Unmasking AI: My Mission to Protect What Is Human in a World of Machines

by Joy Buolamwini

When I visited Cape Town, South Africa, in 2019 during a tech conference, I went to the “Classification Building,” where people could go to have their hair and even their most private parts examined to determine race. The example of Sandra Liang, born to white Afrikaans parents but presenting in a way classified as colored, is an example that reveals how race is constructed. It was thus possible for parents classified white to birth a daughter classified colored who was ostracized by the white community and eventually found refuge in a township. In places like Canada, the term “visible minority” is used, a term that acknowledges that outward appearance is what is used to make assumptions about race that hold real social consequences. In the Canadian case, and in places like the United Kingdom and the United States, racial categorization is used by the government to better understand where to allocate resources and support minority groups or those who might face discrimination. In the U.S. case, I found a contradiction in this stated goal and the existing census classification, which included Middle Easterners in the group of white. The treatment of and discrimination against individuals perceived as white and those perceived as Middle Eastern differed, particularly after the September 11th World Trade Center attack. This would hardly be the only contradiction to be uncovered.