I started out writing about how to make better decisions under conditions of uncertainty. At some point, I became more interested in the meaning and sources of uncertainty than the decision theory itself.
First, I explored the background concepts of probability and the unpredictability that arises from non-linear or discontinous processes, the provence of chaos theory. The problem is that while the world is not predictable as one might expect from a clockwork universe, its also not without regularity. These patterns are what we use to make best guesses when the future is uncertain, complexity.
But what’s most interesting are emergent phenomenon, those things that arise out of their components with no real clue to the nature of the whole in the analysis of the parts. My lifelong area of study, the brain, is perhaps the greatest example of emergence- what we call mind or consciousness. How does it arise? Where does it come from?
In the end we come full circle because we can’t understand or predict these emergent phenomenon. So we rely on simplification and metaphor to make sense of the complex and mysterious. Clearly one of the functions of our mental models and computational tools is purely simplification, a creation of a simpler, more predictable universe to deal with.
