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Notes from research and engineering practice, with a focus on trustworthy AI and real-world systems.
Clinician Trust in AI Is Not an Attitude Problem
There is a recurring frustration in healthcare AI circles. A model gets built, validated, deployed. It performs well on the benchmark. And then clinicians don't use it, or use it inconsistently, or override it…
Read postWhat "Adaptive AI" Actually Means and Why It's Harder Than It Sounds
The phrase "adaptive AI" gets used a lot. In marketing, it usually means a model that personalises recommendations. In research, it means something more specific and considerably more difficult: a system that modifies…
Read postAdaptive AI in Healthcare: The Governance Gap
Most conversations about AI in healthcare focus on whether a model is accurate enough to deploy. That's the right question to ask before go-live. It's not the right question to stop asking. Clinical AI doesn't stay in a…
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