{"id":240,"date":"2025-08-06T07:03:58","date_gmt":"2025-08-06T14:03:58","guid":{"rendered":"https:\/\/scienceblog.com\/neuroedge\/?p=240"},"modified":"2025-08-06T07:03:58","modified_gmt":"2025-08-06T14:03:58","slug":"ai-chatbots-often-spread-medical-falsehoods-study-finds","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/neuroedge\/2025\/08\/06\/ai-chatbots-often-spread-medical-falsehoods-study-finds\/","title":{"rendered":"AI Chatbots Often Spread Medical Falsehoods, Study Finds"},"content":{"rendered":"<p>Artificial intelligence chatbots like ChatGPT are being widely used in healthcare, but a new study warns they may be dangerously susceptible to medical misinformation.<\/p>\n<p>Researchers at the Icahn School of Medicine at Mount Sinai found that leading AI models often repeat or even elaborate on false clinical details embedded in user questions, raising serious safety concerns. The good news? A single, well-placed safety reminder built into the prompt can cut these errors nearly in half. The findings were published August 2 in the journal <i>Communications Medicine<\/i>.<\/p>\n<h2>False Details, Confident Lies<\/h2>\n<p>The researchers designed 300 clinical scenarios, each containing a single fake medical detail: a nonexistent test, symptom, or condition. These vignettes were submitted to six top-performing large language models (LLMs), including GPT-4o, to see how often the chatbots would repeat or expand upon the falsehood.<\/p>\n<p>\u201cWhat we saw across the board is that AI chatbots can be easily misled by false medical details, whether those errors are intentional or accidental,\u201d said lead author Dr. Mahmud Omar, an independent consultant for the research team. \u201cThey not only repeated the misinformation but often expanded on it, offering confident explanations for non-existent conditions.\u201d<\/p>\n<p>In some cases, models responded with detailed clinical advice based entirely on the fabricated term. For example, a made-up syndrome or lab test might trigger an explanation about its supposed causes, implications, or treatments.<\/p>\n<h2>Prompting for Safer Outputs<\/h2>\n<p>The team also tested whether a simple intervention could reduce this behavior. In a second round of testing, they added a one-line warning to the prompt, reminding the AI that some of the information provided might be incorrect. This small change had a big effect.<\/p>\n<ul>\n<li>Without mitigation, hallucination rates ranged from 50% to 83% across models<\/li>\n<li>With the added safety prompt, average error rates dropped from 66% to 44%<\/li>\n<li>For GPT-4o, hallucinations fell from 53% to 23%<\/li>\n<li>Adjusting the model&#8217;s &#8220;temperature&#8221; setting had no significant impact<\/li>\n<li>Shorter prompts led to more hallucinations than longer ones<\/li>\n<\/ul>\n<p>\u201cThe encouraging part is that a simple, one-line warning added to the prompt cut those hallucinations dramatically,\u201d said Dr. Omar. \u201cThat shows small safeguards can make a big difference.\u201d<\/p>\n<h2>Clinical Context Matters<\/h2>\n<p>The authors stress that hallucinations, when AI models generate false but plausible-sounding content, pose unique risks in healthcare. These errors can mislead doctors, confuse patients, or even influence clinical decisions if not caught in time.<\/p>\n<p>\u201cOur goal was to see whether a chatbot would run with false information if it was slipped into a medical question, and the answer is yes,\u201d said Dr. Eyal Klang, Chief of Generative AI in the Windreich Department of Artificial Intelligence and Human Health at Mount Sinai. \u201cEven a single made-up term could trigger a detailed, decisive response based entirely on fiction.\u201d<\/p>\n<p>But the study also offers hope. \u201cWe found that the simple, well-timed safety reminder built into the prompt made an important difference, cutting those errors nearly in half,\u201d Dr. Klang said. \u201cThat tells us these tools can be made safer, but only if we take prompt design and built-in safeguards seriously.\u201d<\/p>\n<h2>A Path Forward for Safer AI<\/h2>\n<p>The research team is now applying this approach to real, de-identified patient records to stress-test AI systems under real-world conditions. They hope their \u201cfake-term\u201d method can serve as a low-cost, scalable way for hospitals, developers, and regulators to evaluate AI safety.<\/p>\n<p>\u201cOur study shines a light on a blind spot in how current AI tools handle misinformation, especially in health care,\u201d said co-senior author Dr. Girish Nadkarni, Chair of the Windreich Department of Artificial Intelligence and Human Health at Mount Sinai. \u201cThe solution isn\u2019t to abandon AI in medicine, but to engineer tools that can spot dubious input, respond with caution, and ensure human oversight remains central. We\u2019re not there yet, but with deliberate safety measures, it\u2019s an achievable goal.\u201d<\/p>\n<h2>Why It Matters<\/h2>\n<p>In recent years, LLMs have been used to summarize clinical notes, answer patient questions, and assist with diagnostic reasoning. But their tendency to generate confident but false information has raised red flags. These so-called \u201challucinations\u201d are especially dangerous in medicine, where misinformation can have life-or-death consequences.<\/p>\n<p>The Mount Sinai study underscores a key lesson: AI in healthcare must be handled with the same rigor as any medical device. A chatbot that sounds confident isn\u2019t necessarily correct. But with targeted safeguards, it may still be a valuable tool.<\/p>\n<p><i>The study, &#8220;Large Language Models Demonstrate Widespread Hallucinations for Clinical Decision Support: A Multiple Model Assurance Analysis,&#8221; appears in the August 2, 2025 issue of <a href=\"https:\/\/doi.org\/10.1038\/s43856-025-01021-3\" target=\"_blank\" rel=\"noopener\">Communications Medicine<\/a>.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence chatbots like ChatGPT are being widely used in healthcare, but a new study warns they may be dangerously susceptible to medical misinformation. Researchers at the Icahn School of Medicine at Mount Sinai found that leading AI models often repeat or even elaborate on false clinical details embedded in user questions, raising serious safety &#8230; <a title=\"AI Chatbots Often Spread Medical Falsehoods, Study Finds\" class=\"read-more\" href=\"https:\/\/scienceblog.com\/neuroedge\/2025\/08\/06\/ai-chatbots-often-spread-medical-falsehoods-study-finds\/\" aria-label=\"Read more about AI Chatbots Often Spread Medical Falsehoods, Study Finds\">Read more<\/a><\/p>\n","protected":false},"author":1297,"featured_media":241,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[2,11],"tags":[],"class_list":["post-240","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-automation-efficiency","category-health-medicine","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.7 (Yoast SEO v27.7) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>AI Chatbots Often Spread Medical Falsehoods, Study Finds - NeuroEdge<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scienceblog.com\/neuroedge\/2025\/08\/06\/ai-chatbots-often-spread-medical-falsehoods-study-finds\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI Chatbots Often Spread Medical Falsehoods, Study Finds\" \/>\n<meta property=\"og:description\" content=\"Artificial intelligence chatbots like ChatGPT are being widely used in healthcare, but a new study warns they may be dangerously susceptible to medical misinformation. 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New research analyzing over 40,000 diagnoses reveals that combining human expertise with AI models creates a powerful diagnostic partnership that outperforms traditional approaches. 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While seasoned specialists still outperform the machines, this milestone suggests we're entering a new era where AI could meaningfully augment medical education\u2026","rel":"","context":"In &quot;Automation &amp; Efficiency&quot;","block_context":{"text":"Automation &amp; Efficiency","link":"https:\/\/scienceblog.com\/neuroedge\/category\/automation-efficiency\/"},"img":{"alt_text":"Clinician at monitoring equipment","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=700%2C400&ssl=1 2x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=1050%2C600&ssl=1 3x"},"classes":[]},{"id":252,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/10\/15\/ai-system-finds-crucial-clues-for-diagnoses-in-electronic-health-records\/","url_meta":{"origin":240,"position":2},"title":"AI System Finds Crucial Clues For Diagnoses In Electronic Health Records","author":"NeuroEdge","date":"October 15, 2025","format":false,"excerpt":"In hospitals where seconds matter, physicians often face a data paradox: vast electronic records but little time to extract meaning. Researchers at the Icahn School of Medicine at Mount Sinai have now developed an artificial intelligence system that transforms this flood of information into structured insight. The tool, called InfEHR,\u2026","rel":"","context":"In &quot;Automation &amp; Efficiency&quot;","block_context":{"text":"Automation &amp; Efficiency","link":"https:\/\/scienceblog.com\/neuroedge\/category\/automation-efficiency\/"},"img":{"alt_text":"clinician carrying a health record","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":287,"url":"https:\/\/scienceblog.com\/neuroedge\/2026\/01\/06\/one-night-of-sleep-data-can-predict-your-disease-risk-years-ahead\/","url_meta":{"origin":240,"position":3},"title":"One Night of Sleep Data Can Predict Your Disease Risk Years Ahead","author":"NeuroEdge","date":"January 6, 2026","format":false,"excerpt":"The next time someone hooks you up to a sleep study, those sensors tracking your brain waves and heartbeat may not just be \u00a0looking for snoring problems. They could be capturing something far more revealing: a physiological signature that can forecast whether you'll develop Parkinson's disease, suffer a heart attack,\u2026","rel":"","context":"In &quot;Brain Health&quot;","block_context":{"text":"Brain Health","link":"https:\/\/scienceblog.com\/neuroedge\/category\/brain-health\/"},"img":{"alt_text":"AI image of woman in a sleep lab","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2026\/01\/ChatGPT-Image-Jan-6-2026-at-06_02_17-AM.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2026\/01\/ChatGPT-Image-Jan-6-2026-at-06_02_17-AM.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2026\/01\/ChatGPT-Image-Jan-6-2026-at-06_02_17-AM.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2026\/01\/ChatGPT-Image-Jan-6-2026-at-06_02_17-AM.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":119,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/05\/05\/ai-companion-chatbots-implicated-in-sexual-harassment-of-users\/","url_meta":{"origin":240,"position":4},"title":"AI Companion Chatbots Implicated in Sexual Harassment of Users","author":"NeuroEdge","date":"May 5, 2025","format":false,"excerpt":"New research reveals disturbing patterns of boundary violations and inappropriate behavior by AI companions designed to provide emotional support, raising urgent questions about regulation and ethical design in the rapidly expanding industry. As AI companion chatbots surge in popularity\u2014reaching over a billion users worldwide in the past five years\u2014Drexel University\u2026","rel":"","context":"In &quot;Society&quot;","block_context":{"text":"Society","link":"https:\/\/scienceblog.com\/neuroedge\/category\/society\/"},"img":{"alt_text":"woman holding an iphone texting","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/05\/iphone-642999_1280.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/05\/iphone-642999_1280.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/05\/iphone-642999_1280.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/05\/iphone-642999_1280.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":90,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/04\/28\/brain-decoder-controls-spinal-cord-stimulation\/","url_meta":{"origin":240,"position":5},"title":"Brain decoder controls spinal cord stimulation","author":"NeuroEdge","date":"April 28, 2025","format":false,"excerpt":"In a significant development for spinal cord injury treatment, researchers at Washington University in St. Louis have created a neural decoder that bridges the communication gap between brain and spine, potentially opening new avenues for rehabilitation. The research team, led by Ismael Se\u00e1\u00f1ez, assistant professor of biomedical engineering at WashU,\u2026","rel":"","context":"In &quot;Computational Innovation&quot;","block_context":{"text":"Computational Innovation","link":"https:\/\/scienceblog.com\/neuroedge\/category\/computational-innovation\/"},"img":{"alt_text":"EEG Cap and walking man","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/eeg-cap.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/eeg-cap.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/eeg-cap.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/eeg-cap.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/posts\/240","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/users\/1297"}],"replies":[{"embeddable":true,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/comments?post=240"}],"version-history":[{"count":1,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/posts\/240\/revisions"}],"predecessor-version":[{"id":242,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/posts\/240\/revisions\/242"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/media\/241"}],"wp:attachment":[{"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/media?parent=240"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/categories?post=240"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/scienceblog.com\/neuroedge\/wp-json\/wp\/v2\/tags?post=240"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}