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University College Dublin, Innovation Research Unit
Though the book is a little belated with respect to the project end and most of its contents has been already published elsewhere (this relates especially to the chapters concerning ABMs or any type of social simulation, which would be of particular interest to a JASSS readership), the compilation is interesting to read, because the editors make a valuable attempt to draw these two thematic streams - social change and innovation - closer together by co-authoring many chapters and trying to relate the two issues. However, this proves to be quite difficult, because the first stream uses the term "innovation" just in the sense of anything new, covering all kinds of developmental features such as "innovation in the traits that makes up an organism" where the new occurs as "innovation in the form of mutation in the genetic material transmitted" (p. 43), or innovation as a change in conceptual systems guiding human behaviour where "innovation can occur at the level of structure and/or in behavioural instantiations of the conceptual system" (page 55). The "innovation innovation" (p. 43ff) is considered as the "crucial stage in the evolution of human societies [...] (which) concerns the beginnings of information processing by (small-scale) societies about societies" (p. 85). These issues are usually called "change" by their disciplinary theoretical frameworks and do not equate to an understanding of innovation. As used in the second thematic stream of the book, innovation is "not just novelty, but also a transformation in the structure of the agent-artifact space, which unleashes a cascade of further changes. The innovation may involve the introduction of a new artifact, but also a change in relationships with other agents, or even a new interpretation of an existing artifact" (p. 365).
According to the editors, one of the conclusions of the ISCOM project was "that innovation and invention have been, in a sense, among the stepchildren of modern research, whether in the social sciences or in the humanities" (pp.1f). Certainly from the point of view of today's innovation research, innovation policy and innovation management, innovation in the sense of the second thematic stream of the book does indeed need and deserve much more research efforts than have hitherto been invested. However, concerning the understanding of "innovation" promoted by the first stream of the book, social sciences disciplines, especially sociology, have provided a profound body of work on social change. The editors' statement seems rather to serve the task of creating an "empty page" in science to be filled with their own entries about topics with long-time debates in the social sciences such as history vs. evolution, determinism vs. voluntarism, causal vs. functional approaches, realism vs. constructivism etc. (an exception is the sound discussion in chapter 4 by Andrea Ginzburg). To put aside what is there and start afresh could indeed lead to originality and interesting ideas. None of the editors seems to be from an economics or sociology background, but perhaps this fresh approach is exactly what can be expected from complexity science.
Therefore, the basic surprise in reading the book is how close the ideas and sometimes consciously speculative considerations (see chapter 3 by Sander van der Leuuw, David Lane and Dwight Read) come to the existing large body of theoretical and empirical work in the social sciences: in Sociology about social change; in Science, Technology and Innovation Studies about the interactive relationship between actors and technology/artefacts, and; in evolutionary Innovation Economics about innovation-related industry and market dynamics. It would have been most interesting to see what the framework developed in the book would have made of this body of evidence and empirically-grounded theory, if they had discussed it alongside their own chosen individual concepts and terminology. As it is, despite some interesting nuggets in this book, the big potential for synergies and mutual learning between complexity science and sociology remains unfulfilled.
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© Copyright Journal of Artificial Societies and Social Simulation, 2009