Predatory Data : Eugenics in Big Tech and Our Fight for an Independent Future

• Autore: Chan Anita Say
• Pubblicazione: Berkeley : , : University of California Press, , 2025; ©2025
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (263 pages)
• Disciplina: 005.7
• Soggetto topico: Technology - Social aspects; Discrimination in science - History; Eugenics - Moral and ethical aspects - History; Quantitative research - Moral and ethical aspects; Big data - Moral and ethical aspects; SOCIAL SCIENCE / Technology Studies; SOCIAL SCIENCE / Discrimination
• Classificazione: SOC071000SOC031000
• Nota di contenuto: Introduction : predatory data : civic amputations in the global data economy -- Immigrant excisions, "race suicide" and the eugenic information market -- Streamlining's laboratories : monitoring cultures and eugenic design in the future city -- Of merit, metrics and myth : cognitive elites and techno-eugenics in the knowledge economy -- Relational infrastructures : feminist refusals & immigrant data solidarities -- The coalitional lives of data pluralism : inter-generational feminist resistance to data apartheid -- Community data : pluri-temporalities in the aftermath of big data -- Conclusion : data pluralism and a playbook for defending improbable worlds.
• Sommario/riassunto: 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 minoritized 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.
• Titolo autorizzato: Predatory Data
• ISBN: 9780520402850; 0520402855
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910896408503321
• Lo trovi qui: Univ. Federico II