Aug 2026· IEEE Energy Sustainability Magazine· Vol 2, pp. 132-139· 0 citations· 9 references
Abstract
Sustainable artificial intelligence (AI) has gained increasing prominence in academic, policy, and industry discussions, yet the concept remains underspecified and frequently deployed in ways that obscure the environmental and social harms associated with contemporary AI systems. This article argues that, for industry, sustainable AI must be understood not as a set of optional efficiency improvements or “AI for good” initiatives, but as a structural and ethical necessity. Building on the distinction between AI for sustainability and the sustainability of AI, the article situates sustainable AI within the broader evolution of AI ethics, identifying it as a hallmark of a third wave characterized by a structural turn. This perspective moves beyond artefact-level concerns such as fairness or transparency to examine AI’s embeddedness within global sociotechnical systems, including energy infrastructures, mineral extraction, data centers, supply chains, and extraplanetary technologies.
This paper argues that most responsible AI (RAI) governance frameworks do not meaningfully address AI’s environmental and social costs, and proposes the concept of critical AI governance, which rests on three overarching principles: critically questioning dominant ideologies and economic imperatives, prioritizing socia...
Paul Schuetze, B. Brevini· AI & SOCIETY· 0 citations
This article argues that AI's developmental value, when applied to the most critical international development challenges humanity faces, still depends on the geopolitical, institutional, environmental, labor, and ethical conditions that determine how AI development and deployment benefits and risks are distributed.
Marta Koch, J. Wang, Shreya Ravikumar et al.· MIT Science Policy Review· 1 citation
This paper introduces the concept of “epistemic infrastructure” to capture AI’s role in constituting the conditions of possibility for thought, and proposes governance mechanisms calibrated to this infrastructural function.
It is argued that considerations of AI ethics must extend beyond models and data to encompass the hardware infrastructures on which they depend, and that embedding stakeholder reflection is critical for anticipatory governance in the physical infrastructure of AI.
Naira Paola Arnez-Jordan, Chiara Ullstein, Michel Hohendanner et al.· 0 citations
The study investigates how AI fosters social welfare, profitable growth, and environmental conservation, while also considering combined enterprises, including ethical business practices, energy consumption, and data sequestration.
Md Soleman Pharcy, Jiaur Rahaman, S. Barman· International Journal of Kno...· 0 citations
The assessments indicate that the European Union's desire to compete with the United States and China in the global artificial intelligence race creates a context that may make prioritizing ethical principles difficult.
Tolgay Ercan· Düzce Üniversitesi Sosyal Bi...· 0 citations
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