Concern 102 · Working draft · editorial review in progress
Medical hallucination
Medical hallucination is an AI-generated health claim that is false, invented, or unsupported by suitable medical evidence.
Understanding the concern
A system may confuse conditions, fabricate a source, or describe a treatment incorrectly. Because a polished answer can sound authoritative, a reader may not recognize where the system has moved beyond reliable evidence.
This concern does not mean every medical AI is unreliable. Tools differ in purpose and testing. Health-related outputs need checks suited to their use and clear responsibility for clinical decisions, rather than relying on a general chatbot's tone.
An example
A summary names a study that cannot be found and uses it to justify a health recommendation.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Hallucination
- An AI output that sounds plausible but is false or unsupported, such as an invented source.
Evidence and its limits
WHO discusses errors and oversight for health uses; no treatment instructions or fabricated clinical facts are presented.
World Health Organization · 2024 · Official guidance
Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models ↗ (opens in a new tab)Explains health-specific risks, governance and evaluation needs; not clinical advice or a product validation.
NIST · AI 600-1 · 2024 · Official risk framework
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile ↗ (opens in a new tab)Describes generative-AI risk categories and management actions; it does not measure the failure rate of every product.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Who verifies the medical evidence and checks whether it applies to this person's situation?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Humility
Humility means recognizing the limits of our knowledge and being willing to learn from others. Expertise can be valuable without answering every question.
State where evidence is weak, invite criticism, and listen to people with different experience. Leave room to revise a decision when new information appears.
Ask together: What might we be missing, and who could help us see it?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
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