Rahnev Dobromir, Denison Rachel N
School of Psychology, Georgia Institute of Technology, Atlanta, GA 30332.
Department of Psychology and Center for Neural Science, New York University, New York, NY 10003.
Behav Brain Sci. 2018 Feb 27;41:e223. doi: 10.1017/S0140525X18000936.
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.
人类的感知决策通常被描述为最优的。这一观点的批评者认为,最优性的说法过于灵活且缺乏解释力。与此同时,最优性的支持者反驳称,此类批评仅针对少数几篇精选论文。为阐明感知决策中的最优性问题,我们回顾了关于感知任务中次优表现的大量文献。我们讨论了八类不同的次优感知决策,包括感知标准的不当设定、维持和调整;速度与准确性之间的权衡不足;置信度评级不当;线索组合中的权重错误;以及与各种感知错觉和偏差相关的发现。此外,我们还讨论了专注于最优性的概念缺陷,如定义困难以及最优性主张本身的有限价值。因此,我们主张该领域应不再强调观察到的行为是否最优,而是专注于构建和测试能够解释广泛任务中行为的详细观察者模型。为推动这一转变,我们汇总了此处所回顾的关于次优感知决策起源的假设。我们认为,验证、反驳和扩展这些关于次优行为的解释——而非评估最优性本身——应成为感知决策科学的主要目标之一。