Joy Buolamwini, 28
MIT Media Lab and Algorithmic Justice League
When AI misclassified her face, she started a movement for accountability.
As a college student, Joy Buolamwini discovered that some facial-analysis systems couldn’t detect her dark-skinned face until she donned a white mask. “I was literally not seen by technology,” she says.
We have to continue to check our systems, because they can fail in unexpected ways.
That sparked the research for her MIT graduate thesis. When she found that existing data sets for facial–analysis systems contained predominantly pale-skinned and male faces, Buolamwini created a gender-balanced set of over a thousand politicians from Africa and Europe. When she used it to test AI systems from IBM, Microsoft, and Face++, she found that their accuracy varied greatly with gender and skin color. When determining gender, the error rates of these systems were less than 1 percent for lighter-skinned males. But for darker-skinned female faces, the error rates were as high as 35 percent.