From AI to EI: Towards an ‘Environmental Intelligence’
Proposal Type
Individual Talk
Location
Algorithms & Imaginaries
Start Date
July 2026
End Date
July 2026
Abstract
Highly critical readings of generative ‘AI’ technologies are presently widespread across the humanities and social sciences. Many critiques invoke not only the social harms precipitated, but also the environmental impacts of rapidly growing data infrastructures (Valdivia 2025; Bashir et al. 2024), alongside a rejection of claims that cast AI (generative or otherwise) as a necessary tool for envisioning and managing the planetary environment (Richardson and Munster 2023). Many critics fiercely reject industry rhetorics of AIs techno-social ‘inevitability’ (Duarte et al. 2025), but there is consequently less consideration of whether generative AI is ‘inevitably’ or irredeemably harmful, or whether alternative imaginaries and practices might be developed that encourage different AI futures that are also far more mindful of the Earthly environment. This is a fraught area of enquiry, and progressive outcomes are not guaranteed, but it is one the author is pursuing through a speculative creative-critical project. This project employs a small-scale generative AI as part of a data-gathering apparatus—collectively characterised using Leonelli’s (2025) term ‘E.I.’, an ‘Environmental Intelligence’—for sensing and mapping local environmental information before weaving it into a generative collage of interlinked words and images—as shaped by a dataset of existing artistic and scientific accounts of human-ecological relationships. The resulting multimodal texts, and the processes behind them, are intended as a speculative meditation on the different relationships between AI and the environment, as entangled ‘more-than-human’ formations, before evaluating whether these can be negotiated progressively to facilitate modes of sensitivity and attentiveness towards a changing planet.
Keywords
AI, Environment, Environmental Intelligence, Generative, Art, Speculative Media
References
Bashir, Noman, Priya Donti, James Cuff, Sydney Sroka, Marija Ilic, Vivienne Sze, Christina Delimitrou, and Elsa Olivetti. 2024. “The Climate and Sustainability Implications of Generative AI.” An MIT Exploration of Generative AI, March. https://doi.org/10.21428/e4baedd9.9070dfe7.
Duarte, T, Kherroubi Garcia, I, Anshur, R, Humfress, H, Orchard, D, Wright, S (2025) Resisting, Refusing, Reclaiming, Reimagining: Charting Challenges to Narratives of AI Inevitability, We and AI, DOI: https://doi.org/10.5281/zenodo.17382120.
Leonelli, S. 2025. Environmental Intelligence: Redefining the Philosophical Premises of AI. Harvard Data Science Review, 7(4). https://doi.org/10.1162/99608f92.ac7c1504.
Richardson, M, and Anna Munster. 2023. “Pluralising the Planetary: The Radical Incompleteness of Machinic Envisioning.” Media+Environment 5 (1). https://doi.org/10.1525/001c.87980.
Valdivia, A. 2025. The supply chain capitalism of AI: a call to (re)think algorithmic harms and resistance through environmental lens. Information, Communication & Society, 28(12), 2118–2134. https://doi.org/10.1080/1369118X.2024.2420021.
From AI to EI: Towards an ‘Environmental Intelligence’
Algorithms & Imaginaries
Highly critical readings of generative ‘AI’ technologies are presently widespread across the humanities and social sciences. Many critiques invoke not only the social harms precipitated, but also the environmental impacts of rapidly growing data infrastructures (Valdivia 2025; Bashir et al. 2024), alongside a rejection of claims that cast AI (generative or otherwise) as a necessary tool for envisioning and managing the planetary environment (Richardson and Munster 2023). Many critics fiercely reject industry rhetorics of AIs techno-social ‘inevitability’ (Duarte et al. 2025), but there is consequently less consideration of whether generative AI is ‘inevitably’ or irredeemably harmful, or whether alternative imaginaries and practices might be developed that encourage different AI futures that are also far more mindful of the Earthly environment. This is a fraught area of enquiry, and progressive outcomes are not guaranteed, but it is one the author is pursuing through a speculative creative-critical project. This project employs a small-scale generative AI as part of a data-gathering apparatus—collectively characterised using Leonelli’s (2025) term ‘E.I.’, an ‘Environmental Intelligence’—for sensing and mapping local environmental information before weaving it into a generative collage of interlinked words and images—as shaped by a dataset of existing artistic and scientific accounts of human-ecological relationships. The resulting multimodal texts, and the processes behind them, are intended as a speculative meditation on the different relationships between AI and the environment, as entangled ‘more-than-human’ formations, before evaluating whether these can be negotiated progressively to facilitate modes of sensitivity and attentiveness towards a changing planet.
Keywords
AI, Environment, Environmental Intelligence, Generative, Art, Speculative Media
References
Bashir, Noman, Priya Donti, James Cuff, Sydney Sroka, Marija Ilic, Vivienne Sze, Christina Delimitrou, and Elsa Olivetti. 2024. “The Climate and Sustainability Implications of Generative AI.” An MIT Exploration of Generative AI, March. https://doi.org/10.21428/e4baedd9.9070dfe7.
Duarte, T, Kherroubi Garcia, I, Anshur, R, Humfress, H, Orchard, D, Wright, S (2025) Resisting, Refusing, Reclaiming, Reimagining: Charting Challenges to Narratives of AI Inevitability, We and AI, DOI: https://doi.org/10.5281/zenodo.17382120.
Leonelli, S. 2025. Environmental Intelligence: Redefining the Philosophical Premises of AI. Harvard Data Science Review, 7(4). https://doi.org/10.1162/99608f92.ac7c1504.
Richardson, M, and Anna Munster. 2023. “Pluralising the Planetary: The Radical Incompleteness of Machinic Envisioning.” Media+Environment 5 (1). https://doi.org/10.1525/001c.87980.
Valdivia, A. 2025. The supply chain capitalism of AI: a call to (re)think algorithmic harms and resistance through environmental lens. Information, Communication & Society, 28(12), 2118–2134. https://doi.org/10.1080/1369118X.2024.2420021.
Bio
Dr. Richard A Carter is a Senior Lecturer in Digital Culture at the University of York.
Website: https://richardacarter.com/
BlueSky: @richardacarter.bsky.social