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Rep. Rashida Tlaib Pushes for Hiring Only African-American Facial Recognition Analysts

Tlaib calls out a flawed facial recognition system that is used to find and identify suspects. Often, incorrectly.

Vermont Senator Bernie Sanders was the first presidential candidate to call for a national ban on facial recognition software by law enforcement. Michigan’s Rep. Rashida Tlaib agrees with him and is pushing the agenda in her state. 

On Monday October 1, during a tour of the Detroit Police Department’s Real Time Crime Center, Tlaib told the African-American Detroit police chief she thinks he should only hire Black facial recognition analysts because “non African-Americans think African-Americans all look the same.”

While viewing live video footage from traffic lights around the city, she explained to police chief, James Craig, how “analysts need to be African-Americans, not people [who] are not.”

After Craig shook his head at her recommendation, she pushed, “No, this happens all the time. It’s true.”

As an example, the 43-year-old Rep. cited the media’s confusion with telling the difference between Rep. Elijah Cummings and Rep. John Lewis, who are frequently confused by non-African Americans. She explained, “They’re totally different people. I’m just saying,” Tlaib concluded. 

Craig responded to Tlaib’s suggestion, stating, “I trust people who are trained, regardless of [their] race and regardless of gender. It is about the training.”

“But it does make a huge difference,” Tlaib persisted, claiming the facial recognition error rate among African-Americans, especially women, was 60 percent.

Later, Tlaib’s spokesman verified Tlaib’s statements to The Detroit News by including a link to a Memorial University of Newfoundland study, which, “has shown that individuals are less accurate when identifying people from a race other than their own.” 

Said Tlaib’s spokesperson, “Detroit has a Black population of more than 80%, so that is where [Rep. Tlaib’s] basis [for her argument] came from and what she was trying to convey when it comes to accurate identification.”

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