Google plans to incorporate a new signal into image ranking, as well as introduce a new type of schema to help make its image search results more racially inclusive and diverse.
The scale will represent a wide range of skin tones, which is important to computer vision technology.
“Updating our approach to skin tone can help us better understand representation in imagery, as well as evaluate whether a product or feature works well across a range of skin tones,” Tulsee Doshi, head of responsible AI, wrote in a post. “This is especially important for computer vision, a type of AI that allows computers to see and understand images. When not built and tested intentionally to include a broad range of skin-tones, computer vision systems have been found to not perform as well for people with darker skin.”
The news of the MST Scale introduced Wednesday at Google I/O, created in partnership with Harvard professor and sociologist Ellis Monk, is a 10-shade scale designed to be more inclusive of the spectrum of skin tones.
Google will incorporate the MST Scale into various Google products during the coming months, and open to release the scale so that anyone can use it for research and product development.
Google plans to adjust how it ranks images, using what is called the Monk Skin Tone (MST) Scale.
The company also calls on creators, brands and publishers to be aware of how to label online content. And in the coming months, the company plans to develop a standard to label web content. The inclusive schema will be used to label content with attributes like skin tone, hair color and hair texture. This will make it possible for content creators or online businesses to label imagery in a way that search engines and other platforms can easily understand.
“Addressing skin tone equity in technology poses an interesting research challenge because it isn’t just a technical question, it’s also a social one,” Molly McHugh-Johnson, staff writer for Google, wrote in a post.
Progress requires a range of people. Contributors include academics in the social sciences who spent years studying social inequality and skin tone stratification through their research; product and technology users, who provide necessary nuance and feedback from life experiences; and ethicists and civil rights activists, who guide on application frameworks to ensure we preserve and honor the social nuances.