Some medical doctors see LLMs as a boon for medical literacy. The common affected person would possibly battle to navigate the huge panorama of on-line medical info—and, specifically, to tell apart high-quality sources from polished however factually doubtful web sites—however LLMs can try this job for them, a minimum of in idea. Treating sufferers who had searched for his or her signs on Google required “a whole lot of attacking affected person anxiousness [and] decreasing misinformation,” says Marc Succi, an affiliate professor at Harvard Medical Faculty and a working towards radiologist. However now, he says, “you see sufferers with a university training, a highschool training, asking questions on the stage of one thing an early med pupil would possibly ask.”
The discharge of ChatGPT Well being, and Anthropic’s subsequent announcement of recent well being integrations for Claude, point out that the AI giants are more and more keen to acknowledge and encourage health-related makes use of of their fashions. Such makes use of definitely include dangers, given LLMs’ well-documented tendencies to agree with customers and make up info relatively than admit ignorance.
However these dangers additionally need to be weighed in opposition to potential advantages. There’s an analogy right here to autonomous automobiles: When policymakers think about whether or not to permit Waymo of their metropolis, the important thing metric is just not whether or not its vehicles are ever concerned in accidents however whether or not they trigger much less hurt than the established order of counting on human drivers. If Dr. ChatGPT is an enchancment over Dr. Google—and early proof suggests it might be—it may doubtlessly reduce the large burden of medical misinformation and pointless well being anxiousness that the web has created.
Pinning down the effectiveness of a chatbot resembling ChatGPT or Claude for shopper well being, nevertheless, is hard. “It’s exceedingly troublesome to judge an open-ended chatbot,” says Danielle Bitterman, the scientific lead for knowledge science and AI on the Mass Normal Brigham health-care system. Massive language fashions rating properly on medical licensing examinations, however these exams use multiple-choice questions that don’t replicate how individuals use chatbots to search for medical info.
Sirisha Rambhatla, an assistant professor of administration science and engineering on the College of Waterloo, tried to shut that hole by evaluating how GPT-4o responded to licensing examination questions when it didn’t have entry to an inventory of doable solutions. Medical specialists who evaluated the responses scored solely about half of them as completely appropriate. However multiple-choice examination questions are designed to be tough sufficient that the reply choices don’t give them completely away, they usually’re nonetheless a reasonably distant approximation for the kind of factor {that a} consumer would kind into ChatGPT.
A totally different research, which examined GPT-4o on extra practical prompts submitted by human volunteers, discovered that it answered medical questions appropriately about 85% of the time. Once I spoke with Amulya Yadav, an affiliate professor at Pennsylvania State College who runs the Accountable AI for Social Emancipation Lab and led the research, he made it clear that he wasn’t personally a fan of patient-facing medical LLMs. However he freely admits that, technically talking, they appear as much as the duty—in any case, he says, human medical doctors misdiagnose sufferers 10% to fifteen% of the time. “If I have a look at it dispassionately, it appears that evidently the world is gonna change, whether or not I prefer it or not,” he says.
For individuals searching for medical info on-line, Yadav says, LLMs do appear to be a better option than Google. Succi, the radiologist, additionally concluded that LLMs is usually a higher various to net search when he in contrast GPT-4’s responses to questions on frequent power medical situations with the data introduced in Google’s data panel, the data field that generally seems on the precise facet of the search outcomes.
Since Yadav’s and Succi’s research appeared on-line, within the first half of 2025, OpenAI has launched a number of new variations of GPT, and it’s affordable to count on that GPT-5.2 would carry out even higher than its predecessors. However the research do have necessary limitations: They concentrate on simple, factual questions, they usually look at solely transient interactions between customers and chatbots or net search instruments. Among the weaknesses of LLMs—most notably their sycophancy and tendency to hallucinate—is likely to be extra prone to rear their heads in additional intensive conversations and with people who find themselves coping with extra advanced issues. Reeva Lederman, a professor on the College of Melbourne who research expertise and well being, notes that sufferers who don’t just like the analysis or remedy suggestions that they obtain from a physician would possibly search out one other opinion from an LLM—and the LLM, if it’s sycophantic, would possibly encourage them to reject their physician’s recommendation.
Some research have discovered that LLMs will hallucinate and exhibit sycophancy in response to health-related prompts. For instance, one research confirmed that GPT-4 and GPT-4o will fortunately settle for and run with incorrect drug info included in a consumer’s query. In one other, GPT-4o incessantly concocted definitions for pretend syndromes and lab checks talked about within the consumer’s immediate. Given the abundance of medically doubtful diagnoses and coverings floating across the web, these patterns of LLM habits may contribute to the unfold of medical misinformation, notably if individuals see LLMs as reliable.
OpenAI has reported that the GPT-5 collection of fashions is markedly much less sycophantic and vulnerable to hallucination than their predecessors, so the outcomes of those research may not apply to ChatGPT Well being. The corporate additionally evaluated the mannequin that powers ChatGPT Well being on its responses to health-specific questions, utilizing their publicly out there HeathBench benchmark. HealthBench rewards fashions that specific uncertainty when acceptable, suggest that customers search medical consideration when mandatory, and chorus from inflicting customers pointless stress by telling them their situation is extra severe that it really is. It’s affordable to imagine that the mannequin underlying ChatGPT Well being exhibited these behaviors in testing, although Bitterman notes that a number of the prompts in HealthBench have been generated by LLMs, not customers, which may restrict how properly the benchmark interprets into the true world.
