How High-Tech Tools Profile, Police, and Punish the Poor
Winner of the Lillian Smith Book Award
“Riveting (an accomplishment for a book on technology and policy). Its argument should be widely circulated, to poor people, social service workers and policymakers, but also throughout the professional classes. Everyone needs to understand that technology is no substitute for justice.”
—The New York Times Book Review
Since the dawn of the digital age, decision-making in finance, employment, politics, health, and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.
Virginia Eubanks is an Associate Professor of Political Science at the University at Albany, SUNY. She is the author of Digital Dead End and co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around. For two decades, Eubanks has worked in community technology and economic justice movements. Today, she is a founding member of the Our Data Bodies Project and a Fellow at New America. She lives in Troy, New York.