Wrongful Arrest Exposes Failures in One of the Oldest Police Face-Recognition Tools in the US
Key takeaways
- The system returned a “93 percent match on facial features,” according to police investigatory notes.
- FACES holds tens of millions of Florida mugshots and driver's license photos and is one of the longest-running police face recognition databases in the United States.
- The American Civil Liberties Union, which filed the suit, says Dillon was arrested at his home in front of his wife, held overnight in a cold cell, and transported in a caged, unlit van.
Why this matters: a development in AI with implications for how people work, create, and decide.
Photo-Illustration: WIRED Staff; Getty Images Comment Loader Save Story Save this story Comment Loader Save Story Save this story A Florida man was wrongfully arrested for attempting to illegally lure a child after police relied on a face recognition match that was inaccurate, according to a lawsuit filed on Wednesday, even though he lived more than 300 miles from the scene and says he had never set foot in the city where the crime took place.
Robert Dillon, a 52-year-old commercial crabber from Fort Myers, was arrested after FACES—a face recognition system operated by Florida’s Pinellas County Sheriff's Office—matched his face against a photo of a man on a computer screen taken with a cellphone. The system returned a “93 percent match on facial features,” according to police investigatory notes. The scores it emits represent how much two images look alike to the algorithm. Not how likely it is that they show the same person.
FACES holds tens of millions of Florida mugshots and driver's license photos and is one of the longest-running police face recognition databases in the United States.