{"id":10319,"date":"2026-04-17T20:06:52","date_gmt":"2026-04-17T20:06:52","guid":{"rendered":"https:\/\/musictechohio.online\/site\/millions-americans-ai-instead-doctor-bad-advice\/"},"modified":"2026-04-17T20:06:52","modified_gmt":"2026-04-17T20:06:52","slug":"millions-americans-ai-instead-doctor-bad-advice","status":"publish","type":"post","link":"https:\/\/musictechohio.online\/site\/millions-americans-ai-instead-doctor-bad-advice\/","title":{"rendered":"Millions of Americans Are Talking to AI Instead of Going to the Doctor, and It\u2019s Giving Them Horrendously Flawed Medical Advice"},"content":{"rendered":"
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While Google\u2019s AI may no longer recommend eating rocks<\/a> or confidently telling users to put glue on their pizza<\/a>, even cutting-edge AI chatbots remain staggeringly incompetent at dispensing medical advice.<\/p>\n

In a new study<\/a> published this week in the journal JAMA Network Open<\/em>, researchers asked 21 frontier large language models (LLMs) to \u201cplay doctor\u201d when confronted with realistic symptoms that an actual patient could feasibly ask about.<\/p>\n

The results painted a damning picture. The AIs\u2019 failure rates exceeded 80 percent when provided with given ambiguous symptoms that could match more than one condition, and for more straightforward cases that included including physical exam findings and lab results, they still failed 40 percent of the time. The researchers also found that unlike human clinicians, the \u201cLLMs collapse prematurely onto single answers,\u201d resulting in \u201cweak performance\u201d across all models.<\/p>\n

\u201cDespite continued improvements, off-the-shelf large language models are not ready for unsupervised clinical-grade deployment,\u201d said corresponding author and Massachusetts General Hospital associate chair of innovation and commercialization Marc Succi in a statement<\/a>. \u201cDifferential diagnoses are central to clinical reasoning and underlie the \u2018art of medicine\u2019 that AI cannot currently replicate,\u201d he added.<\/p>\n

Translated into the real world, an AI that leaps to conclusions when not represented with the full picture could have devastating consequences. Say, if a person were to ask a chatbot about a rash or a sudden onset cough, they may be presented with misleading information and potentially dangerous advice.<\/p>\n

The results highlight the considerable risks of relying on AI for live-or-die health advice, a worrying trend that\u2019s already playing out across the country. As a recent survey<\/a> by the West Health-Gallup Center on Healthcare in America found, one in four American adults \u2014 the equivalent of 66 million people \u2014 are already asking ChatGPT and other chatbots like it for medical advice.<\/p>\n

Respondents often said they were seeking information both before and after seeing a healthcare professional. In many cases, they\u2019re foregoing seeking real-world medical assistance entirely after talking to a chatbot. Among those who asked AI for health advice, 14 percent \u2014 the equivalent of over nine million Americans \u2014 said they never saw a provider they would\u2019ve otherwise seen if it weren\u2019t for the tech.<\/p>\n

According to the survey, 27 percent said they didn\u2019t want to pay for a doctor\u2019s visit as a reason for consulting AI, while 14 percent said they were unable to pay for one. Some participants said they didn\u2019t have time or ability to visit a doctor.<\/p>\n

\u201cArtificial intelligence is already reshaping how Americans seek health information, make decisions and engage with providers, and health systems must keep pace,\u201d said West Health Policy Center president Tim Lash in a statement.<\/p>\n

Taken together, the two studies paint a damning picture of the current healthcare landscape in the US. Not only are millions of Americans heavily relying on AI tools, they\u2019re frequently being presented with flawed advice by hallucinating LLMs \u2014 and choosing not to seek help from far more knowledgeable professionals.<\/p>\n

AI have already caught a large amount of flak from experts for doling out bad medical advice, from Google\u2019s AI Overviews giving dangerously inaccurate or out of context information<\/a> to transcription tools used by doctors inventing nonexistent medications<\/a>.<\/p>\n

Even if the information they\u2019re giving is wrong, AI is giving patients a sense of certainty. Almost half of respondents in the latest survey said that talking to a chatbot about medical problems had made them feel more confident when talking to a provider, 22 percent said it helped them identify issues earlier, and 19 percent said it allowed them to avoid unnecessary tests or procedures.<\/p>\n

At the same time, many Americans remain highly skeptical of AI\u2019s medical advice. Roughly a third of participants who said they consulted AI for health issues said they distrusted the tool. One in ten respondents said the AI gave them potentially unsafe advice.<\/p>\n

One thing\u2019s for sure: the AI industry is in dire need of regulatory oversight<\/a>.<\/p>\n

More on AI and medical advice:<\/strong> Frontier AI Models Are Doing Something Absolutely Bizarre When Asked to Diagnose Medical X-Rays<\/em><\/a><\/p>\n

The post Millions of Americans Are Talking to AI Instead of Going to the Doctor, and It\u2019s Giving Them Horrendously Flawed Medical Advice<\/a> appeared first on Futurism<\/a>.<\/p>\n<\/div>\n

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While Google\u2019s AI may no longer recommend eating rocks or confidently telling users to put glue on their pizza, even cutting-edge AI chatbots remain staggeringly incompetent at dispensing medical advice.…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[177,3841,3844,3955],"tags":[],"class_list":["post-10319","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-ethics","category-health-medicine","category-medical"],"_links":{"self":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10319","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/comments?post=10319"}],"version-history":[{"count":0,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10319\/revisions"}],"wp:attachment":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/media?parent=10319"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/categories?post=10319"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/tags?post=10319"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}