“HISTORY, n. An account mostly false, of events mostly unimportant, which are brought about by rulers mostly knaves, and soldiers mostly fools.”
– Ambrose Bierce, The Devil’s Dictionary
Bierce was being funny when he wrote The Devil’s Dictionary, but his definition of history seems pretty well on target. Or so we might think, given the usual portrayal of history as the speeches, battles, and poor-to-middling decisions of kings, beggars, and senators making the same mistakes over and over again.
That “over and over again” is a problem. If history were just about the decisions of individual human beings, we’d expect their actions to look like chaos on all scales. That doesn’t happen. We see plenty of chaotic behavior in normal life, but the further we zoom out, and the larger the time scale we examine, the more regular and repetitive history appears. To explain this regularity, people have proposed plenty of theories of history, ranging from the reasonable to the bizarre. One problem with most of them is that they tend to be qualitative, or concept-based, rather than quantitative, or based on consistent relationships between numerical data. When you’re trying to systematically predict or describe events, a quantitative theory goes a lot further than a qualitative one.
So I was pleasantly surprised several days ago, when I stumbled across this post on the Long Now Foundation‘s blog: Conway’s Game of Life and Three Millennia of Human History. The post briefly describes a remarkable computer simulation of 3,000 years of Eurasian history, recently conducted by ecologist Peter Turchin and his colleagues.
Simulation? History? That means a quantitative model. I was curious. I dove into Turchin’s report, which you can read here, along with its supporting documents.
Turchin and company created their simulation very simply: they took a map of Africa and Eurasia and chopped it up into “cells” of 100 kilometers square. Each cell was classified as sea or land; land cells were assigned elevation and further classified as desert, steppe, or agricultural land. Every agricultural cell was supplied with a “community” that could possess two types of social traits: military technology and ultrasociality. (Ultrasociality, as the study defines it, is humans’ “ability to live and cooperate in huge groups of genetically unrelated individuals.”) Agricultural cells were randomly populated with ultrasociality traits, while military technology traits were granted initially to cells bordering the steppe, and spread outward from there (a way to simulate the effect of the steppe highway on the transmission and development of military techniques, most notably mounted warfare). The cells were programmed to attack their neighbors. Victorious cells built multi-cell empires, imposing their ultrasociality traits on the vanquished. Victory was more probable over cells with low elevations and fewer ultrasociality and military technology traits than their attackers.
What happened in the simulation was extraordinary. Over time, traits diffused throughout Eurasia, and empires rose and fell. When multiple runs of the simulation were averaged, the results matched rather closely to actual history—in some cases eerily so. Overall, the model matched reality 65% of the time—markedly better than a coin toss.
Cool! I thought. How about running it forward from today? Turchin’s model simulated Eurasia from 1500 B.C. to 1500 A.D. After 1500 A.D., the steppe ceased to disrupt Eurasian society, and warfare lost out to trade and technology as the dominant mode of cultural diffusion. But, with some tweaking, it should be possible to simulate the modern world.
Efforts to do so—on a massively larger scale than Turchin’s study—have already begun. The most ambitious proposal I found is FuturICT: a plan for simulating and visualizing the entire modern world, in order to accurately understand the impacts of changes in technology, the environment, the global economy, and government policies, and produce better information and communication technologies (ICT) to cope with them.
FuturICT would have three major parts: a Planetary Nervous System, a Living Earth Simulator, and a Global Participatory Platform. The Planetary Nervous System would be a “global sensor network” to collect real-time data from millions of information networks on the planet, tracking how those networks and their nodes operate and interact. The Living Earth Simulator would take this data and use it to model future scenarios. Want to see what the impact of a new business regulation would be on urban transportation? Plug it in. How about a rapid economic collapse in East Asia? Simulate it. The effect of a 1°C global temperature rise on industrial production? That could be modeled eventually. Finally, the Global Participatory Platform would allow scientists, officials, and laypeople to examine the simulation results, come to conclusions about them (perhaps in the same way Wikipedia editors collaborate to produce articles), and act accordingly.
FuturICT claims to not be about predicting the future, but it would probably get as close as possible. Its output would be similar to a short-term weather forecast; although meteorologists can be wrong (and we get very mad when they are), they are right most of the time. This would be a near-future forecasting system for the socio-economic environment of the entire planet. And that is an enticing thing to have.
Why? Personally, as a futurist and a writer of speculative fiction, I’d love to be able to try out a few interesting scenarios. (Robot apocalypse, anyone?) On a more serious note, however, modern civilization is up against a lot. We have reached unprecedented heights of technological and social development, but with that comes a tenuous situation, as it stimulates a tremendous amount of chaos and social change economically, politically, ecologically, and ideologically. We are seeing it today, and having a good model of how it all interacts could determine the survival of human civilization over the next 100 years. Many people would be eager to possess such a model.
But simulations of the future are dangerous, in part because people want them so badly. One problem is how the data to drive them are accumulated. The advocates of FuturICT insist, emphatically, that individual privacy would be fully respected by their Planetary Nervous System, but other creators of future simulators might not be so ethical. Likewise, the results of the simulations could be used nefariously, or kept behind closed doors. An accurate, dependable model of how a complex society will respond to various impulses is a powerful tool for good or evil.
There’s a second area of danger. A simulator of history or the future is by necessity linked to a certain historical theory, and theories of history are dangerous by nature. History itself is littered with examples of historical theories gone wrong—Marxism and Nazi Aryanism, for example. Because they promise power, theories of history are naturally seductive, lead people to act with expectations that may not match reality, and can overturn a society’s mores. If—when—the models fail, disaster ensues. A massive, detailed future simulator could end up producing the very collapse it is intended to avoid, if we grew too complacent about its results, or too dependent on its models.
Any model is guaranteed to fail eventually. Societies change over time, and the old theories fail to describe new behavior. Turchin’s war-driven model of civilization cannot model the information and communication-driven modern world, and a modern future simulator will not describe society a century or two from now, if current technological advancement rates continue. Of course, it’s entirely possible that without a future simulator, human civilization will not survive to the point where this becomes an issue. The knaves and fools might win, and our globally interconnected ultrasociality might become a legendary Golden Age that our distant heirs will recall with fear and wonder. Whether we choose to simulate or not, we need to be smart about it—and very, very cautious.