Ancestry tracking services often deliver results in racialized “percentages”; algorithms render medical decisions without necessarily revealing the reasoning for their conclusions; built-into-the-machine algorithmic assortments tag disease and contagion with socially stereotyped categories such as race, religion, and nationality. The question for this session is how we might unpack data about public health in ways that do not re-inscribe the baggage of past historical division.