Ask
Say who you are and what is in front of you. You will get questions to take to a visit, a huddle, a pitch, or a kitchen table.
A scoring error here becomes a body. The job is still the same: name the complication, prepare, proceed with care.
For I am a doctor, nurse, or clinician
Opening
What would we need to know before we let this rank, write, or watch a patient?
Who was this tested on, and do they look like the people we serve?
What is the claimed gain, in minutes or outcomes — and who measured it?
What happens when we refuse a case, a site, or a feature?
Where does the data go, including audio, images, and notes, and who is the controller?
If this fails, is it a nuisance, a delay, or an irreversible harm — and who is named?
Same questions, denser rooms. Go when you are ready — not as a test of seriousness.
Health-specific guidance
World Health Organization
WHO's 2024 guidance on large multimodal models in health: consent, evidence, equity, and the duties that remain with clinicians and states.
The question is not 'is AI risky?' but 'what does care require of this tool?'
How to manage, not only name
U.S. National Institute of Standards and Technology
A voluntary framework for putting AI risk into an organisation's ordinary risk practice. Widely referenced; not a law.
You are past 'what can go wrong' and need a cycle: govern, map, measure, manage.
A law with high-risk lists
European Union
The first broad AI law of its kind. It ranks uses, not vibes. Health, education, and some public services sit in the high-risk band.
You need to know which uses of AI a major jurisdiction treats as high-risk — including several in health.