With the vast scientific knowledge-base available to us, why is it still so hard to accurately predict things like stock market prices and biological evolution? In this essay, I connect several concepts from computability, predictability, data science, and physics together to understand why some systems are so difficult to model. After addressing the important role of navigating particular state spaces in each field, I conclude that modularity may be an under-appreciated and under-utilized tool in our ability to compute our complex world.
Alyssa Adams