Wrongful arrest based on false FRT match sparks lawsuit from Florida man

Another case of wrongful arrest after a false match by facial recognition software has given more ammo to those fighting to restrict law enforcement’s use of the biometric tech.

The American Civil Liberties Union (ACLU) is launching legal action against two Florida police departments on behalf of Robert Dillon, a 52-year old man from Fort Myers who was wrongfully arrested after facial recognition software returned a 93 percent similarity score.

Jacksonville Sheriff’s Office uses the Face Analysis Comparison & Examination System (FACES), which runs Idemia algorithms and is operated by Pinellas County Sheriff’s Office. The facial recognition system is one of the longest-running in American law enforcement, and was being used by 263 local police departments as of midway through 2022. Wired reports the system has been used in attempts to identify peaceful protestors but is not audited for misuse.

Dillon was arrested in August 2024, after FRT matched his face with that of a man in video trying to lure a pre-teen girl at a McDonald’s restaurant in Jacksonville Beach. A statement from the ACLU says police fed “grainy surveillance photos” into the facial recognition engine.

“Using only that, and the statement of a restaurant employee who picked his photo out of a lineup, Jacksonville Beach police got an arrest warrant.” Dillon was arrested months later.

Jacksonville Beach is more than 300 miles from Dillon’s home in Fort Myers, on the opposite end of the state. Dillon says he has never been to Jacksonville Beach. Moreover, a search of license plate scans showed no hits on his car anywhere near the crime scene. His criminal record includes arrests for DUI and a bar fight.

Dillon brings tally of wrongful arrests based on FRT to 15

Dillon was forced to pay to bond out of jail and hire an attorney to defend him. A report in Gulf Coast News says he was exonerated by the State Attorney’s Office in Jacksonville after he sent them text messages indicating that he had a regular day at work on the day the crime occurred.

In a statement, he says that, “over a year later, I’m still picking up the pieces of my life, all because the police relied on this dangerous technology instead of doing their jobs and actually investigating.”

“No one should lose their freedom or be scared to leave their house because an algorithm got it wrong,” says Nate Freed Wessler, deputy director of the ACLU’s Speech, Privacy, and Technology Project. “These Florida police departments owe it to Mr. Dillon to make amends and to take serious steps to make sure this doesn’t happen to anyone else. Police across the country are on notice: unreliable face recognition technology is hurting people, and we will keep fighting to hold them accountable for these abuses.”

Robert Dillon is the fifteenth person to be wrongfully arrested after a facial match with biometric machine learning tools.

Police bias, bad protocol are root problems of misused facial recognition

Notably, Dillon is caucasian. The majority of wrongful arrests based on facial recognition mismatches have targeted Black people. The ACLU ties the pattern directly to purported bias in facial recognition algorithms, the majority of which have exhibited bias in testing by the National Institute of Standards and Technology (NIST) – although the top-ranked algorithms show very low differentials in the latest benchmarks.

More cases that do not involve Black people could weaken the argument that the tech is biased – but, ironically, could also rouse more outrage among policymakers. Moreover, it will not help the overall case for facial recognition matches as a basis for arrest. Nor should it.

Here, the police again failed to follow protocol when using facial recognition tech, which is, according to best practices for law enforcement globally, never to be used as the sole grounds for an arrest, in that it does not constitute probable cause. In not cross-referencing the match beyond an unreliable witness statement from an employee at the restaurant (who told police Dillon was a regular), and failing to establish probable cause, Jacksonville Beach police placed far too much of the burden of proof on an algorithm.

The implications are not new: the tools will fail if the police do.

The ACLU quotes Steve Silverberg, counsel at Hoguet Newman Regal & Kenney, LLP, a law firm supporting Dillon’s case – which, he says, “illustrates the stakes when police deploy AI-assisted identification tools without adequate safeguards. Digital information can be a powerful tool for law enforcement, but its proliferation, supercharged by the AI boom, carries profound Fourth Amendment implications.”

Article Topics

biometric matching  |  biometrics  |  Face Analysis Comparison & Examination System (FACES)  |  facial recognition  |  false arrest  |  Florida