Healthcare AI, explainability, and the human-machine relationship: a (not so) novel practical challenge
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.
Authors
- Giuseppe Basile (ORCID: https://orcid.org/0000-0001-9602-4223)
- Giuseppe Contissa (ORCID: https://orcid.org/0000-0002-8511-1505)
- Claudia Giorgetti
Institutions
- Marche Polytechnic University (IT)
- University of Bologna (IT)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-02-28
- DOI
- https://doi.org/10.3389/fmed.2025.1545409
- Citations
- 9
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 5.89