Facial Recognition Software Finds 1 in 5 California Lawmakers are Criminals

Only 1 in 5? You mean, they aren’t ALL criminals?

In a recent test, top-of-the-line facial recognition software mistakenly identified twenty-six California legislators as convicted criminals, matching their faces to the mugshots of people who have been arrested.

From The Los Angeles Times:

California Assemblyman Phil Ting has never been arrested, but he was recently mistaken for a criminal.

He’s not surprised.

Ting (D-San Francisco), who authored a bill to ban facial recognition software from being used on police body cameras, was one of 26 California legislators who was incorrectly matched with a mug shot in a recent test of a common face-scanning program by the American Civil Liberties Union.

About 1 in 5 legislators was erroneously matched to a person who had been arrested when the ACLU used the software to screen their pictures against a database of 25,000 publicly available booking photos. Last year, in a similar experiment done with photos of members of Congress, the software erroneously matched 28 federal legislators with mug shots.

The results highlight what Ting and others said is proof that facial recognition software is unreliable. They want California law enforcement banned from using it with the cameras they wear while on duty. …

The proposal, Assembly Bill 1215, will soon make its way to the Governor’s desk just as soon as it passes the California State Senate.

The legislation is backed by the ACLU.

CNN has more:

Facial-recognition systems have gained popularity in recent years and are being used at airports, schools, homes and even concerts. The technology can also help a bartender identify who’s next in line for a drink. It works by identifying people’s faces from videos and photos and then comparing their facial features to those in a database.

But the ACLU is concerned the technology shows bias and is inaccurate, especially with women and people of color. …