Four types of health AI each demand a different kind of engineering

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A senior engineer building a health AI argues that the term covers four distinct products, each failing in its own way. Ambient scribes that write visit notes can invent statements, so the author would require clinician review before anything enters the chart. Clinician Q&A tools with citations can link to sources that do not actually support the claim, calling for automated checks of each claim against its cited passage. Patient-facing copilots that flag too much risk being ignored, so their flags need measured precision and recall. The author's own free health-information assistant, Tabibu, is designed around preventing false reassurance and dosing advice, and its limits are published openly. The piece also cites a 2026 Mount Sinai study showing a short safety reminder reduced potentially harmful clinical choices from 16.6% to 10.1%, which the author presents as progress but not a complete fix.

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