Police arrested a man in Florida for attempted child abduction in a town he had never visited, and the only evidence linking him to the crime was an AI facial recognition hit. Represented by the American Civil Liberties Union (ACLU), he is now suing the officers and agencies who put him through it.

In November 2023, police in Jacksonville Beach, Florida, responded to a call about an attempted child abduction at a McDonald's. Witnesses said an adult man allegedly tried to get the child, identified as a girl under 12 years old, to leave the restaurant with him. According to a police report, facial recognition software concluded with 93 percent confidence that the suspect was Robert Dillon.

In August 2024, Deputies arrested Dillon at his home in Fort Myers, Florida—hundreds of miles away, at the opposite end of the state. "Are you shitting me, man?" Dillon asked the arresting deputy. "I haven't been out of Fort Myers in two years." Further, he also said he had never been to Jacksonville Beach.

Dillon posted bail and pleaded not guilty to enticing or luring a child—a third-degree felony, punishable by up to five years in prison. More than two months later, prosecutors dropped the charges after his attorney provided evidence that he was at work on the day in question.

But that doesn't excuse the fact that he was only arrested in the first place, and threatened with prosecution for a particularly heinous offense, because of shoddy police work.

The ACLU is now suing the city of Jacksonville Beach, as well as the individual police officers and officials involved in the case. According to the lawsuit, the responding officer viewed security camera footage of the suspect but didn't take a copy; instead, he took pictures of the screen with his cell phone. "In the photos, the suspect image is low resolution, and the suspect's face is partially shadowed and off-axis," the lawsuit claims.

When an investigator queried the facial recognition system, it was with the officer's grainy secondhand cell phone photos.

But there were other leads that police could have followed, to either bolster their case or point in another direction. For example, when he approached the girl, the suspect was picking up food that had been ordered ahead; this implies he had an online account, with contact information and a form of payment attached.

"These records could have been used to identify the actual person who placed the suspect's order," the lawsuit notes. "Upon information and belief, Jacksonville Beach PD personnel never requested or obtained mobile ordering records, payment data, or online account information from McDonald's."

Further, the McDonald's manager recognized the assailant as a "regular customer"—likely precluding Dillon, who lived and worked on the other side of the state and did not frequently travel. Besides, at no point did investigators search footage for the suspect's previous visits, either for higher quality images or transaction records. And once they settled on Dillon as a suspect, investigators could have gotten a warrant for his cell phone's GPS data, showing whether or not he was at a fast food restaurant 300 miles away from his home on the night in question.

The lawsuit notes that when Dillon's name came up, investigating officer Scott O'Connell queried the police database of license plate readers, which did not detect Dillon's vehicles in Jacksonville Beach within the 48 hours surrounding the attempted abduction.

Otherwise, the investigation seems to have consisted entirely of the grainy cell phone photos of surveillance footage. According to the lawsuit, O'Connell checked them against photos from inmate booking records and the sex offender registry but found no potential matches. Weeks later, with no leads, he sent the photos to other law enforcement agencies, asking for help. It was at this point that an investigator ran them through facial recognition, which flagged Dillon.

But as the ACLU notes, facial recognition's accuracy "depends significantly on the quality of the probe image. Lower-quality images contain less interpretable facial data, degrading the system's ability to produce a reliable template."

At the very least, it requires a much better source image. Besides, no such investigative tool should form the sole basis for an arrest warrant. "If you came to me with a facial recognition hit and that was your probable cause, I would probably kick you out of my office because that's not how it works," Jacksonville Sheriff T.K. Waters told local news. (Waters is among those being sued in the ACLU lawsuit, because it was an investigator from the Jacksonville Sheriff's Office who ran the grainy photo through facial recognition and advised O'Connell it was a "93% match" to Dillon.)

While he was ultimately released, Dillon still had to suffer the indignity of not just being arrested, but being tarred as a possible child abuser. When deputies placed him in a group holding cell after his arrest, the lawsuit says Dillon "sat in silence, too frightened by the gravity of the charge to speak with or interact with anyone." Even after the charges were dropped, it took an entire year for authorities to take down his mug shot and expunge the arrest from his record.

Unfortunately, Dillon is hardly the first person in this position: The ACLU estimates he is one of at least 14 people arrested since 2019 after being erroneously identified by facial recognition.

Dillon's lawsuit, filed this week in the U.S. District Court for the Middle District of Florida, seeks both compensatory and punitive damages, as well as a requirement that the police departments in question will adopt new safeguards against the misuse of facial recognition technology in the future.

"The night I spent in jail after they arrested me for a crime I did not commit still haunts me to this day. I will never get over how terrified and worried I was, wondering if I'd ever go home to my wife and daughter again," Dillon said in a statement. "Florida police must implement safeguards and ensure this never happens to anyone else, because until they do, nobody is safe."

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