The fair reward problem: the illusion of success and how to solve it
Didier Sornette, Spencer Wheatley, Peter Cauwels

TL;DR
This paper examines the challenge of fairly rewarding merit in complex, uncertain systems where luck often confounds success, proposing new measures and an evolutionary framework to better discern true merit.
Contribution
It introduces three measures of merit—raw outcome, risk-adjusted outcome, and prospective—and formalizes an evolutionary system to improve fairness in reward allocation.
Findings
Risk-adjusted and prospective measures better identify true merit.
Analysis of finance, politics, and science highlights current shortcomings.
Proposed solutions aim to foster meritocracy and system resilience.
Abstract
Humanity has been fascinated by the pursuit of fortune since time immemorial, and many successful outcomes benefit from strokes of luck. But success is subject to complexity, uncertainty, and change - and at times becoming increasingly unequally distributed. This leads to tension and confusion over to what extent people actually get what they deserve (i.e., fairness/meritocracy). Moreover, in many fields, humans are over-confident and pervasively confuse luck for skill (I win, it's skill; I lose, it's bad luck). In some fields, there is too much risk taking; in others, not enough. Where success derives in large part from luck - and especially where bailouts skew the incentives (heads, I win; tails, you lose) - it follows that luck is rewarded too much. This incentivizes a culture of gambling, while downplaying the importance of productive effort. And, short term success is often…
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