Cultural Life of Machine Learning: An Incursion into Critical AI Studies

This book explores the origins, practices, and potential futures of contemporary machine learning, drawing from a range of disciplines to address its controversial nature and its increased embeddedness and agency in everyday life. It examines how we can disentangle machine learning from conventional histories of artificial intelligence, theorize the capacity for novelty of machinic agents, and explore reform initiatives for fairness and equity in AI and machine learning.

Format: Hardback
Length: 289 pages
Publication date: 01 December 2020
Publisher: Springer Nature Switzerland AG

This book is a groundbreaking exploration of the origins, practices, and potential futures of contemporary machine learning, a field that has become increasingly intertwined with our daily lives. Drawing on the expertise of historians, sociologists, media studies, communication studies, cultural studies, and information studies, the authors offer a comprehensive analysis of the field's development.

The book begins by tracing the historical roots of machine learning, from its early beginnings in pattern recognition and neural network research in the 1950s and 1960s to the modern-day social and technological dramas of DeepMind's AlphaGo, predictive political forecasting, and the governmentality of extractive logistics. The authors argue that machine learning has become controversial precisely because of its increased embeddedness and agency in our everyday lives.

Chapter 2 of the book is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. This chapter provides a comprehensive baseline for future research, empirically addressing questions such as how can we disentangle the history of machine learning from conventional histories of artificial intelligence? How can we theorize the capacity for novelty of machinic agents? 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?

The book concludes by offering a series of provocations for future research, challenging readers to think critically about the ethical, social, and political implications of machine learning and its potential to shape our world. This is an essential read for anyone interested in the future of technology and society.

Weight: 524g
Dimension: 154 x 217 x 26 (mm)
ISBN-13: 9783030562854
Edition number: 1st ed. 2021