Reviewed by
Thomas Fent
Vienna Institute of Demography, Austrian Academy of Sciences
This is far from being a crazy idea. As a matter of fact, complexity thinking has become increasingly relevant in economics as the liberalisation of markets and technological progress simplifying and multiplying buyer-seller interactions boosted the importance of local interactions. This dramatically reduced the power of market regulations and of all those mechanisms which are planned from a top-down macro perspective. At the same time, the growing participation of local actors, interest groups, non-governmental organisations, and the likes in current political debates makes complexity thinking an essential tool for public policy.
That said, the aim of this book is to provide an introduction to complexity thinking and illustrate its relevance for planning and public policy. The first chapters introduce the main concepts of complexity exemplified by complex systems in the physical and biotic world, but they quickly sketch overlapping features of natural and social systems. The authors present complexity as an intermediate and balanced system state between order and disorder. The paradigm of order is characterised by deterministic relationships of cause and effect, e.g., relationships which can be fully understood by observing the behaviour of system parts. This means the chance of achieving perfect predictions of outcomes given relevant inputs, as well as that of understanding time-space processes. On the other hand, disorder is the reign of not fully understood phenomena. The message of this book is that complexity implies that the accumulation of knowledge about a certain system does not inevitably result into a perfect prediction of it. Therefore, complex physical systems are analysed that exhibit the features of orderly systems mentioned above, but that can violate these same features under certain conditions. While fluid dynamics, Boolean networks, and weather patterns are examples of this in physics, animal interaction and evolution present the case of biotic complex systems.
Once advanced towards key aspects of complex systems in physical and biotic domains, the book aims to translate these aspects into the field of conscious complexity. The authors' position is that the capability of providing a sound theoretical framework on this depends upon a departure from the foundations of both orderly (modernist) and disorderly (post-modernist) social science and public policy. Complexity is presented as a synthesis that can cross the bridge between these two opponents. Norms, values, and language constitute examples of conscious complexity.
To help the reader investigate complex systems, one chapter of the book is devoted to complexity tools. In particular, authors focus on the cascade of complexity, balance and range of outcomes, complexity mapping, fitness landscape, the Stacey diagram, and stakeholder involvement and soft systems methodology. Other chapters illustrate how different fields of planning and public policy, such as health, international relations, development and terrorism, can gain from this complexity perspective.
In sum, the book provides a comprehensive, well-written and easy to understand introduction to complexity. The introductory chapters summarise the ideas and developments of complexity thinking over the last decades. Because of the broad tent view on foundations and the wide range of practical examples, it is not only relevant for scholars of public policy but also for social scientists and anybody interested in complexity. However, due to its narrative style, the book leaves out any formalisation or quantification of complex systems. For instance, the concept of fitness landscapes is motivated by some illustrations showing hillocky scenarios, but nothing is mentioned about how to measure the level of complexity, nor efforts required to find optimal or good solutions within the search space are discussed. But this is exactly the point, since it is on this that classical analytical optimisation methods fail and complexity-grounded adaptive methods enter the picture. Hence, the book skips important insights and does not offer a deeper understanding of complexity. Nevertheless, though its descriptive style, it must be seen as a good starting point for readers interested to get familiar with the very basic ideas of complexity. Moreover, this introduction can motivate the most curious readers to further their understanding of this field.
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© Copyright Journal of Artificial Societies and Social Simulation, 2010