Cultural Life of Machine Learning

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 Warwick’s 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.

• 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. AlphaGo’s 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.