POINT OF VIEW
Transpl. Int.
Beyond generic principles: a framework for the ethical analysis of artificial intelligence in organ transplantation
Institute for the History and Ethics of Medicine, Medical Faculty Heidelberg, University of Heidelberg, Heidelberg, Germany
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Abstract
Artificial intelligence (AI) is increasingly entering clinical medicine, and organ transplantation is no exception. While a growing body of literature addresses the ethical challenges of AI in healthcare, systematic analysis of the specific ethical dimensions of AI use in organ transplantation is missing. This gap reflects a genuine analytical challenge: the transplantation process is ethically complex in ways that general AI ethics frameworks do not adequately capture. Transplantation medicine simultaneously bears ethical obligations to deceased donors, living donors, donor families, organ recipients, and the public at large. These obligations shift substantially across the stages of the transplantation process, from the patient-centred ethics of donor identification and listing decisions, through the distributive justice logic governing organ allocation, to the professional responsibility questions of the peri-and post-transplant phases. A rigorous ethical analysis of AI in organ transplantation therefore requires, first, a systematic mapping of AI use cases and models onto the transplantation process; second, an identification of the stakeholder-specific ethical obligations pertinent at each stage; and third, an in-depth analysis of how those obligations are specifically affected by the properties of the AI system in question. This paper proposes this framework and illustrates it using the example of AI-assisted organ allocation.
Summary
Keywords
Artificial intelligence, distributive justice, ethics, explainability, fairness
Received
04 March 2026
Accepted
17 August 2026
Copyright
© 2026 Primc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Nadia Primc
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