AI in Healthcare: Why Accuracy Is Not Enough

Accuracy is not the whole product

In healthcare, a model can be accurate in a dataset and still be unsafe or unhelpful in practice. The environment is complex, the stakes are high, and human workflows matter.

What else matters

Healthcare AI needs careful evaluation, clear user experience, clinical context, privacy, auditability, and human oversight.

• The model should support decisions, not hide uncertainty.
• The workflow should reduce burden instead of adding confusion.
• The system should make errors easier to catch.

Practical lesson

AI builders should ask more than "How accurate is it?" A better question is: "Can this system help the right person make a safer decision at the right time?"