This article is the first of a 5-part series covering the Real World Risk Institute’s 1-week mini-course on Real World Risk, held in NYC. There’s statistics, complex systems theory, and strong opinions ahead. I’ve learned far more than I can adequately represent here, so these will more or less be my raw notes.
If you want to better understand risk and decision making under uncertainty, then buckle up! Or go straight to the source and save yourself a hop :)
Table of Contents
Part 1: We Don’t Know Nothin’ (you are here)
RWRI is an intensive course in NYC, held a couple times a year and run by practitioners (Nassim Taleb, Robert Frey, Raphael Douady, others)— those who have or are currently taking and analyzing risks. There is a strong belief among the group that while scholarship and deep research are important, academia is a dangerous vacuum where theories are far removed from reality. As such, everything here will have a practical bent. If you talk the talk, you must walk the walk.
Uncertainty and Distributions
An important theme throughout the week was “decision making under uncertainty”, meaning times where there is high volatility or low predictability. The good news is: the more uncertain you are about what could happen, the more clear the actions you take should be.
As an example, consider the insurance industry. When it comes to extreme events that they can’t factor in to pricing, savings, liquidity, etc. they “lawyer up” — they ensure their contracts make exceptions or special previsions for the most exceptional circumstances to protect themselves from going out…