Nassim Taleb concept, fleshed out in Black Swan


In Extremistan, variation within distributions, is far less constrained than in Mediocristan. It is the land of scalability. Generators of events produce distributions with very large or very small extreme values, relatively frequently. And those extreme values often affect the sum of attribute values in a sample distribution, and the mean value of such distributions. The probability of occurrence of extreme values varies greatly from Gaussian models. In fact, many attribute value distributions in Extremistan do not fit any known models well. Examples of them include sales distributions for books per author, wealth and income distributions for individuals and businesses. Since extreme occurrences can greatly affect statistical properties of distributions from Extremistan, it is hard, in contrast with data from Mediocristan, to make reliable inferences from sample data.

It seems to me that there’s a (c): many people will contribute, but not benefit from those contributions, because tomorrow’s jobs will increasingly exist in Extremistan, not Mediocristan.

cf Average Is Over

Edited:    |       |    Search Twitter for discussion