Climate Change and Health: The next Challenge of Ethical AI
Open accessAbstract
Artificial intelligence (AI) is one of the world's most resource-intensive digital technologies, but the environmental impact of AI on health remains largely unaddressed in both global health and bioethics. Effects on the environment have, thus far, been understood as a subsidiary consideration in AI ethics and rarely considered as a key ethical concern. AI technologies exacerbate climate change and sociopolitical instability due to their intensive use of natural resources and energy resources linked to the training and deployment of algorithmic systems. In global health, this intensive resource use is particularly concerning, given the explicit emphasis on improving health and advancing equity across the world. To address this, we interrogate how the inclusion of AI's environmental impact necessarily reshapes established ethical commitments in AI ethics frameworks and propose concrete strategies for accountability in the area of global health. This approach includes building a culture of intentional AI, for example through improved reporting, auditing, and intranational cooperation, in order to better align AI development and AI ethics with critical climate goals.
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SHAP values can rank the importance of different clinical factors and show whether a prognosis was driven primarily by tumor size, patient age, or biomarker status.
“For tabular data, SHAP values can rank the importance of different clinical factors and show whether a prognosis was driven primarily by tumor size, patient age, or biomarker status [162,163,164,165].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [165]
Training a single large language model generates emissions equivalent to approximately 300,000 kg of CO2, which is roughly five times the lifetime emissions of an average automobile.
“Training a single large language model generates emissions equivalent to approximately 300,000 kg of CO2, which is roughly five times the lifetime emissions of an average automobile [165,166].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [165]
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- Authors
- Fiske, A., Radhuber, I. M., Willem, T., Buyx, A., Celi, L. A., & McLennan, S.
- Affiliations
- Technical University of Munich (DE)
- University of Vienna (AT)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Fiske, Amelia
- Venue
- The Lancet Global Health
- Publisher
- Elsevier BV
- Published
- 2025-07
- Volume
- 13
- Issue
- 7
- Pages
- e1314-e1320
- ISSN
- 2214-109X (ISSN-L)
- OpenAlex
- W4411636419
- Cited by
- 25
- References
- 28
- Citations by year
- 2026: 20 · 2025: 5
- FWCI
- 3.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Global Health (publishedVersion, cc-by)
- PubMed (publishedVersion)
- IIASA PURE (International Institute of Applied Systems Analysis) (acceptedVersion)
- Funders
- National Science Foundation (ITEST 2148451)
- National Institutes of Health (R01 EB017205, U54 TW012043\u201301, Bridge2AI OT2OD032701)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
- Keywords
- AI ethics, environmental impact of AI, climate change, global health, bioethics, energy consumption, accountability, auditing, reporting, equity, socio-political instability
- MeSH terms
- Artificial Intelligence, Humans, Global Health, Climate Change
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