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AI fetishism and perverse climate disavowal

Why denying destructiveness facilitates our ecological collapse

Bibliographic Data

ID12175474
AuthorsAlexander M Stoner (0000-0002-5892-8245, Northern Michigan University, Marquette, USA, corresponding author), Anthony J Knowles (0009-0009-3256-1498, University of Tennessee, Knoxville, USA)
Year2025
Publication date2025-11-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCritical Sociology (JOURNAL)
Journal identifiersISSN: 0896-9205 • E-ISSN: 1569-1632
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/08969205251383421
OpenAlexW4415781971
LanguageEN
Citations received1
References cited39

As ecological crises intensify, scholars and activists increasingly question the sustainability of economic growth. Yet, the dominant growth-oriented paradigm remains foundational to advanced capitalist societies and cannot be altered without significant social disruption. The resulting tension between ecological limits and the imperative for continuous growth generates “climate anxiety.” This article advances the concept of perverse climate disavowal : a mode of climate denial that acknowledges climate threats while maintaining faith in the illusion of infinite economic expansion. This disavowal functions as a psychological defense mechanism, enabling individuals and institutions to avoid confronting structural contradictions. The article examines the increasing use of artificial intelligence to address climate change as a key expression of this phenomenon. A directed qualitative content analysis was conducted on USA news articles (2020–2024) concerning AI and climate change. A complete description of the methodology, including rank order frequency of concept codes and representative quotes, is included

Capitalism · Climate change · Denial · Ecological crisis · Environmental sociology · Fetishism · Order (exchange · Political economy of climate change · Sustainability · Climate Change Communication and Perception · Earth Systems and Cosmic Evolution · Innovation, Sustainability, Human-Machine Systems

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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