WASHINGTON, Dec 20 ― Facial recognition systems can produce wildly inaccurate results, especially for non-whites, according to a US government study released yesterday that is likely to raise fresh doubts on deployment of the artificial intelligence technology. The study of dozens of facial...
The study found US-developed face recognition systems had higher error rates for Asians, African Americans and Native American groups, with the American Indian demographic showing the highest rates of false positives. ― AFP pic
The researchers from the National Institute of Standards and Technology , a government research centre, also found two algorithms assigned the wrong gender to black females almost 35 per cent of the time. The NIST study found both “false positives”, in which an individual is mistakenly identified, and “false negatives”, where the algorithm fails to accurately match a face to a specific person in a database.
The study found US-developed face recognition systems had higher error rates for Asians, African Americans and Native American groups, with the American Indian demographic showing the highest rates of false positives.
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