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Adolescents show collective intelligence which can be driven by a geometric mean rule of thumb

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  • Christos C Ioannou
  • Gabriel Madirolas
  • Faith S Brammer
  • Hannah A Rapley
  • Gonzalo G de Polavieja

Abstract

How effective groups are in making decisions is a long-standing question in studying human and animal behaviour. Despite the limited social and cognitive abilities of younger people, skills which are often required for collective intelligence, studies of group performance have been limited to adults. Using a simple task of estimating the number of sweets in jars, we show in two experiments that adolescents at least as young as 11 years old improve their estimation accuracy after a period of group discussion, demonstrating collective intelligence. Although this effect was robust to the overall distribution of initial estimates, when the task generated positively skewed estimates, the geometric mean of initial estimates gave the best fit to the data compared to other tested aggregation rules. A geometric mean heuristic in consensus decision making is also likely to apply to adults, as it provides a robust and well-performing rule for aggregating different opinions. The geometric mean rule is likely to be based on an intuitive logarithmic-like number representation, and our study suggests that this mental number scaling may be beneficial in collective decisions.

Suggested Citation

  • Christos C Ioannou & Gabriel Madirolas & Faith S Brammer & Hannah A Rapley & Gonzalo G de Polavieja, 2018. "Adolescents show collective intelligence which can be driven by a geometric mean rule of thumb," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-17, September.
  • Handle: RePEc:plo:pone00:0204462
    DOI: 10.1371/journal.pone.0204462
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    References listed on IDEAS

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    1. Gabriel Madirolas & Gonzalo G de Polavieja, 2015. "Improving Collective Estimations Using Resistance to Social Influence," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-16, November.
    2. David Engel & Anita Williams Woolley & Lisa X Jing & Christopher F Chabris & Thomas W Malone, 2014. "Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-16, December.
    3. Sniezek, Janet A. & Henry, Rebecca A., 1989. "Accuracy and confidence in group judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(1), pages 1-28, February.
    4. Anonymous, 2009. "Abstract of the discussion," British Actuarial Journal, Cambridge University Press, vol. 15(1), pages 202-217, March.
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    Cited by:

    1. Bertrand Jayles & Ramon Escobedo & Stéphane Cezera & Adrien Blanchet & Tatsuya Kameda & Clément Sire & Guy Théraulaz, 2020. "The impact of incorrect social information on collective wisdom in human groups," Post-Print hal-03019820, HAL.
    2. Bertrand Jayles & Clément Sire & Ralf H J M Kurvers, 2021. "Crowd control: Reducing individual estimation bias by sharing biased social information," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-28, November.

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