Choose your role and situation to find questions for a real conversation.
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Choose your role, then choose a situation. You will see prepared questions you can copy and take to a visit, a team meeting, or a conversation at home.
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
A way to begin
What must remain a human judgement even if the note is faster?
Was the patient told, in words they can refuse, before the recording started?
What is the clinician expected to review, and is that time actually in the day?
How will we know if it fabricates, omits, or smooths away what the patient actually said?
Who is liable if a hallucinated allergy, dose, or history is acted on?
Does it work as well in this language, this accent, this exam room?
AI documentation "ambient scribes"
Ambient-scribe risk arises when a tool listening to a clinical conversation creates an inaccurate record or captures and uses speech in ways the patient did not understand.
Clinical-note summarization errors
Clinical-note summarization error happens when an AI-written summary leaves out, changes or invents information that matters to a patient's care.
AI-driven prescribing
AI-driven prescribing risk arises when a medication suggestion overlooks a patient's circumstances or contains an error in the drug, dose, timing or instructions.
These resources offer more detail. Each title opens the original source in a new tab.
Health-specific guidance
World Health Organization
WHO guidance on the ethics and governance of large multimodal models in health.
Use this when considering generative AI in a health or care setting.
What has already happened
MIT × Responsible AI Collaborative
Reported AI incidents organized using MIT’s risk categories.
Use this to explore patterns across reported incidents.