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That's partly practical-if Pinterest makes assumptions that are wrong, then the site becomes unusable-but also for privacy. Pinterest also wants to make sure filtering for skin tone never feels creepy, so the site never saves the skin tones you’ve selected. Pinterest’s engineers have been training it to recognize shadows and bright lights, and making sure skin tone categories don't get conflated with racial stereotypes. Like all machine learning projects, this one isn't perfect. The result, they hope, will send a strong message: You shouldn’t have to work harder to search Pinterest just because you're a person of color you shouldn't have to qualify “orange lipstick” just because you’re not white. A team at Pinterest has spent months creating the feature, building their own skin tone taxonomy to categorize pins, and training an algorithm to recognize them, so that more users can find pins across a spectrum of skin tones. But Morgan, and others at the company, consider it the first step toward making Pinterest feel like a more diverse place. It's a small, subtle feature-one that many of Pinterest's users will hardly notice. Click on one and the search results show only those skin tones. When you type in a beauty-related term, like "orange lipstick," a set of skin tone options appears below it. Today, Pinterest is introducing its answer: a way to narrow down beauty searches by skin tone.

"We were thinking, how we can look at our database of pins and make sure we were in some way matching and labeling content across different groups of people?" says Morgan. In some cases, the level of specification meant a person couldn't find what they were searching for at all.

But it still took specific keywords to find hair, makeup, or fashion ideas showing women who weren't white. On Pinterest, at least, the search results were less inflammatory.