An artificial intelligence (AI)
algorithm developed by scientists at Stanford University can detect
sexual orientation based on a series of facial images with 91 percent
In their paper, titled Deep Neural
Networks are More Accurate than Humans at Detecting Sexual
Orientation from Facial Images, researchers Michal Kosinski and
Yilun Wang report that the algorithm can correctly distinguish
between gay and straight persons. The software can correctly detect
sexual orientation in men with a single facial image 81 percent of
the time, and 74 percent of the time when the subjects are women.
Human judges accurately determined a person's sexual orientation 61
percent of the time for men and 54 percent for women.
Accuracy climbed to 91 percent in men
and 83 percent in women with five images.
Kosinski and Yilun applied their
algorithm to more than 35,000 facial images uploaded to a U.S. dating
website. The sample did not include black and ethnic minority faces.
Bisexual people were not included.
“Consistent with the prenatal hormone
theory of sexual orientation, gay men and women tended to have
gender-atypical facial morphology, expression and grooming styles,”
the authors wrote. “Average landmark locations revealed that gay
men had narrower jaws and longer noses, while lesbians had larger
jaws. Composite faces suggest that gay men had larger foreheads than
heterosexual men, while lesbians had smaller foreheads than
The researchers warned that the
technology has the potential to be abused.
“Given that companies and governments
are increasingly using computer vision algorithms to detect people's
intimate traits, our findings expose a threat to the privacy and
safety of gay men and women,” they wrote.