Environmentally sustainable development and use of artificial intelligence in health care
Open accessAbstract
Artificial intelligence (AI) can transform health care by delivering medical services to underserved areas, while also filling gaps in health care provider availability. However, AI may also lead to patient harm due to fatal glitches in robotic surgery, bias in diagnosis, or dangerous recommendations. Despite concerns ethicists have identified in the use of AI in health care, the most significant consideration ought not be vulnerabilities in the software, but the environmental impact of AI. Health care emits a significant amount of carbon in many countries. As AI becomes an essential part of health care, ethical reflection must include the potential to negatively impact the environment. As such, this article will first overview the carbon emissions in health care. It will, second, offer five reasons why carbon calculations are insufficient to address sustainability in health care. Third, the article will derive normative concepts from the goals of medicine, the principles of biomedical ethics, and green bioethics—the very locus in which AI in health care sits—to propose health, justice, and resource conservation as criteria for sustainable AI in health care. In the fourth and final part of the article, examples of sustainable and unsustainable development and use of AI in health care will be evaluated through the three‐fold lens of health, justice, and resource conservation. With various ethical approaches to AI in health care, the imperative for environmental sustainability must be underscored, lest carbon emissions continue to increase, harming people and planet alike.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The current trajectory of AI development in health care focuses on integrating and maximizing existing AI technologies to enhance clinical decision-making and sustainable AI.
“This strategy aligns with the current trajectory of AI development in health care, where the focus is on integrating and maximizing existing AI technologies to enhance clinical decision-making and focus on sustainable AI [48,49].”
From Mitigating cognitive biases in clinical decision-making through multi-agent conversations using large language models: simulation study (2024) · cites this paper as [48]
The Conclusion advocates sustainable use of established AI, and the “Sustainable development of AI in health care” section describes triage algorithms that could guide care and resource allocation. Neither passage establishes that integrating and maximizing existing technologies to enhance clinical decision-making is the current focus of AI development in health care; the Conclusion presents sustainable use as a recommendation, not a description of that trajectory. Page numbers are unavailable in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 58 · Cited by 92
- Authors
- Richie, C.
- Affiliations
- Delft University of Technology (NL)
- Corresponding author
- Richie, Cristina
- ORCID
- Richie, Cristina
- Venue
- Bioethics
- Publisher
- Wiley
- Published
- 2022-03-15
- Volume
- 36
- Issue
- 5
- Pages
- 547-555
- ISSN
- 0269-9702 (ISSN-L)
- 1467-8519
- PMC
- PMC9311654
- OpenAlex
- W4220793133
- Cited by
- 92
- References
- 58
- Citations by year
- 2026: 24 · 2025: 37 · 2024: 14 · 2023: 16 · 2022: 1
- FWCI
- 5.13
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioethics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Funders
- East Carolina University
- Brody School of Medicine
- Technische Universiteit Delft
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics and bioethics in healthcare
- Keywords
- artificial intelligence in healthcare, environmental sustainability, CO2 emissions, biomedical ethics, health care ethics, resource conservation, justice, health, sustainable development, environmental impact of AI, medical robotics, algorithmic bias
- MeSH terms
- Sustainable Development, Artificial Intelligence, Carbon, Delivery of Health Care, Health Facilities, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review