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The Myth of Facial Recognition Bias

By Hoan Ton-That BLOG

Since 2018, there has been a perpetual myth that facial recognition technology (FRT) is inaccurate, and worse, racially and demographically biased. It is a technology that has been under attack from activists on this basis. However, the technology has improved dramatically and is more accurate and advanced than the human eye.

According to the National Institute of Standards and Technology (NIST), which tests over 650 algorithms for accuracy, there are now over 100 algorithms that can match a photo out of a lineup of over 12 million photos, over 99% of the time.


NIST is the world’s foremost expert in the independent evaluation of facial recognition algorithms for accuracy in verification and identification use cases. NIST’s Face Recognition Vendor Test (FRVT) accepts any algorithm submission ranging from reputable vendors and government-developed systems to experimental products. Even our geopolitical adversaries, such as China and Russia, submit their technology for testing by NIST and as of November 2022 over 650 algorithms have been evaluated in total.

There are two tests in particular: the NIST FRVT 1:1 and the NIST FRVT 1:N. The 1:1 testing scores each algorithm for positive verification. Given two facial photos, it evaluates the accuracy of a particular algorithm in correctly determining if they are the same person or not. It is broken down by testing each algorithm by different types of photos: mugshots, VISA photos, border photos, and the most difficult: WILD photos. WILD photos are photos of faces taken in all types of angles and under different lighting conditions.

The NIST FRVT 1:1 test also requires 1:1 matching with diverse demographics, genders, and ethnicities.

The NIST FRVT 1:N is a significantly harder test. Like the 1:1 test, it measures accuracy of each algorithm across the same types of categories. However, instead of just measuring the accuracy of matching two photos, it tests the accuracy of the algorithm to match a photo accurately out of a large set of millions of other photos.

The top 100 algorithms in the NIST FRVT 1:N test, in investigation mode, have over 99% accuracy for picking a photo out of a mugshot lineup of 12 million photos. This shows how advanced and phenomenally accurate the technology is in 2022 and much better than the human eye.