Imagine asking a chatbot about a health concern and receiving advice that sounds perfectly reasonable, yet is completely wrong. This isn’t science fiction; it's the very real danger of AI "hallucinations" in healthcare. A new study reveals how large language models (LLMs), the brains behind AI chatbots, can fabricate medical information, potentially misleading patients with dire consequences. Researchers have introduced "MedHalu," a dataset highlighting these AI-generated medical hallucinations, which range from contradicting established medical facts to conflicting with the patient's initial question. They tested different LLMs, even advanced models like GPT-4, on their ability to spot these hallucinations, and the results were alarming. Not only were the LLMs significantly worse at detecting fake medical advice than human experts, they even struggled compared to everyday people with no medical background. This underscores the crucial need for expert oversight. One promising solution is incorporating "expert-in-the-loop" feedback, where LLMs learn from human experts to improve their ability to identify and flag incorrect information. This approach significantly boosts their performance, paving the way for safer and more reliable AI in healthcare. As AI increasingly becomes a part of our lives, studies like this highlight the critical importance of ongoing research and development to address the challenges of AI hallucinations and ensure the responsible use of this powerful technology in sensitive areas like healthcare.