'AI Personality Extraction from Faces: Labor Market Implications' by Marius Guenzel, Shimon Kogan, Marina Niessner and Kelly Shue comments
Human capital — encompassing cognitive skills and personality traits — is critical for labor market success, yet the personality component remains difficult to measure at scale. Leveraging advances in artificial intelligence and comprehensive LinkedIn data, 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, compensation, job seniority, industry choice, job transitions, and career advancement. Using administrative records from top-tier MBA programs, we find that the Photo Big 5 exhibits only modest correlations with cognitive measures like GPA and standardized test scores, yet offers comparable incremental predictive power for labor outcomes. Unlike traditional survey-based personality measures, the Photo Big 5 is readily accessible and potentially less susceptible to manipulation, making it suitable for wide adoption in academic research and hiring processes. However, its use in labor market screening raises ethical concerns regarding statistical discrimination and individual autonomy. ...
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In this paper, we depart from using survey-based personality measures, and instead leverage recent advances in artificial intelligence (AI) that enable us to extract personality traits from a single facial image of a person. These advancements, which facilitate the construction of large-scale personality datasets, reflect a broader trend in which AI facial recognition is increasingly adopted across various settings, including matching in dating markets, political affiliation analysis, and targeted marketing.
Using new alternative data—photos from LinkedIn and photo directories of several top U.S. MBA programs—we extract the Big 5 personality traits for 96,000 MBA graduates, for whom we also observe detailed employment outcomes and education histories. We then assess the ability of the novel “Photo Big 5” to predict labor market outcomes such as school rank, compensation, and advancement within organizational hierarchies. We find that, while the vast majority of variation in labor outcomes remains unexplained, the Photo Big 5 provides predictive power comparable to a person’s race, attractiveness, and educational background. Moreover, because the Photo Big 5 exhibits weak correlations with traditional cognitive measures—such as grades and test scores—typically used in labor market screening, it delivers high incremental predictive power. For example, the compensation disparity between individuals in the top quintile versus the bottom quintile of ‘desirable’ Photo Big 5 personality traits is larger than the compensation gap observed between Black and White graduates for men, and about 65% of the Black-White compensation gap for women.
We focus on the Big 5 personality traits because they are the most widely used and extensively studied measures of ‘soft skills’ in finance and economics (e.g., Heckman and Kautz (2012)). The five traits are: Openness (curiosity, aesthetic sensitivity, imagination), Conscientiousness (organization, productiveness, responsibility), Extraversion (sociability, assertiveness, energy level), Agreeableness (compassion, respectfulness, trust), and Neuroti- cism (anxiety, depression, emotional volatility). We study the labor market for MBA grad- uates, as survey and task-based measures of personality are already heavily used as part of hiring and job screening in the MBA labor market. The focus on MBAs also allows us to examine a high-skill population for which we can compare the predictive power of the Photo Big 5 against cognitive measures such as school rank, GPA, and standardized test scores.
The face-based personality extraction draws upon a robust body of scientific research in genetics, psychology, and behavioral science that has empirically established three primary, non-exclusive channels linking facial features and personality. First, an individual’s genetic profile significantly influences both their facial features and personality. Certain variations in DNA correlate with specific facial features, such as nose shape, jawline, and overall facial symmetry, defined broadly as craniofacial characteristics (Claes et al., 2014). Related evidence indicates that 30%-60% of the variance in Big 5 personality traits across individuals is attributable to genetic factors (Vukasovi´c and Bratko, 2015). Further, a growing body of literature has used large-scale genome-wide association studies (GWAS) to investigate the genetic underpinnings of personality traits (e.g., De Moor et al. (2012), Lo et al. (2017), Nagel et al. (2018)), finding that individual genetic variants collectively contribute to the heritability of personality traits and identifying specific genes linked to cognitive performance and personality traits.
Second, a person’s pre- and post-natal environment, especially hormone exposure, has been shown to affect both facial characteristics and personality. Verdonck et al. (1999) and Whitehouse et al. (2015) study the link between post- and pre-natal testosterone exposure and facial structure. Cohen-Bendahan et al. (2005) focus on prenatal hormone exposure and personality traits such as aggression, empathy, and social interest. Szyf et al. (2007) investigate the postnatal effects of the environment on gene expression (i.e., epigenetics) and behavior.
Finally, perceptions of one’s facial features, whether by oneself or others, can influence and be influenced by personality traits (e.g., the “Quasimodo Complex” as described in Masters and Greaves (1967)). For example, Umberson and Hughes (1987) show that others’ assessments of attractiveness correlate with achievement and psychological well-being. Other studies show that others’ perceptions of personality traits influence behavior such as friendliness and sociability (Snyder et al., 1977). Moreover, Zebrowitz and Montepare (2008) show that “babyfaced” individuals are stereotyped as more naive, warm, and submissive, often leading them to adopt more agreeable behaviors. In this project, we focus on evaluating the predictive potential of the facial-image-based Big 5 assessment, leaving the inquiry into the precise mechanisms underpinning the link between facial features and personality traits to other researchers.
