If we don’t recognize facial recognition’s problems and implement policies to mitigate them, the technology will sweep innocent individuals into investigations, undercut police-community relations, and waste law enforcement resources.

Almost any new technology comes with hyperbolic descriptions of what it can do. For police, this can result in investigators mismanaging leads or working backwards to fill in a narrative that fits what their seemingly impartial and authoritative tool tells them, rather than following evidence from the ground up. We’ve already seen this: in one case police ignored proper procedures for photo arrays and instead asked an eyewitness, “Is this the guy?” with a single photo obtained from a facial recognition search. This sort of tunnel vision is one of the main drivers of false accusations and wrongful convictions.



Facial recognition technology has plenty of problems. One of the most concerning is that it’s often inaccurate. Numerous studies, including one coauthored by an FBI expert, have found this is especially true in identifying and classifying women and people with darker skin tones. This endangers already over-policed communities, increasing the risk that people of color will improperly become investigative targets. Failure to deal with this problem could also expose police departments to discrimination lawsuits.

Facial recognition’s problems are exacerbated when law enforcement uses unreliable methodologies. Even a well-designed facial recognition system can produce unreliable data if its settings permit it to return low-confidence data. Gizmodo revealed earlier this year that Amazon—a major seller of facial recognition technology to law enforcement—had been advising police to set up facial recognition systems to return matches based on low confidence levels, even though the company’s own public statements say doing so is unreliable.

