From prediction to adaptation
I've been attending the NECSI summer school on complex systems . One of the key concepts I've gained from it is the reason of why traditonal methods (such as calculus) are not useful when dealing with complexity. The problem lies in the "averaging assumption", which means that the state of each component is independent of others. This is not true in many systems, so the central limit theorem does not hold. Considering also deterministic chaos, one realizes the limits of prediction in complex systems. It is not that we cannot know them. The thing is that new information is generated by the interactions, so we cannot predict (compress) the future of the system without "running" it. As human societies are becoming increasingly complex, it seems to me that there is a shift between the usefulness of prediction and adaptation. Now, both are useful, but when we can predict less and less what will be the state of the world economy next year, or even next week, we ...