Pattern Discrimination

by Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl

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Book cover for Pattern Discrimination

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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?

  • ISBN10 1517906458
  • ISBN13 9781517906450
  • Publish Date 13 November 2018
  • Publish Status Active
  • Publish Country US
  • Imprint University of Minnesota Press
  • Format Paperback
  • Pages 144
  • Language English