DARR
MR-037 Governance & process Both scope

Environmental footprint of AI

Training and operating AI systems consume substantial energy, water, and materials, producing carbon emissions, e-waste, and ecosystem harm.

Risk family
Governance & process
MIT domain
6. Socioeconomic and Environmental
MIT subdomain
6.6 > Environmental harm
AI type
GPAI, Classical_ML, Agentic
Scope
Both
Source standard
MIT AI Risk Repository v4

Provenance

Source standard
MIT AI Risk Repository v4
MIT source entries
52 entries across 28 papers
  • Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.09.00 58.09.01 58.09.02 58.09.03 58.09.04 58.09.06 58.09.07 58.09.08
  • Bengio2024International Scientific Report on the Safety of Advanced AI49.03.04
  • Bengio2025International AI Safety Report 202560.03.04
  • Chin2025Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks68.05.00
  • Clarke2023A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values55.02.04
  • Coghlan2023Harm to Nonhuman Animals from AI: a Systematic Account and Framework44.01.01 44.01.02 44.02.00 44.03.00 44.03.01 44.03.02 44.04.00 44.05.00
  • Cunha2023Navigating the Landscape of AI Ethics and Responsibility03.06.00
  • EPIC2023Generating Harms - Generative AI's impact and paths forwards31.06.00
  • G'sell2024Regulating under Uncertainty: Governance Options for Generative AI47.04.05 47.04.06
  • Gabriel2024The Ethics of Advanced AI Assistants24.09.03
  • Gipiškis2024Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems62.11.01 62.12.01 62.39.01
  • GOS2023Future Risks of Frontier AI56.03.00
  • Hagendorff2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Review05.15.00
  • IBM2025AI Risk Atlas65.23.06
  • Leech2024Ten Hard Problems in Artificial Intelligence We Must Get Right54.01.02
  • Li2025A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents66.12.01 66.12.02
  • NIST2024Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile48.05.00
  • Paes2023Social Impacts of Artificial Intelligence and Mitigation Recommendations: An Exploratory Study10.09.00
  • Saghiri2022A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions39.02.00
  • Shelby2023Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction11.05.05
  • Solaiman2023Evaluating the Social Impact of Generative AI Systems in Systems and Society13.01.06 13.02.05
  • Stahl2024The Ethics of ChatGPT - Exploring the Ethical Issues of an Emerging Technology32.04.00
  • Tan2022The Risks of Machine Learning Systems15.02.00 15.02.05
  • Tang2025Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy71.03.01
  • Uuk2025A Taxonomy of Systemic Risks from General-Purpose AI61.01.05 61.02.23
  • Weidinger2021Ethical and social risks of harm from language models17.06.00 17.06.01
  • Weidinger2022Taxonomy of Risks posed by Language Models16.06.00 16.06.01
  • Weidinger2023Sociotechnical Safety Evaluation of Generative AI Systems18.06.00 18.06.02

Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.

ISO/IEC references
23894 obj A.5; src 9; mech B.6 | 42001 ctrl A.4.5

Framework crosswalk

Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.

Sourcesframeworks that contributed to the register
1
  • A.5 ISO/IEC 23894 Annex A A.5
1
  • A.4.5 ISO/IEC 42001 Annex A A.4.5
Cross-checksframeworks mapped in to test coverage
3
  • ibm-ai-agents-impact-on-environment AI agents' impact on environment
  • ibm-impact-on-the-environment Impact on the environment
  • ibm-redundant-actions Redundant actions partial
1
  • GENAI.5 Environmental Impacts

Part of the Deployer AI Risk Register, an open-source resource powered by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.