“Learning to Expect the Unexpected”: NASSIM NICHOLAS TALEB

Learning to Expect the Unexpected is a discussion regarding the different types of randomness. However, it seems Nassim Taleb is most interested in the idea that we as humans do not learn that we do not learn…basically, he states that since events such as the internet bubble, 9-11, Google’s popularity or anything else that would be considered a large deviation is hard to model and thus hard to understand — combined with the idea that humans believe we are better forecasters than we really are — Taleb is concerned with why humans don’t learn that we aren’t learning (as much as we could?).

Alright, so imagine our most brilliant people today, transported to 200 years ago. Would they be ’smarter’ than the people originally from that time? I have often wondered something like this because when I first started reading about science history, I think @ first I assumed that people then were not as smart as now — but now I just think there are more people now, more ideas, better health so in turn more time — of course we have advanced as a society and we have built many tools to make us more efficient — so what would happen if we took Newton and ported him to today, 2004? With our better tools and increased knowledge-base…I bet he would prove he is still one of the ’smartest’ in the world.

So then I must say there is some weight in Taleb’s argument — we as people are not learning that we are not learning as much as we think we are relative to the amount of information we create.

If we live in an increasingly connected world where large deviations can create immense ripples that severely dictate our current state and we are currently having trouble modeling or predicting these deviations — then it would make sense that we have a hole in our understanding of our universe.

How do you model or predict something that by nature is supposed to be an oddity? How do you learn to expect the unexpected?