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Complexity (Lewin, 2000)

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Life at the Edge of Chaos

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Review by Dennis Littrell
 
The science of complexity, a discipline unique to the computer age, was born of chaos and a growing sense that there is something amenable to scientific inquiry about complex systems that we are missing. Before we had the number crunching power of computers, complexity could not be explored because the many variables resulted in astronomical calculations.

In this revision of his book originally published in 1992, Roger Lewin explains what the science of complexity is all about through interviews with some of its most important practitioners (and critics) organized around some of the central ideas. As such this is both a fine introduction to the subject and an interesting read. Lewin includes 16 pages of photos of the scientists he interviewed captioned with a significant quote from each. He has added an afterword on the application of complexity science to business, and an appendix about John Holland, whom he dubs, "Mr. Emergence."

"Everything works toward an ecology" is an old dictum of mine. I have the sense that I came up with that myself, but I probably read it somewhere years ago. At any rate, what is being said here is that complex systems work toward a state of equilibrium near a transition phase, near "the edge of chaos." This equilibrium can be an ecology (Darwin's "tangled web"); indeed it can be the entire planet, as in the concept of Gaia in which "the Earth's biological and physical systems are tightly coupled in a giant homeostatic system" (quoting Stuart Kauffman on page 109).

A central idea is that "...large, interactive systems-dynamical systems-naturally evolve toward a critical state" (physicist Per Bak, quoted on page 61). These systems include weather, financial markets, piles of sand, and most significantly, ecologies, so that evolution itself is seen as shaped by the dynamics of complexity. Complexity is the "interesting" middle ground between order and the purely random, between the crystallized structure of ice and the Brownian motion of molecules. I had a curious sense of understanding when I compared these three states with positions at chess. First there is the even, static position, perhaps with bishops of opposite color in which no progress can be made, a drawn the inevitable result. Second there is the wildly chaotic position so complex that no one can completely calculate it, say the board after black takes white's queen knight pawn in the "poisoned pawn" variation of the Najdorf Sicilian. In between are the "interesting" positions in which one side might have a small advantage or there might be a dynamic balance of advantages, space versus material, for example, in which a startling combination might be hidden.

These states-"at the edge of chaos"-are seen here as analogous to the phrase transition states of matter, from liquid to gas, for example. The idea is that there is a naturally occurring property of the physical world that forces complex systems into stable, readiness states near the edge of transition. What is exciting is that these states, because they are so "ripe" for change can be influenced or manipulated into change with small resources. Out of complexity comes something that could not be predicted by an analysis of its individual components, an emergent property of the system. I would note that such a natural phenomenon would be attractive to those who believe in punctuated evolution (e.g., Steven Jay Gould) and to those who believe that social and political change typically comes suddenly and with great force.

Central to what complexity science is saying is that reductionism-which is the technique that has driven science to its present position of power and influence-is limited. "...[Y]ou have to look at the interactions as well as the parts," John Holland is quoted as saying on page 220. In other words, you have to take a holistic approach. However, the use of the word "holistic," a New Age shibboleth, is the just sort of thing that makes traditional scientists wince.

Consequently, complexity science is not without its critics who argue that the fundamental mechanism of complexity exists only in a mystical sense and is therefore anathema to mainstream science. Even its practitioners, such as University of Michigan "complexologist" John Holland, admit they are still searching for the fundamental mechanism of this new science. He is quoted on page 214 as saying, "Our present understanding is not much better than the child saying that Jack Frost explains the wondrous colors of autumn."

However most complexity scientists would say that the mechanism isn't mystical at all. It's just not understood yet. I would add that much of what we think we know about the world is based on relationships and phenomenon that we assume we understand, but really we don't. For example physicists say that gravity curves spacetime, but they don't say how it curves spacetime. Presumably gravitons do the trick, but they haven't been discovered yet! So it could be said that gravity is mystical. I like to compare this lack of understanding to the task of watching grass grow. (This also works for evolution.) Every day I look but at no time do I ever see the grass growing, yet after a while I know it has grown. It seems that it always grows when I'm not looking! By the same token we see the results of complexity, but we do not yet see the inner workings of the process. We may never see the process, but through complexity science we may yet understand it.

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p.12 "...interactions in a dynamical system give you an emergent global order, with a whole set of fascinating properties." Chris [Langton] is at the board again, rapidly sketching a cluster of small circles, joined by double-headed arrows. "These are the components of your system, interacting locally." Above them appears what looks like a child's version of a cloud, and a volley of large arrows shoots up from the cluster below. He then added two arrows, one emerging from each side of the cloud, sweeping down toward the cluster. "From the interaction of the individual components down here emerges some kind of global property up here, something you couldn't have predicted from what you know of the component parts," continued Chris. "And the global property, this emergent behavior, feeds back to influence the behavior of the individuals down here that produced it."
  Order arising out of a complex dynamical system, was how Chris described it, global properties flowing from aggregate behavior of individuals.
 
p.22 Chris [Langton] and others like him at the [Santa Fe] institute are looking for universal principles, fundamental rules that shape all complex adaptive systems.
 
p.131 You start with a simple system, allow the fundamental dynamics to operate, and products of increasing complexity emerged. It was the nature of mathematical models of complex adaptive systems.
 
p.137 Biological complexity has to do with the ability to process information. Computational capability, that's what we see in our cellular automata models, and in other complex adaptive systems. I view organisms as complex dynamical systems, and what drives their evolution is increased computational ability.
 
p.138 Survival has to do with gathering information about the environment, and responding appropriately
 
p.144-145 Natural selection concerns simply the adaptation to local circumstances, continued Steve[n Gould], and as such contains no tendency to global progress. The environment changes in one direction, and adaptation tracks it. The environment changes in another direction, and adaptation tracks it again, blindly and with no direction.
 
p.198 complex adaptive systems are composed of a diversity of agents that interact with each other, mutually affect each other, and in so doing generate novel, emergent behavior for the system as a whole. The system is constantly adapting to the conditions around it, and over time it evolves.
 
p.198 Because the dynamics of complex adaptive systems are complex and largely unpredictable, accepting businesses as being such systems requires a mindset different from that associated with long-established business models: managers and executives cannot control their organizations to the degree that the mechanistic perspective implies, but they can influence where their company is going, and how it evolves.
 
p.199 In 1992, the Harvard Business Review  carried an article titled "Is management Still a Science?" The author, David Freedman, answered the question thus: "Management may indeed be a science - but not the science most managers think."
 
p.202 Complexity scientists have identified a few simple rules by which complex adaptive systems operate...
 
The source of emergence is the interaction among agents who mutually affect each other... Small changes lead to large effects... Emergence is certain, but there is no certainty as to what it will be... Greater diversity of agents in a system leads to richer emergent patterns.
 
p.220 "Reductionism has been tremendously powerful," John [Holland] noted. "You take a system, study the parts, and you can understand a lot about the system. But what complexity science says is that you have to look at the interactions as well as the parts." He made an analogy with a chess game in progress. "If I look at the board and add up the value of the pieces on each side - nine for queen, three for the bishop, and so on - I'm not going to understand how the game is going, because it is the position of the pieces that counts, their interaction," John explained. "You have to look at the way the various pieces support each other to know which side is in the stronger situation. It's the interaction of the pieces from which the strength emerges. It's the same in all complex adaptive systems. Interaction is the key."

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