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The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments

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  • Julia A. Minson

    (Harvard University, Cambridge, Massachusetts 02138)

  • Jennifer S. Mueller

    (University of San Diego, San Diego, California 92110)

  • Richard P. Larrick

    (Duke University, Durham, North Carolina 27708)

Abstract

We evaluate the effect of discussion on the accuracy of collaborative judgments. In contrast to prior research, we show that discussion can either aid or impede accuracy relative to the averaging of collaborators’ independent judgments, as a systematic function of task type and interaction process. For estimation tasks with a wide range of potential estimates, discussion aided accuracy by helping participants prevent and eliminate egregious errors. For estimation tasks with a naturally bounded range, discussion following independent estimates performed on par with averaging. Importantly, if participants did not first make independent estimates, discussion greatly harmed accuracy by limiting the range of considered estimates, independent of task type. Our research shows that discussion can be a powerful tool for error reduction, but only when appropriately structured: Decision makers should form independent judgments to consider a wide range of possible answers, and then use discussion to eliminate extremely large errors.

Suggested Citation

  • Julia A. Minson & Jennifer S. Mueller & Richard P. Larrick, 2018. "The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments," Management Science, INFORMS, vol. 64(9), pages 4177-4192, September.
    • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:9:p:4177-4192
    DOI: 10.1287/mnsc.2017.2823
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    References listed on IDEAS

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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. repec:cup:judgdm:v:14:y:2019:i:3:p:349-363 is not listed on IDEAS
    3. Thomas Schultze & Andreas Mojzisch & Stefan Schulz-Hardt, 2019. "Why dyads heed advice less than individuals do," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(3), pages 349-363, May.
    4. Vincenz Frey & Arnout van de Rijt, 2021. "Social Influence Undermines the Wisdom of the Crowd in Sequential Decision Making," Management Science, INFORMS, vol. 67(7), pages 4273-4286, July.
    5. Joshua Becker & Abdullah Almaatouq & EmH{o}ke-'Agnes Horv'at, 2020. "Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion," Papers 2009.07202, arXiv.org, revised Mar 2021.
    6. Joshua Becker & Douglas Guilbeault & Ned Smith, 2021. "The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy," Papers 2104.11300, arXiv.org.
    7. Lea Ruesch & Murat Tarakci & Maria Besiou & Niels Van Quaquebeke, 2022. "Orchestrating coordination among humanitarian organizations," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 1977-1996, May.
    8. Steffen Keck & Wenjie Tang, 2021. "Elaborating or Aggregating? The Joint Effects of Group Decision-Making Structure and Systematic Errors on the Value of Group Interactions," Management Science, INFORMS, vol. 67(7), pages 4287-4309, July.
    9. 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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