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Rite Aid's Racist AI Gaffe Results In Five-Year Ban

Dec 22, 2023 - mediapost.com
Rite Aid has reached a settlement with the Federal Trade Commission (FTC) over its misuse of artificial intelligence, which led to the wrongful identification of people of color and women as shoplifters. The FTC cited several instances of the technology's failures, including false matches leading to unwarranted searches and accusations. Despite Rite Aid's disagreement with the facial recognition allegations, the settlement restricts the company's use of any facial recognition technology for five years and mandates the deletion or destruction of all photos and videos used or collected in connection with the technology within 45 days.

The news about Rite Aid's flawed technology was first reported by Reuters in 2020, revealing that the company had begun testing the systems in 200 stores in lower-income neighborhoods in New York and Los Angeles in 2012. The FTC report states that Rite Aid's system generated thousands of false-positive matches, sometimes matching customers with people based on activity thousands of miles away or flagging the same person at multiple stores across the U.S. Other retailers, including Walmart and Home Depot, have also explored using facial recognition software to reduce theft.

Key takeaways:

  • Rite Aid and the Federal Trade Commission have reached an agreement over the retailer's misuse of artificial intelligence, which led to the wrongful identification of people of color and women as shoplifters.
  • The settlement restricts Rite Aid’s use of any facial recognition technology for five years and requires the company to delete or destroy all photos and videos of consumers used or collected in connection with the operation of a Facial Recognition or Analysis System within 45 days.
  • Rite Aid began testing the systems in 200 stores in 2012, in lower-income neighborhoods in New York and Los Angeles, and stopped using the technology in 2020.
  • Other retailers, including Walmart and Home Depot, have also explored using facial recognition software to reduce theft.
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