University of Washington researchers emphasized in a new review article that transparency is essential for safely deploying medical artificial intelligence systems, especially given their potential to impact patient health. While AI is increasingly used in healthcare — from diagnostics to clinical documentation — issues like bias, hallucinations and lack of generalizability remain serious concerns.
The researchers advocate for Explainable AI, which helps users understand how models make decisions, thereby revealing flaws and improving trust. They also highlight the role of regulation, such as FDA oversight, in enforcing transparency and ensuring models are tested rigorously. Finally, clinicians play a key role in interpreting AI outputs and must be equipped to explain these systems to patients responsibly.