Facial Recognition Is Accurate, if You’re a White Guy
In her newly published paper, which will be presented at a conference this month, Ms. Buolamwini studied the performance of three leading face recognition systems — by Microsoft, IBM
and Megvii of China — by classifying how well they could guess the gender of people with different skin tones.
Ms. Gebru is a scientist at Microsoft Research, working on its Fairness Accountability Transparency and Ethics in A. I.
Megvii, whose Face++ software is widely used for identification in online payment
and ride-sharing services in China, did not reply to several requests for comment, Ms. Buolamwini said.
But the darker the skin, the more errors arise — up to nearly 35 percent for images of darker skinned women, according to a new study
that breaks fresh ground by measuring how the technology works on people of different races and gender.
To test the commercial systems, Ms. Buolamwini built a data set of 1,270 faces, using
faces of lawmakers from countries with a high percentage of women in office.
In 2015, for example, Google had to apologize after its image-recognition photo app initially labeled African Americans as “gorillas.”
Sorelle Friedler, a computer scientist at Haverford College and a reviewing editor on Ms. Buolamwini’s research paper, said experts had long suspected
that facial recognition software performed differently on different populations.