The Wisdom of Crowds vs. the Madness of Mobs: An Evolutionary Model of Bias, Polarization, and Other Challenges to Collective Intelligence

50 Pages Posted: 22 Dec 2021 Last revised: 25 Apr 2022

See all articles by Andrew W. Lo

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering; Santa Fe Institute

Ruixun Zhang

Peking University; MIT Laboratory for Financial Engineering

Date Written: December 6, 2021

Abstract

Despite its success in financial markets and other domains, collective intelligence seems to fall short in many critical contexts, including infrequent but repeated financial crises, political polarization and deadlock, and various forms of bias and discrimination. We propose an evolutionary framework that provides fundamental insights into the role of heterogeneity and feedback in contributing to collective intelligence failures. The framework is based on a binary choice model of behavior that affects reproductive success, hence behavior is shaped by natural selection and stochastic changes in environmental conditions. We derive collective intelligence as an emergent property of evolution in this framework. We also specify conditions under which collective intelligence fails. We find that political polarization emerges in stochastic environments with reproductive risks that are correlated across individuals. Bias and discrimination emerge when individuals incorrectly attribute random adverse events to observable features that may have nothing to do with those events. In addition, path dependence and negative feedback in evolution may lead to even stronger biases and levels of discrimination, which are locally evolutionarily stable strategies. These results suggest potential policy interventions to prevent such failures by nudging the "madness of mobs'' towards the "wisdom of crowds'' through targeted shifts in the environment.

Keywords: Collective intelligence, Political polarization, Bias, Discrimination, Evolutionarily stable strategy, Group selection

Suggested Citation

Lo, Andrew W. and Zhang, Ruixun, The Wisdom of Crowds vs. the Madness of Mobs: An Evolutionary Model of Bias, Polarization, and Other Challenges to Collective Intelligence (December 6, 2021). Available at SSRN: https://ssrn.com/abstract=3979339 or http://dx.doi.org/10.2139/ssrn.3979339

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

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HOME PAGE: http://web.mit.edu/alo/www

Santa Fe Institute

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Ruixun Zhang (Contact Author)

Peking University ( email )

5 Yiheyuan Road
Beijing, Beijing 100871
China

HOME PAGE: http://www.math.pku.edu.cn/teachers/ZhangRuixun%20/index.html

MIT Laboratory for Financial Engineering

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Cambridge, MA 02142
United States

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