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The Tensions of Algorithmic Thinking

Automation, Intelligence and the Politics of Knowing

David Beer (University of York)

$185

Hardback

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English
Bristol University Press
01 December 2022
This book will be of interest to anyone who is concerned with the rise of algorithmic thinking and the way it permeates society.

We are living in algorithmic times.

From machine learning and artificial intelligence to blockchain or simpler news-feed filtering, automated systems can transform the social world in ways that are just starting to be imagined.

Redefining these emergent technologies as the new systems of knowing, pioneering scholar David Beer examines the acute tensions they create and how they are changing what is known and what is knowable. Drawing on cases ranging from the art market and the smart home through to financial tech, AI patents and neural networks, he develops key concepts for understanding the framing, envisioning and implementation of algorithms.
By:  
Imprint:   Bristol University Press
Country of Publication:   United Kingdom
Dimensions:   Height: 234mm,  Width: 156mm, 
ISBN:   9781529212891
ISBN 10:   1529212898
Pages:   152
Publication Date:  
Audience:   Professional and scholarly ,  General/trade ,  Undergraduate ,  ELT Advanced
Format:   Hardback
Publisher's Status:   Active
1. Introduction: Tense Thinking and the Myths of an Algorithmic New Life 2. The Pursuit of Posthuman Security 3. Overstepping and the Navigation of the Perceived Limits of Algorithmic Thinking 4. (Dreaming of) Super Cognizers and the Stretching of the Known 5. The Presences of Nonknowledge 6. Conclusion: Algorithmic Thinking and the Will to Automate

David Beer is Professor of Sociology at the University of York.

Reviews for The Tensions of Algorithmic Thinking: Automation, Intelligence and the Politics of Knowing

"""With attention to detail and a historical sensitivity, Beer weaves together a compelling story of the forces and frictions surrounding automation today. A treasure trove for anyone interested in the social theory of machine learning."" Taina Bucher, University of Oslo"


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