Ada Palmer

Well, not much, as it turns out.

At least not directly.

Chaos theory was everywhere in the 1990s.

Fractals adorn dorm room posters.

Jurassic Park explained the butterfly effect to moviegoers.

Then chaos theory largely disappeared from public discourse.

Not because it was wrong, the mathematics remains valid, the phenomena real, but because it proved remarkably difficult to apply.

A recent survey of commonly cited applications by Elisabeth van Nostrand and Alex Altair found that most never received wide usage.

The theory excels at explaining what cannot be done.

You cannot make long-range weather predictions.

You cannot predict where exactly a turbulent eddy will form.

You cannot forecast the specific trajectory of a chaotic system beyond a certain time horizon.

These are important insights, but they are negative and thus non-sexy.

They tell us about the limits of prediction, not how to make it better.

So if chaos theory mostly tells us what we cannot do with turbulent systems, what uses it for understanding history?

The answer comes from the one domain where chaos theory achieved genuine practical success.

Weather forecasting.

But not in the way anyone expected.

In the 1940s, when computers first made numerical weather prediction possible, the approach was deterministic.

Measure current conditions, run the physics forward, predict the future.