Race, by Proxy

In algorithmic culture, the problem of racism is a problem of proxies. Though racism still continues in many familiar forms — through structural exclusion and oppression, through systems and policies that serve the neocolonial and/or white supremacist state, through words, actions and attitudes that demean and dehumanise — the tools and techniques that further these racist legacies and turn bodies into racialised subjects now operate in very different registers. Focusing on algorithmic infrastructures, this chapter argues that AI and ML systems inaugurate new ways of seeing and sorting bodies that has implications for understanding what a category like race is, how it functions, and how it is felt. It draws on a range of material from disparate fields, including critical race studies, media studies, science and technology studies, critical data studies, and the technical and legal literature on large-scale data processing to argue that the logic of proxy data substitutions provides us with a framework for understanding how race functions in algorithmic culture. In these instances, race is enacted not through modes of identification grounded in the reading of phenotype or genotype, but by latent associations between features of data - or, by proxy.