Facial recognition software racially biased?

“Facial recognition software proves to be less accurate at identifying people with darker pigmentation,” George Byers II, a black software engineer, told the police board last month. “We live in a major black city. That’s a problem,” reported the New York Times

Researchers at the Massachusetts Institute of Technology reported in January that facial recognition software marketed by Amazon misidentified darker-skinned women as men 31 percent of the time. Others have shown that algorithms used in facial recognition return false matches at a higher rate for African-Americans than white people unless explicitly recalibrated for a black population — in which case their failure rate at finding positive matches for white people climbs. That study, posted in May by computer scientists at the Florida Institute of Technology and the University of Notre Dame, suggests that a single algorithm cannot be applied to both groups with equal accuracy.

Mr. Byers and other critics spoke at a public hearing called by the Detroit Board of Police Commissioners after what the board called unprecedented public interest in two facial recognition items on its agenda. One item, specific to the new traffic light cameras, was approved last week. The other, a comprehensive “acceptable use” policy for facial recognition, has yet to be put to a vote.

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