IN FRONT OF THEIR FACES

Does facial-recognition technology lead police to ignore contradictory evidence?

- EYAL PRESS

On March 26, 2022, at around 8:20 a.m., a man in light-blue Nike sweatpants boarded a bus near a shopping plaza in Timonium, outside Baltimore. After the bus driver ordered him to observe a rule requiring passengers to wear face masks, he approached the fare box and began arguing with her. “I hit bitches,” he said, leaning over a plastic shield that the driver was sitting behind. When she pulled out her iPhone to call the police, he reached around the shield, snatched the device, and raced off. The bus driver followed the man outside, where he punched her in the face repeatedly. He then stood by the curb, laughing, as his victim wiped blood from her nose.

By the time police officers canvassed the area, the assailant had fled, but the incident had been captured on surveillance cameras. Officers with the Maryland Transit Administration Police extracted still images from the footage and created a Be on the Lookout bulletin, which was disseminated to law enforcement agencies. It included several pictures of the alleged perpetrator: a slender Black man whose face was partially obscured by a baseball cap and a hoodie. The bulletin was also sent to the state’s attorney’s office of nearby Harford County, and an analyst there decided to run a facial-recognition search. She fed a still image into software that used algorithms to identify faces that had similar characteristics in a vast database of pictures. This “probe photograph” generated a list of potential matches. (Researchers have identified roughly eighty “nodal points” that convey the distinct geometry of a human face.) The match that stood out to the analyst was Alonzo Cornelius Sawyer, a Maryland resident in his mid-fifties.