Why AI Is Not a Solution to the Healthcare and Climate Crisis

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ID: 338486
2026
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Abstract
Abstract Artificial Intelligence (AI) is increasingly promoted as a solution to the healthcare crisis and as a driver of the green transition. Within biomedical research, clinical practice, and public health, AI is expected to optimize diagnosis, tailor treatments, and improve system efficiency, while also reducing health care’s carbon footprint. These promises fit within the broader vision of a “twin transition,” in which digitalization and sustainability are seen as mutually reinforcing. However, this techno-optimism overlooks the significant environmental costs of AI systems, including the extraction of minerals, energy and water use in data centres, and electronic waste disposal. Current responses to these concerns are predominantly technical—focused on efficiency gains, carbon accounting, and greener hardware. Yet, such measures rest on three problematic assumptions: that quantification is the most urgent gap; that efficiency solves all harms; and that greater efficiency reduces overall energy consumption. In practice, these framings obscure systemic issues, ignore rebound effects, and exclude unquantifiable harms. This chapter argues that bioethics must move beyond AI solutionism by systematically examining the environmental costs of AI in health care. An empirical bioethics approach can help re-frame debates, interrogate when AI is truly needed, and support decision-making that balances health, justice, and planetary well-being.
Reference Key
openalex_W7225181180 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Federica Lucivero, Gabrielle Natalie Samuel
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Journal Oxford University Press eBooks
Year 2026
DOI
10.1093/9780197807262.003.0031
URL
https://doi.org/10.1093/9780197807262.003.0031
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