Findings from a recent study out of Stanford University Business School by Yilun Wang and Michal Kosinski indicate that AI can correctly identify sexual preference based on images of a person’s face. The study used 35,000 images from a popular U.S. dating site to test the accuracy of algorithms in determining self-identified sexual orientation. Their sample images include cis-white people who identify as either heterosexual or homosexual. The researchers’ algorithm correctly assessed the sexual identity of men 81% of the time and women 74%. When the software had access to multiple images of each face, accuracy increased to 91% for images of men and 84% for images of women. In contrast, humans correctly discerned men’s sexual identity 61% of the time and for women, only 54%.
The authors of the study note that algorithmic detection was based on “gender atypical” expressions and “grooming” practices along with fixed facial features, such as forehead size and nose length. Homosexual-identified men appeared more feminized than their heterosexual counterparts, while lesbian women appeared more masculine. Wang and Kosinski argue that their findings show “strong support” for prenatal hormone exposure which predisposes people to same-sex attraction and has clear markers in both physiology and behavior. According to the authors’ analysis and subsequent media coverage, people with same-sex attraction were “born that way” and the essential nature of sexuality was revealed through a sophisticated technological apparatus.
While the authors demonstrate an impressive show of programming, they employ bad science, faulty philosophy, and irresponsible politics. This is because the study and its surrounding commentary maintain two lines of essentialism, and both are wrong. more...