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PERSPECTIVE article
Front. Med.
Sec. Regulatory Science
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1545409
This article is part of the Research Topic Ethical and Legal Implications of Artificial Intelligence in Public Health: Balancing Innovation and Privacy View all articles
Healthcare AI, explainability, and the human-machine relationship: a (not so) novel practical challenge
Provisionally accepted- 1 University of Bologna, Bologna, Italy
- 2 Marche Polytechnic University, Ancona, Marche, Italy
This paper focuses on the lack of explainability that afflicts machine-learning-based AI systems applied in the field of healthcare. After a brief introduction to the topic, from both a technical and legal point of view, this work aims to assess the main consequences that the lack of explainability has on the human-machine relationship in clinical care, through a practical perspective. It then questions whether explainability is truly an objective worth seeking and, if so, to what extent, taking into account the current possible solutions.
Keywords: explainability1, AI2, healthcare2, human-machine relationship3, informed choice4, evidence-based medicine5, liability6, XAI7
Received: 14 Dec 2024; Accepted: 17 Feb 2025.
Copyright: © 2025 Giorgetti, Contissa and Basile. 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:
Claudia Giorgetti, University of Bologna, Bologna, Italy
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