Computer-based personality judgments are more accurate than those made by humans

作者：Wu Youyou, Michał Kosiński, David Stillwell · 发表于：Proceedings of the National Academy of Sciences · 年份：2015 · DOI：10.1073/pnas.1418680112 · 被引用次数：1115 · 研究领域：Personality Traits and Psychology、Evolutionary Psychology and Human Behavior、Cognitive Abilities and Testing

Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.