Masks make it harder for facial recognition algorithms to identify who you are, according to a new government study.
The National Institute of Standards and Technology tested 89 facial recognition algorithms with an error rate of around 0.3%.
When tested on people wearing face masks, the error rate increased from anywhere between 5 to 50%, according to researchers involved in the study.
The study was conducted in collaboration with the Department of Homeland Security and U.S. Customs and Border Protection. Both agencies use facial recognition technology.
Results indicate that wearing a face mask would make a person less likely to be identified by facial recognition software. But the level of recognition varies depending on the type of mask a person is wearing.
People are less identifiable when wearing a mask over their nose than when they leave their nose uncovered, the study found.
Results also indicate that dark masks make it harder to be detected by the software programs than blue surgical masks. The shape also played a factor in evading recognition. A wide masks that covers a person’s entire face tricked the algorithm more than a round, N95-style mask.
"None of these algorithms were designed to handle face masks," said NIST computer scientist Mei Ngan, who authored the report. "With respect to accuracy with face masks, we expect the technology to continue to improve.”
Ngan added that NIST plans to test newer algorithms later this summer that were created with face masks in mind.
© 2025 Newsmax. All rights reserved.