Uploaded June 2026 | Updated September 2026, 3 weeks ago
Does personality matter in the labor market?
Marina Niessner, an assistant professor of finance at Indiana University’s Kelley School of Business, co-authored “AI Personality Extraction from Faces: Labor Market Effects” and presented the paper at the Fink Center for Finance’s seventh annual Conference on Financial Markets. Niessner investigated whether artificial intelligence can infer personality traits from facial images and what this means for labor market outcomes.
Using AI‑based analysis of LinkedIn photos, her study predicts Big Five personality traits and links them to detailed career outcomes for MBA graduates, encompassing school rank, compensation, job tenure and occupational sorting. The results show that photo‑based personality measures have meaningful predictive power beyond traditional credentials such as GPA and test scores, and that personality-job match is priced in the labor market. Followed by remarks by Asaf Manela, an associate professor of finance at Washington University’s Olin Business School, Niessner also discussed ethical concerns around AI use in hiring and previewed related research on facial analysis in credit screening.
The annual conference, hosted by UCLA Anderson School of Management, combines theoretical and methodological rigor with timely policy relevance. Anderson’s leadership tenets include directly confronting both the opportunities and dangers of AI in academic scholarship, while fostering critical dialogue on how institutions must adopt ethical standards for evaluation, disclosure, transparency and accountability in an AI‑accelerated research environment.
00:00 Introduction
00:02 Presentation
22:55 Discussion
Learn more about the Fink Center’s annual Conference on Financial Markets:
https://www.anderson.ucla.edu/about/centers/fink-center-for-finance/news-and-events/conference-financial-markets
#algorithmicbias #facialrecognition #neuralnetworks
Does personality matter in the labor market?
Marina Niessner, an assistant professor of finance at Indiana University’s Kelley School of Business, co-authored “AI Personality Extraction from Faces: Labor Market Effects” and presented the paper at the Fink Center for Finance’s seventh annual Conference on Financial Markets. Niessner investigated whether artificial intelligence can infer personality traits from facial images and what this means for labor market outcomes.
Using AI‑based analysis of LinkedIn photos, her study predicts Big Five personality traits and links them to detailed career outcomes for MBA graduates, encompassing school rank, compensation, job tenure and occupational sorting. The results show that photo‑based personality measures have meaningful predictive power beyond traditional credentials such as GPA and test scores, and that personality-job match is priced in the labor market. Followed by remarks by Asaf Manela, an associate professor of finance at Washington University’s Olin Business School, Niessner also discussed ethical concerns around AI use in hiring and previewed related research on facial analysis in credit screening.
The annual conference, hosted by UCLA Anderson School of Management, combines theoretical and methodological rigor with timely policy relevance. Anderson’s leadership tenets include directly confronting both the opportunities and dangers of AI in academic scholarship, while fostering critical dialogue on how institutions must adopt ethical standards for evaluation, disclosure, transparency and accountability in an AI‑accelerated research environment.
00:00 Introduction
00:02 Presentation
22:55 Discussion
Learn more about the Fink Center’s annual Conference on Financial Markets:
https://www.anderson.ucla.edu/about/centers/fink-center-for-finance/news-and-events/conference-financial-markets
#algorithmicbias #facialrecognition #neuralnetworks
