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

by Joy Buolamwini

Examining the different labels turkers gave to the same face made me see the extent of guesswork that went into attempting to categorize perceived race. After the turkers’ experiments, I started using “perceived race” instead of “race” when talking about classification. Setting up the micro tasks also gave me power and privileged my perspectives. It was my human choice to select categories for classification that the turkers were then boxed into attempting to fit. My own choice of classification categories was informed by how others had grouped people in the past. I looked to existing systems as a starting place, such as the U.S. Census race categories, which have evolved over the centuries and reflected the social, political, and economic context of the day. For example, the U.S. Census, which started in 1790, did not allow people to categorize themselves into multiple racial groups until 2000. It was in 1960 when census takers could first self-identify how they fit into the given options. The categories themselves evolved, with enslaved people becoming “colored,” then “Black,” then “Negro.” The term “African American” debuted in the 2020 census.[1] None of this labeling felt precise, and my choices, just like the census labels, were not neutral. They were subject to the time period and shaped by those who held decision-making power.