Collective Intelligence: Crowd Wisdom Versus Herding

Andreas Engert ()

CRC TR 224 Discussion Paper Series from University of Bonn and University of Mannheim, Germany

Abstract: The chapter provides an introduction to the social science of ‘collective intelligence’, the aggregation of individual judgments for purposes of collective decision making. It starts from the basic logic of the Condorcet jury theorem and summarizes the main determinants of the accuracy of collective cognition. The recent research has focused on developing and refining formal aggregation methods beyond majority voting. The chapter presents the main findings on the two general approaches, surveying and prediction markets. It then contrasts these techniques with informal deliberation as a basic and prevalent aggregation mechanism. One conclusion is that while deliberation is prone to herding and can distort collective judgment, it is also more versatile and robust than formal mechanisms.

JEL-codes: K0 K41 M10 (search for similar items in EconPapers)
Pages: 32
Date: 2020-04
New Economics Papers: this item is included in nep-cdm and nep-hpe
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Persistent link: https://EconPapers.repec.org/RePEc:bon:boncrc:crctr224_2020_166

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