The cultural life of machine learning : an incursion into critical AI studies / Jonathan Roberge, Michael Castelle, editors.
Roberge, Jonathan, 1976- editor.; Castelle, Michael, editor.
2021
Q325.5
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title The cultural life of machine learning : an incursion into critical AI studies / Jonathan Roberge, Michael Castelle, editors.
ISBN 9783030562861 (PDF ebook)
3030562867 (PDF ebook)
9783030562854 (hbk.)
3030562859
DOI https://doi.org/10.1007/978-3-030-56286-1
Published Cham, Switzerland : Palgrave Macmillan, [2021]
Language English
Description 1 online resource : illustrations (black and white, and colour)
Item Number 10.1007/978-3-030-56286-1 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
303.4834
Summary This book brings together the work of sociologists and historians along 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 DeepMinds 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? Contributors empirically address these questions and more to provide a baseline for future research. Jonathan Roberge is an Associate Professor at the Institut National de la Recherche Scientifique in Montreal, Canada. He funded the Nenic Lab as part of the Canada Research Chair in Digital Culture he has held since 2012. His most recent edited volume is Algorithmic Cultures (2016). Michael Castelle is an Assistant Professor at the University of Warwicks Centre for Interdisciplinary Methodologies, UK and a Turing Fellow at the Alan Turing Institute, UK. He has a Ph. D. in Sociology from the University of Chicago and a Sc. B. in Computer Science from Brown University. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 24, 2021).
Added Author Roberge, Jonathan, 1976- editor.
Castelle, Michael, editor.
Available in Other Form Print version : 9783030562854
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1. Toward an End-to-End Sociology of 21st-Century Machine Learning
2. Mechanized Significance and Machine Learning: Why it Became Thinkable and Preferable to Teach Machines to Judge the World
3. What Kind of Learning Is Machine Learning?
4. The Other Cambridge Analytics: Early "Artificial Intelligence" in American Political Science
5. Machinic Encounters: A Relational Approach to the Sociology of AI
6. AlphaGos Deep Play: Technological Breakthrough as Social Drama
7. Adversariality in Machine Learning Systems: On Neural Networks and the Limits of Knowledge
8. Planetary Intelligence
9. Critical Perspectives on Governance Mechanisms for AI/ML Systems.

Browse Subjects

Show more subjects...

Statistics

from
to
Export