In Isaac Asimov's classic science fiction saga Foundation, mathematics professor Hari Seldon predicts the future using what he calls psychohistory. Drawing on mathematical models that describe what happened in the past, he anticipates what will happen next, including the fall of the Galactic Empire.

That may seem like fanciful stuff. But Peter Turchin is turning himself into a real-life Hari Seldon – and he's not alone.

Turchin – a professor at the University of Connecticut – is the driving force behind a field called "cliodynamics," where scientists and mathematicians analyze history in the hopes of finding patterns they can then use to predict the future. It's named after Clio, the Greek muse of history.

These academics have the same goals as other historians – "We start with questions that historians have asked for all of history," Turchin says. "For example: Why do civilizations collapse?" – but they seek to answer these questions quite differently. They use math rather than mere language, and according to Turchin, the prognosis isn't that far removed from the empire-crushing predictions laid down by Hari Seldon in the Foundation saga. Unless something changes, he says, we're due for a wave of widespread violence in about 2020, including riots and terrorism.

>'We start with questions that historians have asked for all of history. For example: Why do civilizations collapse?' Peter Turchin

This burgeoning field is part of a much larger effort to gain more insight into our world through the massive amounts of digital data that are now available via the internet – a movement that ranges from Google's search engine to the data science contests run by San Francisco startup Kaggle. The difference is that cliodynamics uses data from the distant past. Turgin and his cohorts mine historical documents that have only recently come online.

Turchin didn't begin as a historian. His original area of interest was ecosystem dynamics, but he soon decided that many of the interesting problems had already been solved. So he started looking for ways of applying mathematics to other fields. "The only way to do science is to make predictions and then testing them with data," Turchin says. Many other social sciences – including sociology, economics, and even anthropology – had already been revolutionized by mathematics. But historians had resisted quantification.

He founded the movement in the late '90s, and since then, many more have joined in. In 2010, this growing community of researchers started the peer-reviewed publication Cliodynamics: The Journal of Theoretical and Mathematical History.

The basic idea is nothing new. Thinkers from Georg Wilhelm Friedrich Hegel to Oswald Spengler to Leo Tolstoy tried to develop cyclic theories of history that could also predict the future. Austrian philosopher Karl Popper critiqued this notion in his The Poverty of Historicism in 1957. And the '60s spawned a movement called cliometrics. But the approach eventually fell out of favor. "General theories of history are not accepted, in my opinion, for good reason," says Turchin. And yet he followed cliometrics with cliodynamics. The new field, you see, has an edge that predecessors didn't.

It's not the mathematics. Turchin says his methods aren't very complex. He's using common statistical techniques like spectrum analysis – "I used much more sophisticated statistical methods in ecology," he says. And it's not "big data" tools. The data sets he's using aren't all that big. He can analyze them using ordinary statistical software. But he couldn't have built these models even a few decades ago because historians and archivists have only recently started digitizing newspapers and public records from throughout history and putting them online. That gives cliodynamics the opportunity to quantify what has happened in the past – and make predictions based on that data.

In the simplest of terms, Turchin and his colleagues will build a mathematical model using one data set and then test that model against other historical data sets they're unfamiliar with. That way, they can see if the model holds. This isn't exactly the psychohistory described by Isaac Asimov. "For the most part, we don't predict the future. It's too far. We can't wait 200 years to see if something's right," Turchin says. "I'm not a prophet." But cliodynamics moves in that direction – and it's not science fiction. Though traditional historians are often wary of the practice, others very much see the value.

"It's very important to do. It should force traditional historians to respond," says Yale historian Joseph Manning. "Most people in my field just publish documents and don't go behind them."

Peter Turchin's graph describes the regular waves of violence – including riots and terrorism – that characterize U.S. history. Image: Peter Turchin

Waves of Violence

What Turchin and his colleagues have found is a pattern of social instability. It applies to all agrarian states for which records are available, including Ancient Rome, Dynastic China, Medieval England, France, Russia, and, yes, the United States. Basically, the data shows 100 year waves of instability, and superimposed on each wave – which Turchin calls the "Secular Cycle" – there's typically an additional 50-year cycle of widespread political violence. The 50-year cycles aren't universal – they don't appear in China, for instance. But they do appear in the United States.

The 100-year Secular Cycles, Turchin believes, are caused by longer-term demographic trends. They occur when a population grows beyond its capacity to be productive, resulting in falling wages, a disproportionately large number of young people in the population, and increased state spending deficits. But there's a more important factor, one that better predicts instability than population growth. Turchin calls it "elite overproduction." This refers to a growing class of elites who are competing for a limited number of elite positions, such as political appointments. These conflicts, Turchin says, can destabilize the state.

Many of these issues persist in industrial societies. Although population growth is no longer likely to result in mass starvation, it can push the supply of labor beyond demand, leading to increased unemployment.

>Turchin takes pains to emphasize that the cycles are not the result of iron-clad rules of history, but of feedback loops – just like in ecology

Then you have the 50-year cycles of violence. Turchin describes these as the building up and then the release of pressure. Each time, social inequality creeps up over the decades, then reaches a breaking point. Reforms are made, but over time, those reforms are reversed, leading back to a state of increasing social inequality. The graph above shows how regular these spikes are – though there's one missing in the early 19th century, which Turchin attributes to the relative prosperity that characterized the time.

He also notes that the severity of the spikes can vary depending on how governments respond to the problem. Turchin says that the United States was in a pre-revolutionary state in the 1910s, but there was a steep drop-off in violence after the 1920s because of the progressive era. The governing class made decisions to reign in corporations and allowed workers to air grievances. These policies reduced the pressure, he says, and prevented revolution. The United Kingdom was also able to avoid revolution through reforms in the 19th century, according to Turchin. But the most common way for these things to resolve themselves is through violence.

Turchin takes pains to emphasize that the cycles are not the result of iron-clad rules of history, but of feedback loops – just like in ecology. "In a predator-prey cycle, such as mice and weasels or hares and lynx, the reason why populations go through periodic booms and busts has nothing to do with any external clocks," he writes. "As mice become abundant, weasels breed like crazy and multiply. Then they eat down most of the mice and starve to death themselves, at which point the few surviving mice begin breeding like crazy and the cycle repeats."

There are competing theories as well. A group of researchers at the New England Complex Systems Institute – who practice a discipline called econophysics – have built their own model of political violence and concluded that one simple variable is sufficient to predict instability: food prices. In a paper titled "The Food Crises and Political Instability in North Africa and the Middle East," they explain that although many other grievances may be aired once the violence begins, the cost of food is the primary trigger. They make a similarly grim prediction: large-scale riots over food, beginning around October of this year.

Into the Dark Archives

Much has been made of machine learning algorithms and software such as Hadoop and how they're used to mine the enormous amounts of data generated by the average internet user, but cliodynamics shows that we can find just as much value in "dark archives" – the mounds of non-digitized records that we don't realize contain useful data. Quantitative biologist Samuel Arbesman calls this "long data," and he urges the world to take a closer look.

Arbesman says that many traditional historians are beginning to embrace Turchin's practices, opening up opportunities for academics in the humanities to collaborate with mathematicians and economists. But he adds that academics aren't the only ones who can benefit from dark archives brought online. Even businesses, he says, can mine such data.

Some businesses, explains says, have been around for hundreds of years, changing with the times. IBM was founded in 1911 and originally sold tabulating machines. Nintendo started out in 1889 as as a playing card company. The construction company Kongō Gumi existed for over 1,400 years.

Their future, he says, can benefit from their past.