- Main
- Computers - Computer Science
- Pattern Discrimination
Pattern Discrimination
Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, Hito SteyerlSukakah anda buku ini?
Bagaimana kualiti fail ini?
Muat turun buku untuk menilai kualitinya
Bagaimana kualiti fail yang dimuat turun?
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?
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?
Kategori:
Tahun:
2018
Edisi:
Paperback
Penerbit:
Meson Press, University of Minnesota Press
Bahasa:
english
Halaman:
144
ISBN 10:
1517906458
ISBN 13:
9781517906450
Fail:
PDF, 2.19 MB
Tag anda:
IPFS:
CID , CID Blake2b
english, 2018
Selama 1-5 menit fail akan dihantar ke e-mel anda.
Dalam masa 1-5 minit fail akan dihantar ke akaun Telegram anda.
Perhatian: Pastikan bahawa anda telah memautkan akaun anda kepada bot Telegram Z-Library.
Dalam masa 1-5 minit fail akan dihantar ke peranti Kindle anda.
Harap maklum: anda perlu mengesahkan setiap buku yang ingin dihantar ke Kindle anda. Semak e-mel anda untuk pasti ada e-mel pengesahan dari Amazon Kindle Support.
Penukaran menjadi sedang dijalankan
Penukaran menjadi gagal
Faedah Status Premium
- Menghantar ke pembaca elektronik
- Peningkatan had muat turun
- Tukar fail
- Lebih banyak hasil carian
- Faedah lain