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Confidence reflects a noisy decision reliability estimate

Nature Human Behaviour volume 7, pages 142–154 (2023)Cite this article

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Abstract

Decisions vary in difficulty. Humans know this and typically report more confidence in easy than in difficult decisions. However, confidence reports do not perfectly track decision accuracy, but also reflect response biases and difficulty misjudgements. To isolate the quality of confidence reports, we developed a model of the decision-making process underlying choice-confidence data. In this model, confidence reflects a subject’s estimate of the reliability of their decision. The quality of this estimate is limited by the subject’s uncertainty about the uncertainty of the variable that informs their decision (‘meta-uncertainty’). This model provides an accurate account of choice-confidence data across a broad range of perceptual and cognitive tasks, investigated in six previous studies. We find meta-uncertainty varies across subjects, is stable over time, generalizes across some domains and can be manipulated experimentally. The model offers a parsimonious explanation for the computational processes that underlie and constrain the sense of confidence.

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Fig. 1: CASANDRE, a two-stage process model of decision confidence, accounts for the relation between confidence reports and choice consistency.
Fig. 2: Impact of the different model components on primary choice behaviour and confidence reports.
Fig. 3: Comparison of different model architectures.
Fig. 4: Model recovery analysis.
Fig. 5: Evaluating meta-uncertainty as a psychological construct.
Fig. 6: Meta-uncertainty depends on task structure.

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Data availability

This study generated no new data. The data used in this study are available from the Confidence Database (available at: https://osf.io/s46pr/).

Code availability

The code supporting the findings of this study and a software package implementing the CASANDRE model is publicly available (https://github.com/gorislab/CASANDRE.git).

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Acknowledgements

We thank the creators and contributors to the Confidence Database and J. Navajas for making their data available. This work was supported by the US National Science Foundation (Graduate Research Fellowship to Z.M.B.-S.), the US National Institutes of Health (grant nos. T32 EY021462 and K99 EY032102 to C.M.Z., and EY032999 to R.L.T.G.), and the Whitehall Foundation (grant no. UTA19-000535 to R.L.T.G.). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

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  1. These authors contributed equally: Zoe M. Boundy-Singer, Corey M. Ziemba.

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  1. Center for Perceptual Systems, The University of Texas at Austin, Austin, TX, USA

    Zoe M. Boundy-Singer, Corey M. Ziemba & Robbe L. T. Goris

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Z.M.B.-S., C.M.Z. and R.L.T.G. conceived the study, developed the theory, performed the simulations, analysed the data, and wrote the paper.

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Correspondence to Robbe L. T. Goris.

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Boundy-Singer, Z.M., Ziemba, C.M. & Goris, R.L.T. Confidence reflects a noisy decision reliability estimate. Nat Hum Behav 7, 142–154 (2023). https://doi.org/10.1038/s41562-022-01464-x

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