of the, 22 scientific revolutions in the, 22 wrong copy, 22, 30 Natural selection limitations of, 133 powers of, 133 understanding of, 133 Nature at all levels of, 43 of categories and perspectives, 142 of causal interaction, 145 of complexity, 3, 21, 50, 112, 183, 199, 219, 231 computable, 106 creative, 111 creativity of, 46, 157, 224, 227 dualist, 111 emergent, 98 evolutionary creativity of, 157 fabric of, 216, 249, 254–256 of the fabric of nature, 216, 254–256 free, 111 generative, 3, 21, 60, 66, 112, 176, 206, 231, 258 interconnectedness in, 136 intrinsic creativity of, 157, 227 is a structure of evolving processes, 49, 246 laws of, 89, 123, 140, 255

301 limited, 142 look afresh at, 43 loving, 111 mere reflections of, 43 of reality, 48, 66, 67, 89–91, 93, 96–98, 110, 123, 241, 252 self-generative, 21, 176 spiraling, 67, 98, 107 subdue, 125 of things, 46, 48, 59, 70, 88, 89, 109 transitory, 86, 94, 112, 124, 144, 247 Nauman, B., 54, 108, 125 Navigating (in) the sea of uncertainty, 65, 125, 139, 145 Network(s) of actors, 57 of ants, 187 augmented transition, 176, 194 causal, 80, 144, 153, 154, 161, 167, 168, 187–188, 190–193, 203–205, 215, 226, 248, 252–254, 261–263 causality, 158 of causal relations, 80, 143 connectivity of, 262 of cycles, 201 dynamic, 61, 62, 65, 126, 150, 152, 153, 179, 191, 193, 194, 202, 247, 249, 250 dynamic loop, 4, 255 evolving, 194 fluid, 187, 226 interactivity of, 62, 63 interconnected, 187 interweaving of a, 57 layered (loop), 224, 226, 248, 254 loop, 4, 194, 200, 201, 205, 219, 224, 226, 229, 232, 247, 250, 255 of loop networks, 188, 229, 232, 247, 250 of (knotted) loops, 60, 61, 63, 255 loops of the, 61, 63 multi-layered, 215 neuron, 187, 212 in the real(m), 164 of the real, 226 of relating (entities), 164 relational matrices of the, 254, 262 self-generating, 67, 86, 143, 147, 150, 153, 154, 167 self-generative, 67, 86, 99, 158, 191, 226, 255 transition in, 67 webbed, 4, 83, 97, 101, 113, 193, 194, 215, 226, 231, 232, 248, 253, 254, 257 web-like, 192, 193

302 New science of complexity, 1–3, 5–9, 34, 41, 47, 48, 83, 84, 113, 115, 121, 130, 137, 138, 145, 153, 177, 181, 187, 194, 198, 201, 206, 211, 225–228, 241, 243–245, 247, 248, 256, 257, 259–260 Newton, I., 160, 217 Newtonian model, 126 Nexus causal, 67 Niche construction, 61 Nietzsche, 216 Nonlinear linking the linear with the, 40 Non-teleological, 214 Normal science boundaries of, 68 in a Kuhnian sense, 44 Normative idea, 125 tension, 122 Notion about the future of science, 128 of causal dynamics, 57, 161 of control, 36, 113, 125 of critical reflection, 128 deceptive, 128 of effective complexity, 55, 139, 165, 226, 257 modeling, 57 more fluid kind of, 126 of morphogenesis, 143 of morphostasis, 143 relational, 97 web-like, 263 Notion of complexity insufficiently complex, 199 Novelty(ies) complex, 66, 67 creation of, 28, 31, 60, 83, 102, 153 description of, 24, 67 development of, 63 effective, 45 explanation of, 24, 67 explanatory about, 262, 263 of fact, 20, 23, 30, 31, 33, 49, 71, 78, 102, 122, 159 fundamental nature of, 46 generate(d), 30, 50, 93, 261, 262 inability to ‘produce,’ 30 of life, 263 possibility of, 256 in practice, 262 question of, 262

Index scientific, 45 of theory, 20, 23, 30, 33, 71, 122, 159 topic of (potential of) true, 32 (utilize) unexpected, 45 world of, 256 Novelty and innovation as fundamental complex phenomena, 67 question of, 262 NWO (Dutch Organization of Science), 6 O Ontological effectively, 120 Ontological complicity problem of the, 133 Ontological creativity of the entire world, 133, 134, 138, 143 of reality, 134, 136, 138, 143, 144, 157, 158 Ontologically, 61, 82, 90, 91, 102, 103, 120, 123, 125, 126, 129, 130, 133, 134, 136, 138, 140, 143–145, 157, 158, 198, 214, 224, 225, 250, 253 Ontological principle, 123, 138, 144 Ontological structures, 144–145 Ontology adequate, 156 a different kind of, 109 problem of, 29, 90, 91, 120, 130, 133 social, 156 a things, 109 true, 120 Opening humanities, 70, 98, 256 a new science, 27, 65, 227, 256 a new world, 215, 257 real, 231, 254, 256 realistic, 6 the social, 1, 6, 44, 45, 48, 59, 70, 98, 105, 237, 239, 256 (the) social sciences, 6, 104, 105, 111, 256 (the) space of the possible, 2, 5, 6, 145, 215, 228, 230, 242, 244, 249, 252, 254, 255 spaces of possibility, 28, 54, 66, 73, 84, 105, 111, 114, 122, 124, 210, 230, 244, 255 third window, 244, 254, 256 unexpected, 9 Openness, 223

Index Operations complex, 255 inner, 51 Opportunities period of, 27 potential, 27 welcome, 28 Opposites unity of, 81, 96 Opposition(s) binary, 232 of mind and brain, 232 of nature-nurture, 232 of system and environment, 232 traditional, 232 Order generation of, 72, 224, 225 generative, 146, 204, 205, 224–226, 231, 240, 256, 258, 263 generic, 226 out of chaos, 69, 73, 135 self-generation of, 72, 224 spontaneous, 135 Organic growth, 171, 175 Organism(s) complex, 207 human, 207 learning characteristics of, 217 real, 217 whole, 50 Organization hyper-cyclic, 4 Orthodoxy of the time, 127 of the traditional scientific method, 115 Oversimplification escape the, 126 of the real world, 126, 128 Oyama, S., 3, 25, 156, 205, 242, 246, 250 P Paradigm(s) blinding, 20, 25, 30, 39, 72, 75, 76, 138, 142, 180, 190, 248, 258, 268 naturalistic, 214, 249 new causal, 262, 263 problem of, 55 shift of, 8, 44, 46, 47, 49, 55, 88, 137, 189, 192, 199, 202, 227, 231, 237, 245, 247, 258, 260, 261 of thinking, 22, 76, 208 in use, 48, 82, 87

303 Paradigm shift constitutive of a, 260 preconditions for a, 25 Paradox of unity, 118, 120 Para Limes, 2, 6, 39, 78, 263 Paralyzing belief, 36 Parochialism, 43 Past event-sequential, 98 Path analysis, 161, 171 of bifurcations, 116 of development, 238 of discovery, 262 of (real) innovation, 190 linear, 139 methodological, 37 more general, 37 of new thinking in complexity, 257 for new ways of knowing, 118 philosophical, 132 of reflection, 124, 132 research, 36 scientific, 136 (of) spiral development, 61 of strengthening, 213 tortuous, 49, 54, 55, 67, 83, 86, 136, 145, 158, 191, 238 unknown, 54, 104, 256 Pathologies disciplinary, 14, 25, 26 Pattern(s) within complex networks, 63, 200 of development, 9 emphasis on, 255 evolving over time, 152, 167, 263 explanation, 194 of life, 263 of loops, 149 model, 190, 200, 243, 263 of processes, 255 of relating, 56, 62, 149 of relationships, 167 woven, 61, 63, 152, 263 Patterning of threads, 194 Pattern model of explanation, 190, 200, 243, 263 Paul Weiss, 158 Peat, D.M., 224, 240 People unlock, 43, 64 Pereira, 167

304 Perennial of causal analysis, 159 of causality, 159 complex, 120, 131 hardy, 31, 82, 83, 106, 120, 131, 160 Period of opportunities, 27 pre-revolutionary, 22 Periodicity, 95 Perpetuation of culture, 66 Personal experience effects of, 223 Perspective complexity, 4, 38, 64, 93, 110, 238 of complex responsive processes, 62 emerging, 107 epistemological, 107 historical, 49, 92–94, 159 holistic, 50 scientific, 231, 238 systemic, 50 trans-disciplinary, 101, 189, 242 unifying, 138 Wittgensteinian, 201 Perverse of thinking, 23, 24 of writing, 23, 24 Perversion, 19 Phenomena fields of simple, 116 Phenomenon of emergence, 36, 84 Snowball, 4, 113, 226, 249 Philosophy of the complexity of reality, 72, 111, 117 Pictures of dynmic landscapes, 222 Play of causes and effects, 60 Point of view, 30, 76, 92, 106, 170, 171 Position of (‘real’) causality, 231 Possibility(ies) of bootstrapping effects, 231 of bootstrapping processes, 147, 229, 231 for complex systems, 222, 225 for creativity, 231 of dynamic quality, 68 emergent, 113 explosive, 19, 32, 34, 101, 230, 249 hitherto unknown, 2, 41, 45, 99, 104, 105, 111, 118, 199, 202, 226, 230, 232, 233, 237, 243, 244, 255 of a new kind of epistemology, 5–6, 34 opening, 5, 6, 54, 66, 84, 105, 113, 114, 119, 168, 210, 215, 224, 225, 228, 230–232, 242, 244, 246, 252, 254, 255, 257

Index ranges of, 134 realms of, 2, 115, 260 (social) space of, 54 state spaces of, 226 suppression of the, 231 of transformation, 113, 194, 215, 246 vistas of, 114, 229, 231, 232, 244, 256 Possible epistemology of the, 5, 6, 118, 129, 199, 226, 243, 257 a new world of the (new) spaces of the, 6, 28, 38, 45, 54, 73, 84, 98, 105, 111, 114, 118, 122, 145, 201, 204, 229, 230, 242, 244, 246, 252, 254, 255 world of the, 2, 5, 6, 104, 113, 114, 118, 122, 134, 189, 195, 202–204, 215, 217, 237, 242–244, 250, 252, 254, 256, 257 Potency causal, 64 of a generative concept, 139 Potential creative, 35, 231 for emergent order, 261 exerted by force, 261 generative, 32, 147, 148, 188, 201, 205, 206, 248, 261 unexplored, 261 unlimited, 231 working, 129 Potentialities (new) domain(s) of, 33, 54, 73 emergent, 68 (the) key for, 66 space of, 201, 210, 220 unknown, 98, 101, 241 Power(s) of becoming trans-disciplinary, 64 of bootstrapping, 209, 232 causal, 7, 9, 32, 64, 99, 129, 162, 164, 165, 177, 197, 204, 215, 219, 225, 226, 256, 261 creative, 165 emergent, 134 to evolve with time, 262–263 explanatory, 9, 64, 134, 165, 228 to generate, 144 (causally) generative, 9, 205 of mechanisms, 129 nth, 57, 58 self-generative, 255 of self-potentiating, 21, 232, 244, 257 unexpected (explanatory), 228

Index Practical of organized complexity, 183 Practice(s) complexity of, 49–51, 57, 94, 124, 132, 138–140, 165, 183, 257, 259 ongoing, 98 our theories, 117 teaching, 107 unity of theory and, 107 work in, 49, 50, 57, 60, 104 Precondition for the development of a new science, 47 for the emergence of novel theories, 43 necessary, 43 Predecessors dreams of our, 122 Predictability degree of, 120 Predictable, 13, 36, 79, 80, 99 Prediction emphasis on, 50, 227, 247 Preference for simplicity, 130 systematicity, 130 uniformity, 130 Prejudices functioning, 206 hindrance of, 206 Presence coming into, 51, 230 Prigogine, I., 45, 69, 70, 72–74, 76 Principle building, 153 of causality, 61, 263 constitutive (ontological), 123 of description, 61 fundamental, 263 (causal) generative, 97, 168 hitherto unknown, 104, 130 integrative, 136 a kind of, 29, 39, 63–64, 97, 129, 138, 144, 177 ontological, 123, 138, 144 of own habits of thinking, 48, 49 of science, 85, 91, 93 transdisciplinary, 136 Prisoner, 2, 48, 61, 69, 76, 103, 105, 125, 145, 157, 180, 251, 258 Problem(s) (of) action and reaction, 106 (of) causality, 3, 83, 106, 159, 160, 248 (of) communication, 46, 47 for complexity, 44, 46, 72, 120, 132, 153, 154, 159, 165, 166, 248, 259

305 (of) complexity, 7, 44, 46, 72, 120, 132, 153, 154, 159, 165, 166, 248, 259 (of) crisis, 27 (of) economy, 31, 106 epistemological, 25, 59, 91, 115–136 (of) epistemology, 117 foundational, 92 of getting knowledgeable, 115 of giving birth to a new science, 117 intertwined, 120 of inventing a new science, 55 of life, 59, 60, 194 methodological, 85, 91, 121 of mind, 241 of nature, 106 ontological, 90, 91, 120, 130 of ontology, 29, 120 of our knowledge, 115 philosophical, 138, 165, 237, 258 of the process of knowing, 115 shift in, 26 of shift(ing) of paradigm(s), 46, 55 of society, 35 of theory and practice, 21, 87, 107, 117, 257 of thinking in complexity, 116 too difficult to answer, 29 (apparently) unsolvable, 12 Problem solving modes of, 125 Process(es) all the way down, 255 all the way up, 255 alternative, 130 autocatalytic, 113, 163, 176, 263 of becoming, 27, 51, 67, 130, 134, 205 of being, 54, 55, 130, 145 causal, 7, 31, 32, 63, 142, 144, 148, 155, 157, 158, 160, 167, 170, 172, 175–177, 186, 191, 192, 241, 249, 260, 261 complex, 4, 19, 45, 51, 56, 57, 62, 66, 67, 94, 95, 99, 112, 130, 134, 138, 143, 145, 146, 152, 157, 184, 189, 206, 216, 225, 229, 230, 244, 255, 256 cultural, 212 cyclic (causal), 172 deviation-amplifying, 142 dialectical, 95 of dynamic interweaving, 4, 56, 57, 66, 113, 152, 226, 255, 263 dynamics of causal, 144, 157 of emergent processes, 230 of evolution, 95, 99, 163, 242 evolutionary, 133, 167, 212

306 Process(es) (cont.) of generating influences, 61 (causally) generative, 32, 63, 64, 134, 148, 158, 175, 259 of human relating, 57 hypercomplex, 229 of inter-action, 214, 249 interactive view of, 168 inter-generative, 211, 214 interpretation of, 125 intertwined, 100 of interweaving, 56, 151, 153, 169, 255, 263 interwoven, 99 of intra-action, 229 intra-generative, 205 of invention, 53, 54, 56, 96, 118, 119, 149 of involution, 129, 130 of learning and development, 31, 51 long-term, 212 medium-term, 212 of metamorphosis, 216 mutual causal, 142, 148, 149 of mutual causal, 142, 148, 149 nature of, 50, 59, 94, 98, 157, 163, 176, 206, 247 non-gradual, 144 patterns of, 255 in the real(m), 39, 54, 134, 255 recurrent, 168 (complex) responsive, 56, 62 of revolution, 130 self-creating, 163, 164, 167 self-creative, 176 self-enhancing, 63 self-generating, 145, 147, 152–153, 163, 167 self-generative, 158, 205, 206, 229, 255 self-producing, 126, 147 of self-propagating influence, 263 self-sufficing, 168 spiral, 129 transactional, 9 of transformation, 129, 130 transient, 134 of transition, 129, 130 transitory, 9, 94, 247 understanding of, 125 unpredictable, 62 Producing causal effects, 162–163 generative way of, 162

Index Progress hindrance for, 49 as a kind of normative idea, 125 of science, 49, 119, 125 Progression geometrical, 163 mathematical process of, 163 Promise of a better future, 32 of complexity, 41 Properties basic, 172 symmetric, 172 Prophet of thinking in complexity, 57 Provincialism kind of, 43 Proximal zone of human being, 67 Proximate causation, 261 Psychologist Russian, 4, 13 Psychology (the) crisis in, 14, 25, 29, 45, 76, 77, 85, 91, 93, 98, 121, 251, 252 (the) crisis of, 21, 26, 77, 88, 91, 94, 133 development of, 30–31 discipline of, 251, 456 humanized, 30–31 Q Quality(ies) based on diversity, 67 of complexity, 204–206, 243, 244, 247 degree of, 206 dynamic, 67, 110, 204 of (the) dynamics, 68, 205 generating, 67 of interaction, 55, 210, 213, 215, 218–220, 226 is a quality, 205 kinds of, 204 of networks, 204 of reciprocal relationship(s), 210, 226, 232 of relating, 55 Quality mark dynamic, 67 Quantum gravity, 202 Quantum physics, 86, 96 Quest for certainty, 65 escape the, 65

Index for explanation(s), 260 perennial, 260, 261 Question(s) about evolution, 210, 262 big, 2, 6, 33, 129, 254 crucial, 122 epistemological, 106, 117 ignored, 210 of innovation, 262 key, 39, 47, 87, 100, 101, 103 nagging, 29 of novelty, 262 for science, 90, 122, 129 unanswerable, 66 unanswered, 30 unsolved, 29 unthinkable, 66 Vygotskian, 100 R Random, 107, 113, 115, 117, 120, 167 Rationalist-objective view, 149 Readiness to open up new spaces, 54 Real(m) of cause and effect, 141 complex, 118, 133 complexity of the, 72, 93, 95, 139, 140 complexly, 120 domain of, 85 generated in the, 256, 261 generative power in the, 177 inherently complex, 89, 118, 133 of life, 141 of mechanism and physical law, 141 of possibility, 207, 225, 226, 228, 231, 243, 249, 255, 256, 260 really, 59, 93, 242, 243, 245, 254–256 realm of the, 256 of space and time, 141 (causal) thinking about the, 224 unifies the, 141 (the) whole of the, 65 Realist anti, 93 critical, 59, 65, 93, 95, 99, 117, 129, 130 turn, 103 Realistic critical, 74, 87, 93, 165 escape, 145 Realist theory of the social sciences, 155 Realist turn, 103

307 Reality absolute, 145, 253 accepted, 99 (our) account of, 225, 226, 241 (a more) active, 65 assumed version of, 35 augmented, 168, 195 causal dynamics of, 112, 159 as a (kind of) choice, 35, 44, 49, 96 classical view of, 95 (more) close to, 62 complex, 8, 14, 32, 36, 39, 40, 45, 47, 54, 58, 59, 74, 88, 95, 96, 98, 100, 103, 104, 107, 109–111, 115, 117, 124, 126, 136, 138, 139, 144, 150, 155–158, 160, 165–168, 174, 179–182, 188, 189, 191, 198, 200, 202, 203, 205, 206, 215, 219, 223, 225–227, 232, 240–243, 247–249, 254–257, 260 complexification of, 203 complexifying, 11, 34, 199, 200 complexifying (of), 19, 23 complexity of, 11, 12, 18, 19, 30, 34, 36–38, 40, 45, 46, 48, 49, 58, 59, 62, 72, 74, 87, 89, 93, 95, 100–103, 105, 107, 109–111, 113, 115–136, 138, 141, 148, 155–157, 159, 180, 181, 198–204, 239, 241, 242, 248, 251, 258, 260 the (very) complexity of, 18, 34, 37, 72, 118, 127, 130, 198, 203 complexly different, 102 complex view of, 97 confusing, 200 constructed, 21, 49, 73, 77, 96, 99 creating, 50 creating a (new), 35 decoding, 50, 84, 135 deeper level of, 67 deeply layered kind of, 226 delivered, 11, 19, 39, 82, 89, 128 deliverer(s) of, 25, 62, 70 delivering, 34, 39, 74, 132, 159, 206, 242, 248 descriptive of, 66 difference of, 124 different kind of, 19, 32, 168, 203, 232 different view about, 58, 92 a distorted notion of, 111 dynamic, 54, 67, 130 dynamic complexity in, 168 elaborated (version of), 14 emergent, 101, 106, 112, 113 enlarged, 73 enriching, 202

308 Reality (cont.) essence of, 85 evolving, 34 expanding (of), 38, 39, 44, 74, 226 expanding (our view of), 39 explanative of, 61 fluid (kind of), 97, 107, 160, 165, 248 fluid conception of, 97 generative nature of, 166 generative order of, 240, 256 given, 17, 19, 58, 72, 95, 96, 99, 102 greater, 19, 21, 32, 33 hidden complexity of, 19 (not) homogenuous, 21 human, 65, 66, 79 inexhaustibly complex, 136 intellectual, 123 of interconnectedness, 136 invent(ed), 17, 21, 73, 76, 96 language-effected, 34, 70, 127, 202, 206, 219, 252 lived, 5, 35 map of, 49, 65, 95 mental, 232 multi-dimensional, 123 nature of, 48, 66, 67, 89–91, 93, 96–98, 123, 241, 252 nonlinear complex, 8, 14, 32, 39, 40, 45, 58, 88, 100, 104, 107, 111, 124, 126, 139, 150, 155–158, 160, 165–168, 174, 179–182, 189, 191, 198, 200, 202, 203, 205, 206, 215, 219, 223, 225–227, 232, 240–243, 247–249, 254–257 ‘old,’ 128, 130 ontological creativity of, 136, 143, 157, 158 ontologically different, 102 (as) outcome, 19 part and parcel of, 66 participatory nature of, 66 perverse version of, 18 of phenomena, 32 philosophy of, 117 (misleading) picture of, 58 physical, 232 plural, 19 problem about, 90 profound, 60 as real, 11, 87, 122 realist notion of, 97 reality of, 83, 85–114, 130 really different, 112

Index (as) ‘really’ real, 59 as ‘really real,’ 59 realm of, 90, 249, 254, 255 realm of (natural), 225, 249, 254, 255 ‘real’ part of, 19 real-world complexity of, 46 real-world dynamics of, 122 rebellion against, 13, 34, 74 reclaiming, 38, 59, 65, 72, 96, 111, 241 re-defining of, 59 reduced version of, 96 reductive of, 110 re-enchantment of, 3, 11, 19, 23 related aspects of, 40 relationship of complexity with, 58 remained unknown, 121 rethink, 58 (much) richer (sort of), 233, 246, 247 as a richer reality, 140 richer version of, 35 richer view of a, 124 for the sake of, 11 of science, 123 simple view of, 96 single, 19, 96 social, 32, 35, 36, 199, 232, 246 spiralling nature of, 67 static (version of), 39 static version of, 109 of the system, 90 taken for granted, 83, 130 too complex to be mastered, 32, 36 trans-disciplinary, 90–91 transformation of, 96, 98, 121 transitory nature of, 124 true, 17, 21, 121, 122 (new) type of, 90 ultimate, 62 underlying, 79, 122, 166 understanding, 45, 240 (hitherto) unknown, 74, 98, 106, 121, 130, 232 as usual, 13 the very complexity of, 18, 34, 36, 37, 72, 103, 118, 127, 130, 198, 203, 260 (different) view of, 3, 256 (the) whole of (the), 44, 65, 141 (new) window upon, 3, 254, 256 wrong version of, 35 Realization of the living, 244, 256, 263 of living systems, 228, 256

Index Realize, 5, 13, 33, 39, 54, 74, 88, 89, 115, 133, 136, 139, 145, 157, 163, 181, 190, 192, 195, 208 Realizing (a) potential, 125 stepwise kind of, 125 themselves, 5, 228, 254 Realm(s) different, 3, 8, 39, 112, 141 expanding, 225 hitherto unknown, 2, 226 networks in the, 143 scientific, 1–3, 7–9, 39, 71, 78, 90, 93, 112, 115, 141, 152, 175, 177, 181, 182, 189, 199, 201, 245, 260, 262 traditional, 2 Real-world complexity, 1–3, 5–9, 19, 21, 23, 34, 37, 40, 44, 46, 50, 74, 116, 122, 126–129, 131, 134, 135, 142, 143, 145, 146, 160, 165–168, 176, 179, 180, 189, 191, 194, 195, 200, 202, 203, 210, 214, 216, 217, 219, 224, 225, 230, 231, 242, 243, 247–250, 252, 256, 257 complex nature of, 126 complication of the, 126, 127 dynamics, 6, 40, 44, 45, 51, 54, 59, 61, 62, 65–67, 72, 73, 89, 93, 104, 116, 117, 121–124, 126–129, 134, 135, 145, 148, 156, 164–166, 168, 179, 181, 189, 192, 203, 224, 225, 231, 250 flying in the, 128 oversimplification of the, 126 Real-world complexity complexity of, 1–3, 5–9, 19, 21, 34, 37, 40, 46, 50, 61, 65, 74, 116, 121, 127, 129, 131, 134, 142, 145, 165–167, 176, 180, 189, 191, 194, 200, 202, 203, 210, 216, 219, 225, 230, 231, 243, 247–249, 252, 256, 257 facing the, 143 knowledge about, 146, 203 producing the, 168 understanding of the, 128, 129 world of, 2, 230, 252 Real-world dynamics complexity of, 61, 62, 65, 73, 93, 104, 121, 123, 126–129, 135, 145, 168, 181, 224, 225, 231 concepts of, 135 knowing about, 128 ontological creativity of, 134 thinking about, 72

309 Reasoning different kind of, 127 everyday, 127 inversion of, 127 Rebel against the system, 26 Rebellion feeling of, 34 a kind of, 13, 18, 45, 116 against the old way of thinking, 45 Reciprocal causation, 155, 175, 177, 255 relationships, 31, 55, 117, 135, 143–145, 147, 157, 161, 163, 169–177, 182–185, 187, 188, 204, 210, 213, 215, 224, 226, 229, 231, 232, 241, 256 Reciprocity the idea of, 169, 170 Recursion, 204 Reducing, 13, 102, 142 Reductionism black hole of, 21, 24, 30, 260 kind of, 18, 30 theoretical, 74, 94 voracious kind of, 30 Reductionistic stance, 79, 94, 217, 231 Reflection at all fronts, 128 path of, 124 repression of, 130 Reflective on becoming, 55–58, 69–84 Reflex arcs, 58 Reform of our habitual ways of thought, 129 of thinking, 59, 98 of thought, 47, 48, 66, 98, 104, 128, 140, 149 Reframe our understanding of the world, 140 Regions different, 212 flat, 212 Regularities kind of, 18, 260 ‘producing,’ 260 (in) the real, 260 Reid, R., 199, 260, 262 Relating the activity of, 176 parameters of the, 176 quality of, 55 reciprocal (kind of), 4, 183 reciprocal kind of, 4, 183 response to a, 164, 183

310 Relational fundamental, 183 interaction, 97, 138, 144, 150, 167, 202 matrix, 201, 202 organized, 113 view, 183 view of interaction, 183 Relation(ship)s bi-directional, 185 causal-dynamic, 24, 36 complexly interwoven, 202 dynamic, 73, 117–119, 211 dynamic causal, 62 dynamic loops of, 175 fluid kind of, 140 growth-producing, 175 between inter-action and intra-action, 211 interactive, 4, 7, 167, 211, 213, 219, 220 is the essence of synthesis, 204 matrix of, 202 mutual, 61, 162 of ontological complicity, 61, 140 with the real(m), 87, 119, 121 reciprocal (causal), 7, 31, 55, 62, 63, 70, 80, 117, 135, 142–145, 147–150, 153, 156, 157, 161, 163, 167, 169–177, 182–185, 187, 188, 192, 204, 210, 213, 215, 224, 226, 229, 231, 232, 241, 255, 256, 261 self-and-other, 63 structures of, 97 tripartite, 38, 119, 121, 126, 139, 147, 148, 153, 160 two-way causal, 62 of whole-part (mutual) implication, 153 Relevance for any science, 65 core, 65 general, 65 Renewal continual, 13 Replace ‘normal’ science, 8 our common preferences, 129 Representation, 80, 94, 97, 105, 169, 170, 184, 185, 192, 213, 214, 219, 220, 222, 246 Repression of reflection, 130 tendencies of, 19 of (reflective) thinking, 29 Rescher, N., 2, 19, 72, 73, 87, 88, 90, 95, 96, 99, 101, 102, 112, 176, 179, 182, 198, 214, 216, 217, 224, 225, 228, 237, 242–244, 249, 251, 252, 255–257

Index Research (new) real-world, 6 scientific, 103, 106 Research engagement, 14 Research field unmined, 12 Resistance potential, 125 Resisting, 102 Resources existing, 209 Response(s) circular, 56 complex, 4, 57 (is always) to a relating, 56, 150, 151, 164, 183, 184 Responsiveness potentiating, 183 Rethink modus operandi, 116, 128, 140 need to, 39, 128, 179, 259 structure, 116, 128, 134, 140 Rethinking causality, 139, 155–177, 260 interaction, 139, 147–154, 165, 179, 240, 259 of our role as scientists, 134 our ways of knowing, 39, 59 by reinvention, 134 start to, 21, 39, 110, 165, 259 steps of, 139, 179, 198, 239–241, 258 of the structure of science, 116, 134 Retooling our ways of knowing, 6, 88, 189 the social sciences and humanities, 88 Reversals, 63 Revolt, 27 Revolution potential of a, 27 scientific, 14, 18, 22, 26, 28, 33, 47, 69, 75, 86, 105, 141, 159, 239 structure of scientific, 26, 33, 47, 141 Richness complex, 110 Robson, 6 Role of causality, 142, 156, 159, 198, 204, 260, 262 complex, 142 of emergent effects, 230 of emergent processes, 230 Rose, S., 151, 222 Rosser, 117, 120, 122, 129 Rupture(s) required, 64

Index S Sabelli, 208 Salmon, W., 167 Sandywell, B., 20, 24, 103 Santa Fé, 6 Sassone, L., 205 Satisficers as a kind of, 30 Satisficing role of, 30 Scala, P., 195 Scandal of reductionism, 44 Scheffer, M., 2, 41 Schorr, 230 Schrödinger, E., 92 Science(s) about the real (m), 75, 85, 99, 102, 121 (more) adequate, 37, 100, 120, 122 as-usual, 3, 12, 25, 39, 41, 69, 72, 82, 84, 86, 87, 103–105, 122, 132, 145, 159, 173, 203, 206, 227, 228, 232, 238, 248, 256–258 as-we-know-it, 19, 22, 70–72, 74–76, 81, 82, 85, 87, 90, 124, 126, 127, 133, 140 bad, 3, 25, 78, 122, 206 basics of, 105 of being, 86, 88, 94, 123, 140 better kind of, 206 big question for, 129 birth of a new, 41 blind alleys of, 33, 75–77, 133 blind spots of our, 125 broader implications for, 117 builders of, 8, 94, 105, 121, 144, 176, 187, 251 building a (new), 11, 12, 14, 21, 22, 40, 47, 87, 103–105, 109–111, 137–139, 147, 159, 179, 241, 247, 256, 257 complementary, 1, 8 of complexity (ScoC), 1–3, 5–9, 34, 41, 47, 48, 65, 70, 72, 83, 84, 113, 115, 120, 121, 130–132, 137, 138, 145, 146, 153, 177, 181, 187, 194, 198, 201, 206, 211, 225–228, 230, 241, 243–245, 247, 248, 250, 256, 257, 259–264 (our) conception of, 206 constitutive of, 49, 102, 134 core of, 3 damage to our, 232 danger of, 12, 25, 34 (separate) disciplines of our, 37 (method of) doing, 35, 36, 64, 95, 242, 247 domain of potentialities of the new, 54 effectiveness of, 206

311 expanding of (our), 227 features of, 28, 33 (specific) fields of, 5, 13, 64, 75, 127, 132, 141, 142, 161, 180, 198, 217, 238 foundational kind of, 8 foundation of a new, 1, 53, 92, 177, 227, 256 fragmentation of, 106 future of, 13, 17, 70, 83, 84, 89, 109, 110, 128, 134 general, 88, 94, 120, 123, 140 general theory of, 117, 121 generative (social), 60, 63, 64, 123, 130, 134, 258 giving birth to a new, 43–51, 81–83, 99, 105, 116, 117, 121, 130 good, 2, 3, 9, 41, 86, 122, 206 hardy perennial of, 106, 160, 248 hidden agenda of, 25, 39, 43, 48, 70, 71, 76, 107 history of the, 18, 22, 26–30, 55, 77, 78, 103, 111, 122–124, 140, 148, 159, 160, 181, 200, 223, 240, 260 of hope, 9 humanize(ing) of our, 4, 200, 244 innovation of, 14 integrative, 7 intellectual realities of, 123 invention of a new, 49, 63, 82, 87, 89, 91, 92, 99, 102, 128, 132, 134, 257 is not an independent variable, 90, 99 and its modus operandi, 116, 140 lacking of potentiality for innovation and novelty, 21 liberating, 14 limiting view of, 1 mission of a new, 127 modern, 50, 227, 247 myopia of our, 125 natural, 9, 13, 17, 22, 26, 29, 30, 65, 77, 87, 90, 96, 101, 180, 240, 244 for the near future, 14, 123 new agenda for, 45, 48, 53–69, 96, 116, 117, 130, 206 of new (states of) being, 130, 134 new kind of, 19, 28, 102, 188, 227, 245, 257 new kind of complexity, 183 new method of, 35, 36 new type of, 116 new vistas for a, 27 normal, 8, 18, 20–26, 30, 33, 39, 44, 68, 69, 76, 78, 82, 87, 102, 105, 106, 122, 130, 147, 159, 227, 228

312 Science(s) (cont.) objective, 18 open up, 45 in operation, 22, 48, 122 our history of, 18, 22, 27, 28, 30, 55, 123, 159, 160, 181, 223, 240, 260 phenomenon of, 28 of (hitherto unknown) possibilities, 230 of (such) potentialities, 60 practical kind of, 2 ‘progress’ of, 49, 125 project of (doing), 28 promising, 12, 104 psychological, 76, 77, 91 of psychology, 14, 24, 37, 77, 91, 94, 99, 123, 176, 251 reality of ‘normal,’ 130 reality of reality for, 13, 83, 85–114, 130 renewed, 29 retooling of, 8, 166 scientific revolution in our, 18 single, 130 social, 1, 11, 17, 43, 53–69, 87, 118, 137, 147, 155, 179, 197, 207, 237 theorizing about, 122 traditional way of doing, 18 trans-disciplinary, 9, 53, 55, 67, 130, 211 transformation of our, 105 of transition, 55, 88, 123, 130, 134 (method of) viewing, 64, 242, 247 Western, 103 Science-as-usual beyond the, 71, 127, 203, 238 Scientific outlook, 226–228 revolutions, 14, 18, 22, 26, 28, 33, 47, 69, 75, 86, 105, 141, 159, 239 Scientists worldview of, 14 Sea of uncertainty navigating, 125, 145 Seeing new way of, 88, 231, 239, 240, 249 Selection limitations of, 133 natural, 133, 190 powers of, 133 Self-amplifying, 146, 242, 253 Self-and-other loop of, 63 Self-assembling, 146 Self-causation complex, 191

Index dynamics of, 191 immediate, 191 modeling, 194 Self-cause circularity of, 164 ongoing, 61, 63, 146, 149, 154, 164, 263 Self-change generate, 61, 63, 152 Self-creating, 146, 163, 164, 167 Self-creative, 146, 167, 176 Self-enhanced causal loops, 143, 146, 197 loop effects, 142, 158, 164, 175, 180, 187, 189, 204, 261, 263 Self-generated states of affairs, 87, 101, 106, 112, 113 Self-generating network, 86, 143, 147, 150 Self-generating process, 145, 163 Self-generative dynamics, 191, 226 process, 158, 205, 206, 229, 255 system, 79, 227, 229, 230, 246 Self-growth generating, 63 Self-maintaining process, 146, 153, 163 Self-maintenant system, 143, 145, 146 Self-organization interleaving of, 37, 100 Self-organizing being, 145, 146 Self-patterning, 167 Self-potentiating dynamic of, 214, 255 inherently, 203 nonlinearly in time and space, 36 power of, 21, 140, 227, 232 in the real, 36, 201, 222, 228 Self-realizing systems, 146, 189 Self-strengthening, 102 Self-sustaining process, 167, 210 Selves, 103 Senge, 199 Sense, 43–45, 55, 56, 62, 64, 65, 68, 74, 78, 82, 86, 92, 96, 100, 107, 117, 132, 133, 138, 140, 147, 157, 209, 223, 238, 239, 242, 244, 246 Sequence causal, 192 different, 192 of emotions, 223 rhythmical, 223 Shaped, 3, 9, 38, 41, 70, 88, 206, 207, 261, 262

Index Shaping causal, 144, 145, 260 each other, 5 (by) force, 4, 7, 138, 144, 145, 153, 167, 170, 173, 180, 182, 183, 186, 200, 205–207, 215–217, 229, 260, 262, 263 Shift of focus, 8 of mind, 8, 38, 124, 241 of paradigm, 8, 44, 46, 47, 49, 55, 82, 88, 137, 189, 192, 199, 202, 227, 231, 237, 245, 247, 258, 260, 261 of thinking, 203, 239 towards a new science of complexity, 34 of view, 237, 256 Shoulders standing on the, 55, 61 Silence a book of, 223, 228 choice of, 223 conditions(s) of, 224 experience of, 223, 224 (creative, generative) power of, 223 reality of, 223 ‘working’ of, 223, 224 Similarity empirical, 95 Simon, H.A., 29, 30, 205, 251 Simplicity change from, 138 to complexity, 138, 188–189, 191 create, 120, 124 increasing, 119 rebellion against, 14 solid grounding of, 142 Situations idealized, 45 simplified, 45 Smith, T., 183 Smolin, L., 87, 90, 92, 118, 129, 180–183, 185, 188, 202 Snowball Phenomenon, 4, 113, 226, 249 Snow, C.P., 13 Social nature of man, 37 Social organization complex, 46 healthy, 46 Social realities changing nature of, 199 Social science(s) building anew of the, 40 critical about the, 30, 65, 126 degeneration of, 17, 18

313 (better) future of, 12, 14, 72, 83, 88, 104, 126 generative, 60, 63, 64 humanizing (of) the, 19, 34, 38, 67, 230 new avenues of the, 41 new foundation for the, 47, 64, 124 new generative, 60, 63 open up new vistas for the, 47 picture of the, 30 (basic) problem for the, 31, 90 retooling of the, 88, 166 survival of the, 30 theorizing about, 40 Society better, 14 delusive, 35 future of, 3, 13, 206 at large, 3, 7, 13, 17, 18, 20, 27, 34, 35, 39, 48, 199, 200, 206, 233 (the) practical analyst of, 36 reality of our, 35 self-organization of, 66 vexatious fact of, 37 warp and woof of, 180 Solé, R., 158, 229, 247 Solid approach, 65 Solution of the crisis of psychology, 88 Sörbom, D., 161 Sotolongo, 206 Space(s) of bipolar order, 222 in the brain, 228, 233, 244 3-D, 212, 213, 220 in the domain of possibilities, 67 in the domain of potentialities, 67 of the (total) effects, 212 enlarged, 2, 32, 34, 134, 202 enlarging, 114, 228, 242, 246 freeing up, 228, 233, 244 generative, 7, 205, 210, 246, 249, 250, 254, 255 high-dimensional, 201, 249, 250, 255 hyper, 80, 110, 201, 202, 210, 214, 221–226, 228, 234, 249, 250, 263 (state) hyper-, 80, 110, 210, 214, 221–226, 234, 249, 263 infinite, 225 n-dimensional, 210 new, 6, 28, 38, 45, 54, 73, 84, 98, 102, 105, 111, 114, 118, 122, 135, 145, 201, 204, 229, 230, 242, 244–246, 252, 254, 255 of a new world, 189 open up new, 28, 38, 54, 73, 122, 230

314 Space(s) (cont.) of possibility, 28, 33, 45, 54, 62, 66, 73, 84, 98, 104–106, 111, 113, 114, 119, 121, 122, 124, 134, 201, 204, 205, 210, 225, 226, 229–233, 242–244, 246, 249, 252, 255 of the possible, 2, 5, 6, 19, 28, 32–34, 41, 99, 101, 104, 113, 114, 118, 134, 145, 189, 195, 199, 202, 207, 215, 217, 226, 228–230, 239, 240, 242, 244, 246, 249, 252, 254, 255 social, 54 state, 222, 226 of (possible) states, 233 for thinking, 102 three-dimensional, 162, 163, 187, 222 transition, 162, 163, 187 unexpected, 118, 134 unknown, 35, 41, 99, 233, 243, 255 Space of the possible enlarged, 2, 32, 34, 134, 204 enlargement, 33 enlarging, 2, 5, 19, 32, 114, 118, 189, 195, 199, 215, 228, 229, 239, 242, 246 Spectrum of human lived experience, 59 the whole, 59 Spiralling movement, 98 Stacey, R.D., 38, 62, 113, 117, 120, 130, 131, 149 Stance reductionistic, 79, 94, 217, 231 reductive, 30, 110, 131 theoretical, 94 Stanley, D., 27 Starobinski, J., 156, 180 State(s) of affairs, 87, 101, 106, 112, 113, 233 of art, 11, 20, 23, 26, 35, 44, 65, 69, 100, 101, 133, 136, 141, 243, 251 of being, 22, 40, 54, 86, 93, 98, 111, 112, 126, 130, 134, 201, 205, 210, 214, 215, 222, 228, 229, 243, 249 of (human) being, 40, 86, 98, 126, 201, 249 complex, 210, 222, 229, 249 (quality of) complexity of the, 206 connected, 191 creative, 112, 201 dynamic, 98, 249, 261 dynamics of, 224 of evolvability, 86, 112 of (generating) expansion, 210 fluid, 80, 140

Index of free play, 224 generative, 112, 113, 201, 228, 229, 249 of generativity, 40, 98, 205, 243, 261 high-dimensional, 126, 226 inherently complex, 112, 126 (amputation of) internal, 30 of knowingness, 112 multi-dimensional, 126 new, 54, 130, 134, 215 (acquired) potential, 98, 229 of psychology, 127 State hyperspaces, 221–226, 234, 249, 263 State of art in the field of complexity, 141 State of being landscape(s) of, 214 State space(s) of bipolar order, 222 high-dimensional, 226 of possibility, 226 Stengers, 69, 70, 72–74, 76 Step outside of our system of thinking, 35 of the system, 86 Steps complexly interwoven, 49, 74, 202 individual, 49, 201 necessary, 48, 86, 101, 189 of new thinking, 47, 49, 53, 68, 81, 127, 239 separate, 49, 54 Stepwise kind of change, 125 Sterk, N., 195, 196, 253 Stimuli-devices, 36 Stone(s) (new) building, 32, 40, 153 corner, 105, 183, 187 disdained, 8, 21, 94, 105, 123, 125, 144, 153, 181, 187, 251, 258 foundation, 18, 21, 23, 87, 89, 94, 121, 123, 124, 181, 187, 201, 202, 243, 247, 251 rejected, 121, 176 Strands in complexity science, 127 different, 127, 130 of different silences, 223 interwoven, 223 Strategies learning, 113 search, 130 Strengthening causal, 212 path of, 213

Index potential of, 213 trajectories of, 193 Structural changes, 157 Structural equation modelling (SEM), 143, 156, 161, 163, 173, 240, 241, 260 Structure(s) of evolving processes, 49, 246 (a kind of) fluid, 80, 168 forcing, 252, 262 generative, 146, 163, 168, 175, 188, 191, 201, 202, 205, 248, 253, 259, 261 loop-like, 205 organization of many complex, 116 powerful, 215 rethinking the, 116, 140 of science, 116, 134 web-like, 4, 101, 116, 192, 193, 215, 261, 263 Struggle of escape, 82, 94, 124, 125, 127, 130–134, 158 personal, 124 Style academic writing, 127 controlling, 125 dreadfully limited, 127 Subject complex, 41, 60, 63, 65, 77, 191, 238 like the tapestry of life, 65 reacting, 36 Subjectivity beyond the subject, 63 (as a) self-and-other relationship, 63 true, 63 Subject of study complex nature of, 110 complex unity of the, 59 human being as, 110, 207 humanizing, 13, 14, 38 inherently limited, 13 inherent trivialization of, 14 trivialization of the, 14, 34 Subject of study a real complex, 60 Summation rule of path analysis, 172 Surge of hope, 223 of possibility, 223 Synthesis for coherence, 167 essence of, 204 generative, 167, 262 generative processes of, 167

315 new, 68 of new forms, 262 selective, 167 Synthesizing views of complexity, 143 System(s) (causally) interactive, 157, 159, 168 challenging, 208 circular, 157 closed, 13, 18, 22–24, 26, 30 closure of, 22 complex, 4, 6, 9, 39, 70, 79, 107, 133, 137, 156–158, 160, 181, 185, 188, 190, 191, 202, 207, 222, 225, 228, 229, 243, 246, 251, 252, 256–258, 260, 261 complexly constitutive, 144 ecological, 157 education, 208 ensemble, 207, 210, 241 generating, 139 generative, 70, 79, 160, 163, 164, 168, 183–185, 188, 191, 201, 227, 229, 230, 242, 245, 246, 262 interactive, 159, 168 of knowledge, 88, 89 at large, 28 as living systems, 228, 230 of loops, 188 members of the, 207 in nature, 157, 158 network, 188, 204, 205 perverted, 18, 24 properties of the, 139 realization of, 227 rebellion against the, 18, 27 self-constructing, 259 self-creative, 164 self-generative, 79, 227, 229, 230, 246 self-maintenant, 143, 145, 146 self-organized, 28 self-organizing, 70, 188, 189, 242 self producing, 242, 259 self-realizing, 146, 158, 181, 189 stepping outside of the, 84 of study, 106 and their (actual) realization, 230 of thought, 29 unknown, 139, 163 Systematicity in dealing with complexity, 119, 142 System of study complexity of, 106

316 T Tackle, 7 Tapestry architecture of, 65 complex, 136, 191 dynamic, 97, 101, 193 of functions, 74, 94, 100, 191, 193 functions of the, 74, 94, 100, 191, 193 of life, 65, 136, 144 strands in the, 75, 100 themes in the, 75, 100 webbed, 94 woven, 74, 89, 94, 100, 191 Taylor, M., 123 Techniques shift in, 26 Temporality inherent, 97 Terminology new, 136, 137, 158, 249, 250 sophisticated, 210 Terms(s) long, 190, 198, 212 mathematical, 145 medium, 212 Terrain to be discovered, 11 to be invented, 11, 12 new, 11 re-invented, 12, 150 for social theorizing, 11, 36, 38, 99, 159, 160 Territory, 49, 96, 110, 111 Testimonium Pauperitatis, 102 Theoretical physics science of, 90, 126, 180 Theorize our practices, 117 Theorizing on becoming, 140 the core of, 139 distorting, 30 on evolution, 110, 127, 217, 250, 261, 262 new terrain for, 11 social, 11 Theory(ies) catastrophe, 12, 104, 237 causal, 217, 261, 262 of change, 18, 40, 74 chaos, 12, 104, 237 complexity, 12, 83, 104, 138, 242, 250 of complex systems, 156, 157, 190 computational, 12, 104 of the crisis, 18, 21, 28–32, 87

Index deep, 106, 242, 248 describing, 7, 25, 28, 60, 64, 74, 87, 88, 151, 158, 224, 243, 251 developmental, 263 of evolution, 110, 127, 217, 250, 254, 261, 262 explanatory, 88 formulating, 18, 25, 54, 241, 251 grounded, 7 of life, 183 of network causality, 158 power of, 7, 104 prisoner of, 105 realist, 91, 93, 101, 155 scandal of reductionistic, 44 social, 11, 36, 38, 99, 159, 160 testable, 261 unfolding a, 29 unity of, 107 Things mutual relations of, 61, 162 ontology, 109, 112 true nature of, 109 Thinkable rethinking of the, 12, 34, 35, 104, 134, 137, 227, 248 Thinker futurist, 102 Think(ing) about research on education, 208 abstract-logical, 95 captives of (old), 3 causal, 3, 156, 175, 224, 231, 248 common ways of, 72, 78–82, 165, 259 in (generative) complexity, 55, 59, 64, 100, 111, 136, 185, 189, 191, 194, 225, 227, 259, 263 complexive, 95 in a complex manner, 49, 116 danger of linear, 26, 33, 40, 48, 75, 87, 95, 104, 139, 150, 155, 200 entry for new, 83, 189, 215 explanatory, 24, 160, 216, 260 explanatory mode of, 24 fallacies of, 130 incapable of, 116 integrative, 7, 44, 47, 50, 249, 250 key of new, 46 lacuna of our, 13 learn to, 33, 47–49, 55, 59, 65, 78, 95, 103, 107, 119, 129, 157, 238, 239, 248, 263 linear, 1, 12, 26, 33, 40, 48, 58, 75, 80, 84, 87, 95, 100, 104, 139, 149, 150, 155, 156, 199, 200, 258

Index map for, 49 mode of, 24, 95, 98, 118, 174, 194, 248 mono-causal way of, 155 network, 194, 225, 231, 242, 248, 249, 263 new elements of, 96, 136, 141 new kind of, 5, 18, 19, 23, 33, 46, 67, 84, 88, 100, 110, 112, 113, 115, 124, 155, 158, 167, 183, 206, 226, 229, 230, 248, 259 new mode of, 98, 174, 194, 248 new principles of, 115 for the new science, 81, 87, 139 new ways of, 8, 27, 28, 45, 66, 72, 79, 96, 115, 124, 125, 130, 132, 159, 249 old elements of, 124 (leave) old ways of, 48, 75, 78, 82, 96, 115, 124, 125, 130, 132, 227 omniscient, 116 oncrete-empirical, 95 opposite ways of, 96 other ways of, 27 out(side) of the box, 43, 68, 191, 240, 258 paradigm(s) of, 208 perverse of, 24 seductiveness of this type of, 155 shift of mind in, 124 simplicity of, 133 starting new ways of, 132 that arises among other discourses, 126, 127 that does not rise over, 126 type of, 155 unified way of, 53 unlearning the old ways of, 48 web of new, 48, 49 Western, 103 which thinks itself, 115 Third culture, 13, 68, 203, 244 Thought disjunctive, 59 method of, 118, 138, 143 mode of, 152 new tools of, 41, 138, 145–146 (escaping dear) old habits of, 24, 29, 30, 33, 46, 55, 65, 72, 98, 107, 110, 133 reform of, 47, 48, 66, 98, 104, 128, 140, 149 Thread spinning a, 64 strength of the, 64 Time into the equation, 125, 167, 176, 181, 183 excluding, 175 orthodoxies of the, 127

317 role of, 39, 74, 100, 125, 161, 175 as a variable, 222 Tinkering causal, 260 at the edge of our own thinking, 158 through causal processes, 260 Tononi, G., 125 Tool(s) for becoming explanatory, 62 complex, 65, 211, 255 conceptual, 100 for describing complexity, 58 different, 12, 104, 106 for explaining complexity, 241 scientific, 211 of thinking, 185, 189 Toolkit complex, 65, 211, 255 enabling new thinking, 65 Topic difficult, 61 for discussion, 22 of enlightenment, 76 of new thinking in causality, 61 popular, 22 serious, 1, 77, 206 of study, 1, 161, 206 Totality of the human being, 51, 60 open, 51, 60 unbroken, 44, 60 the ‘working’ of, 60 Tradition generating a (new), 226 Training teacher, 107 Trajectories of development, 97, 125 individual, 125 of strengthening, 193 successive, 62 unknown, 35 unpredictability of, 62 unpredictable, 62 Trans-disciplinarity, 50, 120, 121 Trans-disciplinary science, 9, 53, 55, 67, 130, 211 Transference meeting transference, 183 Transfers, 95 Transform mutually, 215, 230 one another, 215

318 Transformation(s) chain, 149, 150 generic, 98 modeling, 121 phenomena of, 129, 134 possibilities of, 113, 194, 215, 246 potential, 61 qualitative, 51, 95, 98, 110, 134, 216, 255 reciprocal, 32 self-, 32 Transition (causal) dynamics of, 60, 67 (generative) dynamics of, 67, 123 modeling, 121 new science of, 55 phenomena of, 129 realize a, 54 social science of, 55 within the space of possibilities, 54 Transitory, 9, 86, 88, 89, 94, 110, 112, 124, 144, 176, 194, 247, 251, 252 Trap of constructivism, 149 of functionalism, 149 Tri-angular dynamics, 126 Tripartite link, 36, 38, 119 relationship, 38, 119, 121, 126, 139, 147, 148, 153, 160 Trivialization avoid the, 35 of causality, 143 common, 1, 11 of complexity, 155 inherent, 14, 231 of reality, 34 of the relationship of our sciences with the complexity of reality, 155 Truism, 36 Truth deep, 67 Tunnel vision, 25 Turning point for a new science, 34 of new thinking, 34 qualitative, 34 real, 34 for society at large, 34 of thinking in complexity, 34 Tutelage self-imposed, 116 self-incurred, 21, 23 Two cultures separation of, 13

Index Types of entity, 259 fluid, 259 U Ulanowicz, R., 206, 216, 254, 255 Uncertainty eliminate, 28 embrace, 31 face, 124, 125 sea(s) of, 65, 125, 139, 145 Uncontrollable, 110 Uncreative unhappily, 30 Understanding, 2, 3, 6, 7, 21, 31, 36, 38, 50, 63, 66, 79, 87, 106, 121, 125, 128–130, 132, 133, 140, 158, 198, 204, 246, 250, 258 gaps in our, 119 new avenues for, 119, 122, 134, 177 reframe our, 140 superior manner of, 50, 137 Unevenness, 255 Unexpected, 2, 3, 9, 19, 21, 31, 32, 45, 72, 77, 86, 118, 134, 167, 223, 225, 226, 228, 240 Unexplained explaining the as yet, 261 Unforeseeable, 3 Unification concrete, 95 Unified way of thinking, 53 Unifying-perspectives, 138 Unit of the human being, 61 of the individual, 61 as a whole, 62 Unitas multiplex, 96 Unit of study dynamic unit of, 60, 241 Unity complex, 5, 59 cyclical-helical, 143, 201, 202, 208, 211 dynamic, 96, 106 fundamental, 138 of the human, 59 other-reference, 118 of self-reference, 118 Universe of chance, 72, 224 a chaotic, 224 counterintuitive, 79, 226

Index a different, 86 fascinating, 226 at home in the, 37, 133 Newtonian, 144 Unknowable exploring the, 35 field of, 12 learning within the, 12, 28, 30, 35 seemingly, 15, 26, 54, 110 space of, 15, 33 spaces of the, 28, 35 Unknown possibilities, 199, 202, 230 potentialities, 101 space(s) of the, 28, 33, 35 trajectories, 35 Unlearning old ways of knowing, 118–119 old ways of thinking, 48 Unlock people, 43, 64 Unpredictability intrinsic, 62 Unpredictable, 57, 62, 67, 80, 101, 107, 110, 164, 226 Unreal, 89, 93 Unthinkable path to the, 35 thinking of the, 35 Upheavals, 63 Urwick, 179 V Valsiner, 24, 181, 201 van Benthem, 127 Van der Veer, 24 van Ryswyck, L., 233, 235 Varela, F.J., 188, 244, 245, 247, 248, 260 Velmans, M., 110 Venue new, 60 Vico, G., 17, 35 Victims of blinding paradigms, 180 of misguided paradigms, 25, 260 View about cognitive development, 51 about complexity, 203 adequate, 131 all-encompassing, 54 blinkered, 190 complex, 94, 95, 97 of complexity, 87, 88, 128–130, 144, 214, 224, 237, 263

319 comprehensive, 94 Darwinian, 51, 263 deepening (our), 8 different, 20, 29, 58, 92, 239, 256 distorted kind of, 107 dominant, 51, 162, 263 generative, 67 of gradual change, 51 of the nature of life, 129 on the origin of life, 129 programmatic, 12, 40, 48, 56, 64, 65, 100, 110, 189 of the real, 18, 87 reductive, 93, 110 synthesizing, 143 of the world, 17–19, 28, 40, 50, 73, 190, 239 Viewing new framework of, 13 rethinking of our, 34, 40, 50 Vision(s) alternating of, 41 enlarges (our), 206 of (both) nature and science, 206 Visionary work, 145 Vistas opening panoramic, 41 open up new, 47, 229, 256 of possibility, 114, 229, 231, 244, 256 Vocabulary evolving new, 128 new, 7, 46, 47, 127, 128, 135–137, 158, 165 Vygotsky essential, 100 Vygotsky, L., 4, 13, 18, 24–26, 29, 36, 37, 40, 44, 45, 51, 61, 63, 64, 85–114, 122, 123, 138, 144, 149, 176, 227, 239, 244–247, 251, 252, 260, 262 W Wallerstein, I., 247, 256 Wave(s) of delight, 223 of gratitude, 223 of peace, 223 Weave dynamic, 193 what is the, 65, 75, 101, 136, 189, 193, 246, 251, 252 Weaver in the web, 63

320 Weaving complex, 98 dynamic, 45, 193 dynamics of, 152, 153 inter, 57, 66 mutual, 152 their own web, 56 tortuous kind of, 68 of a web, 68 Web(s) complex, 49, 209, 215 of concepts, 47 dynamic, 49, 63, 68, 246 emerging, 101 entangled, 47, 49 hypercyclic, 4, 101, 261, 263 intertwined, 49 of meaning, 68 of new thinking, 48 self-ordering, 194 of sense making, 68 of structural dependencies, 209 weaver in the, 63 weaving their own, 56 without a spider, 194 woven, 63 Web-like causal network,structure(s), 193 Webster, 61, 62, 64 Wechselwirkung, 156 Wertsch, J., 25 Western thought, 118 Western ways of thinking, 118 Whitehead, A.N., 27, 49, 60, 76, 82, 246 Wholes coherent, 68, 246 functional, 101 functioning of, 5 Wilden, 67 Wilso, E., 181 Wimsatt, 163, 165, 168 Window first, 254 new, 3, 206, 254, 256 third, 206, 244, 254, 256 upon reality, 3, 254, 256 on the world, 254, 256 Wittgenstein, 228, 232, 233 Wolfram, 188 Work misunderstood, 217 of Newton, 217 in practice, 49, 50, 56, 57, 60, 67, 104

Index Working potential, 129 of totalities of the human being, 60 World of being through becoming, 14, 39 causal, 203, 204, 240, 248, 253, 254 complex, 2, 87, 118, 129, 146, 157, 180, 257 complexity of the, 217, 242, 250 conceptions of a real, 44 of daily experience, 44 dehumanized view of the, 18 embedded in a, 50, 227, 247 enlarged, 203 expanding, 114, 202, 204 fluid nature of the, 140 fundamentally different, 50, 227, 247 generating (of this), 67, 226 of human experience, 255 (the) limits of my, 232 (the) limits of our, 203, 228, 231, 257 (the) limits of the, 203, 228, 257 mental, 107 as a network of relations, 202 new, 6, 104, 114, 122, 134, 189, 195, 202, 215, 226, 243, 252, 257 nonlinear, 157 of novelty and innovation, 256 ontological creativity of the entire, 133 physical, 107 possible, 50 of the possible, 2, 5, 6, 104, 113, 114, 118, 122, 134, 189, 195, 202–204, 215, 217, 237, 242–244, 250, 252, 254, 256, 257 random, 115, 117 real, 1–3, 5–9, 19, 21, 23, 34, 37, 40, 44–46, 50, 51, 54, 59, 61, 62, 65–67, 72–75, 89, 93, 103, 104, 112, 116, 117, 121–129, 131, 134, 135, 137, 140, 142, 143, 145, 146, 148, 155–157, 160, 164–168, 175–177, 179–181, 189, 191, 192, 194, 195, 200, 202, 203, 210, 214, 216, 217, 224, 225, 230, 231, 242, 243, 247–250, 252, 255–257 of real-world complexity, 2, 230, 252 social, 3, 5, 107 understanding of the, 50, 69, 106, 128, 129, 140 unexplored, 217, 248, 254 unknown, 2, 104, 106, 237 viewing of the, 13

Index view of the, 17–19, 28, 40, 50, 73, 190, 239 web-like, 133 window on, 254, 256 window to the, 206 wo/man made construction of the, 17 World disclosure, 103 World of the possible hitherto unknown, 2 World-orientation, 103 World’s make-up simplicity of, 123 Worldview change our, 40 distorted, 17 enlarged, 6, 43, 73

321 enlarging of the, 140 larger, 73 system’s, 18 Wounds self-inflicted, 101 Woven patterns, 61, 152, 263 webs, 61, 63 Wright, S., 161 Z Zilsel, E., 61 Ziman, J., 93 Zone(s) of shadow, 141