Navigating online health information can be overwhelming, with generic content lacking personalization. To empower medical patients, tailored insights are essential. Large language models (LLMs) have great potential, but current AI tools often serve as passive “question-answerers,” failing to replicate the interactive approach of healthcare professionals who ask clarifying questions. In the research article, “Towards Better Health Conversations: The Benefits of Context-Seeking,” we introduce “Wayfinding AI,” a prototype aiming to enhance user experience by proactively seeking context. Through four mixed-method studies with 163 participants, we tested this AI’s ability to uncover user needs and provide tailored health information. The findings revealed that this context-seeking approach resulted in significantly more relevant and helpful interactions compared to traditional AI. This innovation holds promise for improving health communication, ensuring patients receive the necessary support in understanding their unique medical situations.
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