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Atlas of AI: The Real Worlds of Artificial Intelligence

Autor Kate Crawford

Editorial YALE UNIVERSITY PRESS

Atlas of AI: The Real Worlds of Artificial Intelligence
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  • Publisher YALE UNIVERSITY PRESS
  • ISBN13 9780300209570
  • ISBN10 0300209576
  • Type BOOK
  • Pages 336
  • Published 2021
  • Language English
  • Bookbinding Hard cover

Atlas of AI: The Real Worlds of Artificial Intelligence

Autor Kate Crawford

Editorial YALE UNIVERSITY PRESS

-5% disc.    28,90€
27,46€
Save 1,45€
Not available, ask for avalaibility
Free shipping
Mainland Spain
FREE shipping from €19

to mainland Spain

24/48h shipping

5% discount on all books

FREE pickup at the bookstore

Come and be surprised!

Book details

The hidden costs of artificial intelligence—from natural resources and labor to privacy, equality, and freedom.



What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award‑winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity. Rather than taking a narrow focus on code and algorithms, Crawford offers us a material and political perspective on what it takes to make AI and how it centralizes power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.

Kate Crawford is a leading scholar of the social implications of AI. She is a Research Professor at USC Annenberg, a senior principal researcher at Microsoft Research, and the inaugural chair of AI and Justice at the École Normale Supérieure.

"This study argues that [artificial intelligence] is neither artificial nor particularly intelligent. . . . A fascinating history of the data on which machine-learning systems are trained." —New Yorker

"A valuable corrective to much of the hype surrounding AI and a useful instruction manual for the future." —John Thornhill, Financial Times

"It’s a masterpiece, and I haven’t been able to stop thinking about it." —Karen Hao, senior editor, MIT Tech Review