Predatory Data
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Predatory Data
The first book to draw a direct line between the datafication and prediction techniques of past eugenicists and today's often violent and extractive "big data" regimes.
Predatory Data illuminates the throughline between the nineteenth century's anti-immigration and eugenics movements and our sprawling systems of techno-surveillance and algorithmic discrimination. With this book, Anita Say Chan offers a historical, globally multisited analysis of the relations of dispossession, misrecognition, and segregation expanded by dominant knowledge institutions in the Age of Big Data.
While technological advancement has a tendency to feel inevitable, it always has a history, including efforts to chart a path for alternative futures and the important parallel story of defiant refusal and liberatory activism. Chan explores how more than a century ago, feminist, immigrant, and other minoritised actors refused dominant institutional research norms and worked to develop alternative data practices whose methods and traditions continue to reverberate through global justice-based data initiatives today. Looking to the past to shape our future, this book charts a path for an alternative historical consciousness grounded in the pursuit of global justice.
A free ebook version of this title is available through Luminos, University of California Press's Open Access publishing program. Visit www.luminosoa.org to learn more.
Book Details
INFORMATION
ISBN: 9780520402843
Publisher: University of California Press
Format: Paperback / softback
Date Published: 07 January 2025
Country: United States
Imprint: University of California Press
Illustration: 1 b-w figure, 6 color figures
Audience: Professional and scholarly
DIMENSIONS
Spine width: 15.0mm
Width: 152.0mm
Height: 229.0mm
Weight: 363g
Pages: 262
About the Author
Anita Say Chan is a feminist and decolonial scholar of Science and Technology Studies and Associate Professor of Information Sciences and Media Studies at the University of Illinois, Urbana-Champaign.
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