AI software defines people as male or female. That's a problem

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Artificial intelligence doesn't know what to make of Os Keyes.

The 29-year-old graduate student is dark-haired, tattooed and openly transgender, using the pronouns"they" or"them." Facial analysis software, however, typically assigns each face it analyzes one of two labels: male or female.Yet for Keyes, who studies gender, technology and power at the University of Washington, this technology is not simply software that doesn't get it right.

As these societal changes proliferate, AI-driven conclusions have become more than a gender identity concern. Some AI experts and members of the transgender community are worried about the potential for serious repercussions if gender recognition, as it exists today, is put to use for more complicated and sensitive tasks, whether it be using AI to help screen job candidates or nab criminal suspects.

"I think we need to push back on the idea that these systems should exist at all, and look at these kind of assumptions — that someone's body or face or style or hair can kind of detect their interior state or identity," said Meredith Whittaker, a former Google employee and cofounder of New York University's AI Now Institute, which studies social impacts of AI.The tech companies are mostly staying quiet on these concerns. Amazon and Microsoft declined to comment for this story.

Yet, he also said Clarifai is talking to companies that offer single-sex dormitories about how the startup's automated gender-identification could be used for safety and security purposes — not to deny someone entry to a building, but to flag a security guard"who would need to make the human determination" about whether a person should be rejected from a building.

The results? On average, the services classified photos tagged"woman" as"female" 98.3% of the time, and photos tagged"man" as"male" 97.6% of the time. It may also be seen as another way in which the technology humans build falls short when it comes to analyzing a more diverse population than may be found on some tech engineering teams — which are often largely male and white. Human biases, such as sexist notions, can seep into machine-learning software in particular, regardless of creators' intentions.

Yet Woo, an Indian dating app that matches heterosexual couples, uses Rekognition's gender-identifying feature mainly to help make sure the gender that users state in their profile matches up with the images of themselves they post within the app, said Woo cofounder and CEO Sumesh Menon.

 

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