推论
贝叶斯推理
心理学
规范性
贝叶斯概率
计算机科学
罕见事件
认知心理学
统计
计量经济学
社会心理学
人工智能
数学
认识论
哲学
作者
Yeon Soon Shin,Yaron Niv
标识
DOI:10.1038/s41562-021-01065-0
摘要
How do we evaluate a group of people after a few negative experiences with some members but mostly positive experiences otherwise? How do rare experiences influence our overall impression? We show that rare events may be overweighted due to normative inference of the hidden causes that are believed to generate the observed events. We propose a Bayesian inference model that organizes environmental statistics by combining similar events and separating outlying observations. Relying on the model's inferred latent causes for group evaluation overweights rare or variable events. We tested the model's predictions in eight experiments where participants observed a sequence of social or non-social behaviours and estimated their average. As predicted, estimates were biased toward sparse events when estimating after seeing all observations, but not when tracking a summary value as observations accrued. Our results suggest that biases in evaluation may arise from inferring the hidden causes of group members' behaviours.
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