A Typo Could Change Your Ai Medical Advice Study Warns
A new study reveals that large language models (LLMs) used in healthcare can be influenced by seemingly irrelevant details in patient messages. Minor typos in messages reduced AI accuracy by up to 9%. Female patients got worse advice 7% more often than male patients. AI changed recommendations based on tone, slang, and pronouns. This can result in inconsistent and even biased treatment recommendations. Presented at the 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’25), the research raises serious concerns about the reliability of AI tools in medical decision-making....