A Twitter image-cropping algorithm that went viral last year when users discovered it preferred white people to Black people was also coded with implicit bias against a number of other groups, researchers have found.
But that unintended racism wasn’t unusual, said Parham Aarabi, a professor at the University of Toronto and director of its Applied AI Group, which studies and consults on biases in artificial intelligence. Programs that learn from users’ behavior almost invariably introduce some kind of unintended bias, he said.
While the photo-cropping incident was embarrassing for Twitter, it highlighted a broad problem across the tech industry. When companies train artificial intelligence to learn from their users’ behavior — like seeing what kind of photos the majority of users are more likely to click on — the AI systems can internalize prejudices that they would never intentionally write into a program.
“The most common effect it has is it crops out people who are older,” Aarabi said. “The older demographic is predominantly marginalized with the algorithm.” Another submission found that Twitter would be more likely to ignore people who wore head coverings, which effectively cut out people who wore them for religious reasons, like a Muslim hijab.that the more a person’s face is photoshopped to look slimmer, younger or softer, the more likely Twitter’s algorithm will be to highlight them.
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