A Convoluted Coil, This World

Having recently read Mark C. Taylor's book The Moment of Complexity: Emerging Network Culture, I've lately been pretty fascinated by the weird worlds of emergent and complexity sciences. Somewhere in-between -- connected, appropriately enough -- you have one of the latest fads in academic circles, quite possibly due to the academy's generall embrace of inter-disciplinarity: networks.

The basic idea of network theory, as you might guess, is the study of the phenomenon and implications of the interactivity between multiple nodes, agents, individuals, etc. If you're philosophically inclined at all, think of the Kantian distinction between machine and organism. In the former, the whole [i.e, the machine] is a sum of its individual parts, with the parts forming the properties of the whole; in other words, it is externally defined. In contrast, organisms, Kant claims, are governed by an "inner teleology," in which it exists for its own sake; or, in other words, the parts and the whole constitute one another, internally. Now, jump ahead two hundred years or so, and you still have philosophers, mathematicians, biologists, physicists, economists, social scientists, literary critics, and even theologians thinkering with the complex dynamics that this kind of thinking sets in motion.

The focus of network theory is similar, but, in effect, it steps back and examines the larger matrix in which such an "organism" exists for and by way of other organisms, who are, of course, themselves interconnected similarly. When one starts thinking globally, like you might if you were, say, an investment firm, it all begins to sound like mass chaos. Here's the thing, though, our friends, the network theorists of the world, say that it's not. Saturday's New York Times has a pretty helpful survey of some of the recent literature and thoughts:

It wasn't until the mid-1990's and the advent of powerful computers that network scientists were able to analyze real-life networks of significant size and complexity. And in doing so, Mr. Watts and his colleagues made some tantalizing discoveries. By 1998, they had found that networks as diverse as actors, power grids, the World Wide Web, the proteins in a human cell and the neurons of a wormlike organism called C. elegans aren't random at all but obey the same simple, powerful rules.

For example, whether the network has nearly a billion nodes (the estimated number of Web pages) or just half a million (roughly the number of actors in the Internet Movie Database), the paths between any two nodes tend to be extremely short — such that, for example, any two movie actors can be connected by an average of less than four links.

And this is the really eerie, or perhaps it's just exciting, part: there is no discernible reason for any such "small world" order to manifest itself the way it generally does in closed systems. In 1999, for instance, two researchers at Notre Dame

found that many of these small-world networks are also what scientists call scale-free. Many natural phenomena, including traits like height and I.Q., tend to cluster around an average (producing the familiar bell curve distribution). By contrast, scale-free networks go in for extremes: a few hubs — nodes with lots of links — and many more nodes with hardly any links at all. (Think of Google, the search engine, as a hub, and your personal homepage — which probably has just a few links — as an ordinary node.)

Some of the possible benefits for all this, outside of the academic-masturbatory rites it has incited throughout doctoral programs, is the potential many people think it may hold for any number of practical fields, from city and highway planning, intra- and inter-business models, psycho- / spiritual-consciousness expansion, AIDS and cancer research, and even to counterterrorism.