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Information aggregation and collective intelligence beyond the wisdom of crowds

Nature Reviews Psychology volume 1, pages 345–357 (2022)Cite this article

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Abstract

In humans and other gregarious animals, collective decision-making is a robust behavioural feature of groups. Pooling individual information is also fundamental for modern societies, in which digital technologies have exponentially increased the interdependence of individual group members. In this Review, we selectively discuss the recent human and animal literature, focusing on cognitive and behavioural mechanisms that can yield collective intelligence beyond the wisdom of crowds. We distinguish between two group decision-making situations: consensus decision-making, in which a group consensus is required, and combined decision-making, in which a group consensus is not required. We show that in both group decision-making situations, cognitive and behavioural algorithms that capitalize on individual heterogeneity are the key for collective intelligence to emerge. These algorithms include accuracy or expertise-weighted aggregation of individual inputs and implicit or explicit coordination of cognition and behaviour towards division of labour. These mechanisms can be implemented either as ‘cognitive algebra’, executed mainly within the mind of an individual or by some arbitrating system, or as a dynamic behavioural aggregation through social interaction of individual group members. Finally, we discuss implications for collective decision-making in modern societies characterized by a fluid but auto-correlated flow of information and outline some future directions.

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Fig. 1: Consensus decision-making and combined decision-making with human and animal examples.
Fig. 2: Consensus decision-making based on the combination of communicated confidence can fail to achieve the best possible group accuracy.
Fig. 3: How social learning strategies may generate collective intelligence in combined decision-making.

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Acknowledgements

This work was supported by Japan Society for the Promotion of Science (JP16H06324) and Japan Science and Technology Agency CREST (JPMJCR17A4 (17941861)) to T.K.

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Authors and Affiliations

  1. Department of Social Psychology, The University of Tokyo, Tokyo, Japan

    Tatsuya Kameda

  2. Centre for Experimental Research in Social Sciences, Hokkaido University, Sapporo, Japan

    Tatsuya Kameda

  3. Department of Psychology, University of Konstanz, Konstanz, Germany

    Wataru Toyokawa

  4. Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany

    Wataru Toyokawa

  5. Department of Psychology, Loyola University of Chicago, Chicago, IL, USA

    R. Scott Tindale

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  2. Wataru Toyokawa
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  3. R. Scott Tindale
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Glossary

Herding

The alignment of the thoughts or behaviours of individuals in a group (herd) through local interaction and without centralized coordination.

Unanimity rule

A voting rule that requires unanimous approval by all members for a group to decide on an alternative.

Tandem-running

A recruiting behaviour that guides another nest mate to new food sources or nest sites, whereby a knowledgeable scout individual adjusts her behaviour to ensure that the follower learns the route.

Quorum threshold

A critical threshold number of individuals in a group performing a behaviour, upon which the entire group shifts from an exploration phase to a commitment or action phase.

Forecasting tournament

A series of tournaments sponsored by the Intelligence Advanced Research Projects Activity in the United States between 2011 and 2014, in which five university-based research groups competed to develop new methods of assigning probabilistic estimates to high-impact events around the globe.

Information scrounging

A behavioural strategy that avoids the costs of information search, relying instead on information produced by others.

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Kameda, T., Toyokawa, W. & Tindale, R.S. Information aggregation and collective intelligence beyond the wisdom of crowds. Nat Rev Psychol 1, 345–357 (2022). https://doi.org/10.1038/s44159-022-00054-y

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