Mediocristan v/s Extremistan
by Chetan Parikh
  
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In a fascinating book “The Black Swan”, the author, Nassim Nicholas Taleb, writes about the differences between the “tyranny of the collective, the routine, the obvious, and the predicted” i.e. Mediocristan and “the tyranny of the singular, the accidental, the unseen and the unpredicted” i.e. Extremistan.  There is a table which summarised the main points.

 

Table

Mediocristan

Extremistan

Nonscalable

Scalable

Mild or type 1 randomness

Wild (even superwild) or type 2 randomness

The most typical member is mediocre

The most “typical” is either giant or dwarf, i.e., there is no typical member

Winners get a small segment of the total pie

Winner-take-almost-all effects

Example: audience of an opera singer before the gramophone

Today’s audience for an artist

More likely to be found in our ancestral environment

More likely to be found in our modern environment

Impervious to the Black Swan

Vulnerable to the Black Swan

Subject to gravity

There are no physical constraints on what a number can be

Corresponds (generally) to physical quantities, i.e., height

Corresponds to numbers, say, wealth

As close to utopian equality as reality can spontaneously deliver

Dominated by extreme winner-take-all inequality

Total is not determined by a single instance or observation

Total will be determined by a small number of extreme events

When you observe for a while you can get to know what’s going on

It takes a long time to know what’s going on

Tyranny of the collective

Tyranny of the accidental

Easy to predict from what you see and extend to what you do not see

Hard to predict from past information

History crawls

History makes jumps

Events are distributed* according to the “bell curve” (the GIFT) or its variations

The distribution is either Mandelbrotian “gray” Swans (tractable scientifically or totally intractable Black Swans

What I call “probability distribution” here is the model used to calculate the odds of different events, how they are distributed.   When I say that an event is distributed according to the “bell curve,” I mean that the Gaussian bell curve (after C.F. Gauss; more on him later) can help provide probabilities of various occurrences.