ISBN: 9781517906450 - pattern discrimination (in search of media) (17 resultados)

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Taschenbuch. Condición: Neu. Pattern Discrimination | Clemens Apprich (u. a.) | Taschenbuch | Englisch | University of Minnesota Press | EAN 9781517906450 | Verantwortliche Person für die EU: Mare Nostrum Group B.V., Doelen 72, 4831 GR BREDA, NIEDERLANDE, gpsr[at]mare-nostrum[dot]co[dot]uk | Anbieter: preigu.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 144 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…