Facial recognition use has been rising as law enforcement, immigration services, banks and other institutions rely on it more and more.
But “A recent study by computer-science researchers at the University of Colorado Boulder found that major AI-based facial analysis tools—including Amazon’s Rekognition, IBM’s Watson, Microsoft’s Azure, and Clarifai—habitually misidentified non-cisgender people.”, Quartz reports.
The article continues, “The researchers gathered 2,450 images of faces from Instagram, searching under the hashtags #woman, #man, #transwoman, #transman, #agenderqueer, and #nonbinary.
“The images were then divided by hashtag, amounting to 350 images in each group. Scientists then tested each group against the facial analysis tools of the four companies.
“The systems were most accurate with cisgender men and women, who on average were accurately classified 98% of the time. Researchers found that trans men were wrongly categorized roughly 30% of the time. The tools fared far worse with non-binary or genderqueer people, inaccurately classifying them in all instances.”