Facial Recognition Designed To Detect Around Face Masks Is Failing, Study Finds

Many facial recognition companies have claimed they can identify people with pinpoint accuracy even while they’re wearing face masks, but the latest results from a study show that the coverings are dramatically increasing error rates.

In an update Tuesday, the US National Institute of Standards and Technology looked at 41 facial recognition algorithms submitted after the COVID-19 pandemic was declared in mid-March. Many of these algorithms were designed with face masks in mind, and claimed that they were still able to accurately identify people, even when half of their face was covered. In July, NIST released a report noting that face masks were thwarting regular facial recognition algorithms, with error rates ranging from 5% to 50%. NIST is widely considered the leading authority on facial recognition accuracy testing, and expected algorithms to improve on identifying people in face masks. That day has yet to come, as every algorithm experienced at least marginal increases in error rates once masks came into the picture. While some algorithms still had accuracy overall, like Chinese facial recognition company Dahua’s algorithm error rate going from 0.3% without masks to 6% with masks, others had error rates that increased up to 99%.

Rank One, a facial recognition provider used in cities like Detroit, had an error rate of 0.6% without masks, and a 34.5% error rate once masks were digitally applied. In May, the company started offering “periocular recognition,” which claimed to be able to identify people just off their eyes and nose. TrueFace, which is used in schools and on Air Force bases, saw its algorithm error rate go from 0.9% to 34.8% once masks were added. The company’s CEO, Shaun Moore, told CNN on Aug. 12 that its researchers were working on a better algorithm for detecting beyond mas

Fearing Coronavirus, a Michigan College is Tracking Its Students With a Flawed App

Albion College, a small liberal arts school in Michigan, said in June it would allow its nearly 1,500 students to return to campus for the new academic year starting in August. Lectures would be limited in size and the semester would finish by Thanksgiving rather than December. The school said it would test both staff and students upon their arrival to campus and throughout the academic year. But less than two weeks before students began arriving on campus, the school announced it would require them to download and install a contact-tracing app called Aura, which it says will help it tackle any coronavirus outbreak on campus.

There’s a catch. The app is designed to track students’ real-time locations around the clock, and there is no way to opt out. The Aura app lets the school know when a student tests positive for COVID-19. It also comes with a contact-tracing feature that alerts students when they have come into close proximity with a person who tested positive for the virus. But the feature requires constant access to the student’s real-time location, which the college says is necessary to track the spread of any exposure. The school’s mandatory use of the app sparked privacy concerns and prompted parents to launch a petition to make using the app optional.