When you’re running a complex computer simulation with many different factors, small scale changes in initial conditions can lead to large scale changes in final outcomes, making prediction possible, but limited in scope and fundamentally based on probability.
In chaos theory, you try to make your models better by accounting for the unaccountable. Your models are fallible, but honest. Because all models are fallible.
There’s a parallel phrase in Daoism: The Dao that can be spoken is not the eternal Dao.
Chaos theory is also closely related to the second law of thermodynamics and its application to information theory. All information is in flux, as is our ability to measure it.
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