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Kosinski maintains that the study wasn’t testing PHT, only whether an algorithm could be used to “out” gay people, and that he wants to warn people about such technologies. “Look — in the context of a person, country or institution that wants to ‘out’ people, it’s just a great pre-screening tool,” he said. Yet even Kosinski admitted that the computer might be picking up something besides immutable facial features. His algorithm, for example, posits that gay men are more likely to wear glasses. “Many wondered why faces with glasses are considered by algorithm to be more likely to be gay,” Kosinski said. “It might be something else in the face that’s also correlated with having glasses.” Wu’s detractors also noted similar problems in the data used to train computer algorithms purporting to identify criminals. His work used identification photos for the convicted criminals, and pictures taken from web searches for the non-convicted set. But Carl Bergstrom, a professor of evolutionary biology at the University of Washington, and Jevin West, an assistant professor in the Information School at the university, said in their evaluation of Wu’s work that it’s possible that the artificial intelligence algorithm was finding small differences in expression. (Wu acknowledged this in his open letter to his critics). “Our study was on the perception of socio-psychological perceptions of faces only.” Still, even if there really are physiological differences between the faces of criminals pictured in photographs and the non-criminals fed into the computer, that may simply reveal more about stereotypes Skip Tracer within the Chinese criminal justice system than the people in the photos. Critics have also noted a lack of transparency in the origin of the photo set for the convicted criminals.
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