Federal study of top facial recognition algorithms finds empirical evidence of bias

A new federal study has found that many of the world’s top facial recognition algorithms are biased along lines of age, race, and ethnicity. According to the study by the National Institute of Standards and Technology (NIST), algorithms currently sold in the market can misidentify members of some groups up to 100 times more frequently than others.

NIST says it found “empirical evidence” that characteristics such as age, gender, and race impact accuracy for the “majority” of algorithms. The group tested 189 algorithms from 99 organizations, which together power most of the facial recognition systems in use globally.

The findings provide yet more evidence that many of the world’s most advanced facial recognition algorithms are not ready...

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