Google Researchers share user insights from a novel research AI agent that helps people find their way to better health information through proactive conversational guidance, goal understanding, and tailored conversations.
The ability to find clear, relevant, and personalized health information is a cornerstone of empowerment for medical patients. Yet, navigating the world of online health information is often a confusing, overwhelming, and impersonal experience. We are met with a flood of generic information that does not account for our unique context, and it can be difficult to know what details are relevant.
Large language models (LLMs) have the potential to make this information more accessible and tailored. However, many AI tools today act as passive “question-answerers” — they provide a single, comprehensive answer to an initial query. But this isn’t how an expert, like a doctor, helps someone navigate a complex topic. A health professional doesn’t just provide a lecture; they ask clarifying questions to understand the full picture, discover a person’s goals, and guide them through the information maze. Though this context-seeking is critical, it’s a significant design challenge for AI.
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