Chaotic systems, the butterfly effect and underlying patterns of human interactions and international relations.
Today, most theorists have more modest goals. Chaotic systems are extremely difficult to predict in the long run, but they’re also not entirely random – as Lorenz observed – and with enough detailed information, patterns emerge allowing short-term predictions to be made, though always with a degree of uncertainty. As Kalev Leetaru told me recently discussing the GDELT events database, “Most datasets that measure human society, when you plot them out, don’t follow these nice beautiful curves,” he says. They’re very noisy because they reflect reality. So mathematical techniques now let us peer through that to say, what are the underlying patterns we see in all this.”
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Can chaos theory teach us anything about international relations?
By Joshua Keating
Source – Foreign Policy, published Thursday, May 23, 2013
This year marks that 50th anniversary of the branch of mathematics known as chaos theory. Appropriately enough for a field of study premised on the idea that seemingly insignificant events can have large and unpredictable consequences, the eureka moment of chaos is generally considered to be a short dense paper titled “Deterministic Nonperiodic Flow” published on page 130 of volume 20 of the Journal of the Atmospheric Sciences in 1963.
As James Gleick writes in his very entertaining history, Chaos: Making of a New Science, “In the thousands of articles that made up the technical literature of chaos, few were cited more often than “Deterministic Nonperiodic Flow.” For years, no single object would inspire more illustrations, even motion pictures, than the mysterious curve depicted at the end, the double spiral that became known as the Lorenz attractor.”
The paper’s author, Edward Lorenz, was an MIT mathematician working on an early computer weather modeling simulation. One day in 1961, in an effort to save time waiting for his vacuum tube-powered Royal McBee computer to run the program, Lorenz started his simulation from the middle, manually entering in data from an earlier simulation, but crucially, rounding a six decimal point number to three decimal points in order to save space. What Lorenz found after returning from a coffee break was that these tiny, seemingly arbitrary changes in his initial inputs had led to vastly different outcomes in the weather models he created.
As Gleick writes, “Lorenz saw more than randomness embedded in his weather model. He saw a fine geometrical structure, order masquerading as randomness.” Lorenz, who died in 2008, would later become best known for coining the metaphor of the “butterfly effect” to describe systems that are extremely sensitive to their initial conditions.
Please click here to read the full article at Foreign Policy.