Every few months, another well-educated academic asks: What if I tried to reproduce the failed race science of the 18th century, but with AI?

the latest entry to the AI ​​phrenology portfolio comes from a group of economics professors who say they have developed a method for algorithmically analyzing a photo of a person’s face to calculate their personality and predict their outcomes in education and career.

Some recent academic forays into AI phrenology—such as algorithms that predict a person’s sexuality or the likelihood that they will commit a crime based on their facial features— WIDESPREAD Denounced and denied. Investigations have also shown that commercial AI tools that claim to measure personality traits extremely unreliable.

However, Marius Guenzel and Shimon Kogan, of the Wharton School at the University of Pennsylvania; Marina Niessner, of Indiana University; and Kelly Shue, from Yale University decided that a snapshot of a person’s face can determine their personality. They have received funding for their research from multiple AI and finance research funds at Wharton and have presented their findings at financial technology conferences and universities around the world, according to their paper.

The authors collected the LinkedIn profile pictures of 96,000 MBA program graduates and ran them through a facial analysis algorithm that purportedly measures how a person scores on the Big Five personality test, which rates people on their perceived openness, conscientiousness, extraversion, agreeableness, and neuroticism.

They then measured the correlation between the obtained personality scores and the excellence of the MBA program they completed and their final workforce compensation (as estimated by a proprietary model that analyzed data on LinkedIn).

Based on this analysis, the authors concluded that personality plays an “important role” in predicting whether a person will attend a school with a highly ranked MBA program and how much they will earn at their first job. after graduation. For example, men in the top 20 percent of “desirable” personalities attended MBA programs that ranked 7.3 percent higher and had an estimated income 8.4 percent higher than men whose personality is in the bottom 20 percent of desire. When the researchers controlled for factors such as a person’s race, age, and attractiveness (all of which are known), the effects became smaller.

Notably, the authors do not appear to have made any independent effort to establish that the Big Five personality scores their algorithm derived from LinkedIn headshots were accurate. None of the people whose profile pictures were analyzed took a Big Five personal test to confirm the algorithm’s conclusions.

The professors wrote that their findings highlight “the critical role of non-personal skills in shaping career outcomes” and that using AI to analyze faces, rather than reality administering personality tests to people, “provides new avenues for academic inquiry … (and invites) further exploration of the ethical, practical, and strategic considerations inherent in the use of such technologies .”

At the same time, they wrote that the technique they demonstrated should not be used for labor market screening and that “extracting personality from faces represents statistical discrimination in its most basic form.”

That is, scientists stopped to think about whether they should, concluded that it was discrimination, and then did it.