Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
Descripción general
Resumen del artículo
Explainability in clinical decision support systems (CDSS) is crucial for maintaining patient autonomy, trust, and ethical medical practice. Opaque AI algorithms pose challenges to informed consent, shared decision-making, and the equitable distribution of healthcare resources, potentially hindering the responsible integration of AI into medicine.
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Scientists found that when computers help doctors make choices, it's super important to know *how* the computer decided. This helps patients understand, trust their doctors, and pick what's best for them.
Posibles conflictos de intereses
The authors declare no competing interests, and no obvious conflicts are apparent from their affiliations or the funding source (EU Horizon 2020).
Limitaciones identificadas
Explicación de la calificación
This paper provides a valuable multidisciplinary perspective on the critical issue of explainability in healthcare AI. The analysis covers technological, legal, medical, and patient viewpoints, offering a comprehensive assessment of the ethical implications. While the technical analysis could be strengthened, the paper's strength lies in its ethical discussion and its focus on the importance of explainability for patient trust and autonomy.
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