The wisdom of crowds versus the madness of mobs: An evolutionary model of bias, polarization, and other challenges to collective intelligence
The wisdom of crowds versus the madness of mobs: An evolutionary model of bias, polarization, and other challenges to collective intelligence
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群体的智慧与暴民的疯狂：偏见、两极分化和集体智慧面临的其他挑战的进化模型
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Ruixun Zhang
中科院分区：
文献类型：
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作者：
A. Lo;Ruixun Zhang
尽管集体智慧在金融市场和其他领域取得了成功，但在许多关键情况下，包括偶尔但反复发生的金融危机、政治两极分化和僵局以及各种形式的偏见和歧视，集体智慧似乎都不够。我们提出了一个进化的框架，提供了基本的见解异质性和反馈回路的作用，有助于失败的集体智慧。该框架是基于影响健身行为的二元选择模型;因此，行为是由进化动力学和环境条件的随机变化塑造的。在这个框架中，我们得出集体智慧是进化的一种涌现属性，并指定了它失败的条件。我们发现，政治极化出现在随机环境中的生殖风险是相关的个人。当个人错误地将随机不良事件归因于可能与这些事件无关的可观察特征时，偏见和歧视就会出现。此外，进化中的路径依赖和负反馈可能会导致更强的偏见和歧视水平，这是局部进化稳定的策略。这些结果表明，潜在的政策干预，以防止这种失败的轻推“暴徒的疯狂”对“群众的智慧”，通过有针对性的环境变化。
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 loops in contributing to failures of collective intelligence. The framework is based on a binary choice model of behavior that affects fitness; hence, behavior is shaped by evolutionary dynamics and stochastic changes in environmental conditions. We derive collective intelligence as an emergent property of evolution in this framework, and also specify conditions under which it 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.