When AI Makes Medical Decisions: Designing Human-in-the-Loop Clinical Systems
A few years back, a hospital in the Midwest rolled out a sepsis prediction model across its ICU. Within weeks, nurses were quietly muting the alerts. Not because the model was wrong exactly, but because it fired so often that people stopped trusting it, and eventually stopped listening to it altogether. That's the story that keeps coming up whenever someone tells me AI is "ready" to make clinical calls on its own. It usually isn't a story about bad math. It's a story about bad design around the math.
I think that distinction matters more than most people give it credit for. Building a model that predicts patient deterioration, flags a suspicious mass on a scan, or recommends a drug dosage is, honestly, the easier half of the problem now. There's plenty of tooling for that. The harder half, the part that barely gets discussed at conferences, is figuring out...
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