Countering the Cloud

Thinking With and Against Data Infrastructures
1. Auflage 2024
ISBN: 978-1-032-37642-4
Verlag: Routledge

Buch, Englisch, 98 Seiten, Format (B × H): 140 mm x 216 mm, Gewicht: 138 g

Reihe: Routledge Focus on IT & Society

How do cables and data centers think? This book investigates how information infrastructures enact particular forms of knowledge. It juxtaposes the pervasive logics of speed, efficiency, and resilience with more communal and ecological ways of thinking and being, turning technical “solutions” back into open questions about what society wants and what infrastructures should do.

Moving from data centers in Hong Kong to undersea cables in Singapore and server clusters in China, Munn combines rich empirical material with insights drawn from media and cultural studies, sociology, and philosophy. This critical analysis stresses that infrastructures are not just technical but deeply epistemological, privileging some actions and actors while sidelining others.

This innovative exploration of the values and visions at the heart of our technologies will interest students, scholars, and researchers in the areas of communication studies, digital media, technology studies, sociology, philosophy of technology, information studies, and geography.

Zielgruppe

Academic

Autoren/Hrsg.

Munn, Luke

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Wissenssoziologie, Wissenschaftssoziologie, Techniksoziologie
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften

Inhaltsverzeichnis

1. Epistemic Infrastructure; 2. Fast & Slow Knowledge; 3. Efficiency & Waste; 4. Resilience & Failure; 5. Epilogue: Alternative Infrastructure; Acknowledgements; Index

Über Autor(innen)

Luke Munn is a media studies scholar based in Tamaki Makaurau, Aotearoa New Zealand. His research investigates the sociocultural impacts of digital cultures and their broader intersections with race, politics, and the environment. He is the author of Unmaking the Algorithm, Logic of Feeling, and Automation is a Myth.