Massive errors found in facial recognition tech, especially in case of nonwhites: U.S. study

WASHINGTON – Facial recognition systems can produce wildly inaccurate results, especially for nonwhites, according to a U.S. government study released Thursday that is likely to raise fresh doubts on deployment of the artificial intelligence technology. The study of dozens of facial recognition algorithms showed "false positives" rates for Asians and African-Americans as much as 100 times higher than for whites. The researchers from the National Institute of Standards and Technology (NIST), a government research center, also found two algorithms assigned the wrong gender to black females almost 35 percent of the time. The study comes amid widespread deployment of facial recognition for law enforcement, airports, border security, banking, retailing, schools and for personal technology such as unlocking smartphones. Some activists and researchers have claimed the potential for errors is too great and that mistakes could result in the jailing of innocent people, and that the technology could be used to create databases that may be hacked or inappropriately used.