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Wisdom of crowds

Over a century of research showing that aggregating the opinions, estimates, or judgments of many ordinary people can produce results equal to or better than individual experts. The core insight: diversity + decentralization + aggregation can outperform centralized expertise.

Key principles

Diversity of opinion: Participants have different perspectives, information sources, and cognitive approaches.

Independence: Judgments are formed without direct coordination or conformity pressure.

Decentralization: Participants do not need to be co-located or part of a hierarchical organization.

Aggregation: Averaging or voting mechanisms combine individual judgments into a collective estimate.

Applications to misinformation

Platforms can harness the wisdom of crowds to scale fact-checking. Rather than relying on a small number of professional fact-checkers, open the problem to the community: users flag misleading content and add context; aggregation mechanisms identify which flags and context are most credible across diverse populations. Examples: Twitter's Community Notes, Birdwatch, similar systems.

Success depends on maintaining diversity (so one political faction cannot dominate) and designing aggregation mechanisms that reward accuracy over partisanship.

Key papers and videos

  • Rand — How Polarization May Help Combat Misinformation — Theoretical model of competing motivations (accuracy vs. partisanship) in crowd-sourced flagging; empirical evidence that polarized individuals may enhance aggregated accuracy by more strongly flagging false information.