Anna Lauren Hoffman is Assistant Professor at the Information School at the University of Washington, where she is also co-founder and co-director of AfterLab. Her research examines how ethics, values and norms are (or are not) grounded and articulated in data and information technologies, with specific attention to 1) competing conceptions of justice and injustice, and inclusion and exclusion related to data. , information and technology, and 2) the ways in which these technologies evoke or omit issues of gender, race, and other categories of social organization.
Fair, inclusive, trustworthy, just, responsible, humane, good—these are the ethical keywords transforming how we talk about applications of artificial intelligence, machine learning, and algorithmic decision-making shaping our lives. Combined, they constitute an emerging ethical grammar fueling dramatic institutional, educational, and political reorientations toward AI and its uses. AI investments are grounded in the hope that it can—in the words of one prominent institute — “help us realize our shared dream of a better future for all of humanity.” In this work, Anna Lauren Hoffmann describes this emerging ethical grammar as, in part, enabled by an ideal of potential that stakes out a moralized space within (racialized and gendered) matrices of technological progress and human development that have long served as justifications for the imposition of racialized and gendered social controls. By situating AI ethics projects within a longer biopolitical history of potential, Hoffmann shows how eugenic and populationist thinking inflects not only AI's most egregious phrenological applications but also its most progressive ethical projects. Accordingly, she argues that we need to move away from instrumentalist ethical projects focused on a narrow idea of AI “impacts” and towards dynamic engagements with AI as a crucible of normativity, cultural meaning-making, and social reproduction.