Reviewed by
Paul Smaldino
Johns Hopkins University
In their new book, Complex Human Dynamics, editors Nowak, Winkowska-Nowak, and Brée attempt to bridge the gap of understanding between the social and mathematical sciences. This is a daunting but extremely worthwhile ambition. Successful social scientists of the future will need to incorporate perspectives and methods from dynamical systems theory and complexity theory, including concepts such as attractors, dynamic feedback, and synchrony, and methodologies such as coupled differential equations and agent-based modelling. Meanwhile, scientists with a more mathematical background wishing to study social problems will need to fold their research into traditional social science. Rather than being a pedagogical textbook, the book’s 13 chapters are a hodgepodge of conceptual reviews, empirical studies, and theoretical models that form a collage of ideas from psychology and group dynamics, unified by a determination on the part of each of the chapters’ authors to adopt a "dynamical systems theory" perspective. Each author is an affiliate of the Centre of Complex Systems of the Institute of Social Studies, at the University of Warsaw. The chapter topics vary widely, ranging through neural connectivity, self-perception, novelty recognition, commitment in sports, conflict, multicultural integration, social change, interpersonal coordination, trust, and group organization.
The book’s stated goals are twofold: first, to introduce psychologists to applications of dynamical systems theory in order to convince them of the wisdom of its adoption, and second, to introduce more mathematical scientists to relevant theories in the social sciences and to highlight areas in which the application of formal methods may be successful. The method by which the authors attempt to achieve these goals is by providing examples of dynamical systems theory as it relates to social and psychological phenomena. Unfortunately, the attempt largely fails. Tragically, many of the chapters are poorly written and have the feel of graduate-level term papers in which the students are attempting to please a professor with an agenda - in this case, the editors' presentation of "dynamical social psychology," which is introduced in the opening chapter and repeated throughout the book - falling victim to sweeping overgeneralizations, ambiguous phrasing, and insufficient citation. Many of the chapters pay lip service to dynamical systems theory, but don’t elaborate. For example, the concept of the attractor is mentioned often, but is rarely employed as anything other than metaphor. Human cognitive and social systems are surely dynamical, but this fact alone does not necessitate a referral to the rather specific language of dynamical systems theory, and such a linkage often feels rather forced. Several of the book’s chapters concern interesting ideas, but ultimately are slipshod reviews of a rather scattered assortment of topics: e.g., functional connectivity in the brain (chapter 2), novelty recognition (chapter 4), social entrepreneurship (chapter 9), and the social psychology of trust as measured by the Trust Game paradigm (chapter 11).
Tackling a fascinating and important topic, chapter 12, titled "Group as a unit of analysis," by Karolina Lisiecka, attempts to discuss the complexity of group organization and the emergent properties which make a group’s behaviour irreducible to the sum of the behaviours of its constituents. Unfortunately, the chapter meanders through fragments of philosophy, empirical data, and methodology without presenting any concrete thesis or recommendation. This chapter was for me the most disappointing, as I feel this is a crucial and understudied area for researchers across the social sciences (e.g., Smaldino 2013).
The book is published by Springer, which thankfully makes its chapters available to those with an academic subscription. For those readers, I highlight three chapters which stand out in contrast to the rest of the book, and constitute interesting and potentially important contributions. Although none of these fulfil the book’s lofty goals, they may nonetheless be of interest to researchers studying related topics. Chapter 5, "The dynamics of patterns of commitments in sports," by Dariusz Parzelski and Andrzej Nowak, presents a novel study that introduces a survey method based on dynamic body mechanics, which is less ambiguous and more predictive than traditional verbal surveys. Chapter 8, "A dynamic approach to multicultural integration," by Wouter E. de Raad, presents an agent-based model of integration and discrimination between minority and majority ethnic groups. The analysis and discussion are preliminary, but appear promising, and illustrate a real application of complex systems methodologies to the study of social phenomena. Chapter 10, "Interpersonal fluency: Toward a model of coordination and affect in social relations," by Wojciech Kulesza, Robin R. Vallacher, and Andrzej Nowak, presents two computer-assisted experiments that investigate relationships between interpersonal coordination, goals, and affect. The work does not specifically utilize dynamical systems theory, but it does address important questions in the psychology of group dynamics.
Overall, I am not really sure who would benefit from this book in its entirety. Mathematical scientists familiar with dynamical systems can get a much better overview of social science elsewhere. For example, Aronson’s (2004) The Social Animal is an excellent overview of social psychology. I also don’t see this as being a particularly useful resource for social scientists. Many dynamical concepts are presented opaquely. A much better reference has been provided previously by the book’s first editor and one of his major co-authors in their book Dynamical Social Psychology (Nowak and Vallacher 1998). In addition, Mitchell’s (2009) book Complexity: A Guided Tour, provides an excellent (and largely math-free) primer on important concepts and methodologies in complex systems research, much of which could be useful to social scientists.
I understand that Complex Human Dynamics was set up to give examples of social science applications of dynamical systems theory, but I do not think this was adequately accomplished. I am also somewhat sceptical of the goal in general. The systems studied by social and behavioural scientists are indeed dynamical, and almost universally involve processes such as feedback, coupling, and attraction. I am therefore completely on board with the editors’ hope that a familiarity with the concepts and formalisms of dynamical systems theory spreads more widely among social and behavioural scientists. Because of this wide applicability, however, dynamical systems theory may be too weak a thread to connect the wide range of themes encompassed by "social science."
ReferencesMITCHELL, M. (2009). Complexity: A Guided Tour. Oxford: Oxford University Press.
NOWAK, A. and Vallacher, R. R. (1998). Dynamical Social Psychology. New York: Guilford.
SMALDINO, P. E. (2013). The cultural evolution of emergent group-level traits. Behavioral and Brain Sciences, in press.
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