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