Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
Hosted by the Algorithmic Fairness & Opacity Working Group (AFOG)
Co-sponsored by the UC Berkeley Center for Technology, Society & Policy (CTSP), the Berkeley Institute for Data Science (BIDS), and CITRIS
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 book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lies dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. “This book is downright scary,” says Naomi Klein, “but with its striking research and moving, indelible portraits of life in the ‘digital poorhouse,’ you will emerge smarter and more empowered to demand justice.” Join us for a lively discussion of this timely book.
Virginia Eubanks is an associate professor of political science at the University at Albany, SUNY. She is the author of Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor and Digital Dead End: Fighting for Social Justice in the Information Age and co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. Her writing about technology and social justice has appeared in The American Prospect, The Nation, Harper’s, and Wired. 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, NY.
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