Predatory Data
Predatory Data illuminates the connections between the nineteenth century’s anti‑immigration and eugenics movements and today’s sprawling systems of techno-surveillance and algorithmic discrimination. Historical and globally multisited, the book examines how dispossession, misrecognition, and segreg...
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| Главный автор: | |
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| Формат: | Online |
| Язык: | английский |
| Опубликовано: |
University of California Press
2025
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| Предметы: | |
| Online-ссылка: | https://library.oapen.org/handle/20.500.12657/96950 |
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| _version_ | 1869521646053752832 |
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| author | Chan, Anita Say |
| author_browse | Chan, Anita Say |
| author_facet | Chan, Anita Say |
| author_sort | Chan, Anita Say |
| collection | Directory of Open Access Books |
| description | Predatory Data illuminates the connections between the nineteenth century’s anti‑immigration and eugenics movements and today’s sprawling systems of techno-surveillance and algorithmic discrimination. Historical and globally multisited, the book examines how dispossession, misrecognition, and segregation are being magnified by dominant knowledge institutions in the Age of Big Data.
Technological advancement has a history, including efforts to chart a path for alternative futures. Anita Say Chan explores these important parallel stories of defiant refusal and liberatory activism, such as how feminist, immigrant, and other minoritized actors worked to develop alternative data practices. Their methods and traditions, over a century old, continue to reverberate through global justice‑based data initiatives today. Predatory Data charts a path for an alternative historical consciousness grounded in the pursuit of global justice.
“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
“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
“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
“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 |
| format | Online |
| id | doab-20.500.12854ir-150231 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | University of California Press |
| publisherStr | University of California Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1502312025-07-21T15:44:02Z Predatory Data Chan, Anita Say eugenics movement thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) Predatory Data illuminates the connections between the nineteenth century’s anti‑immigration and eugenics movements and today’s sprawling systems of techno-surveillance and algorithmic discrimination. Historical and globally multisited, the book examines how dispossession, misrecognition, and segregation are being magnified by dominant knowledge institutions in the Age of Big Data. Technological advancement has a history, including efforts to chart a path for alternative futures. Anita Say Chan explores these important parallel stories of defiant refusal and liberatory activism, such as how feminist, immigrant, and other minoritized actors worked to develop alternative data practices. Their methods and traditions, over a century old, continue to reverberate through global justice‑based data initiatives today. Predatory Data charts a path for an alternative historical consciousness grounded in the pursuit of global justice. “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 “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 “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 “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 2025-01-22T07:55:23Z 2025-01-22T07:55:23Z 2025-01-13T10:18:44Z 2025 book https://library.oapen.org/handle/20.500.12657/96950 9780520402843 https://directory.doabooks.org/handle/20.500.12854/150231 eng open access image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://library.oapen.org/bitstream/20.500.12657/96950/1/predatory-data.pdf University of California Press The Chinese University of Hong Kong Press 10.1525/luminos.215 10.1525/luminos.215 19856893-4bf2-4e3e-9137-c7692d64e4c1 60de9db5-5473-4eec-8298-565c2675bad7 9780520402843 263 Oakland open access |
| spellingShingle | eugenics movement thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) Chan, Anita Say Predatory Data |
| title | Predatory Data |
| title_full | Predatory Data |
| title_fullStr | Predatory Data |
| title_full_unstemmed | Predatory Data |
| title_short | Predatory Data |
| title_sort | predatory data |
| topic | eugenics movement thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) |
| topic_facet | eugenics movement thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) |
| url | https://library.oapen.org/handle/20.500.12657/96950 |
| work_keys_str_mv | AT chananitasay predatorydata |