Discriminating Data: Correlation, Neighborhoods, and the New Politics of RecognitionКНИГИ » ОС И БД
Название: Discriminating data: Correlation, Neighborhoods, and the New Politics of Recognition Автор: Wendy Hui Kyong Chun, Alex Barnett Издательство: The MIT Press Год: 2021 Страниц: 344 Язык: английский Формат: epub Размер: 10.1 MB
How Big Data and Machine Learning encode discrimination and create agitated clusters of comforting rage.
In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within Big Data and Machine Learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds Big Data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine Learning and data analytics thus seek to disrupt the future by making disruption impossible.
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Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition 
Название: Discriminating data: Correlation, Neighborhoods, and the New Politics of Recognition
