Confidence reflects a noisy decision reliability estimate

Zoe M. Boundy-Singer, Corey M. Ziemba and Robbe L. T. Goris ()
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Zoe M. Boundy-Singer: Center for Perceptual Systems, The University of Texas at Austin
Corey M. Ziemba: Center for Perceptual Systems, The University of Texas at Austin
Robbe L. T. Goris: Center for Perceptual Systems, The University of Texas at Austin

Nature Human Behaviour, 2023, vol. 7, issue 1, 142-154

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41562-022-01464-x

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