The Fitzpatrick Scale has been in the open domain for decades and was adopted by the tech industry primarily for use in machine learning and artificial intelligence. Humans must annotate images or videos to train machine-learning algorithms for things like face detections.
“Instead of using this Fitzpatrick Scale, which wasn’t designed to classify diverse skin tones among different groups of people, you would use the Monk Skin Tone Scale, which gives you a more granular understanding,” Monk said. He chose 10 color points to better represent the range of skin tones, opting out of wider range as a larger numbers would begin to create problems with annotation. Extensive fieldwork on skin tone and colorism in the US and Brazil informed the final color selection.
Monk’s collaboration with Google began a few years ago when he was contacted by its Research Responsible AI team, and over time, the work turned to finding an alternative to the Fitzpatrick Scale, the sociologist said. That is when the team learned that Monk had developed a scale of his own.
Google is already using the Monk Skin Tone Scale in its image search. When users search makeup looks, for example, they can refine those searches by skin tone to find more relevant matches. The tech giant also used the scale to update its own Real Tone filters (an initiative it had already launched to deal with the skin-tone problem) on its Pixel cameras so that they can capture a wider, more realistic palette of shades.
“There’ve also been some refinements to search where people have complained that in the past, if you search for certain images, you only get back certain types of people,” Monk said. “One example is if you search for ‘cute babies,’ you might get a completely homogenous set of babies that basically all look white. That’s not a very inclusive experience for people at all.”
Google says the scale will be useful in checking the diversity of results for problems with algorithms. “This has been a longstanding issue, not just at Google, but across the tech industry,” Monk said.
Monk plans to publish research, testing the scale on a diverse group of people. He and the Google team conducted research together to validate the scale in the US, which was an extension of his own work.
Developers who do not intentionally design their products to work well across the continuum of skin tones will have products that do not work as well, Monk added. The new scale is open-source so that all companies around the world can make their products more inclusive.
“My hope is that other companies, not just Google, take on the work of auditing and making sure that their products are designed to work equally well across the entire range of skin tones, whether that’s using the Monk Skin Tone Scale or not,” Monk said. “I hope they do that work.”