Choose your role and situation to find questions for a real conversation.
Ask
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
If this goes well, who is in a position to say so? If it goes badly, who can be named?
Which of our current tools have we never put on this table?
Where is our evidence of unequal performance, and where have we not looked?
What is the smallest trial that would teach us, and what would make us stop?
Who is missing from this room who will live with the decision?
Triage algorithm bias
Triage algorithm bias occurs when an automated urgency score gives some groups lower priority than their medical needs justify.
Substance-use disorder screening bias
Substance-use risk-score bias occurs when automated estimates of misuse or overdose unfairly shape how people are assessed or given access to treatment.
Automation bias in clinical decisions
Clinical automation bias occurs when a health professional gives an automated suggestion more weight than the patient's evidence warrants.
These resources offer more detail. Each title opens the original source in a new tab.
How to manage, not only name
U.S. National Institute of Standards and Technology
A voluntary framework for organizing work to identify, assess, and manage AI risks.
Use this when your organization needs a process for managing AI risk.
Laws and policies against risks
MIT × Georgetown CSET
A map of how AI governance measures address different risks.
Use this to explore the relationship between risks and policy responses.
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.