Notwithstanding the folk wisdom that history repeats itself, the rise and fall of civilizations is an experiment that runs only once, which makes the job of those who study society inherently challenging. Indeed, the inability to conduct repeatable, verifiable experiments on social phenomena has caused some in the physical sciences to denigrate the social sciences as "soft."

Well, the social sciences just got a little harder. Researchers at the Brookings Institution in Washington, D.C., have devised a sophisticated software program to study societies in silico, allowing economists, demographers, and other social scientists to rerun history, as it were, changing single variables and testing the results. Their so-called "artificial societies," the program's developers say, offer unique insights into issues ranging from racial segregation to mass migration, and may just revolutionize the way social scientists pursue their research.

The road to such artificial societies was laid down in 1953, when mathematician John von Neumann invented self-replicating automata. These cellular automata, as they are also known, consist of a lattice of cells with specific values that change according to fixed rules for computing a cell's new value based on its current value and the values of its immediate neighbors. Von Neumann found that, when left to their own devices, cellular automata naturally formed patterns, reproduced, even "died."

The first attempt to apply such techniques specifically to social science occurred in the 1970s, when economist Thomas Schelling created an artificial world using nothing more than pennies and dimes that he moved around a checkerboard according to simple rules. Schelling's study showed, among other findings, how even slight preferences for living and working with one's own kind can result in extreme segregation.
Though primitive by today's standards, both efforts revealed how social patterns develop of their own accord out of the discrete interactions of individuals. Yet so-called artificial life did not take off until the 1980s with the giant leap in computing power and the advent of object-oriented programming, a technique that allows programmers to define objects, or entities, in terms of specific characteristics and actions.