Priors and payoffs in confidence judgments

Abstract

Priors and payo↵s are known to a↵ect perceptual decision-making, but little is understood about how they influence confidence judgments. For optimal perceptual decision-making, both priors and payo↵s should be considered when selecting a response. However, for confidence to reflect the probability of being correct in a perceptual decision, priors should a↵ect confidence but payo↵s should not. To experimentally test whether human observers follow this normative behavior for natural confidence judgments, we conducted an orientation-discrimination task with varied priors and payo↵s that probed both perceptual and metacognitive decision-making. The placement of discrimination and confidence criteria were examined according to several plausible Signal Detection Theory models. In the normative model, observers use the optimal discrimination criterion (i.e., the criterion that maximizes expected gain) and confidence criteria that shift with the discrimination criterion that maximizes accuracy (i.e., are not a↵ected by payo↵s). No observer was consistent with this model, with the majority exhibiting non-normative confidence behavior. One subset of observers ignored both priors and payo↵s for confidence, always fixing the confidence criteria around the neutral discrimination criterion. The other group of observers incorrectly incorporated payo↵s into their confidence by always shifting their confidence criteria with the same gains-maximizing criterion used for discrimination. Such metacognitive mistakes could have negative consequences outside the 2 laboratory setting, particularly when priors or payo↵s are not matched for all the possible decision alternatives.

Is blindsight possible under signal detection theory? Comment on Phillips (2021).

“…Other studies have suggested that perceptual and postperceptual biases can be distinguished by their different effects on confidence ratings: While perceptual biases typically induce shifts in confidence, response biases (induced for instance by changing the payoff structure of the task) do not necessarily do so (Gallagher et al, 2018(Gallagher et al, , 2019; see also Locke et al, 2020).…”

Affective Bias Through the Lens of Signal Detection Theory

“…Namely, the need for our sense of confidence to best reflect the true probability of being correct, as sacrificing some gains for better accuracy may foster more accurate judgements of perceptual confidence (Locke, Gaffin-Cahn, Hosseinizaveh, Mamassian, & Landy, 2020). The payoffs of a task can influence confidence ratings (Lebreton et al, 2018;Locke et al, 2020) despite not changing that probability that the decision was correct. For example, this can be an overconfidence when reporting the highly-rewarded stimulus and underconfidence when reporting the low-reward option.…”

“…Additionally, confidence judgements, on the correctness of their decision, could be included after every trial. Standard extensions of the SDT framework for confidence would then reveal if that observer let the rewards influence their confidence (Locke et al, 2020). If affective bias is driven by a need for high accuracy, we would see the anxiety/mood disorder individuals giving greater preference for being correct over earning more reward and being more susceptible to letting reward influence their sense of confidence.…”

Suprathreshold perceptual decisions constrain models of confidence

“…In the case of categorical confidence judgements (e.g., binary report, scale, etc. ), additional confidence criteria delineate the mapping between distance and confidence [ 6 , 7 , 21 ]. Most DFC-metric models also allow this sensory measurement to differ from that used for the perceptual decision [ 22 ], either by additional confidence noise corrupting the measurement [ 23 – 25 ] and/or from altering the measurement with parallel decision processes [ 7 , 26 ].…”