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Facial-Recognition Software Mistook One in Five California Lawmakers for Convicts

Legislators were erroneously matched to criminal mugshots in an ACLU experiment testing the reliability of the software for law enforcement’s use.

One in five California lawmakers were mistaken for convicted criminals in an experiment testing the reliability of facial-recognition software in identifying potentially dangerous suspects. The Los Angeles Times reports that local assemblyman Phil Ting called for the experiment as part of a bill to ban the use of such technology by police and law-enforcement agencies. The experiment incorrectly matched his face to a convicted felon, which he argues could put innocent people in jeopardy if police mistakenly identify them as dangerous criminals. “The software clearly is not ready for use in a law-enforcement capacity,” Ting said. “These mistakes, we can kind of chuckle at it, but if you get arrested and it’s on your record, it can be hard to get housing, get a job. It has real impacts.” Proponents of the technology argue that it is useful in searching for lost children or elderly people in large group situations.