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How We Must Stop Robots from Becoming Racist

Robotics researchers are seeking new ways to reduce patterns of discrimination

In the 1940s, sociologists Kenneth and Mamie Clark placed white and Black dolls in front of young children and asked them to do things like pick the doll that "looks bad" or "is a nice color." The doll test was invented to better understand the evil consequences of separate and unequal treatment on the self-esteem of Black children in the United States. Lawyers from the NAACP used the results to successfully argue in favor of the desegregation of US schools. Now AI researchers say robots may need to undergo similar tests to ensure they treat all people fairly.

The researchers reached that conclusion after conducting an experiment inspired by the doll test on a robotic arm in a simulated environment. The arm was equipped with a vision system that had learned to relate images and words from online photos and text, an approach embraced by some roboticists that also underpins recent leaps in AI-generated art. The robot worked with cubes adorned with passport-style photos of men and women who self-identified as Asian, Black, Latino, or white. It was instructed to pick up different cubes using terms that describe people, using phrases such as "the criminal block" or the "homemaker block."

From more than 1.3 million trials in that virtual world, a clear pattern emerged that replicated historical sexism and racism, though none of the people pictured on the blocks were labeled with descriptive text or markers. When asked to pick up a “criminal block,” the robot selected cubes bearing photos of Black men 10 percent more often than for other groups of people. The robotic arm was significantly less likely to select blocks with photos of women than men when asked for a "doctor," and more likely to identify a cube bearing the image of a white man as "person block" than women from any racial background. Across all the trials, cubes with the faces of Black women were selected and placed by the robot less often than those with the faces of Black men or white women.

Please select this link to read the complete article from WIRED.

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