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The Inner World of Artificial Intelligence.

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Format:
Book
Author/Creator:
Bahmanteymouri, Elham.
Contributor:
Bahmanteymouri, Elham
Language:
English
Subjects (All):
Artificial intelligence.
Physical Description:
1 online resource (300 pages)
Edition:
1st ed.
Place of Publication:
2026.
Milton : Taylor & Francis Group, 2026.
Summary:
The Inner World of Artificial Intelligence offers a critical and interdisciplinary exploration of how artificial intelligence (AI) is reshaping the contemporary world. The book examines the hidden infrastructures, political economies, and spatial imaginaries that underpin AI.
Contents:
Cover
Endosement
Half Title
Title
Copyright
Contents
Contributors' Bios
1 Editorial Introduction: The Inner World of Artificial Intelligence
Section 1 Hidden and Subsumed Humans in Artificial Intelligence
2 Human Subsumption in Training Datasets for Music Generation
3 Authorship, Ownership, Authority, Validation, and Creativity through AI
4 Humanness in the Context of Artificial Intelligence: Performative Imaginaries in Popular Science Narratives
5 Reclaiming Agency! Algoactivism beyond Resistance
Section 2 Political Economies and Fantasies of AI
6 AI in the Shadow of Big Other: Planning, Power, and the Locus of Control
7 Land for AI: Data Center Real Estate Markets
8 Artificial Intelligence and Surveillance in the City: Implications for Urban Governance, Democracy, and Power
9 Can Artificial Intelligence Facilitate Faster Development Assessment? The Case of an Early Adopter Programme
10 AI and the Governance of Risk: Fantasies, Safety, and Situated Futures
Section 3 AI, Urban Knowledge, and the Repressed Real
11 Urban Artificial Intelligence and Planning: Symbolic and Imaginary Representations and the Repressed Real
12 From Urban Surveillance to Urban Care: Care-Full Justice in the Age of AI
13 Tackling the Bias Problem at the Design Stage: Empirical Evidence from the CommuniCity Project
14 Machine Learning-Driven Framework for SDG-Based Impact Assessment of Transport Infrastructure Projects
15 From Classical Models to Intelligent Systems: AI and Machine Learning in Transportation Planning
Index.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
1-04-051288-7
1-04-064016-8
1-003-48016-0

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