Healthcare AI Has a Reliability Problem Nobody Talks About

Healthcare AI is often evaluated on accuracy, but reliability is just as important. Small changes in patient data can sometimes lead to unstable predictions or inconsistent explanations. This article argues that AI systems should assess both prediction stability and explanation stability before influencing clinical decisions. A reliability-aware approach can help clinicians understand not only what a model predicts, but whether that prediction is trustworthy enough to act upon.