Algorithmic Abolitionism and the Racial Algorithm

In this chapter, I argue that the algorithmic fairness literature systematically under-theorizes race by treating bias as a modular technical problem. Drawing on Charles Mills's The Racial Contract and Black philosophical traditions, I demonstrate why incremental technical reforms often fail and may even reinforce patterns of racial stratification. I introduce the concept of the Racial Algorithm: The process through which causal mechanisms structured by the Racial Contract generate data distributions, algorithms learn from those distributions, and public or private actors make decisions that, in turn, reaffirm and lock in the structures of the Racial Contract. With this analysis in mind, I then discuss the tension between reform and abolition, concluding with a non-ideal framework of procedural and substantive criteria to determine when algorithmic governance is legitimate and when it must be abolished. Readers may be interested in these Handbook chapters as well: Justin B. Biddle, “Artificial Intelligence: Values, Governance, and Policy”; Heather Douglas, “Science and Social Justice”; Yasmin Haddad and Celso Neto, “Values in Human Genomics”; Zinhle Mncube, “Science, Values, and Race Correction.”