Resolving uncertainty in a social world

Subjects

Abstract

Consider the range of social behaviours we engage in every day. In each case, there are a multitude of unknowns, reflecting the many sources of uncertainty inherent to social inference. We describe how uncertainty manifests in social environments (the thoughts and intentions of others are largely hidden, making it difficult to predict a person’s behaviour) and why people are motivated to reduce the aversive feelings generated by uncertainty. We propose a three-part model whereby social uncertainty is initially reduced through automatic modes of inference (such as impression formation) before more control-demanding modes of inference (such as perspective-taking) are deployed to narrow one’s predictions even more. Finally, social uncertainty is attenuated further through learning processes that update these predictions based on new information. Our framework integrates research across fields to offer an account of the mechanisms motivating social cognition and action, laying the groundwork for future experiments that can illuminate the impact of uncertainty on social cognition.

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Fig. 1: Model for how humans resolve social uncertainty.
Fig. 2: Iterative reduction of social uncertainty through inference and learning.
Fig. 3: The unfolding of automatic and controlled components of social inference.

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Acknowledgements

We thank C. Dean Wolf for creation of the figures and thank M. Frank and D. Tamir for helpful comments on early drafts. This research was supported by a Center of Biomedical Research Excellence grant (P20GM103645) from the National Institute of General Medical Sciences to O.F.H. and A.S.

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FeldmanHall, O., Shenhav, A. Resolving uncertainty in a social world. Nat Hum Behav 3, 426–435 (2019). https://doi.org/10.1038/s41562-019-0590-x

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