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How do “human”prejudices reemerge in algorithmic cultures allegedly devised to be blind to them?How do “human”prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? To answer this question, this book investigates a fundamental axiom in computer science: pattern discrimination. By imposing identity on input data, in order to filter-that is, to discriminate-signals from noise, patterns become a highly political issue. Algorithmic identity politics reinstate old forms of social segregation, such as class, race, and gender, through defaults and paradigmatic assumptions about the homophilic nature of connection.Instead of providing a more “objective”basis of decision making, machine-learning algorithms deepen bias and further inscribe inequality into media. Yet pattern discrimination is an essential part of human-and nonhuman-cognition. Bringing together media thinkers and artists from the United States and Germany, this volume asks the urgent questions: How can we discriminate without being discriminatory? How can we filter information out of data without reinserting racist, sexist, and classist beliefs? How can we queer homophilic tendencies within digital cultures?
Author: Apprich, Clemens & Wendy Hui Kyong Chun & Florian Cramer & Hito Steyerl Year: 2018 ISBN: 9781517906450 Pages: 144 Language: English Publisher: University of Minnesota Press Publisher's city: Minneapolis Publication date: