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Jewish World Review
July 16, 2004
/ 27 Tamuz 5764
Asimov's ‘Foundation’ theories on society move from fiction to academia
By
Tom Siegfried
With the movie adaptation of 'I, Robot' opening this weekend, a look at how the legendary novelist is having some of his theories — those of 'psychohistory' — utilized in research papers and scientific journals in a slew of disciplines.
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A little over half a century ago, Isaac Asimov created a new universe, home to a decaying galactic empire and a novel form of social order known as the "Foundation."
Asimov's "Foundation" novels — the most famous science-fiction trilogy between "Lord of the Rings" and "Star Wars" — described a new science of social behavior called psychohistory. Mixing psychology with math, psychohistory hijacked the methods of physics to precisely predict the future course of human events.
Today, Asimov's vision is no longer wholly fiction. His psychohistory exists in a loose confederation of research enterprises seeking equations that capture patterns in human behavior. These enterprises go by different names and treat different aspects of the issue. But they all share a goal of better understanding the present in order to foresee the future, and possibly help shape it.
Almost daily, research papers in this genre appear in scientific journals or on the Internet. Some examine voting patterns in diverse populations, how crowds behave when fleeing in panic, or why societies rise and fall. Others describe ways to forecast trends in the stock market or the likely effect of antiterrorist actions. Still others analyze how rumors, fads or new technologies spread.
Once the province of sociologists, political scientists, economists or philosophers, such issues are now routinely analyzed by physicists and mathematicians. At the same time, psychologists are learning more about what goes on in the brain when humans interact. And anthropologists have begun to study how economic activity influences behavior in different cultures.
Put it all together, and Asimov's idea for a predictive science of human history no longer seems unthinkable. It may be inevitable.
Universities and institutions around the world have seized versions of Asimov's vision for new research themes. At the Santa Fe Institute in New Mexico, a new behavioral sciences program focuses on economic behavior and cultural evolution. The National Science Foundation has identified "human and social dynamics" as a new funding priority area. At various schools, collaborators from diverse departments are creating new hybrid disciplines, with names like econophysics, socionomics, evolutionary economics, social cognitive neuroscience and experimental economic anthropology.
"It's become pretty obvious from 9/11, from terrorism, that we need to understand human behavior better," says Rita Colwell, former director of the National Science Foundation. "Not only for prediction, but also for prevention."
Among the newest of the enterprises — and closest to the spirit of Asimov's psychohistory — is a discipline called sociophysics. The name has been around for decades, but only in the 21st century has it become more science than slogan.
Like Asimov's psychohistory, sociophysics is rooted in statistical mechanics, the math used by physicists to describe the big picture when lacking data about the details. Nobody can track the trillion trillion molecules of air floating around in a room, for instance, but statistical mechanics can tell you how an air conditioner will affect the overall temperature.
In a similar way, science cannot describe how any given individual will behave. But put enough people together, Asimov's psychohistorian Hari Seldon reasoned, and laws of human interaction will produce predictable patterns — just as the way molecules move and interact determines the temperature and pressure of a gas.
Statistical mechanics math is nowadays routinely recruited for problems far removed from its standard uses with gases or chemical reactions or magnetic materials. Everything from the flow of funds in the stock market to the flow of traffic on interstate highways has been the subject of statistical-physics study. And more and more, that math is used to describe people as though they were molecules, by physicists who are, in effect, taking the temperature of society.
Physicists have invented many forms of social thermometers. Among the most fruitful are those that construe society as a mixture of many complex networks.
In general, networks are like gases in which molecules are somehow connected; the role of the molecules can be played by almost anything — local affiliates in a TV network, power plants in an electric grid, airports linked by direct flights, home pages on the World Wide Web. Connections can be as simple as wires linking computers or as intangible as sharing a common interest.
People, of course, belong to many different kinds of networks. There are networks of family, networks of friends, networks of professional collaborators. There are networks of people who share common investments, political views or sexual partners.
Networks offer scientists many temperatures to measure. For instance, you can calculate the average number of links between a network's members (called nodes). That tells you something about how connected the network is, just as a real temperature tells you how fast (on average) a gas's molecules are moving.
Networks have other quantifiable features. You can specify the average number of steps it takes to get from one node to another — how many flights, say, it takes to get from Fargo to Fayetteville. In a "small-world" network, it takes only a few steps to get from any one node of the network to any other.
As it turns out, when a network's nodes are people, small worlds are the rule. So discovering the rules governing small-world networks may be the key to forecasting the social future.
Network math offers obvious social uses. It's just what the doctor ordered for tracking the spread of an infectious disease, for instance, or plotting vaccination strategies. And because ideas can spread like epidemics, similar math may govern the spread of opinions and social trends.
Numerous versions of network — or other statistical-physics math have attempted to identify patterns of opinion flow. Serge Galam, of the French research institute CNRS, has studied the spread of terrorism, for instance, trying to identify what conditions drive the growth of terrorism networks. In other work, Galam has analyzed opinion transmission and voting behaviors, concluding that "hung election scenarios," like the 2000 U.S. presidential contest, "are predicted to become both inevitable and a common occurrence."
Other opinion-spreading papers try to explain whether an extreme minority view can eventually split a society into two polarized opposite camps, or even overwhelm the rest of the population. One analysis suggests that higher connectivity among the people in a population boosts the chances for social takeover by an extreme position.
Another new paper examines the idea of "contagion" in general — the spread of anything through a population, whether infectious disease or ideas, fads, technological innovations, or social unrest. As it turns out, fads need not always spread the same way as a disease, as different scenarios may guide the course of different contagions.
In some cases, a small starting "seed" (a literal virus, perhaps, or just a new idea) can eventually grow into an epidemic; in other cases a seed infects too few people and the disease or idea dies out, Peter Dodds and Duncan Watts of Columbia University write in a paper to be published in Physical Review Letters. What happens can depend on how much more likely a second exposure is to infect an individual than a first exposure.
The findings suggest that the spread of diseases or ideas depends less on "super spreaders" or opinion leaders than on how susceptible people are — how resistant to disease or how adamant about their current opinion.
Such results imply that the best way to hamper or advance contagion would be strategies that increase or reduce the odds of infection. Better health procedures, for instance, or financial incentives to change voting preferences, could tip the future one way or another.
"Our results suggest that relatively minor manipulations ... can have a dramatic impact on the ability of a small initial seed to trigger a global contagion event," Dodds and Watts declare.
In real life, of course, people don't necessarily transmit opinions or viruses in the simple ways that such analyses assume. So some experts question how useful the statistical mechanics approach to society will ultimately be.
"I think in some limited domains it might be pretty powerful," says Cornell University mathematician Steven Strogatz. "It really is the right language for discussing enormous systems of whatever it is, whether it's people or neurons or spins in a magnet. ... But I worry that a lot of these physicist-style models of social dynamics are based on a real dopey view of human psychology."
So to succeed, then, statistical-physics math may have to meet face to face with social cognitive neuroscience, a booming research field that is all about understanding face-to-face interactions between real people. Brain scans and experiments with brain-damaged patients reveal how people respond to or empathize with others they encounter, providing insights about behaviors people choose in different social situations.
Further help may come from neuroscientists who study the brain activity underlying economic choices, in the new field of neuroeconomics. An offshoot, neuromarketing, may use brain activity-analyses to plan advertising for political campaigns that enlist brain-based strategies for maneuvering the future in one direction or another.
All these approaches still generate but a shadow of Asimov's full-scale psychohistory. Everybody knows there's much more work to be done to match the predictive power achieved by Hari Seldon. Ironically, some of that needed new work may come from scientists who are unwittingly following in the footsteps of Seldon himself.
In later prequels to the "Foundation Trilogy," written decades after the original stories, Asimov described how Seldon gathered the data needed to perfect psychohistory — by visiting different cultures spread across the planet Trantor. By observing a variety of societies, Seldon discovered the common features of human social behavior needed to make sound predictions.
Much as Seldon traveled around Trantor, anthropologists have traveled around the Earth in the last few years, playing economic games in small-scale societies. Human nature as gauged by the games varies considerably from culture to culture — data that must be incorporated into any effort to forecast the social future.
It illustrates the need for today's psychohistoric collaborations to grapple with real people in the real world to find true laws governing human behavior.
"We have this weird, I think untenable, situation in the social sciences," says UCLA anthropologist Robert Boyd. A student learns one story about human behavior in an economics class, and then something quite different in sociology. Psychology class offers yet another version.
"And they come up here and we anthropologists tell them all kinds of different things because we don't agree about hardly anything," Boyd said. "This is not OK. It's not acceptable that the economists are happy with their world and the sociologists are happy with their world, and that this persists in an institution which is supposed to be about getting at the truth."
But as various enterprises mix economic experiments with math and psychology, evolution and culture, a new understanding of human nature and human behavior does seem to be emerging.
"I see a lot of progress happening right now," Boyd said. "But I don't think we're very close myself right now to offering policy recommendations."
In the end, better-informed public policy is what human science is all about. It's an old dream, predating Asimov's psychohistory by centuries. Many philosophers have envisioned laws of human behavior analogous to Isaac Newton's laws of motion. Early sociologists discovered mathematical regularities in birth and death rates and height and weight and even in crime rates. (In fact, such statistical analysis of human affairs influenced the development of statistical mechanics in the 19th century by the British physicist James Clerk Maxwell.)
But past efforts have been, to put it charitably, far from perfect. Science today has much more to work with — the mathematics of statistical physics, economic game theory and networks merged with modern neurobiology, brain scanning and anthropological experiments. All these tools and the new scientific fields built with them suggest that the efforts of earlier centuries were not misguided, just premature.
It's becoming clear that Asimov's psychohistory reflects an undoubtable truth that all the world's different social networks interact in multiple ways to generate a single future. From people to corporations, cities to governments, all the pieces of society must mesh. What appears to be the madness of crowds must ultimately have a method, a method that science can discover.
"We're sort of working on little bits of it, trying to make connections," says Princeton University's Joshua Greene, a philosopher and neuroscientist.
"The idea is really to have, in the end, a seamless understanding of the universe, from the most basic physical elements, the chemistry, the biochemistry, the neurobiology, to individual human behavior, to macroeconomic behavior — the whole gamut seamlessly integrated," he says. "Not in my lifetime, though."
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Tom Siegfried is science editor for The Dallas Morning News. To comment, please click here.
© 2004, The Dallas Morning News. Distributed by Knight Ridder/Tribune Information Services
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