Muons penetrate much further than X-rays, they do essentially zero damage, and they are provided for free by the cosmos.
Image credit: Science Source/Digital Globe.
Edited by David Funder, University of California, Riverside, CA, and accepted by the Editorial Board December 2, 2014 (received for review September 28, 2014)
Significance
This study compares the accuracy of personality judgment—a ubiquitous and important social-cognitive activity—between computer models and humans. Using several criteria, we show that computers’ judgments of people’s personalities based on their digital footprints are more accurate and valid than judgments made by their close others or acquaintances (friends, family, spouse, colleagues, etc.). Our findings highlight that people’s personalities can be predicted automatically and without involving human social-cognitive skills.
Abstract
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.
Footnotes
↵1W.Y. and M.K. contributed equally to this work.
- ↵2To whom correspondence should be addressed. Email: yw341{at}cam.ac.uk.
Author contributions: W.Y. and M.K. designed research; W.Y., M.K., and D.S. performed research; W.Y. and M.K. contributed new reagents/analytic tools; W.Y. and M.K. analyzed data; and W.Y., M.K., and D.S. wrote the paper.
Conflict of interest statement: D.S. received revenue as the owner of the myPersonality Facebook application.
This article is a PNAS Direct Submission. D.F. is a guest editor invited by the Editorial Board.
Data deposition: The data used in the study are shared with the academic community at mypersonality.org.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1418680112/-/DCSupplemental.
Freely available online through the PNAS open access option.
Computers judge personalities better than humans
Article Classifications
- Social Sciences
- Psychological and Cognitive Sciences
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