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Suboptimality in perceptual decision making

Published online by Cambridge University Press:  27 February 2018

Dobromir Rahnev  and
Rachel N. Denison
Dobromir Rahnev
Affiliation:
School of Psychology, Georgia Institute of Technology, Atlanta, GA 30332. [email protected]
Rachel N. Denison
Affiliation:
Department of Psychology and Center for Neural Science, New York University, New York, NY 10003. [email protected]
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Abstract

Human perceptual decisions are often described as optimal. Critics of this view have argued that claims of optimality are overly flexible and lack explanatory power. Meanwhile, advocates for optimality have countered that such criticisms single out a few selected papers. To elucidate the issue of optimality in perceptual decision making, we review the extensive literature on suboptimal performance in perceptual tasks. We discuss eight different classes of suboptimal perceptual decisions, including improper placement, maintenance, and adjustment of perceptual criteria; inadequate tradeoff between speed and accuracy; inappropriate confidence ratings; misweightings in cue combination; and findings related to various perceptual illusions and biases. In addition, we discuss conceptual shortcomings of a focus on optimality, such as definitional difficulties and the limited value of optimality claims in and of themselves. We therefore advocate that the field drop its emphasis on whether observed behavior is optimal and instead concentrate on building and testing detailed observer models that explain behavior across a wide range of tasks. To facilitate this transition, we compile the proposed hypotheses regarding the origins of suboptimal perceptual decisions reviewed here. We argue that verifying, rejecting, and expanding these explanations for suboptimal behavior – rather than assessing optimality per se – should be among the major goals of the science of perceptual decision making.

Keywords

Bayesian decision theorycue combinationmodelingoptimalityperceptual decision makingsuboptimalityuncertaintyvision
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 41 , 2018 , e223
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

Authors D. Rahnev and R. N. Denison contributed equally to this work.

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