Tech Ethicists & Critics
Automating Inequality
Virginia Eubanks · 2018 · St. Martin's Press
Follows how automated eligibility systems and predictive algorithms affect people navigating welfare, homelessness services, and child protective services.
Cover image: Open Library.
Summary
“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.”
This book examines how automated decision-making systems, such as data mining, policy algorithms, and predictive analytics, are used to manage and penalize poor and working-class people in the United States. The author argues that these high-tech tools perpetuate historical patterns of discrimination and control, creating a "digital poorhouse" that mirrors earlier institutions designed to regulate poverty. The work explores specific examples where such systems have impacted access to social services, housing, and child welfare, highlighting how they classify, investigate, and punish individuals. It contends that these technologies enable the nation to maintain an ethical distance from the consequences of policies that disproportionately affect marginalized populations, ultimately weakening democratic values.
Summary based on the publisher's page ↗
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About the author
Virginia Eubanks
Virginia Eubanks (born 1972) is an American political scientist, professor, and author studying technology and social justice. She is an associate professor in the Department of Political Science at the University at Albany, SUNY. Previously Eubanks was a Fellow at New America researching digital privacy, economic inequality, and data-based discrimination. Eubanks has written and co-edited multiple award-winning books, the most well-known being Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor.
Source: Wikipedia ↗
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