ReviewAI & society2026
The ethics in sustainable AI: a scoping literature review on normativity in the academic discourse on the environmental sustainability of AI.
Review in AI & society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AI is developing rapidly, as are concerns about the environmental impact of its training and deployment. Studies about the environmental sustainability of AI have begun to emerge in the past five years, stressing the need for critical reflection on the discursive underbelly of this emerging scholarship. For example, how do authors frame the problem of the environmental impact of AI? Are there any ethical reflections accompanying their reporting, and if so, which ethical theories and principles guide normative considerations about the environmental impact of AI? In this study, we conduct a scoping literature review on (1) how authors refer to and frame the problem of the environmental impact of AI systems, (2) who is ascribed responsibility for mitigating said impact, (3) what mitigative measures are proposed, and (4) what normative commitments justify such prescriptive normative statements. Our findings indicate that most literature on the topic is concentrated in computer science, engineering, and natural sciences, and the humanities are mostly absent. This results in a dominance of technofix attitudes towards the problem, and a narrow and limited engagement with ethical principles and theories. As such, we argue for more interdisciplinary work on the environmental sustainability of AI, leading to more diverse solutions and more explicit and pluralistic ethical starting points, grounded, for example, in relational and more-than-human ethics. The findings of this review highlight gaps in the literature and opportunities for developers, social scientists, and AI ethicists for more effective and diverse responses to AI's environmental impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.