Automation And Autonomy: Labour, Capital And Machines In The Artificial Intelligence Industry (Marx, Engels, And Marxisms) - 9783030716912

Palgrave Macmillan
SKU:
9783030716912
|
ISBN13:
9783030716912
$149.40
(No reviews yet)
Condition:
New
Usually Ships in 24hrs
Current Stock:
Estimated Delivery by: | Fastest delivery by:
Adding to cart… The item has been added
Buy ebook
This 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.


  • | Author: James Steinhoff
  • | Publisher: Palgrave Macmillan
  • | Publication Date: Jun 23, 2022
  • | Number of Pages: 266 pages
  • | Language: English
  • | Binding: Paperback/Political Science
  • | ISBN-10: 3030716910
  • | ISBN-13: 9783030716912
Author:
James Steinhoff
Publisher:
Palgrave Macmillan
Publication Date:
Jun 23, 2022
Number of pages:
266 pages
Language:
English
Binding:
Paperback/Political Science
ISBN-10:
3030716910
ISBN-13:
9783030716912