Advancing ethical AI in healthcare through interpretability.
expert_opinion · Level V
Where this comes from
- Record sourced from PubMed, PMID 40575122.
- Also identified by DOI 10.1016/j.patter.2025.101290 and PMC identifier 12191714.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Interpretability is essential for building trust in health artificial intelligence (AI), but ensuring trustworthiness requires addressing broader ethical concerns, such as fairness, privacy, and reliability. This opinion article discusses the multilayered role of interpretability and transparency in addressing these concerns by highlighting their fundamental contribution to the responsible adoption and regulation of health AI.