AI in Clinical Decision Support: What Responsible, Evidence-Based Solutions Should Look Like

A new analysis outlines how AI-powered clinical decision support must be designed to enhance, not replace, clinician judgment, emphasizing transparency about evidence sources, ongoing bias monitoring, and explicit safeguards for patient safety. The piece highlights risks such as automation bias, uneven performance across demographic groups, and the need for continuous post-deployment evaluation to prevent harm in real-world care settings.