A man suing Florida police alleges that cops relied on a faulty facial recognition match and concealed exculpatory evidence when they arrested him on a charge of attempting to lure a child in August 2024. The plaintiff, Robert Dillon, was arrested after a facial recognition system flagged him as a 93 percent match to a suspect filmed by a McDonald’s surveillance camera.
“This case is about what happens when police let an error-prone artificial intelligence system stand in for an investigation,” said the lawsuit filed today. “A facial recognition algorithm flagged Robert Dillon as the man who tried to lure or entice a child under twelve years old at a Jacksonville Beach McDonald’s. It was wrong. Mr. Dillon, a fifty-two-year-old resident of Fort Myers, had never set foot in Jacksonville Beach. But rather than test the machine’s answer against the evidence that would have cleared him, the officers built a case to confirm it. Mr. Dillon was arrested and prosecuted for one of the most stigmatizing crimes a person can face.”
Dillon lives more than 300 miles from Jacksonville Beach, and a police search of a license plate reader database found no evidence he was in the area when the alleged crime was committed, the lawsuit said. Dillon was flagged as the suspect based on a low-quality image, specifically a photo taken of a McDonald’s computer screen that was displaying video surveillance footage, the lawsuit said.
This post raises important issues about the reliability of facial recognition technology and its implications for justice. It’s crucial to examine how such tools are used in law enforcement and the potential consequences for individuals. Looking forward to seeing how this case unfolds.