Explainability in Artificial Intelligence for Ethical Decision-Making in Healthcare Systems

Antoine Bernard

Explainability in Artificial Intelligence for Ethical Decision-Making in Healthcare Systems

Authors

Antoine Bernard

AI Ethics Researcher, France.

Keywords:

Explainable Artificial Intelligence, Ethical AI, Healthcare Decision-Making, Transparency, Clinical AI, Accountability, Medical Ethics

Synopsis

As artificial intelligence (AI) continues to evolve within healthcare systems, the demand for explainability in its decision-making processes becomes increasingly critical, particularly when ethical considerations are involved. This paper examines the role of explainable AI (XAI) in promoting transparency, accountability, and trust in healthcare settings. It analyzes the intersection of technical approaches to AI explainability and the ethical imperatives that arise when algorithms impact patient care and clinical outcomes. Through a review of literature and current technical practices, we explore how explainability supports ethical frameworks in real-time clinical decision-making. A conceptual framework is presented that links explainability with ethical principles such as autonomy, beneficence, and justice. The study concludes by highlighting best practices and identifying ongoing challenges in integrating XAI effectively within healthcare systems.

References

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Published

July 15, 2025

Series

Research paper

License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.