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      The Cultural Life of Machine Learning: An Incursion into Critical AI Studies

      2 in stock

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      SKU 9783030562854 Categories ,
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      This book brings together the work of historians and sociologists with perspectives from media studies, communication studies, cultural studies, and information studies to address the origins, practices, and possible futures of contemporary machine learning.
      This book bring...

      £79.99

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      Description

      Product ID:9783030562854
      Product Form:Hardback
      Country of Manufacture:CH
      Title:The Cultural Life of Machine Learning
      Subtitle:An Incursion into Critical AI Studies
      Authors:Author: Jonathan Roberge, Michael Castelle
      Page Count:289
      Subjects:Society and culture: general, Society & culture: general, Cultural studies, Media studies, Cultural studies, Media studies
      Description:Select Guide Rating
      This book brings together the work of historians and sociologists with perspectives from media studies, communication studies, cultural studies, and information studies to address the origins, practices, and possible futures of contemporary machine learning.
      This book brings together the work of historians and sociologists with perspectives from media studies, communication studies, cultural studies, and information studies to address the origins, practices, and possible futures of contemporary machine learning. From its foundations in 1950s and 1960s pattern recognition and neural network research to the modern-day social and technological dramas of DeepMind''s AlphaGo, predictive political forecasting, and the governmentality of extractive logistics, machine learning has become controversial precisely because of its increased embeddedness and agency in our everyday lives. How can we disentangle the history of machine learning from conventional histories of artificial intelligence? How can machinic agents'' capacity for novelty be theorized? Can reform initiatives for fairness and equity in AI and machine learning be realized, or are they doomed to cooptation and failure? And just what kind of "learning" does machine learning truly represent? We empirically address these questions and more to provide a baseline for future research.

      Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

      Imprint Name:Springer Nature Switzerland AG
      Publisher Name:Springer Nature Switzerland AG
      Country of Publication:GB
      Publishing Date:2020-12-01

      Additional information

      Weight524 g
      Dimensions154 × 217 × 26 mm