- The Experience
- The Programs
- MBA Program
- MSx Program
- PhD Program
- Executive Education
- Stanford Ignite
- Research Fellows Program
- Summer Institute for General Management
- Stanford LEAD Certificate: Corporate Innovation
- Stanford Innovation & Entrepreneurship Certificate
- Executive Program for Nonprofit Leaders
- Executive Program in Social Entrepreneurship
- Executive Program for Education Leaders
- Stanford go.to.market
- Faculty & Research
- Insights
- Alumni
- Events
You are here
Computer-based personality judgments are more accurate than those made by humans
Computer-based personality judgments are more accurate than those made by humans
Proceedings of the National Academy of Sciences of the United States of America. January
27, 2015, Vol. 112, Issue 4, Pages 1036–1040
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.