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Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds

Author

Listed:
  • Joaquin Navajas

    (Universidad Torcuato Di Tella
    University College London)

  • Tamara Niella

    (Universidad Torcuato Di Tella
    University of Oregon)

  • Gerry Garbulsky

    (TED)

  • Bahador Bahrami

    (University College London
    Ludwig Maximilian University)

  • Mariano Sigman

    (Universidad Torcuato Di Tella)

Abstract

The aggregation of many independent estimates can outperform the most accurate individual judgement 1–3 . This centenarian finding 1,2 , popularly known as the 'wisdom of crowds' 3 , has been applied to problems ranging from the diagnosis of cancer 4 to financial forecasting 5 . It is widely believed that social influence undermines collective wisdom by reducing the diversity of opinions within the crowd. Here, we show that if a large crowd is structured in small independent groups, deliberation and social influence within groups improve the crowd’s collective accuracy. We asked a live crowd (N = 5,180) to respond to general-knowledge questions (for example, "What is the height of the Eiffel Tower?"). Participants first answered individually, then deliberated and made consensus decisions in groups of five, and finally provided revised individual estimates. We found that averaging consensus decisions was substantially more accurate than aggregating the initial independent opinions. Remarkably, combining as few as four consensus choices outperformed the wisdom of thousands of individuals.

Suggested Citation

  • Joaquin Navajas & Tamara Niella & Gerry Garbulsky & Bahador Bahrami & Mariano Sigman, 2018. "Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds," Nature Human Behaviour, Nature, vol. 2(2), pages 126-132, February.
    • Handle: RePEc:nat:nathum:v:2:y:2018:i:2:d:10.1038_s41562-017-0273-4
    DOI: 10.1038/s41562-017-0273-4
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    Citations

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    Cited by:

    1. Joshua Aaron Becker & Douglas Guilbeault & Edward Bishop Smith, 2022. "The Crowd Classification Problem: Social Dynamics of Binary-Choice Accuracy," Management Science, INFORMS, vol. 68(5), pages 3949-3965, May.
    2. Mariam Maki Sy & Charles C. Figuières & Helene Rey-Valette & Richard B Howarth & Rutger de Wit, 2021. "Valuation of Ecosystem Services and Social Choice: The Impact of Deliberation in the context of two different Aggregation Rules," Working Papers halshs-03145117, HAL.
    3. Valeria Burdea & Jonathan Woon, 2023. "Getting it Right: Communication, Voting, and Collective Truth Finding," Rationality and Competition Discussion Paper Series 443, CRC TRR 190 Rationality and Competition.
    4. Mavrodiev, Pavlin & Schweitzer, Frank, 2021. "The ambigous role of social influence on the wisdom of crowds: An analytic approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    5. Joshua Becker & Douglas Guilbeault & Ned Smith, 2021. "The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy," Papers 2104.11300, arXiv.org.
    6. Boris Maciejovsky & David V. Budescu, 2020. "Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets," Organization Science, INFORMS, vol. 31(6), pages 1497-1514, November.
    7. Jon Atwell & Marlon Twyman II, 2023. "Metawisdom of the Crowd: How Choice Within Aided Decision Making Can Make Crowd Wisdom Robust," Papers 2308.15451, arXiv.org.

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