Why are neighborhoods so often segregated? Why did tense but stable situations in the Balkans and Rwanda suddenly tip into genocide? Why did crime rates across the country drop precipitously in the 1990s? These questions may seem unrelated, but insight into all of them has been garnered from the relatively new science of artificial societies. In "Seeing Around Corners," Atlantic correspondent Jonathan Rauch surveys the field, and argues that A-societies may become a powerful tool for peering into some historical mysteries and societal trends that have until now resisted explanation. As Rauch writes,
Researchers are creating cyber-models of ancient Indians of Colorado's Mesa Verde and Mexico's Oaxaca Valley; they are creating virtual Polynesian societies and digital mesolithic foragers; they are growing crime waves in artificial neighborhoods, price shocks in artificial financial markets, sudden changes in retirement trends among artificial Social Security recipients, and epidemics caused by bioterrorism.
What the creators of artificial societies have learned is that even by setting just a few simple rules for how human beings interact, they can create "societies" of great complexity—ones that in many ways mirror what's going on in the real world. These models imply that there are certain patterns into which human beings unconsciously arrange themselves—and the models help to identify what those patterns are. A-societies, of course, will not be able to tell us exactly when the next genocide will happen, or precisely when the next crime wave will crest. But, as Rauch points out, they may help us realize the sorts of targeted interventions that would be most effective.
Jonathan Rauch and I spoke by telephone on March 21.
In Thomas Schelling's simulation of a segregated neighborhood, people who may very well have no desire to live in a neighborhood that's all white or all black inevitably end up getting exactly that, because they want a few of their neighbors to be of the same background. In a way the study of artificial societies seems to imply that society, or certain aspects of it, is organized as much by certain immutable rules as it is by free will. Do these simulations imply that we have less control over how society organizes itself than we'd thought?
"Seeing Around Corners" (April 2002)
The new science of artificial societies suggests that real ones are both more predictable and more surprising than we thought. Growing long-vanished civilizations and modern-day genocides on computers will probably never enable us to foresee the future in detail—but we might learn to anticipate the kinds of events that lie ahead, and where to look for interventions that might work. By Jonathan Rauch
Yes, but the first thing to say is that what these models show is that our conventional either/or dichotomy between immutable rules and free will, as you put it so aptly, is wrong. In fact, there is an entire third realm in which society is shaped—in its large shapes—neither by free will nor by immutable rules. On the one hand, in Schelling's demonstrations people are making choices that they do not in any way regard as racist but that produce segregated outcomes. So plainly you don't have a free-will situation where people are trying to create a segregated society or even want to live in one. But on the other hand, it's not immutable rules either, because no two of these simulations are exactly alike. That's true even in as simple a model as Schelling's. Random events take over. Although you can generalize that the outcome will be segregated, you can never predict exactly where the neighborhoods will wind up or where particular people will be living. So it's also not immutable rules or free will, it's something different from either. It's unpredictable, self-ordered complexity. To me, that's the real revelation of these kinds of models. That we have much less control than you might expect when it comes to societies' behavior, but we have more power to predict large-scale patterns and outcomes than we might have thought.
I would think it would be a big leap to go from replicating phenomena already known about the world to predicting what could happen in the future. How much potential do A-societies have in this regard? Are you aware of any interesting things the A-societies have predicted?
The answer to the second question is easy—No. There are no real-world future predictions based on these models. In fact, this whole science is so brand new that it's just beginning to cope with the difficult job of predicting the past. As we see from the Anasazi model, even predicting the past is very difficult. What these models show is that the only way to predict the future is actually to live through it. Each of these models is different. Each run is its own reality, and no matter how powerful your computer is, or how smart you are, or how good your intuition is, knowing the rules and the starting point of a model never allows you to predict the exact outcome, and in fact rarely allows you to foresee the surprises that are likely to happen. What the models prove, then, is that we will never be able to predict the future in social science with any exactitude. What they may do is give some sense of what are the types of surprises, unexpected phenomena, that are likely to come along. That doesn't mean we know when they'll happen, or even that they'll ever happen at all. But we'll have some sense for how we may be blindsided, and where the tipping points may be out there in which small interventions can reap large rewards. That's not predicting the future, but it's way better than anything we've got right now.
Are there examples of ways that artificial societies have challenged conventional ideas of how society organizes itself?
I think that the results of this stuff, in some sense, challenge every idea of how society organizes itself, in that we tend to have an intuitive belief that if we understand individual people and ourselves and our family, then we understand society. Social scientists have been casting doubt on that for years. But these models all take it a step further, and they say that society really does have a life of its own, a mind of its own, a biography of its own. It's something that individuals can't control. Nor can we intuit the outcomes. So I think that shakes the thinking of a lot of social science, which is based on equations and straight lines and curves and projections. In some ways it's worth pointing out that this also confirms a lot of existing social science. For example, we know from experience that broken-windows policing actually works, because it worked in New York, and it's worked in a number of other places. These models are going to help show us why it works—how it is that just getting a few key offenders at a few key moments can completely reverse the course of crime. Then it no longer looks like hocus pocus—we start to get some real understanding of what's going on out there in the world.
"Broken Windows" (March 1982)
The police and neighborhood safety. By James Q. Wilson and George L. Kelling
It does seem that artificial societies could be especially effective in shaping law enforcement. What are some other ways that you think the lessons could be applied to the real world?