People, health and care
Clinical AI safety reviewer
Checking that AI used in care is safe for the actual patients in front of you, and stopping it when it is not.
Written by Nivaan, founder of OffLadder ยท Last reviewed
Test it this week
Take one publicly documented clinical AI tool and write down three questions you would ask before letting it near a patient you love. Then see whether the published material answers them.
What the work actually contains
- Reading how a tool performs and asking whether the population it was tested on resembles yours
- Sitting with clinicians while they use it, watching what they do with a wrong suggestion
- Running incident reviews when something goes wrong
- Writing the guidance that says when the tool must not be relied on
Why it is appearing now
Diagnostic support, documentation and triage tools are entering clinical settings, and services need people who can judge them locally.
What AI changes about it
It creates the role. The important skill is clinical scepticism, which models cannot supply about themselves.
The human abilities it leans on
- Clinical or care experience, or the appetite to learn it properly
- Statistical care without needing to be a statistician
- Willingness to be the person who says stop
What it can grow out of
- Nursing, allied health, pharmacy, clinical audit
- Patient safety and governance roles
- Health informatics
What nobody knows yet
Whether this sits with governance teams, clinicians, or a new specialism.
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