Clemens Apprich,Wendy Hui Kyong Chun,Florian Cramer,Hito Steyerl
Pattern Discrimination
Pattern Discrimination
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"Human" prejudices reemerge in algorithmic cultures through pattern discrimination, reinstating old forms of social segregation and further inscribing inequality into media. This book investigates how to discriminate without being discriminatory, filter information out of data without reinserting racist, sexist, and classist beliefs, and queer homophilic tendencies within digital cultures.
Format: Paperback / softback
Length: 144 pages
Publication date: 13 November 2018
Publisher: University of Minnesota Press
How do “human” prejudices reemerge in algorithmic cultures allegedly devised to be blind to them? This book investigates a fundamental axiom in computer science: pattern discrimination. By imposing identity on input data, algorithms filter signals from noise, but this process can reinstate old forms of social segregation, such as class, race, and gender. Machine-learning algorithms deepen bias and further inscribe inequality into media, but pattern discrimination is essential to human-and nonhuman-cognition. This volume asks how we can discriminate without being discriminatory, filter information out of data without reinserting racist, sexist, and classist beliefs, and queer homophilic tendencies within digital cultures.
Weight: 146g
Dimension: 128 x 177 x 11 (mm)
ISBN-13: 9781517906450
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