Core Viewpoint - A recent MIT study reveals that AI, such as ChatGPT, may mislead patients into avoiding medical consultations due to minor communication errors, such as typos or informal language, with a higher misguidance rate observed in female patients compared to male patients [1][2][6]. Group 1: AI Miscommunication Issues - Minor details like extra spaces or the use of slang can significantly affect the understanding of medical AI, leading to a higher likelihood of incorrect advice [3][4]. - The study indicates that AI models are more prone to misunderstanding when patients express medical concerns in vague or uncertain terms, particularly for non-native speakers [4][17]. - The presence of "perturbations" in patient messages can lead to a 7% to 9% increase in the likelihood of AI suggesting self-management instead of seeking medical help [15][18]. Group 2: Gender Disparities in AI Recommendations - The research highlights a concerning trend where female patients are more frequently advised against seeing a doctor compared to male patients, raising questions about underlying biases in AI systems [6][9][21]. - The clinical accuracy of AI models shows significant gender-based discrepancies, with male patients receiving more reliable advice than female patients [8][10]. Group 3: Implications for Healthcare AI - The increasing reliance on AI in clinical settings for tasks such as triage and patient communication raises concerns about the reliability of AI systems that frequently misinterpret information [19][20]. - The study emphasizes the need for rigorous evaluation of AI models before their deployment in healthcare to mitigate the risks associated with inherent biases [22][25]. - Researchers advocate for deeper investigations into how non-clinical information influences AI decision-making in healthcare contexts [25].