Every few months, another highly educated academic asks: What if I tried to do debunked 18th century race science, but with AI?
THE last entry in the AI phrenology portfolio comes from a group of economics professors who say they have developed a method for algorithmically analyzing a single photo of a person’s face in order to calculate their personality and predict their outcomes school and professional.
Other recent academic forays into AI phrenology— such as algorithms that claim to predict a person’s sexuality or the likelihood of them committing a crime based on their facial features — have been widely critical And demystified. Surveys have also shown that commercial AI tools claiming to measure personality traits are extremely unreliable.
However, Marius Guenzel and Shimon Kogan, of the Wharton School of the University of Pennsylvania; Marina Niessner, of Indiana University; and Kelly Shue of Yale University decided that a snapshot of a person’s face could determine their personality. They received funding for their research from several AI and finance research funds at Wharton and have presented their results at fintech conferences and universities around the world, according to their paper.
The authors collected the LinkedIn profile photos of 96,000 MBA program graduates and submitted them to a facial analysis algorithm that would have measured the person’s score on the Big Five personality test, which rates people based on their open-mindedness, their awareness, their extroversion, their agreeableness and their perception. neuroticism.
They then measured the correlation between these extracted personality scores and the prestige of the MBA program they attended and their eventual compensation in the job market (as estimated by a proprietary model that analyzes LinkedIn data).
Based on this analysis, the authors concluded that personality plays a “significant role” in predicting whether a person will attend a school with a top MBA program and how much they will earn in their first job after obtaining their diploma. For example, men in the top 20 percent of “desirable” personalities who attended MBA programs ranked 7.3 percent higher and had estimated incomes 8.4 percent higher than men whose personalities were in the in the bottom 20 percent of desirability. When researchers controlled for factors like a person’s race, age, and attractiveness (all of which were inferred), the effects became smaller.
Notably, the authors appear to have made no independent effort to establish that the Big Five personality scores their algorithm extracted from LinkedIn portraits were accurate. None of the people whose profile photos were analyzed took the Big Five personality test to confirm the algorithm’s findings.
The professors wrote that their findings highlight “the critical role of non-cognitive skills in shaping career outcomes” and that using AI to analyze faces, rather than administering personality tests to people, “presents new avenues of academic research… (and invites) further exploration of the ethical, practical and strategic considerations inherent in the exploitation of these technologies.
At the same time, they wrote that the technique they just demonstrated should not be used for labor market selection and that “personality extraction from faces represents statistical discrimination in its most extreme form.” fundamental”.
In other words, scientists debated whether they should do it, concluded that it was discriminatory, and then did it anyway.