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Flexible social inference facilitates targeted social learning when rewards are not observable

Nature Human Behaviour volume 7, pages 1767–1776 (2023)Cite this article

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Abstract

Groups coordinate more effectively when individuals are able to learn from others’ successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others’ underlying knowledge and success from observable trajectories of behaviour. We compared our social inference model against simpler heuristics in three studies of human behaviour in a collective-sensing task. Experiment 1 demonstrated that average performance improved as a function of group size at a rate greater than predicted by heuristic models. Experiment 2 introduced artificial agents to evaluate how individuals selectively rely on social information. Experiment 3 generalized these findings to a more complex reward landscape. Taken together, our findings provide insight into the relationship between individual social cognition and the flexibility of collective behaviour.

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Fig. 1: Example states of the collective-sensing task used in computational simulations and first experiment.
Fig. 2: Results of simulations and first experiment.
Fig. 3: Design of second experiment.
Fig. 4: Results of second experiment.
Fig. 5: Results of third experiment.
Fig. 6: State-based analysis of behaviour in third experiment.

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Data availability

All data are available at https://github.com/hawkrobe/emergent-sensing.

Code availability

All experiment and analysis code are available at https://github.com/hawkrobe/emergent-sensing.

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Acknowledgements

A preliminary version of our work reporting experiment 3 appeared at the 2015 Annual Conference of the Cognitive Science Society. This work was supported by the Center for Minds, Brains and Machines (CBMM), funded by NSF STC award CCF-1231216, and NSF Graduate Research Fellowships under grant number 1122374 to P.M.K. and grant number DGE-114747 to R.D.H. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. A.M.B. was supported by the H. Mason Keeler Endowed Professorship in Sports Fisheries Management. Special thanks to C. Torney for providing the code to make the score field gradients, to H. Fang for assisting with analyses and to R. Goldstone for helpful feedback on the interpretation of our results.

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Authors and Affiliations

  1. Department of Psychology, Stanford University, Stanford, CA, USA

    Robert D. Hawkins & Noah D. Goodman

  2. Department of Psychology, University of Wisconsin–Madison, Madison, WI, USA

    Robert D. Hawkins

  3. School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA

    Andrew M. Berdahl

  4. MIT Media Lab, MIT, Cambridge, MA, USA

    Alex ‘Sandy’ Pentland

  5. Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA

    Joshua B. Tenenbaum & P. M. Krafft

  6. Department of Computer Science, Stanford University, Stanford, CA, USA

    Noah D. Goodman

  7. Creative Computing Institute, University of Arts London, London, UK

    P. M. Krafft

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Contributions

R.D.H., P.M.K., A.P., N.D.G. and J.B.T. formulated the study. R.D.H. and P.M.K. designed the experiments, implemented the experiments and analysed the data. R.D.H., P.M.K. and A.M.B. wrote the paper. All authors gave final approval for publication and agree to be held accountable for the work performed therein.

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Correspondence to Robert D. Hawkins.

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Nature Human Behaviour thanks Wataru Toyokawa and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Hawkins, R.D., Berdahl, A.M., Pentland, A.‘. et al. Flexible social inference facilitates targeted social learning when rewards are not observable. Nat Hum Behav 7, 1767–1776 (2023). https://doi.org/10.1038/s41562-023-01682-x

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