The Cultural Life of Machine Learning - An Incursion into Critical AI Studies (Paperback, 1st ed. 2021)


This book brings together the work of historians and sociologists 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 DeepMind's 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? We empirically address these questions and more to provide a baseline for future research. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

R1,849

Or split into 4x interest-free payments of 25% on orders over R50
Learn more

Discovery Miles18490
Mobicred@R173pm x 12* Mobicred Info
Free Delivery
Delivery AdviceOut of stock

Toggle WishListAdd to wish list
Review this Item

Product Description

This book brings together the work of historians and sociologists 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 DeepMind's 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? We empirically address these questions and more to provide a baseline for future research. Chapter 2 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Customer Reviews

No reviews or ratings yet - be the first to create one!

Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Release date

December 2021

Availability

Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.

First published

2021

Editors

,

Dimensions

210 x 148 x 22mm (L x W x T)

Format

Paperback

Pages

289

Edition

1st ed. 2021

ISBN-13

978-3-03-056288-5

Barcode

9783030562885

Categories

LSN

3-03-056288-3



Trending On Loot