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OverviewThis book argues that Marxist theory is essential for understanding the contemporary industrialization of the form of artificial intelligence (AI) called machine learning. It includes a political economic history of AI, tracking how it went from a fringe research interest for a handful of scientists in the 1950s to a centerpiece of cybernetic capital fifty years later. It also includes a political economic study of the scale, scope and dynamics of the contemporary AI industry as well as a labour process analysis of commercial machine learning software production, based on interviews with workers and management in AI companies around the world, ranging from tiny startups to giant technology firms. On the basis of this study, Steinhoff develops a Marxist analysis to argue that the popular theory of immaterial labour, which holds that information technologies increase the autonomy of workers from capital, tending towards a post-capitalist economy, does not adequately describe the situation of high-tech digital labour today. In the AI industry, digital labour remains firmly under the control of capital. Steinhoff argues that theories discerning therein an emergent autonomy of labour are in fact witnessing labour’s increasing automation. Full Product DetailsAuthor: James SteinhoffPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: 1st ed. 2021 Weight: 0.354kg ISBN: 9783030716912ISBN 10: 3030716910 Pages: 245 Publication Date: 23 June 2022 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of Contents1. Introduction: Automation, Autonomy and Artificial Intelligence Your Means of Production Revolutions AI in the Real World Machinery and Marxists The Central Argument Computing Machinery Recursion What this Book is Not Chapter Outline 2. Labour, Capital, Machine: Marxist Theory and Technology Introduction Political Economy Marx on Value and Labour Marx on Machines The Fragment on Machines Marxism(s) Soviet Marxism Western Marxism Labour Process Theory The New Reading of Marx Cybernetic Capitalism Conclusion 3. Post-Operaismo and the New Autonomy of Immaterial Labour Introduction From Operaismo to Post-operaismo Post-operaismo Immaterial Labour Theory Human-Machine Hybridization Abstract Cooperation New Autonomy from Capital The Technological Argument for New Autonomy Conclusion 4. Industrializing Intelligence: A Political Economic History of the AI IndustryIntroduction The Historical Context The Advent of AI Research The AI Winter Expert Systems: The First Era of the AI Industry Strategic Computing: AI and the State Part I The Decline of Expert Systems The Rise of Machine Learning Deep Learning: The Second Era of the AI Industry Conclusion 5. Machine Learning and Fixed Capital: The Contemporary AI Industry Introduction Charting the AI Industry AI Capital Composition AI Tech Giants AI Dinosaurs AI Startups AI Think Tanks National AI Strategies: AI and the State Part II AI Capital Concentration Open Source AI, Clouds, AI Chips Labour in the AI Industry Labour Composition: Race and Gender AI Labour Organization Conclusion 6. A Dark Art: The Machine Learning Labour Process Introduction The Machine Learning Labour Process Stage 1: Data Processing Stage 2: Model Building Stage 3: Deployment The Commodity Form of AI Empirical Control AI as Automation The Automation of AI Work Automated Machine Learning Synthetic Automation Other Forms of Automation in Machine Learning Conclusion 7.New Autonomy and Work in the AI Industry Introduction AI Work and Human-Machine Hybridization AI Work and Abstract Cooperation AI Work and New Autonomy Autonomy for What? Conclusion 8. Conclusion: Harry Braverman OverdriveIntroduction Theoretical Synthesis Automation on Steroids Optimism and Agency ConclusionReviewsThe author is very clear and concise in showing the reader what his objectives are and are not, and in guiding the reader through the arguments and evidence. He is explicit in reviewing what he has completed and what the next steps will be. The reader should be aware that this book is basically a philosophical treatise. ... It is worth the effort to read this book. (Anthony J. Duben, Computing Reviews, August 1, 2022) Author InformationJames Steinhoff is a Postdoctoral Fellow at the University of Toronto, Canada. Tab Content 6Author Website:Countries AvailableAll regions |
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