The insidious legacy of eugenics lives on in the techno-surveillance, and algorithmic authoritarianism, and data-driven discrimination of Big Tech — this book explains how it happened and why we need to fight back.
Predatory Data
EUGENICS IN BIG TECH AND OUR FIGHT FOR AN INDEPENDENT FUTURE
About
At the turn of the 20th century, eugenicists compiled harmful data about marginalized people, fueling racial divisions and political violence under the guise of streamlining society towards the future. Now, even as Big Tech champions itself as a global leader of progress and innovation, we are falling into the same trap, and the consequences of technological infrastructure feed the vitriol that divides people on and offline.
Predatory Data: Eugenics in Big Tech and Our Fight for an Independent Future (University of California Press, January 7, 2025) is the first book to draw this direct line between the datafication and prediction techniques of past eugenicists and today's often violent and extractive "big data" regimes.
Chan reveals how the AI-driven and market-based models of Big Tech are built on data that exploit women and immigrant groups, amplifying social hierarchies, suppressing diverse voices and influencing AI's predictions of majoritarian outcomes as the most probable, likely, and “ideal” futures.
But she also shows us that it doesn’t have to be this way. Chan illuminates alternatives that “center repair and equity-driven reform.” She documents the trailblazing efforts of feminist and immigrant activists from a century ago who resisted dominant institutional research norms and sought to develop alternative data practices. Their legacy continues to inspire today’s global justice-based data initiatives. By looking to the past to shape our future, this book charts a path for an alternative historical consciousness rooted in global justice.
*Praise for Predatory Data
"This groundbreaking book connects historical practices of eugenics to big data's contemporary challenges. Anita Say Chan highlights the power of community-based alternatives to extractive data that are rooted in feminist, people of color, and Indigenous perspectives. An essential book for anyone looking to envision more equitable technological futures."
—Shaka McGlotten, author of Virtual Intimacies: Media, Affect, and Queer Sociality
"Predatory Data is the framework that we have been waiting for—to refuse, resist, and reimagine new possibilities as a part of decolonizing algorithmic and data practices."
—Nishant Shah, Associate Professor and Director of the Digital Narratives Studio, Chinese University of Hong Kong
"By taking eugenics as the founding moment of modernity's drive to data extraction, Chan's book dislodges all comforting notions of technology as trustworthy and upends ruling assumptions about who has the right to speak through data. An essential retelling of how data happened that also rethinks whose futures really matter in the worlds that data and AI are now building."
—Nick Couldry, coauthor of The Costs of Connection
"Predatory Data asks readers to consider the striking parallels between the eugenics movement of the early twentieth century and today's big data practices. With unflinching and careful analysis, Chan shows how the quest to capture and map human differences creates an extractive and destructive course that profits from marginalizing the most marginalized among us, often in the name of knowledge regimes. This book delivers a critical examination of the persistent continuity of predatory data methods across generations and a call to action to reimagine how data infrastructures could promote justice and pluralism. Drawing on examples from community leaders, partners, experts, and fellow researchers, Chan inspires us to understand the power and politics of data, and how to fight for an independent and inclusive future without compromising our humanness."
—Mary L. Gray, MacArthur Fellow and coauthor of Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass
About the Author
Anita Say Chan, PhD (she/her) is a scholar and educator dedicated to feminist and decolonial approaches to technology.
She is an Associate Professor of Information Sciences and Media, and founder of the Community Data Clinic at the University of Illinois at Urbana-Champaign.