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Complexity-thinking and social science: Self-organization involving human consciousness
New Ideas in Psychology 47 (2017) 10e15
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Complexity-thinking and social science: Self-organization involving human consciousness Stephen A. Sherblom* Lindenwood University, 209S. Kingshighway, St. Charles, MO 63301, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 6 February 2016 Received in revised form 1 January 2017 Accepted 16 March 2017
Complexity-thinking refers to a cluster of concepts popularized in several branches of science, primarily in the physical sciences but increasingly in the social sciences. There is reason to be cautious regarding how the concepts are used across disciplines and branches of science. This paper discusses self-organization in dynamic systems, tracing its roots in social science and critiquing current usage of the term with regard to systems involving consciousness - humans and groups of humans. A brief sketch of the levels of complexity sets the groundwork for understanding the critique of self-organization to follow. I argue that consciousness fundamentally changes the terms of discussion in self-organization by adding a self/selves that is not equivalent to the system as a whole, but which directly influences what is organized, how, and toward what end. Self-organization in complex adaptive systems involving consciousness should be distinguished as self-cultivating self-organization and self-presenting self-organization. © 2017 Published by Elsevier Ltd.
Keywords: Self-organization Complexity-thinking Self-cultivating self-organization Self-presenting self-organization
1. Introduction Several books appeared in the 1980s and 1990s that popularized a group of concepts in science: specifically the concepts complexity (Holland, 1995; Waldrop, 1992), chaos (Gleick, 1987), self-organization, emergence (Nowak & Vallacher, 1998; Prigogine & Stengers, 1984) and dynamic systems (Capra, 1996; Thelen & Smith, 1994). While these concepts have different disciplinary histories, they are frequently grouped together, often under the rubric complexity thinking (Capra, 1996). These complexity concepts are now widely used in many branches of science, and increasing are being applied in psychology, education, nursing, and other social sciences. There is reason to be cautious regarding how these concepts are used, however, especially across the levels of complexity that separate material science and social science. On the other hand, insights of complexity science may hold great promise for a more adequate social scientific perspective if we can avoid the dangers of uncritically using concepts developed in material science to conceptualize living systems such as persons and groups of people. This paper begins by grappling with some of the terminology of complexity thinking, noting that some terms, and ‘systems
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thinking’ in general, have long been used in social science. A brief sketch of the levels of complexity sets the groundwork for understanding the critique of self-organization to follow. The critique, in short, is that there is a vital difference between self-organization in systems that involve consciousness (those of interest to psychologists, educators, and social scientists generally) and selforganization in systems that are not conscious. If this is the case, several implications follow, including changing the way we speak about self-organization in the social sciences to reflect the role of consciousness in that self-organization. 1.1. The complexity cluster Some of the terms in the complexity cluster can be found historically in both social science and material science (including physics), while others, such as chaos and complexity were developed and are used almost exclusively in material science. I will focus on dynamic systems and self-organization e each of which grew at least partly out of studies in nonlinear change in the organization and growth of living things - living systems. Accounts of the development of complexity thinking as a whole suggest that this perspective has coalesced since the 1930s through insights in a variety of fields including physics, biology, psychology, ecology, and material science (Capra, 1996; Gleick, 1987). As noted in the following brief review, these terms have been active in social science discussion for longer than that, and hence, the full story of
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social scientists' contribution to dynamic systems has yet to be told. The scientists who formulated the science (Bertalanffy, 1968; Boulding, 1956; Holland, 1995; Prigogine & Stengers, 1984); the writers who popularized the ideas (Capra, 1996; Gleick, 1987; Waldrop, 1992); and those in the social sciences who have taken up aspects of this approach (Thelen & Smith, 1994; van Geert, 2012) all speak of complexity thinking as a universalizable approach to non-linear change. It is useful, they argue, for describing certain types of complex systems wherever they are found. This includes non-linear behavior in micro-particles, in cells, in organisms, including humans, in ecologies and societies, and in the universe of planets and stars (Capra, 1996; Waldrop, 1992). While I am not challenging that claim of universal relevance, I do argue that selforganization is sufficiently different as a process when dealing with human consciousness that some way of designating that distinction is intellectually necessary in psychology and social science more broadly.
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wide array of intellectuals, including Darwin, Marx, Parsons, Durkheim, and Weber, illustrating something of the role social science has played already in the development of this aspect of complexity thinking. They note: “systems theories [and] explanations with an evolutionary character have emerged alongside, rather than deriving from, natural science and they continue to play an important role in much social theory to the present day” (Byrne & Callaghan, 2014, p. 88). In A dynamic systems approach to the development of cognition and action, (1994) Thelen and Smith argue that dynamic systems and related concepts are the appropriate way to think about and describe the complexities of human development. In our approach to fundamental questions of mental life, we invoke principles of great generality. These are principles of nonlinear dynamic systems, and they concern problems of emergent order and complexity: how structure and patterns arise from the cooperation of many individual parts. (Thelen & Smith, 1994, p. xiii)
2. Dynamic systems, complex systems, and systems thinking Of all the concepts in the complexity thinking cluster, systems thinking and dynamic systems terminology are perhaps the most accessible to social scientists, having a long history in psychology. Capra (1996) reports that “the main characteristics of systems thinking emerged simultaneously in several disciplines” (p.17) during the first half of the 20th century, especially biology which “emphasized the view of living organisms as integrated wholes,” Gestalt psychology, and ecology (p. 17e18). Byrne and Callaghan (2014) argue that what makes complexity thinking a universalizable explanatory frame is that it speaks in terms of complex systems, and systems that can be described as complex exist in many scientific disciplines. “When we talk about complexity we are talking about systems. Complexity is a property of systems” Byrne and Callaghan note (2014 p. 3). Morin (2008) argues that: The scope of system theory is… quasi-universal, because, in a certain sense, all known reality, from the molecule to the cell to an organism to a society, can be conceived of as systems. That is to say, they can be conceived as the interaction of different elements” (Morin, 2008 p. 9 p. 9) Murphy (1997) notes that systems thinking emphasizes process: One has to give up the traditional Western philosophical bias in favor of things, with their intrinsic properties, for an appreciation of processes and relations; the components of systems are not things, but processes. (p. 32 emphasis added) In their book Dynamical Social Psychology (1998), Nowak and Vallacher argue that dynamic systems thinking is congruent with many important traditions in social science: The subject matter of social psychology is inherently dynamic. It is hard to conceive of action without movement, judgment without a flow of thoughts, emotion without volatility, social interaction without an ebb and flow of gestures and words, or social relation without ongoing evolution of roles and sentiment. (Nowak & Vallacher, 1998 p. vii) Further, they note that “the nature of human dynamism provided a focal point in the earliest attempts to characterize experience in interpersonal contexts, as reflected in the seminal work of such figures as James, Mead, Cooley, Lewin, and Asch” (Nowak & Vallacher, 1998 p. vii). Byrne and Callaghan (2014) trace systems thinking back to a
The authors argue that this approach allows us to ask questions we have not previously been equipped to address, such as: “What are the organic and environmental factors that engender change?” and “How can we begin to untangle the complex web of causality when real infants live and develop in a world filled with people, things, and events in continuous interaction?” (p. xiii). Like other systems that have been studied, such as the development of weather patterns or growth patterns of species in a geographic region, the development of cognition and action are not preprogrammed, Thelen and Smith note (1994). Rather, cognition and action emerge from a complex interaction in development, and in interaction with the environment, itself best conceptualized as a complex system. Thelen and Smith say in summary: “It is a science for systems with a history, systems that change over time, where novelty can be created, where the end-state is not coded anywhere, and where behavior at the macrolevel can, in principle, be reconciled with behavior at the microlevel” (1994, p. 49). The developing systems Thelen and Smith described include aspects of learning to walk, and learning to think. Additionally, Nowak and Vallacher (1998) argue that a systems perspective will help synthesize the atomized social psychology of the past hundred years: For the better part of the 20th century, social psychological research has attempted to isolate causal mechanisms with respect to distinct aspects of interpersonal experience. The methods spawned within this approach have been quite successful in identifying the key features of human thought and behavior. With the advent of the dynamical approach, it is now possible for investigators to assemble sets of such mechanisms into coherent systems. (p. viii) Waldrop (1992) discusses similarities across complex systems as diverse as: the political entity the Soviet Union, the New York Stock Exchange, ecosystems, birth rates among rural poor families, the creation of living cells from ‘chemical soup’, natural selection and evolution, and the human mind. He argues that every one of these systems …is complex in the sense that a great many independent agents are interacting with each other in a great many ways. Think of the quadrillions of chemically reacting proteins, lipids, and nucleic acids that make up a living cell, or the billions of interconnected neurons that make up the brain, or the millions of
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mutually interdependent individuals who make up a human society. (Waldrop, 1992 p.11 p.11) He concludes: “In every case, groups of agents seeking mutual accommodation and self-consistency somehow manage to transcend themselves, acquiring collective properties such as life, thought, and purpose that they might never have possessed individually” (Waldrop, 1992, p. 11). In Harnessing Complexity, Axelrod and Cohen (2000) set out the concepts of complexity thinking as they might be applied to any complex system, including those studied in social science. By this they meant to include things of interest to managers, policy makers, historians, and other kinds of change agent. Axelrod and Cohen include a range of examples of complex systems usefully understood this way (p.3): (i) a member of a work team wants to elicit cooperation from coworkers; (ii) an impoverished woman in Bangladesh wants to borrow a little money to rent a stall at the local market; (iii) a computer program scans the Internet for helpful resources; (iv) the United States wants to foster among nations goals that the U.S. cannot impose by force. All of these contexts and processes, they argue, can be described with the common language of complexity. Granic and Hollenstein (2003) have articulated “dynamic systems methods appropriate for testing systems-based models in developmental psychopathology” (p. 641) such as in family therapy or couples counseling. Lichtwarck-Aschoff and van Geert (2004) developed a dynamic systems perspective on social cognition and problem behavior. The authors utilized complexity language and techniques of attractor states and topography modeling to discuss and describe problem behavior as a system. They argue that “the attractor metaphor helps us explain the interindividual variability in intervention effects” (p. 406). Hollenstein and colleagues have researched affect during parent-adolescent child interactions “using state space grid analysis” to describe the evolving emotional tenor of the interchange on the part of both parent(s) and children (Hollenstein, Allen, & Sheeber, 2016). Writing in the area of marital interaction research and computer modeling, Griffin and Li (2016) attempt to describe the dynamics of a couple or a family in terms of self-organization. Their attempt to model the emotional flow of relational discourse is in order to support the emerging field of affective computing, which will help realize “realistic robots and avatars” (p.641). Lastly, in Social Emergence: Societies as complex systems, Sawyer (2005) explored the concept of emergence as it has long been used in social science. Though now commonly included as a concept in complexity thinking, Sawyer points out that emergence has a long and varied history in the disciplines of psychology and sociology with discussion of emergence dating back to the mid-nineteenth century (p.27). Emergence is intimately connected to selforganization in that what emerges as a new property in the system is, after all, stemming directly from what has been selforganized among the components of the system. This brief review illustrates that many social scientists are already using at least some aspects of complexity thinking. In order to understand the concerns with self-organization explored in this paper, a greater understanding of the levels of complexity is required, and so that is addressed next. 3. Levels of complexity e a property of systems Levels of complexity, as a concept, figures prominently in complexity thinking. It has been argued that all systems can be characterized by the level of complexity involved, and at least roughly organized into a hierarchy of levels (Boulding, 1956). Complexity is, in some abstract ways, similar across contexts and
sciences, and at the same time, complexity is expected to look quite different depending on the level of complexity in the system being observed (Capra, 1996; Prigogine & Stengers, 1984). By way of illustration, an early and simple example of a hierarchy of levels of complexity was offered by Kenneth Boulding (1956) in his General Systems Theory - the skeleton of science. He proposed eight levels of complexity across all of science. 1. Level of frameworks e “the geography and anatomy of the universe e the patterns of electrons around a nucleus, the patterns of atoms in a molecular formula, the arrangement of atoms in a crystal, the anatomy of the gene, the cell, the plant, the animal, the mapping of the Earth, the solar system, the astronomical universe.” p.6 2. Level of clockworks e “simple dynamic systems with predetermined necessary motions.”p.6 3. Level of the thermostat e “a controlled mechanism or cybernetic system” p.7 4. Level of the open system - “a self-maintaining structure” such as a cell. p.7 5. Level of the plant- “the genetic-societal level…typified by the plant.” p.7 6. Level of the animal e characterized by increased mobility, teleological behavior, and self-awareness.” p.7 7. Level of the human e “the individual human being considered as a system… [including] self-consciousness” p.8 8. Level of social organizations e the social systems that surround us, including culture, such as ”the vital importance for the individual man of symbolic images and behavior based on them” p.8 There are many perspectives on levels of complexity and how best to parse a unified world, but further discussion is beyond the scope of this paper. Despite the similarity of various types of systems in the world, there are differences worth noting at each level of complexity. Social science is interested in systems that are highly complex (levels 7 and 8 in Boulding's model), and that is centrally important for assessing the promise of, and challenge to, complexity thinking for psychology and social science.
4. Self-organization Mainzer (1994) traces the concept of self-organization back to the beginnings of Western philosophy as a rejoinder to reductionist accounts: From Aristotle to Goethe and Schelling, teleological selforganization and the spontaneity of life from living cells to consciously acting humans have been mentioned to demonstrate that physical reductionism is impossible. Wholeness is a primary feature of an organism which cannot be reduced to the sum of its building blocks. (p. 86) As Capra (1996) reports it in The Web of Life, “the [complexity] concept of self-organization originated in the early years of cybernetics, when scientists began to construct mathematical models representing the logic inherent in neural networks” (p. 83). As they created computer programs to model the process they found that “even though the initial state of the network was chosen at random, after a while these ordered patterns would emerge spontaneously, and it was that spontaneous emergence of order that became known as self-organization” (p.84). Capra (1996) summarizes the common features of selforganization:
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Self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations. (p. 85) Nowak and Vallacher argue that “self-organization in the self system reflects the ongoing process of integration…[by which] the self becomes differentiated… and the unit of analysis may change from single elements to clusters of elements that correspond to various aspects of the self, such as roles, domains, and self-schemata” (1998, p. 180). In the following I first give examples of simpler self-organization from material science, and then in contrast, examples of self-organization involving consciousness from published psychology reports. 4.1. Self-organization in systems with a low level of complexity A classic example of self-organization at a low level of complexity, given in many histories, is that of the emergent behavior of heated liquids (Capra, 1996, p. 87). As first discovered by physicist Henri Benard, when a thin layer of liquid is heated, “strangely ordered structures” (p. 86) appear. When the liquid is uniformly heated from below, a constant heat flux is established, moving from the bottom to the top. The liquid itself remains at rest, and the heat is transferred by conduction alone. However, when the temperature difference between the top and bottom surfaces reaches a certain critical value, the heat flux is replaced by heat convection, in which the heat is transferred by the coherent motion of large numbers of molecules. At this point a very striking ordered pattern of hexagonal (“honeycomb”) cells appear, in which hot liquid rises through the center of the cells, while the cooler liquid descends to the bottom along the cell walls. (Capra, 1996 p.86-7) In a second example of self-organization Capra describes the creation of lasers, saying: “although the laser needs to be pumped energetically from the outside to remain in a state far from equilibrium, the coordination of emissions is carried out by the laser light itself; it is a process of self-organization” (Capra, 1996, p. 91). Prigogine and Stengers (1984) describe another example of selforganization in chemical reactions, in what are referred to as chemical clocks: Suppose we have two kinds of molecules, “red” and “blue.” Because of the chaotic motion of the molecules we would expect that at a given moment we would have more red molecules, say, in the left part of a vessel. Then a bit later more blue molecules would appear, and so on. The vessel would appear to us as “violet,” with occasional irregular flashes of red or blue. However, this is not what happens with a chemical clock; here the system is all blue, then it abruptly changes its color to red, then again to blue. Because all these changes occur at regular time intervals, we have a coherent process…. To change color all at once, molecules must have a way to “communicate.” The system has to act as a whole. (p. 147-8) Three examples of self-organization - involving water, light, and chemicals interacting e all in systems with a low level of complexity. The central phenomena described in two of the three examples involve the coordination of large numbers of molecules, and in the third, light waves/particles, in bringing about a new emergent behavior. The use of the term self, however, in the phrase self-organizing refers to the system it-self. I argue that the term self
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is used metaphorically in self-organization, drawing on a similarity between the seemingly purposeful ‘behavior’ of these simple systems, in the creation of some unexpected emergent property, and the organized behavior we associate with conscious selves (the only real selves there are). I don't take any of these authors to be suggesting that an actual self, as we experience selfhood, capable of conscious choice and behavior, is created in the system developing in the teapot when I put it on to boil. So the term self, referring to the system developing in the heating water in the teapot, is metaphoric. I contrast these now with examples from studies involving humans, having higher levels of complexity. 4.2. Self-organization in systems with a high level of complexity In psychology any example of self-organization is likely to involve a human self or selves that are at least partly conscious and self-willed in ways I imagine to be significantly different than nonliving materials (Sherblom, 2012). The addition of consciousness (conscious and unconscious response) to the self-organization process is worthy of conceptual distinction e a distinction not currently being made in psychology or social science more broadly. A growing body of research in social science declares itself specifically to be using the concept self-organization in a manner consistent with complex adaptive systems thinking. In “Nonlinear Dynamics and Interpersonal Correlates of Verbal Turn-Taking Patterns in a Group Therapy Session” Pincus and Guastello (2005) analyze verbal turn-taking among six adolescent male sexoffenders. I am not critical of their method, or their conclusion that “the turn-taking patterns within a clinical family discussion were indeed characteristic with the type of complex patterning observed in self-organizing systems across a variety of scientific disciplines” (p. 638). My point is that there are a number of features that separate this self-organization from examples in material science. Some of those differences start with the research context. As the researchers describe their research process: The [participants] were led as a group to the observation room….They were told that they would be observed by the principal investigator and their group therapist from behind the one-way mirror and reminded that they were expected to do their best to reach consensus opinion on a series of therapeutic questions regarding sex-offenders. They were allowed to choose their own seats, which were arranged in a semi-circle with a radius of approximately 6 feet. (Pincus & Guastello, 2005, p. 644, p. 644) There are a number of noteworthy features of this context and process that bear on the self-organization that takes place: (a) first, this seems a highly contrived context in which to observe ‘naturally occurring’ behavior, which self-organization is usually conceived to be (Byrne & Callaghan, 2014; Prigogine & Stengers, 1984). (b) Second, it is a coercive environment: the consciousness of the participants is engaged, and meant to be influenced by reminding them that they are being watched by two authority figures, researcher & therapist, at least one of whom is a part of the justice system controlling their freedom. (c) Third, the group of boys is the system being observed, yet it is actively being influenced by the therapist with a certain outcome in mind, as they are reminded that there are expectations regarding ‘reaching consensus’ on therapeutic issues; and (d) Fourth, freedom in this system is defined in terms of being allowed to pick which nearly identical seat in the circle they may occupy while engaging in this directed public task. These dynamics are directly tied to the fact that the participants in this system are conscious selves and in a context controlled by other conscious selves. The conscious input of the facilitators of the group and the
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participants in the group into this process of self-organization makes the differences from low-complexity self-organization at least as significant as the similarities, a point further illustrated in a second example. In an analysis of the formation of rural village water cooperatives in Finland, Heino and Anttiroiko (2015) discuss selforganization in the development of these water services. The authors comment that: In practice, increasing understanding and creating a spirit conducive to change are largely effected only by a few people or sometimes even just one enthusiast who has a clear picture of the problem and a vision of what needs to be done. Thus, in typical cases, a self-organizing system seems to require a critical human component, some individual who can identify problems, inspire others, and implement the feasible actions required” (p. 306). The particularity of this consciousness, that is, this clear-eyed enthusiast who sparks the organizing of other people in the system, is one dynamic characterizing conscious self-organization. Where water molecules being heated in a kettle go through a predictable sequence resulting in a predictable organization (precisely because the self is metaphoric), in social science selforganization is far more unpredictable (precisely because while the self of the group may be metaphoric, the selves of the people involved are considerably less so). In short, in the self-organization of non-conscious systems there is a radical equality among all the participants. The molecules in the pan of heated water perform synchronized swimming, and no one takes the lead. Among conscious complex adaptive systems, on the other hand, radical inequality is often the case, as in a small number of participants having an out-sized influence on the resulting organizing. This is reminiscent of Margaret Mead's famous saying e ‘Never doubt that a small group of thoughtful, committed citizens can change the world, indeed, it's the only thing that ever has.’ This suggests that this dynamic of radical inequality of influence among participants in conscious self-organization may be wide-spread and has been noted previously. 5. Alternatives - soft complexity for the social sciences? Davis and Sumara (2006), writing on complexity and education, suggested that the social sciences do a “soft” version of complexity science. “Soft complexity science… refers to an increasingly popular movement within the social sciences toward an embrace of images and metaphors to highlight the intricate intertwining of complex phenomena” (p. 24). Davis and Sumara (2006) argue that there have been many studies of complexity that were observational and descriptive e suggesting that complexity may be explored in the social sciences in non-mathematical ways. Their examples include Rachel Carson's 1962 book Silent Spring which looked at ecology; Jane Jacobs 1961 book The death and life of great American cities; and Friedrich Engel's book The condition of the working class in England. It is not clear which of the terms in the complexity-cluster Davis and Sumara are referring to when they indicate that social scientists are using the language of complexity in a soft metaphoric fashion. But Davis and Sumara (2006) seem unbothered by the fact that social scientists are, on their reckoning, using complexity language in a wholly metaphoric way. If the concept selforganization is sometimes used in a way that is wholly metaphoric and other times more directly representative of the phenomena or process being described, confusion seems inevitable. In the following I suggest clarifying language for self-organization in
systems involving human consciousness, of which there are two broad categories. 5.1. Self-cultivating self-organization Earlier, I reviewed Boulding's (1956) model of the eight levels of complexity that encompass all of science, from galaxies, to society, to living cells. Level 7 he calls ‘the level of the human’ and this is the level of the developing inter-dependent self, or the self-system, as I have referred to it here. It has been widely noted that one thing that is characteristic of developing humans is that we are selfcultivating (Sherblom, 2012). By this I mean to emphasize that we all have some influence in our own development, in what we become sensitive to, on what we focus our attention, to what we give our time and energy, and with what we come to identify ourselves and strive to improve. We all have unique socialpsychological struggles, to which we adapt ourselves, cultivating our personality and capacity repertoire in conjunction with our family, society, and circumstances. I believe that this characteristic of being self-cultivating, self-creating, and self-defining within limits, well characterizes the self-organization in the development of the self-system. For this reason, I contend, when social scientists refer to self-organization in a developing and integrating person, they should recognize and make clear that this is self-cultivating self-organization e the self is having influence on the organization of the self. 5.2. Self-presenting self-organization Boulding's 8th level is the ‘level of the social organization’ and includes any grouping of humans. I believe self-organization at this level needs to be characterized differently than self-organization at the level of the individual person, emphasizing that people do not necessarily bring all of who they are to any group (though they are arguably all of who they are in the self-system). To state the obvious, we behave differently in different situations, at the office or at the supermarket, in church or at the sports arena, with peers or with children, with people we know well or with strangers, with another person or alone. Additionally, we behave differently even in the same grouping (system) from one time to another. Perhaps you are more reserved at first, slowly speaking up more, perhaps volunteering or assuming a leadership role over time. Perhaps we are introverted with strangers or in high pressure situations, but quite open and affable with friends and when comfortable. I suggest the self-organization that occurs among groups of people is characterized by what the people choose to bring to the interchange, including their perspectives on it. Will they bring energy and passion, or be easily deterred? Will they wait for a leader, or roll up their sleeves and jump right in? Will they cooperate and play well with others, or will they manipulate, backbite, and attempt to dominate the group? What are their ideological commitments and value orientations? It is not just a matter of understanding the culture and values of the participants generally, it is what they embody in this group at this time, what they bring to the table, so to speak. Further, beyond individual choices and dispositional embodiment, there are a range of cultural elements that come into play within social groups. The self-organizing of a group of Quakers will likely be quite different than the self-organizing of a band of armed fighters, which will vary from the self-organizing of migrant workers, which differs from the self-organization occurring in a Kindergarten class meeting. In all these examples, how participants come to the task, with their sets of values, forms of social etiquette, and habits of inter-personal interaction will influence in significant ways what is organized and how. For this reason, I suggest self-
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organization in groups of people is self-presenting self-organization. 6. Conclusion I have argued that the phenomena of self-organization is fundamentally different when occurring in a conscious medium of people and society than it is on the other side of the consciousness divide. Psychology is by its very nature concerned with a different level of complexity than material science and physics, and while acknowledging similarities is useful, distinguishing divergences is also important. I have argued that self-organization in a system involving consciousness (a person) can be distinguished from selforganization in material science by (a) being at least partly, and significantly, self-cultivating self-organization involving that person's conscious awareness and self-directed action (not inherent in the physics or chemistry involved); and (b) partly, and significantly, this self-organization is socially influenced as is the person by their culture, time period, and present challenges. As persons interact in groups, the self-organization emergent from the system of people differs from material science systems by having (c) possible radical inequality in the influence of particular participants; (d) the participants themselves are heavily influenced by culture and other value systems that vary between different groups of humans. I do not question the potential usefulness of complexity thinking, especially with regard to the systems aspect of that cluster of thought. I do, however, think it imperative that social scientists be prepared to adapt the concepts to fit our own context of inquiry e systems involving human consciousness. Acknowledgments I would like to thank Melinda Bier, Bob Coulter, John Sherblom and two anonymous reviewers for responses to earlier drafts of this paper. References Axelrod, R., & Cohen, M. D. (2000). Harnessing Complexity: Organizational implications of a scientific frontier. New York: Basic Books. Bertalanffy, L. V. (1968). General systems theory e a critical review. In W. Buckley (Ed.), Modern systems research for the behavioral scientist (pp. 11e30). Chicago:
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Aldine Publishing (1968/1962). Boulding, K. E. (1956). General systems theory- the skeleton of science. In W. Buckley (Ed.), Modern systems research for the behavioral scientist (pp. 3e10). Chicago: Aldine Publishing (1968/1956). Byrne, D., & Callaghan, G. (2014). Complexity theory and the social sciences. Abington, England: Routledge. Capra, F. (1996). The web of life: A new scientific understanding of living systems. New York: Doubleday. Davis, B., & Sumara, D. (2006). Complexity and Education: Inquiries into learning, teaching, and research. Mahwah, NJ: Lawrence Erlbaum Associates. van Geert, P. (2012). Dynamic systems. In B. Laursen, T. D. Little, & N. A. Card (Eds.), Handbook of developmental research methods (pp. 725e741). New York: Guilford Press. Gleick, J. (1987). Chaos: Making a new science. New York: Penguin. Granic, I., & Hollenstein, T. (2003). Dynamic Systems methods for models of developmental psychopathology. Development and Psychopathology, 15.3(Sept 2003), 641e669. Griffin, W. A., & Li, X. (2016). Using bayesian nonparametric hidden semi-markov models to disentangle affect processes during marital interaction. PLoS One, 11(5), e0155706. http://dx.doi.org/10.1371/journal.pone.0155706). Heino, O., & Anttiroiko, A. (2015). Inverse infrastructures: Self-organization in the water services. Water Policy, 17, 299e315. Holland, J. (1995). Hidden Order: How adaptation builds complexity. Reading, MA: Addison-Wesley. Hollenstein, T., Allen, N., & Sheeber, L. (2016). Affective patterns in triadic family interactions: Associations with adolescent depression. Development and Psychopathology, 28.1(Feb 2016), 85e96. Lichtwarck-Aschoff, A., & van Geert, P. (Dec 2004). A dynamic systems perspective on social cognition, problematic behaviour, and intervention in adolescence. European Journal of Developmental Psychology, 1(4), 399e411. http://dx.doi.org/ 10.1080/17405620444000157, 13pp. Mainzer, K. (1994). Thinking in complexity: The complex dynamics of matter, mind, and mankind. Berlin: Springer. Morin, E. (2008). On complexity. Creeskill, NJ: Hampton Press Inc (Translated by Robin Postel). Murphy, N. (1997). Reductionism: How did we fall into it and can we emerge from it? In N. Murphy, & W. R. Stoeger (Eds.), Evolution and emergence (pp. 19e39). Oxford University Press. Nowak, A., & Vallacher, R. R. (1998). Dynamical social psychology. New York: Guilford Press. Pincus, D., & Guastello, S. J. (2005). Nonlinear dynamics and interpersonal correlates of verbal turn-taking patterns in group therapy session. Small Group Research, 36, 635e677. Prigogine, I., & Stengers, I. (1984). Order out of chaos. New York: Bantam. Sawyer, R. K. (2005). Social Emergence: Societies as complex systems. Cambridge University Press. Sherblom, S. A. (2012). What develops in moral development? A model of moral sensibility. Journal of Moral Education, 41(1), 117e142. Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT Press. Waldrop, M. M. (1992). Complexity: The emerging science at the edge of order and chaos. New York: Touchstone.
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New Ideas in Psychology journal homepage: www.elsevier.com/locate/newideapsych
Complexity-thinking and social science: Self-organization involving human consciousness Stephen A. Sherblom* Lindenwood University, 209S. Kingshighway, St. Charles, MO 63301, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 6 February 2016 Received in revised form 1 January 2017 Accepted 16 March 2017
Complexity-thinking refers to a cluster of concepts popularized in several branches of science, primarily in the physical sciences but increasingly in the social sciences. There is reason to be cautious regarding how the concepts are used across disciplines and branches of science. This paper discusses self-organization in dynamic systems, tracing its roots in social science and critiquing current usage of the term with regard to systems involving consciousness - humans and groups of humans. A brief sketch of the levels of complexity sets the groundwork for understanding the critique of self-organization to follow. I argue that consciousness fundamentally changes the terms of discussion in self-organization by adding a self/selves that is not equivalent to the system as a whole, but which directly influences what is organized, how, and toward what end. Self-organization in complex adaptive systems involving consciousness should be distinguished as self-cultivating self-organization and self-presenting self-organization. © 2017 Published by Elsevier Ltd.
Keywords: Self-organization Complexity-thinking Self-cultivating self-organization Self-presenting self-organization
1. Introduction Several books appeared in the 1980s and 1990s that popularized a group of concepts in science: specifically the concepts complexity (Holland, 1995; Waldrop, 1992), chaos (Gleick, 1987), self-organization, emergence (Nowak & Vallacher, 1998; Prigogine & Stengers, 1984) and dynamic systems (Capra, 1996; Thelen & Smith, 1994). While these concepts have different disciplinary histories, they are frequently grouped together, often under the rubric complexity thinking (Capra, 1996). These complexity concepts are now widely used in many branches of science, and increasing are being applied in psychology, education, nursing, and other social sciences. There is reason to be cautious regarding how these concepts are used, however, especially across the levels of complexity that separate material science and social science. On the other hand, insights of complexity science may hold great promise for a more adequate social scientific perspective if we can avoid the dangers of uncritically using concepts developed in material science to conceptualize living systems such as persons and groups of people. This paper begins by grappling with some of the terminology of complexity thinking, noting that some terms, and ‘systems
* Permanent address: 500 West Kirkham Ave, Webster Groves, MO 63119, USA. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.newideapsych.2017.03.003 0732-118X/© 2017 Published by Elsevier Ltd.
thinking’ in general, have long been used in social science. A brief sketch of the levels of complexity sets the groundwork for understanding the critique of self-organization to follow. The critique, in short, is that there is a vital difference between self-organization in systems that involve consciousness (those of interest to psychologists, educators, and social scientists generally) and selforganization in systems that are not conscious. If this is the case, several implications follow, including changing the way we speak about self-organization in the social sciences to reflect the role of consciousness in that self-organization. 1.1. The complexity cluster Some of the terms in the complexity cluster can be found historically in both social science and material science (including physics), while others, such as chaos and complexity were developed and are used almost exclusively in material science. I will focus on dynamic systems and self-organization e each of which grew at least partly out of studies in nonlinear change in the organization and growth of living things - living systems. Accounts of the development of complexity thinking as a whole suggest that this perspective has coalesced since the 1930s through insights in a variety of fields including physics, biology, psychology, ecology, and material science (Capra, 1996; Gleick, 1987). As noted in the following brief review, these terms have been active in social science discussion for longer than that, and hence, the full story of
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social scientists' contribution to dynamic systems has yet to be told. The scientists who formulated the science (Bertalanffy, 1968; Boulding, 1956; Holland, 1995; Prigogine & Stengers, 1984); the writers who popularized the ideas (Capra, 1996; Gleick, 1987; Waldrop, 1992); and those in the social sciences who have taken up aspects of this approach (Thelen & Smith, 1994; van Geert, 2012) all speak of complexity thinking as a universalizable approach to non-linear change. It is useful, they argue, for describing certain types of complex systems wherever they are found. This includes non-linear behavior in micro-particles, in cells, in organisms, including humans, in ecologies and societies, and in the universe of planets and stars (Capra, 1996; Waldrop, 1992). While I am not challenging that claim of universal relevance, I do argue that selforganization is sufficiently different as a process when dealing with human consciousness that some way of designating that distinction is intellectually necessary in psychology and social science more broadly.
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wide array of intellectuals, including Darwin, Marx, Parsons, Durkheim, and Weber, illustrating something of the role social science has played already in the development of this aspect of complexity thinking. They note: “systems theories [and] explanations with an evolutionary character have emerged alongside, rather than deriving from, natural science and they continue to play an important role in much social theory to the present day” (Byrne & Callaghan, 2014, p. 88). In A dynamic systems approach to the development of cognition and action, (1994) Thelen and Smith argue that dynamic systems and related concepts are the appropriate way to think about and describe the complexities of human development. In our approach to fundamental questions of mental life, we invoke principles of great generality. These are principles of nonlinear dynamic systems, and they concern problems of emergent order and complexity: how structure and patterns arise from the cooperation of many individual parts. (Thelen & Smith, 1994, p. xiii)
2. Dynamic systems, complex systems, and systems thinking Of all the concepts in the complexity thinking cluster, systems thinking and dynamic systems terminology are perhaps the most accessible to social scientists, having a long history in psychology. Capra (1996) reports that “the main characteristics of systems thinking emerged simultaneously in several disciplines” (p.17) during the first half of the 20th century, especially biology which “emphasized the view of living organisms as integrated wholes,” Gestalt psychology, and ecology (p. 17e18). Byrne and Callaghan (2014) argue that what makes complexity thinking a universalizable explanatory frame is that it speaks in terms of complex systems, and systems that can be described as complex exist in many scientific disciplines. “When we talk about complexity we are talking about systems. Complexity is a property of systems” Byrne and Callaghan note (2014 p. 3). Morin (2008) argues that: The scope of system theory is… quasi-universal, because, in a certain sense, all known reality, from the molecule to the cell to an organism to a society, can be conceived of as systems. That is to say, they can be conceived as the interaction of different elements” (Morin, 2008 p. 9 p. 9) Murphy (1997) notes that systems thinking emphasizes process: One has to give up the traditional Western philosophical bias in favor of things, with their intrinsic properties, for an appreciation of processes and relations; the components of systems are not things, but processes. (p. 32 emphasis added) In their book Dynamical Social Psychology (1998), Nowak and Vallacher argue that dynamic systems thinking is congruent with many important traditions in social science: The subject matter of social psychology is inherently dynamic. It is hard to conceive of action without movement, judgment without a flow of thoughts, emotion without volatility, social interaction without an ebb and flow of gestures and words, or social relation without ongoing evolution of roles and sentiment. (Nowak & Vallacher, 1998 p. vii) Further, they note that “the nature of human dynamism provided a focal point in the earliest attempts to characterize experience in interpersonal contexts, as reflected in the seminal work of such figures as James, Mead, Cooley, Lewin, and Asch” (Nowak & Vallacher, 1998 p. vii). Byrne and Callaghan (2014) trace systems thinking back to a
The authors argue that this approach allows us to ask questions we have not previously been equipped to address, such as: “What are the organic and environmental factors that engender change?” and “How can we begin to untangle the complex web of causality when real infants live and develop in a world filled with people, things, and events in continuous interaction?” (p. xiii). Like other systems that have been studied, such as the development of weather patterns or growth patterns of species in a geographic region, the development of cognition and action are not preprogrammed, Thelen and Smith note (1994). Rather, cognition and action emerge from a complex interaction in development, and in interaction with the environment, itself best conceptualized as a complex system. Thelen and Smith say in summary: “It is a science for systems with a history, systems that change over time, where novelty can be created, where the end-state is not coded anywhere, and where behavior at the macrolevel can, in principle, be reconciled with behavior at the microlevel” (1994, p. 49). The developing systems Thelen and Smith described include aspects of learning to walk, and learning to think. Additionally, Nowak and Vallacher (1998) argue that a systems perspective will help synthesize the atomized social psychology of the past hundred years: For the better part of the 20th century, social psychological research has attempted to isolate causal mechanisms with respect to distinct aspects of interpersonal experience. The methods spawned within this approach have been quite successful in identifying the key features of human thought and behavior. With the advent of the dynamical approach, it is now possible for investigators to assemble sets of such mechanisms into coherent systems. (p. viii) Waldrop (1992) discusses similarities across complex systems as diverse as: the political entity the Soviet Union, the New York Stock Exchange, ecosystems, birth rates among rural poor families, the creation of living cells from ‘chemical soup’, natural selection and evolution, and the human mind. He argues that every one of these systems …is complex in the sense that a great many independent agents are interacting with each other in a great many ways. Think of the quadrillions of chemically reacting proteins, lipids, and nucleic acids that make up a living cell, or the billions of interconnected neurons that make up the brain, or the millions of
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mutually interdependent individuals who make up a human society. (Waldrop, 1992 p.11 p.11) He concludes: “In every case, groups of agents seeking mutual accommodation and self-consistency somehow manage to transcend themselves, acquiring collective properties such as life, thought, and purpose that they might never have possessed individually” (Waldrop, 1992, p. 11). In Harnessing Complexity, Axelrod and Cohen (2000) set out the concepts of complexity thinking as they might be applied to any complex system, including those studied in social science. By this they meant to include things of interest to managers, policy makers, historians, and other kinds of change agent. Axelrod and Cohen include a range of examples of complex systems usefully understood this way (p.3): (i) a member of a work team wants to elicit cooperation from coworkers; (ii) an impoverished woman in Bangladesh wants to borrow a little money to rent a stall at the local market; (iii) a computer program scans the Internet for helpful resources; (iv) the United States wants to foster among nations goals that the U.S. cannot impose by force. All of these contexts and processes, they argue, can be described with the common language of complexity. Granic and Hollenstein (2003) have articulated “dynamic systems methods appropriate for testing systems-based models in developmental psychopathology” (p. 641) such as in family therapy or couples counseling. Lichtwarck-Aschoff and van Geert (2004) developed a dynamic systems perspective on social cognition and problem behavior. The authors utilized complexity language and techniques of attractor states and topography modeling to discuss and describe problem behavior as a system. They argue that “the attractor metaphor helps us explain the interindividual variability in intervention effects” (p. 406). Hollenstein and colleagues have researched affect during parent-adolescent child interactions “using state space grid analysis” to describe the evolving emotional tenor of the interchange on the part of both parent(s) and children (Hollenstein, Allen, & Sheeber, 2016). Writing in the area of marital interaction research and computer modeling, Griffin and Li (2016) attempt to describe the dynamics of a couple or a family in terms of self-organization. Their attempt to model the emotional flow of relational discourse is in order to support the emerging field of affective computing, which will help realize “realistic robots and avatars” (p.641). Lastly, in Social Emergence: Societies as complex systems, Sawyer (2005) explored the concept of emergence as it has long been used in social science. Though now commonly included as a concept in complexity thinking, Sawyer points out that emergence has a long and varied history in the disciplines of psychology and sociology with discussion of emergence dating back to the mid-nineteenth century (p.27). Emergence is intimately connected to selforganization in that what emerges as a new property in the system is, after all, stemming directly from what has been selforganized among the components of the system. This brief review illustrates that many social scientists are already using at least some aspects of complexity thinking. In order to understand the concerns with self-organization explored in this paper, a greater understanding of the levels of complexity is required, and so that is addressed next. 3. Levels of complexity e a property of systems Levels of complexity, as a concept, figures prominently in complexity thinking. It has been argued that all systems can be characterized by the level of complexity involved, and at least roughly organized into a hierarchy of levels (Boulding, 1956). Complexity is, in some abstract ways, similar across contexts and
sciences, and at the same time, complexity is expected to look quite different depending on the level of complexity in the system being observed (Capra, 1996; Prigogine & Stengers, 1984). By way of illustration, an early and simple example of a hierarchy of levels of complexity was offered by Kenneth Boulding (1956) in his General Systems Theory - the skeleton of science. He proposed eight levels of complexity across all of science. 1. Level of frameworks e “the geography and anatomy of the universe e the patterns of electrons around a nucleus, the patterns of atoms in a molecular formula, the arrangement of atoms in a crystal, the anatomy of the gene, the cell, the plant, the animal, the mapping of the Earth, the solar system, the astronomical universe.” p.6 2. Level of clockworks e “simple dynamic systems with predetermined necessary motions.”p.6 3. Level of the thermostat e “a controlled mechanism or cybernetic system” p.7 4. Level of the open system - “a self-maintaining structure” such as a cell. p.7 5. Level of the plant- “the genetic-societal level…typified by the plant.” p.7 6. Level of the animal e characterized by increased mobility, teleological behavior, and self-awareness.” p.7 7. Level of the human e “the individual human being considered as a system… [including] self-consciousness” p.8 8. Level of social organizations e the social systems that surround us, including culture, such as ”the vital importance for the individual man of symbolic images and behavior based on them” p.8 There are many perspectives on levels of complexity and how best to parse a unified world, but further discussion is beyond the scope of this paper. Despite the similarity of various types of systems in the world, there are differences worth noting at each level of complexity. Social science is interested in systems that are highly complex (levels 7 and 8 in Boulding's model), and that is centrally important for assessing the promise of, and challenge to, complexity thinking for psychology and social science.
4. Self-organization Mainzer (1994) traces the concept of self-organization back to the beginnings of Western philosophy as a rejoinder to reductionist accounts: From Aristotle to Goethe and Schelling, teleological selforganization and the spontaneity of life from living cells to consciously acting humans have been mentioned to demonstrate that physical reductionism is impossible. Wholeness is a primary feature of an organism which cannot be reduced to the sum of its building blocks. (p. 86) As Capra (1996) reports it in The Web of Life, “the [complexity] concept of self-organization originated in the early years of cybernetics, when scientists began to construct mathematical models representing the logic inherent in neural networks” (p. 83). As they created computer programs to model the process they found that “even though the initial state of the network was chosen at random, after a while these ordered patterns would emerge spontaneously, and it was that spontaneous emergence of order that became known as self-organization” (p.84). Capra (1996) summarizes the common features of selforganization:
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Self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations. (p. 85) Nowak and Vallacher argue that “self-organization in the self system reflects the ongoing process of integration…[by which] the self becomes differentiated… and the unit of analysis may change from single elements to clusters of elements that correspond to various aspects of the self, such as roles, domains, and self-schemata” (1998, p. 180). In the following I first give examples of simpler self-organization from material science, and then in contrast, examples of self-organization involving consciousness from published psychology reports. 4.1. Self-organization in systems with a low level of complexity A classic example of self-organization at a low level of complexity, given in many histories, is that of the emergent behavior of heated liquids (Capra, 1996, p. 87). As first discovered by physicist Henri Benard, when a thin layer of liquid is heated, “strangely ordered structures” (p. 86) appear. When the liquid is uniformly heated from below, a constant heat flux is established, moving from the bottom to the top. The liquid itself remains at rest, and the heat is transferred by conduction alone. However, when the temperature difference between the top and bottom surfaces reaches a certain critical value, the heat flux is replaced by heat convection, in which the heat is transferred by the coherent motion of large numbers of molecules. At this point a very striking ordered pattern of hexagonal (“honeycomb”) cells appear, in which hot liquid rises through the center of the cells, while the cooler liquid descends to the bottom along the cell walls. (Capra, 1996 p.86-7) In a second example of self-organization Capra describes the creation of lasers, saying: “although the laser needs to be pumped energetically from the outside to remain in a state far from equilibrium, the coordination of emissions is carried out by the laser light itself; it is a process of self-organization” (Capra, 1996, p. 91). Prigogine and Stengers (1984) describe another example of selforganization in chemical reactions, in what are referred to as chemical clocks: Suppose we have two kinds of molecules, “red” and “blue.” Because of the chaotic motion of the molecules we would expect that at a given moment we would have more red molecules, say, in the left part of a vessel. Then a bit later more blue molecules would appear, and so on. The vessel would appear to us as “violet,” with occasional irregular flashes of red or blue. However, this is not what happens with a chemical clock; here the system is all blue, then it abruptly changes its color to red, then again to blue. Because all these changes occur at regular time intervals, we have a coherent process…. To change color all at once, molecules must have a way to “communicate.” The system has to act as a whole. (p. 147-8) Three examples of self-organization - involving water, light, and chemicals interacting e all in systems with a low level of complexity. The central phenomena described in two of the three examples involve the coordination of large numbers of molecules, and in the third, light waves/particles, in bringing about a new emergent behavior. The use of the term self, however, in the phrase self-organizing refers to the system it-self. I argue that the term self
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is used metaphorically in self-organization, drawing on a similarity between the seemingly purposeful ‘behavior’ of these simple systems, in the creation of some unexpected emergent property, and the organized behavior we associate with conscious selves (the only real selves there are). I don't take any of these authors to be suggesting that an actual self, as we experience selfhood, capable of conscious choice and behavior, is created in the system developing in the teapot when I put it on to boil. So the term self, referring to the system developing in the heating water in the teapot, is metaphoric. I contrast these now with examples from studies involving humans, having higher levels of complexity. 4.2. Self-organization in systems with a high level of complexity In psychology any example of self-organization is likely to involve a human self or selves that are at least partly conscious and self-willed in ways I imagine to be significantly different than nonliving materials (Sherblom, 2012). The addition of consciousness (conscious and unconscious response) to the self-organization process is worthy of conceptual distinction e a distinction not currently being made in psychology or social science more broadly. A growing body of research in social science declares itself specifically to be using the concept self-organization in a manner consistent with complex adaptive systems thinking. In “Nonlinear Dynamics and Interpersonal Correlates of Verbal Turn-Taking Patterns in a Group Therapy Session” Pincus and Guastello (2005) analyze verbal turn-taking among six adolescent male sexoffenders. I am not critical of their method, or their conclusion that “the turn-taking patterns within a clinical family discussion were indeed characteristic with the type of complex patterning observed in self-organizing systems across a variety of scientific disciplines” (p. 638). My point is that there are a number of features that separate this self-organization from examples in material science. Some of those differences start with the research context. As the researchers describe their research process: The [participants] were led as a group to the observation room….They were told that they would be observed by the principal investigator and their group therapist from behind the one-way mirror and reminded that they were expected to do their best to reach consensus opinion on a series of therapeutic questions regarding sex-offenders. They were allowed to choose their own seats, which were arranged in a semi-circle with a radius of approximately 6 feet. (Pincus & Guastello, 2005, p. 644, p. 644) There are a number of noteworthy features of this context and process that bear on the self-organization that takes place: (a) first, this seems a highly contrived context in which to observe ‘naturally occurring’ behavior, which self-organization is usually conceived to be (Byrne & Callaghan, 2014; Prigogine & Stengers, 1984). (b) Second, it is a coercive environment: the consciousness of the participants is engaged, and meant to be influenced by reminding them that they are being watched by two authority figures, researcher & therapist, at least one of whom is a part of the justice system controlling their freedom. (c) Third, the group of boys is the system being observed, yet it is actively being influenced by the therapist with a certain outcome in mind, as they are reminded that there are expectations regarding ‘reaching consensus’ on therapeutic issues; and (d) Fourth, freedom in this system is defined in terms of being allowed to pick which nearly identical seat in the circle they may occupy while engaging in this directed public task. These dynamics are directly tied to the fact that the participants in this system are conscious selves and in a context controlled by other conscious selves. The conscious input of the facilitators of the group and the
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participants in the group into this process of self-organization makes the differences from low-complexity self-organization at least as significant as the similarities, a point further illustrated in a second example. In an analysis of the formation of rural village water cooperatives in Finland, Heino and Anttiroiko (2015) discuss selforganization in the development of these water services. The authors comment that: In practice, increasing understanding and creating a spirit conducive to change are largely effected only by a few people or sometimes even just one enthusiast who has a clear picture of the problem and a vision of what needs to be done. Thus, in typical cases, a self-organizing system seems to require a critical human component, some individual who can identify problems, inspire others, and implement the feasible actions required” (p. 306). The particularity of this consciousness, that is, this clear-eyed enthusiast who sparks the organizing of other people in the system, is one dynamic characterizing conscious self-organization. Where water molecules being heated in a kettle go through a predictable sequence resulting in a predictable organization (precisely because the self is metaphoric), in social science selforganization is far more unpredictable (precisely because while the self of the group may be metaphoric, the selves of the people involved are considerably less so). In short, in the self-organization of non-conscious systems there is a radical equality among all the participants. The molecules in the pan of heated water perform synchronized swimming, and no one takes the lead. Among conscious complex adaptive systems, on the other hand, radical inequality is often the case, as in a small number of participants having an out-sized influence on the resulting organizing. This is reminiscent of Margaret Mead's famous saying e ‘Never doubt that a small group of thoughtful, committed citizens can change the world, indeed, it's the only thing that ever has.’ This suggests that this dynamic of radical inequality of influence among participants in conscious self-organization may be wide-spread and has been noted previously. 5. Alternatives - soft complexity for the social sciences? Davis and Sumara (2006), writing on complexity and education, suggested that the social sciences do a “soft” version of complexity science. “Soft complexity science… refers to an increasingly popular movement within the social sciences toward an embrace of images and metaphors to highlight the intricate intertwining of complex phenomena” (p. 24). Davis and Sumara (2006) argue that there have been many studies of complexity that were observational and descriptive e suggesting that complexity may be explored in the social sciences in non-mathematical ways. Their examples include Rachel Carson's 1962 book Silent Spring which looked at ecology; Jane Jacobs 1961 book The death and life of great American cities; and Friedrich Engel's book The condition of the working class in England. It is not clear which of the terms in the complexity-cluster Davis and Sumara are referring to when they indicate that social scientists are using the language of complexity in a soft metaphoric fashion. But Davis and Sumara (2006) seem unbothered by the fact that social scientists are, on their reckoning, using complexity language in a wholly metaphoric way. If the concept selforganization is sometimes used in a way that is wholly metaphoric and other times more directly representative of the phenomena or process being described, confusion seems inevitable. In the following I suggest clarifying language for self-organization in
systems involving human consciousness, of which there are two broad categories. 5.1. Self-cultivating self-organization Earlier, I reviewed Boulding's (1956) model of the eight levels of complexity that encompass all of science, from galaxies, to society, to living cells. Level 7 he calls ‘the level of the human’ and this is the level of the developing inter-dependent self, or the self-system, as I have referred to it here. It has been widely noted that one thing that is characteristic of developing humans is that we are selfcultivating (Sherblom, 2012). By this I mean to emphasize that we all have some influence in our own development, in what we become sensitive to, on what we focus our attention, to what we give our time and energy, and with what we come to identify ourselves and strive to improve. We all have unique socialpsychological struggles, to which we adapt ourselves, cultivating our personality and capacity repertoire in conjunction with our family, society, and circumstances. I believe that this characteristic of being self-cultivating, self-creating, and self-defining within limits, well characterizes the self-organization in the development of the self-system. For this reason, I contend, when social scientists refer to self-organization in a developing and integrating person, they should recognize and make clear that this is self-cultivating self-organization e the self is having influence on the organization of the self. 5.2. Self-presenting self-organization Boulding's 8th level is the ‘level of the social organization’ and includes any grouping of humans. I believe self-organization at this level needs to be characterized differently than self-organization at the level of the individual person, emphasizing that people do not necessarily bring all of who they are to any group (though they are arguably all of who they are in the self-system). To state the obvious, we behave differently in different situations, at the office or at the supermarket, in church or at the sports arena, with peers or with children, with people we know well or with strangers, with another person or alone. Additionally, we behave differently even in the same grouping (system) from one time to another. Perhaps you are more reserved at first, slowly speaking up more, perhaps volunteering or assuming a leadership role over time. Perhaps we are introverted with strangers or in high pressure situations, but quite open and affable with friends and when comfortable. I suggest the self-organization that occurs among groups of people is characterized by what the people choose to bring to the interchange, including their perspectives on it. Will they bring energy and passion, or be easily deterred? Will they wait for a leader, or roll up their sleeves and jump right in? Will they cooperate and play well with others, or will they manipulate, backbite, and attempt to dominate the group? What are their ideological commitments and value orientations? It is not just a matter of understanding the culture and values of the participants generally, it is what they embody in this group at this time, what they bring to the table, so to speak. Further, beyond individual choices and dispositional embodiment, there are a range of cultural elements that come into play within social groups. The self-organizing of a group of Quakers will likely be quite different than the self-organizing of a band of armed fighters, which will vary from the self-organizing of migrant workers, which differs from the self-organization occurring in a Kindergarten class meeting. In all these examples, how participants come to the task, with their sets of values, forms of social etiquette, and habits of inter-personal interaction will influence in significant ways what is organized and how. For this reason, I suggest self-
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organization in groups of people is self-presenting self-organization. 6. Conclusion I have argued that the phenomena of self-organization is fundamentally different when occurring in a conscious medium of people and society than it is on the other side of the consciousness divide. Psychology is by its very nature concerned with a different level of complexity than material science and physics, and while acknowledging similarities is useful, distinguishing divergences is also important. I have argued that self-organization in a system involving consciousness (a person) can be distinguished from selforganization in material science by (a) being at least partly, and significantly, self-cultivating self-organization involving that person's conscious awareness and self-directed action (not inherent in the physics or chemistry involved); and (b) partly, and significantly, this self-organization is socially influenced as is the person by their culture, time period, and present challenges. As persons interact in groups, the self-organization emergent from the system of people differs from material science systems by having (c) possible radical inequality in the influence of particular participants; (d) the participants themselves are heavily influenced by culture and other value systems that vary between different groups of humans. I do not question the potential usefulness of complexity thinking, especially with regard to the systems aspect of that cluster of thought. I do, however, think it imperative that social scientists be prepared to adapt the concepts to fit our own context of inquiry e systems involving human consciousness. Acknowledgments I would like to thank Melinda Bier, Bob Coulter, John Sherblom and two anonymous reviewers for responses to earlier drafts of this paper. References Axelrod, R., & Cohen, M. D. (2000). Harnessing Complexity: Organizational implications of a scientific frontier. New York: Basic Books. Bertalanffy, L. V. (1968). General systems theory e a critical review. In W. Buckley (Ed.), Modern systems research for the behavioral scientist (pp. 11e30). Chicago:
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