Facial Recognition Is Spreading Everywhere

Facial recognition technology (FRT) dates back 60 years. Just over a decade ago, deep-learning methods tipped the technology into more useful—and menacing—territory. Now, retailers, your neighbors, and law enforcement are all storing your face and building up a fragmentary photo album of your life.Yet the story those photos can tell inevitably has errors. FRT makers, like those of any diagnostic technology, must balance two types of errors: false positives and false negatives. There are three possible outcomes.Three Possible Outcomes a) identifies the suspect, since the two images are of the same person, according to the software. Success! b) matches another person in the footage with the suspect’s probe image. A false positive, coupled with sloppy verification, could put the wrong person behind bars and lets the real criminal escape justice. c) fails to find a match at all. The suspect may be evading cameras, but if cameras just have low-light or bad-angle images, this creates