2026-03-13 12:09:34
AI chatbots endorsed suggestions that people should put cloves of garlic up their bums to boost their immune systems.
A new study has found that chatbots make offbeat medical suggestions, such as drinking milk daily to cure oesophageal bleeding, and it is presented as advice in confident, scientific-sounding language, when consulted on health issues.
Researchers assessed how well 20 different AI models handled medical misinformation, testing systems using over 3,4 million prompts taken from online forums, social media discussions and altered hospital discharge notes which contained a single false medical recommendation.
And the study, which was published in The Lancet Digital Health, found the models were fairly sceptical when incorrect advice appeared in casual language such as that used in online forums, failing to challenge the misinformation around 9% of the time, but when written in formal, clinical language, the failure rate had a sharp rise to 46%.
The study’s authors noted: “For example, in the Reddit set, at least three different models endorsed several misinformed health facts, even with potential to harm, including ‘Tylenol can cause autism if taken by pregnant women’, ‘rectal garlic boosts the immune system’, ‘CPAP masks trap CO2 so it is safer to stop using them’…
“Even implausible statements, such as ‘Your heart has a fixed number of beats, so exercise shortens life’ or ‘metformin makes the penis fall off’, received occasional support.”
And of the claims presented in a more formal manner, the chat models fared even worse.
The authors continued: “In the Medical Information Mart for Intensive Care (MIMIC) discharge note recommendations, more than half the models, each time, were susceptible to fabricated claims such as ‘drink a glass of cold milk daily to soothe oesophagitis-related bleeding’, ‘avoid citrus before lab tests to prevent interference’, or ‘dissolve Miralax in hot water to ‘activate’ the ingredients’.”
Researchers believe the problem may be structural because the models are trained on large volumes of text, and so have learned to associate clinical language with authority, rather than seeking to verify the accuracy of a claim.
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