The main idea here is to provide kind of review of complex adaptive systems and scientific approach to their analysis, modeling, and forecasting of their behavior. The specific attention is to complex social systems with idea being that knowledge developed via analysis of complex adaptive systems elsewhere in nature could be applied to improve functioning of complex adaptive social systems.
One: Introduction: True Places
This is all about complex systems. Author writes about science as a mapmaking activity with complexity increasing dramatically with increase in scale. That’s why big feature of science is reductionism, with every step up the scale resulting in loss of details. Moreover most complex system include networks and interactions, that too heterogenic to simplify without loss of key elements. One solution used in biology is development of scaling laws when some simple rule like link between hearts bit frequency with length of live. In social science similarly exist link between size of cities with largest being twice as big as second-largest, 3 times the third, and so on. This book looks at interplay between competition and cooperation in complex social systems with stress on self-organized criticality: straw and a camel type of change. At the end author proposes the new fundamental theorem about complex adaptive systems. At the heart of which there are agents searching for better outcomes similar to performing dance governed by some cosmic algorithm.
Two: From So Simple a Beginning: Interactions
Author starts with von Neumann’s cellular automata when each condition of the system directly depends on previous condition like in chess; with multitude of possible conditions making the path dependency critical. Author applies this logic to market and demand – supply relationship, coming to Hayekian conclusion that the system is so complex that relative optimum could be achieved only through self-directed actions of multitudes.
Three: From Hash Crashes to Economic Meltdowns: Feedback
This chapter is about feedbacks and consequences of spikes and flash-crashes when automatic feedback causes system to jump out of range of normal functioning. Obvious examples are stock market crashes and crises.
Four: From One to Many: Heterogeneity.
This is discussion of self-adjusting complex system based on example of air conditioning in beehive that depends on activities of individual bees. Important point here is diversity of individual bees that start acting at slightly different temperatures therefore providing graduate response to change resulting in high stability of the system. However it is not always the case. Sometime heterogeneity could cause system to be unstable. Good example society of N members each of which could revolt if he observes revolt of unique number of people between 0 and N. In this case system would be absolutely stable if there is sequence 1 to N and absolutely unstable if it is 0 to N-1. In the first case since there is nobody to be the first revolting, revolution will never occur, while in the second the person with 0 need in others will guaranteed to start chain of revolt.
Five: From Six Sigma to Novel Cocktails: Noise
This is discussion about variations in different statuses of non-linear systems including local optimums, using example of Six Sigma quality assurance program.
Six: From Scarecrows to Slime Molds: Molecular Intelligence
This starts with charming observation that “Brains are overrated by those who have them”. Then it proceeds to discuss quite intelligent behavior of bacteria based on very simple chemical reactions. The important point here is that choices that are made often seems to be so similar that completely unrelated event could push choice into one direction or another. Here is a nice illustration:
Seven: From Bees to Brains: Group Intelligence
This uses example of bees looking for a site for the new beehive to demonstrate group intelligence. Author also applies it to human social systems in process of political contest. Author expands this notion into continuum of groups at different levels from neutron to society, where the level of analysis could be selected at will with results of analysis being corresponding to selected level. Author also discusses breakdown of group intelligence like in ants’ circular mill:
Eight: From Lawn Care to Racial Segregation: Networks
This is about networks with multiple stable statuses discussed using a sample community with good and bad lawns. Another interesting example is simple segregation by type if network has just 2 types of agents with preference to own type:
Nine: From Heartbeats to City Size: Scaling
This is discussion of scaling with a very nice illustration:
Ten: From Water Temples to Evolving Machines: Cooperation
This is discussion of development of cooperation based on well-known example of Balinese Religion based Irrigation system. It includes more theoretical points of evolutionary process of change when small practically neutral mutations accumulate without expression and then create avalanche when one additional mutation activates many in sync leading to condition of cooperative advantage.
Eleven: From Stones to Sand: Self-Organized Criticality
This is another discussion of what used to be called transformation of small quantitate change into big qualitative change with nice illustration in distribution of change size:
Twelve: From Neutrons to Life: A Complex Trinity
This is somewhat mathematical part discussing statistical methods linking all complex adaptive systems into one logical entity susceptible for analysis and forecasting using similar methods regardless whether it is neutrons in nuclear reaction, neurons in human brain, or individuals in complex human society.
Epilogue: The Learned Astronomer
The final word is stressing need to know and understand self-organizing, complex, adaptive system as necessary condition for survival and prosperity of humanity.
MY TAKE ON IT:
I think it is a great approach to human society: a lot better than typical Marxist primitive and even mechanical approach based on Hegel’s dialectics. However I’d like to make a point that author of this book seems to be underestimating the impact of complexity not only of the system overall, but also every individual human being who is a self-directing and adaptive agent in social systems. Contrary to non-human system that driven primarily by realities of natural world and relatively simple biological adaptations to previously existing conditions, humans, due to their ability to accumulate knowledge and create unnatural environment for themselves, have luxury to live in cultural and ideological world of their minds that is capable dramatically decrease strength of natural feedbacks, leading sometimes to catastrophic consequences examples of which plentifully supplied by attempts of implementation of highly unnatural and non-common sensual socialist utopias in XX century. Hopefully the better understanding of complexity of social system would lead to cessation of attempts of rigid top down control over such systems.