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Published on: June 3, 2013
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Computer-based personality judgments are more accurate than those made by humans
Wu Youyou1, Michal Kosinski2, David Stillwell3
1Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom; and yw341@cam.ac.uk.
Summary
Computer models accurately predict personality using digital footprints, outperforming human judgment. This advancement in personality assessment offers new possibilities and concerns for various fields.
Area of Science:
- Social Psychology
- Computational Social Science
- Psychological Assessment
Background:
- Accurate personality judgment is crucial for social interaction.
- Social-cognitive skills enable human personality assessment.
- Machine learning models demonstrate potential in personality judgment.
Purpose of the Study:
- To compare the accuracy of human versus computer-based personality judgments.
- To evaluate the predictive validity of computer-derived personality insights.
- To explore the implications of AI in personality assessment.
Main Methods:
- Utilized a large dataset of 86,220 volunteers.
- Collected personality data via a 100-item questionnaire.
- Analyzed personality predictions derived from Facebook Likes (digital footprint) and peer ratings.
Main Results:
- Computer predictions from Facebook Likes (r = 0.56) surpassed those from Facebook friends (r = 0.49).
- Computer models exhibited superior interjudge agreement.
- Computer-based personality judgments demonstrated higher external validity in predicting life outcomes, sometimes exceeding self-ratings.
Conclusions:
- AI-driven personality assessment, particularly using digital footprints, can be more accurate than human judgment.
- The findings highlight significant opportunities and challenges for psychological assessment, marketing, and privacy.
- Further research is needed to understand the ethical implications of AI in understanding human personality.
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