NIST Study Evaluates Effects of Race, Age, Sex on Face Recognition Software

A figure in a blue circle sits to the left of a computer labeled "face recognition search."

How accurately do face recognition software tools identify people of varied sex, age and racial background? According to a new study by the National Institute of Standards and Technology (NIST), the answer depends on the algorithm at the heart of the system, the application that uses it and the data it’s fed — but the majority of face recognition algorithms exhibit demographic differentials. A differential means that an algorithm’s ability to match two images of the same person varies from one demographic group to another.

Results captured in the report, Face Recognition Vendor Test (FRVT) Part 3: Demographic Effects (NISTIR 8280), are intended to inform policymakers and to help software developers better understand the performance of their algorithms.