For years, tech companies have relied on something called the Fitzpatrick scale to classify skin tones for their computer vision algorithms. Originally designed for dermatologists in the 1970s, the system comprises only six skin tones, a possible contributor to AI’s well-documented failures in identifying people of color. Now Google is beginning to incorporate a 10-skin tone standard across its products, called the Monk Skin Tone (MST) scale, from Google Search Images to Google Photos and beyond. The development has the potential to reduce bias in data sets used to train AI in everything from health care to content moderation.
Google first signaled plans to go beyond the Fitzpatrick scale last year. Internally, the project dates back to a summer 2020 effort by four Black women at Google to make AI “work better for people of color,” according to a Twitter thread from Xango Eyeé, a responsible AI product manager at the company. At today’s Google I/O conference, the company detailed how wide an impact the new system could have across its many products. Google will also open source the MST, meaning it could replace Fitzpatrick as the industry standard for evaluating the fairness of cameras and computer vision systems.
“Think anywhere there are images of people’s faces being used where we need to test the algorithm for fairness,” says Eyeé.