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AI Personality Extraction from Faces: Labor Market Implications

Author

Listed:
  • Marius Guenzel
  • Shimon Kogan
  • Marina Niessner
  • Kelly Shue

Abstract

Human capital—encompassing cognitive skills and personality traits—is central for labor-market success, yet personality remains difficult to measure at scale. Leveraging advances in AI and comprehensive LinkedIn microdata, we extract the Big 5 personality traits from facial images of 96,000 MBA graduates, and demonstrate that this novel “Photo Big 5” predicts school rank, job matching, compensation, job transitions, and career advancement. The Photo Big 5 provides predictive power comparable to race, attractiveness, and educational background, and is only weakly correlated with cognitive measures such as test scores. We show that individuals systematically sort into occupations where their personality traits are valued and earn higher wages when traits align with occupational demands. While the scalability of the Photo Big 5 enables new academic insights into the role of personality in labor markets, its growing use in industry screening raises important ethical concerns regarding statistical discrimination and individual autonomy.

Suggested Citation

  • Marius Guenzel & Shimon Kogan & Marina Niessner & Kelly Shue, 2026. "AI Personality Extraction from Faces: Labor Market Implications," NBER Working Papers 34808, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:34808
    Note: CF LS
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    More about this item

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • M5 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics

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