Ecological Impacts

On this page you will find a range of references related to the ecological impacts of digital technologies, with an emphasis on artificial intelligence. The list is divided into three sections:

1. Starting Points

    2. Quantitative and Policy Research

    3. Critical Assessments in the Social Sciences and Humanities

    The entries in each section are organized by year, with the most recent first. Each section begins with a short summary offering a sense of its contents. The list as a whole aims to highlight some prominent debates, concepts, and analyses but is not intended to provide a comprehensive perspective on this fast-emerging and vast field.

    This section includes recent, short pieces curated from scientific, policy, and news media sources, which indicate growing awareness that the increasing integration of AI technologies and digital platforms in economic, military, and consumer spheres of activity entails significant ecological impacts. Many pieces on this list emphasize that AI technology and its infrastructure–perhaps most easily recognizable in the integration of AI search and chat functions in mobile devices–requires far more energy, water, and mineral resources than the “cloud” image implies. These requirements in turn translate into specific ecological impacts, notably GHG emissions, but also, for example, the depletion of ground water reserves in the vicinity of data centers, and the destruction of ecosystems in rare earth mining locales. Others highlight concepts and debates within the broader research context, such as: identifying and quantifying impacts, achieving “sustainable AI,” and drawing connections between the expansion of AI systems, quantifiable ecological impacts, and unacknowledged societal harms, including but not limited to those characterized in terms of post-neoliberal “green extractivism” in the global south. See the pieces published by the UN Environment Programme (Sept 2024) for an introductory, policy-oriented synopsis of the current state of affairs.

    Berreby, D. 2024. “As Use of A.I. Soars, So Does the Energy and Water It Requires.” YaleEnvironment360 (Feb 6).

    Brevini, B. 2024. “An Eco-Political Economy of AI to Understand the Complexities of Its Environmental Costs.VoxEU (Nov 22).

    Crawford. K. 2024. “Generative AI’s Environmental Costs Are Soaring — and Mostly Secret.” Nature 626: 693 (Feb 20).

    Friends of the Earth, et al. 2024. Artificial Intelligence: A Threat to Climate Change, Energy Usage and Disinformation. Report.

    Luccioni, S., L. Trevelin, and M. Mitchell. 2024. “The Environmental Impacts of AI — Primer.” Hugging Face (Sept 3).

    Milmo, D. 2024. “Google’s Emissions Climb Nearly 50% in Five Years Due to AI Energy Demand.” The Guardian (July 2).

    Obrien, I. 2024. “Data Center Emissions Probably 662% Higher than Big Tech Claims. Can It Keep Up the Ruse?The Guardian (Sep 15).

    Stokel-Walker, C. 2024. “Concerned About Your Data Use? Here Is the Carbon Footprint of an Average Day of Emails, WhatsApps and More.” The Guardian (Oct 31).

    United Nations Environment Programme. 2024. “AI Has an Environmental Problem. Here’s What the World Can Do About That.” UNEP Newletter (Sept 21).

    United Nations Environment Programme. 2024. “Artificial Intelligence (AI) End-to-End: The Environmental Impact of the Full AI Life Cycle Needs to Be Comprehensively Assessed.” Issue Note (21 September 2024). Nairobi: UNEP.

    Zhang, M. 2024. “Data Center Water Usage: A Comprehensive Guide.” DGTL Infra (Jan 17).

    Bruna, N. 2023. “Green Extractivism and Expropriation of Emission Rights: Are Rural Workers in the Global South Subsidizing the Next Leap of Postcolonial Capitalism?Berliner Gazette (Nov 23).

    Erdenesanaa, D. 2023. “A.I. Could Soon Need as Much Electricity as an Entire Country.” The New York Times (Oct 23).

    Heikka, M. 2023. “Making an Image with Generative AI Uses as Much Energy as Charging Your Phone.” MIT Technology Review (Dec 1)

    Lehuedé, S. 2022. “Big Tech’s New Headache: Data Centre Activism Flourishes Across the World.” Media@LSE Blog (Nov 2).

    Monserrate, S.G. 2022. The Staggering Ecological Impacts of Computation and the Cloud.” The MIT Press Reader (Feb 14). 

    Schütze, P. 2022. “Mining the Future? The Artificial Intelligence of Climate Breakdown.” Berliner Gazette Blog, Mediapart (May 26).

    Walkley, S. 2022. “The Carbon Cost of Email.” Our News [blog]. The Carbon Literacy Project (Sep).

    Chan, D. 2021. “Your Website is Killing the Planet.” WIRED (Mar 22).

    Cohen, J. 2021. “These Are the Worst (and Best) Websites for Carbon Emissions.” PCMag (May 21).

    Anair, D., J. Martin, M. C. Pinto de Moura, and J. Goldman. 2020 “Ride-Hailing’s Climate Risks: Steering a Growing Industry Toward a Clean Transportation Future.” Union of Concerned Scientists (Feb).

    Donaghy, T., C. Henderson, and E. Jardim.“ 2020. Oil in the Cloud: How Tech Companies Are Helping Big Oil Profit from Climate Destruction.”  Greenpeace Reports (May 19).

    Griffiths, S. 2020. “Why Your Internet Habits Are Not as Clean as You Think.” BBC (Mar 5).

    2. Quantitative and Policy Research

    This section primarily lists recent research articles and policy reports on methods and results of efforts to identify and quantify the ecological impacts of AI and digital platforms. Carbon and water “footprinting,” and “life cycle analysis” are prominent methodological frameworks in these literatures. Also included are references to solution-oriented policy discourses, frequently framed in terms of “green” and “sustainable” AI, and the “ethics” thereof. As the literature on both quantification and policy solutionism is extensive and fast-expanding, the list is intended to be indicative rather than comprehensive.

    Bashir, N., P. Donti, J. Cuff, S. Sroka, M. Ilic, V. Sze, C. Delimitrou, and E. Olivetti. 2024. “The Climate and Sustainability Implications of Generative AI.” An MIT Exploration of Generative AI, March 27. doi.org/10.21428/e4baedd9.9070dfe7

    Istrate, R., V. Tulus, R.N. Grass et al. 2024. “The Environmental Sustainability of Digital Content Consumption.” Nature Communications 15: 3724. doi.org/10.1038/s41467-024-47621-w.

    Kamiya, G. and P. Bertoldi. 2024. “Energy Consumption in Data Centres and Broadband Communication Networks in the EU.” Publications Office of the European Union, Luxembourg. doi.org/10.2760/706491.

    Luccioni, A, Y. Jernite, and E. Strubell. 2024. “Power Hungry Processing: Watts Driving the Cost of AI Deployment?” FAccT ’24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (June 5), 85-99. doi.org/10.1145/3630106.3658542.

    Sheldon, T. L., and R. Dua. 2024. “Impacts of Ride-Hailing on Energy and the Environment: A Systematic Review.” Environmental Research Letters 19 (4): 043004. doi.org/10.1088/1748-9326/ad3285.

    de Vries, A. 2023. “The Growing Energy Footprint of Artificial Intelligence.” Joule 7 (10): 2191-94. doi.org/10.1016/j.joule.2023.09.004.

    Li, P., J. Yang, M. A. Islam, and S. Ren. 2023. “Making AI Less ‘Thirsty’: Uncovering and Addressing the Secret Water Footprint of AI Models.” Arxiv preprint: 2304.03271v3. doi.org/10.48550/arXiv.2304.03271

    Louguet, A., M. Caspani, D. Pytel, A. Pirlot, M. Faura Rosendo, and H. Blanadet. 2023. Assessment of the Energy Footprint of Digital Actions and Services. Publications Office of the European Union.

    Luccioni, A. S., S. Viguier, and A-L. Ligozat. 2023. “Estimating the Carbon Footprint of BLOOM, A 176B Parameter Language Model.” Journal of Machine Learning Research 24: 1-15.

    Moulierac, J., G. Urvoy-Keller, and M. Dinuzzi, Zhejiayu Ma. 2023. “What is the Carbon Footprint
    of One Hour of Video Streaming?
    ” Hal Open Science Repository: hal-04069500 v2.

    Roussilhe, G., A-L. Ligozat, and S. Quinton. 2023. “A Long Road Ahead: A Review of the State of Knowledge of the Environmental Effects of Digitization.” Current Opinion in Environmental Sustainability 62: 101296. doi.org/10.1016/j.cosust.2023.101296.

    Verdecchia, R., J. Sallou, and L. Cruz. 2023. “A Systematic Review of Green AI.” WIREs Data Mining and Knowledge Discovery 13 (4): e1507. doi.org/10.1002/widm.1507.

    Wright , D. B., C. Igel, G. Samuel and R. Selvan. 2023 “Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI.” Arxiv preprint: 2309.02065v1. doi.org/10.48550/arXiv.2309.02065.

    Al Kez, D. et al. 2022. “Exploring the Sustainability Challenges Facing Digitalization and Internet Data Centers.”Journal of Cleaner Production 371 (15 Oct): 133633. doi.org/10.1016/j.jclepro.2022.133633.

    Batmunkh, A. 2022. “Carbon Footprint of the Most Popular Social Media Platforms.” Sustainability 14 (4): 2195. doi.org/10.3390/su14042195.

    Reyes-García, V. et al. 2022. “Decarbonizing the Academic Sector: Lessons from an International Research Project.”Journal of Cleaner Production 368 (25 Sep): 133174. doi.org/10.1016/j.jclepro.2022.133174.

    Wu, C-J. et al. 2022. “Sustainable AI: Environmental Implications, Challenges and Opportunities.” Proceedings of Machine Learning and Systems 4: 795-813.

    Gupta, U. et al. 2021. “Chasing Carbon: The Elusive Environmental Footprint of Computing.” In 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA 2021), 854-867.

    Obringer, R. et al. 2021. “The Overlooked Environmental Footprint of Increasing Internet Use.” Resources, Conservation and Recycling 167, (April): 105389. doi.org/10.1016/j.resconrec.2020.105389.

    Pirson, T. and D. Bol. 2021. “Assessing the Embodied Carbon Footprint of IoT Edge Devices with a Bottom-up Life-cycle Approach.”Journal of Cleaner Production 322, (1 Nov): 128966. doi.org/10.1016/j.jclepro.2021.128966.

    Siddik, A. B., A. Shehabi, and L. Marston. 2021. “The Environmental Footprint of Data Centers in the United States.Environmental Resource Letters 16, 064017. doi.org/10.1088/1748-9326/abfba1.

    van Wynsberghe, A.. 2021. “Sustainable AI: AI for Sustainability and the Sustainability of AI.” AI and Ethics 1: 213-218. doi.org/10.1007/s43681-021-00043-6.

    Itten, R., R. Hischier, A.S.G. Andrae et al. 2020. “Digital Transformation—Life Cycle Assessment of Digital Services, Multifunctional Devices and Cloud Computing.” International Journal of Life Cycle Assessment 25: 2093–2098. doi.org/10.1007/s11367-020-01801-0.

    Schwartz, R., J. Dodge, N. A. Smith, and O. Etzione. 2020. Green AI. Communications of the ACM 63 (12): 54-63. doi.org/10.1145/3381831.

    3. Critical Assessments in the Social Sciences and Humanities

    This section gathers a range of research articles and books that critically illuminate the intertwinement of ecological impacts with various economic, social, and political implications ensuing from the expansion of AI and digital platforms. In general, this research counters hyperbolic claims in the “green” and “sustainable” AI discourses by showing how such systems depend on physical infrastructures that entail damaging material effects like increasing GHG emissions, giving rise to “green sacrifice zones.” Concepts like “supply chain analysis” recontextualize “life cycle analysis” within the capitalist dynamics driving the expansion of AI, and illuminate some of the contradictions in the “green energy transition” that AI is supposed to assist with. Investigations of “upstream” resource extraction processes (e.g., water, rare earth minerals) and “downstream” pollutants (e.g., e-waste), reveal how the expanding infrastructure intensifies “unequal exchanges” of profits and resources between the wealthy “north” and regions of the “global south,” as well as within the “hinterlands” of the global north. Among other things, the literature demonstrates that expansion of the energy-and-water hungry physical infrastructure supporting the accelerating use of AI-enhanced “data,” as well as the need for the rare earth minerals that the AI infrastructure depends on, has not only produced contradictions as exemplified in the concept of “green extractivism,” but also a resurgence of social and political resistance to “postcolonial” capitalist appropriation projects claiming legitimancy under a “green” mantle.

    Caple, Z. and H. A. Swanson. 2024. “Amazon vs the Amazon: Green Capitalist Imaginaries and the Death of Biodiversity.” Capitalism Nature Socialism (Oct): 1-22. doi:10.1080/10455752.2024.2410755

    Franz, T. and A. McNelly. 2024. “The ‘Finance-Extraction-Transitions Nexus’: Geographies of the Green Transition in the 21st Century.” Antipode 56 (4): 1069-1603. doi.org/10.1111/anti.13049.

    Kovacic, Z., C. García Casañas, L. Argüelles, P. Yáñez Serrano, R. Ribera-Fumaz, L. Prause, and H. March. 2024. “The Twin Green and Digital Transition: High-Level Policy or Science Fiction?Environment and Planning E: Nature and Space. doi.org/10.1177/25148486241258046.

    Lehuedé, S. 2024. “An Elemental Ethics for Artificial Intelligence: Water as Resistance Within AI’s Value Chain.AI & Society.

    Lukacz, P. M. 2024. “Imaginaries of Democratization  and the Value of Open Environmental Data: Analysis of Microsoft’s Planetary Computer.” Big Data & Society 11 (2). doi.org/10.1177/20539517241242448.

    Riemens, R. 2024. “Fixing the Earth: Whole-Systems Thinking in Silicon Valley’s Environmental Ideology.”  Internet Histories 8 (4): 294-311. doi:10.1080/24701475.2024.2416295.

    McNelly, A. and Tobias Franz. 2024. “Making and Unmaking the Actually Existing Hegemonic Green Transition.” The Extractive Industries and Society 20 (Dec): 101525.

    Valdivia, A. 2024. “The Supply Chain Capitalism of AI: A Call to (Re)Think Algorithmic Harms and Resistance Through Environmental Lens.” Information, Communication & Society (Oct): 1–17. doi:10.1080/1369118X.2024.2420021.

    Bresnihan, P., and P. Brodie. 2023. “Data Sinks, Carbon Services: Waste, Storage and Energy Cultures on Ireland’s Peat Bogs.” New Media & Society 25 (2): 361-383.

    Brevini, B. 2023. “Myths, Techno Solutionism and Artificial Intelligence: Reclaiming AI Materiality and Its Massive Environmental Costs.” In Handbook of Critical Studies of Artificial Intelligence, edited by Simon Lindgren. Edward Elgar Publishing.

    Brodie, P. 2023. “Data Infrastructure Studies on an Unequal Planet.” Big Data & Society 10 (1).

    Cournet, P. and N. S. Bensi (eds). 2023. Datapolis: Exploring the Footprint of Data on Our Planet and Beyond. Rotterdam: NAi Publishers.

    Mejia-Muñoz, S. and S. Babidge. 2023. “Lithium Extractivism: Perpetuating Historical Asymmetries in the ‘Green Economy.'” Third World Quarterly 44 (6): 1119–1136.

    Pasek, A., H. Vaughan, and N. Starosielski. 2023. “The World Wide Web of Carbon: Toward a Relational Footprinting of Information and Communications Technology’s Climate Impacts.” Big Data & Society 10 (1).

    Schrader, N. and J. Seijdel (eds). 2023. Acid Clouds: A Critical Atlas of Dutch Data Centres. Rotterdam: NAi Publishers.

    Taffel, S. 2023. “Data and Oil: Metaphor, Materiality and Metabolic Rifts.” New Media & Society 25 (5): 980-998.

    Taffel, S. 2023. “AirPods and the Earth: Digital Technologies, Planned Obsolescence and the Capitalocene.” Environment and Planning E: Nature and Space 6 (1): 433-454.

    Riofrancos, T. 2023. “The Security–Sustainability Nexus: Lithium Onshoring in the Global North.” Global Environmental Politics 23 (1): 20–41. doi: https://doi.org/10.1162/glep_a_00668.

    Brevini, B. 2022. Is AI Good for the Planet? Digital Futures Series. Polity Press.

    Dauvergne, P. 2022. “Is Artificial Intelligence Greening Global Supply Chains? Exposing the Political Economy of Environmental Costs.” Review of International Political Econonmy 29 (3): 696-718. 

    Goldstein, J., and E. Nost (eds). 2022. The Nature of Data: Infrastructures, Environments, Politics. Lincoln, NE: University of Nebraska Press.

    Hristova, T., B. Neilson and N. Rossiter (eds). 2022. Data Farms: Circuits, Labour, Territory. London: Open Humanities Press.

    Kloppenburg, S., A. Gupta, S.R.L. Kruk, S. Makris, R. Bergsvik, P. Korenhof, H. Solman, and H.M. Toonen. 2022. “Scrutinizing Environmental Governance in a Digital Age: New Ways of Seeing, Participating, and Intervening.” One Earth 5 (3): 232-241.

    Monserrate, S.G. 2022. “The Cloud Is Material: On the Environmental Impacts of Computation and Data Storage.” MIT Case Studies in Social and Ethical Responsibilities of Computing, (January). 

    Nost, E. and E. Colven. 2022. “Earth for AI: A Political Ecology of Data-Driven Climate Initiatives.” Geoforum 130: 23-34.

    Robbins, S. and A. van Wynsberghe. 2022. “Our New Artificial Intelligence Infrastructure: Becoming Locked into an Unsustainable Future.” Sustainability 14 (8): 4829. 

    Voskoboynik, D. M. and D. Andreucci. 2022. “Greening Extractivism: Environmental Discourses and Resource Governance in the ‘Lithium Triangle.’Environment and Planning E: Nature and Space 5 (2): 787-809.

    Zografos, C. 2022. “The Contradictions of Green New Deals: Green Sacrifice and Colonialism.” Soundings: A Journal of Politics and Culture, no. 80 (Spring): 37-50. https://doi.org/10.3898/SOUN.80.03.2022.

    Crawford, K. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.

    Furlong, K. 2021. “Geographies of Infrastructure II: Concrete, Cloud and Layered (In) Visibilities.” Progress in Human Geography 45 (1): 190–198.

    Machen, R. and E. Nost. 2021. “Thinking Algorithmically: The Making of Hegemonic Knowledge in Climate Governance.” Transactions of the Institute of British Geographers 46 (3): 555–569. 

    Sætra, H.S. 2021. “AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System.” Sustainability 13: 1738. 

    Arboleda, M. 2020. Planetary Mine:Territories of Extraction Under Late Capitalism. Verso.

    Brevini, B. 2020. “Black Boxes, Not Green: Mythologizing Artificial Intelligence and Omitting the Environment.” Big Data and Society 7 (2).

    Brodie, P. 2020. “Climate Extraction and Supply Chains of Data.” Media, Culture & Society 42 (7-8): 1095-1114.

    Dauvergne, P. 2020. AI in the Wild: Sustainability in the Age of Artificial Intelligence. Cambridge, MA: MIT Press.

    Gabrys, J. 2020. “Smart Forests and Data Practices: From the Internet of Trees to Planetary Governance.” Big Data & Society 7 (1). 

    Arboleda, M. 2019. “From Spaces to Circuits of Extraction: Value in Process and the Mine/City Nexus.” Capitalism Nature Socialism 31 (3): 114–33. doi:10.1080/10455752.2019.1656758.

    Levenda, A.M. and D. Mahmoudi. 2019. “Silicon Forest and Server Farms: The (Urban) Nature of Digital Capitalism in the Pacific Northwest.” Culture Machine

    Murdock G. and B. Brevini. 2019. “Communications and the Capitalocene: Disputed Ecologies, Contested Economies, Competing Futures.” The Political Economy of Communication 7 (1): 51–82. 

    Pasek, A. 2019. “Managing Carbon and Data Flows: Fungible Forms of Mediation in the Cloud.” Culture Machine

    Brevini, B. and G. Murdock (eds). 2018. Carbon Capitalism and Communication: Confronting Climate Crisis. London: Palgrave Macmillan.

    Bakker, K., & M. Ritts. 2018. “Smart Earth: A Meta-review and Implications for Environmental Governance.” Global Environmental Change 52: 201–211. 

    Thayyil, N. 2018. “Constructing Global Data: Automated Techniques in Ecological Monitoring, Precaution and Reification of Risk.” Big Data & Society 5 (1). https://doi.org/10.1177/2053951718779407.

    Gabrys, J. 2016. Program Earth: Environmental Sensing Technology and the Making of a Computational Planet. Electronic Mediations 49. Minneapolis: University of Minneapolis Press.

    Hogan, M. 2015. “Data Flows and Water Woes: The Utah Data Center.” Big Data & Society 2 (2).