Metacognitive Demands and Strategies While Using Off-The-Shelf AI Conversational Agents for Health Information
🤖 AI Summary
This study addresses the high metacognitive burden users often experience when seeking health information through off-the-shelf AI conversational agents, which can significantly impair their information-seeking experience. Through a think-aloud experimental protocol, the research systematically identifies, for the first time, three core categories of metacognitive demands induced by AI dialogue agents and the corresponding user coping strategies. Integrating human-computer interaction analytical methods, the work not only uncovers key cognitive challenges inherent in current health information interactions with AI but also derives actionable design recommendations aimed at experience optimization. These findings provide empirical evidence and practical guidance for reducing users’ cognitive load and improving the design of health-focused AI interfaces.
Application Category
📝 Abstract
As Artificial Intelligence (AI) conversational agents become widespread, people are increasingly using them for health information seeking. The use of off-the-shelf conversational agents for health information seeking could place high metacognitive demands (the need for extensive monitoring and control of one's own thought process) on individuals, which could compromise their experience of seeking health information. However, currently, the specific demands that arise while using conversational agents for health information seeking, and the strategies people use to cope with those demands, remain unknown. To address these gaps, we conducted a think-aloud study with 15 participants as they sought health information using our off-the-shelf AI conversational agent. We identified the metacognitive demands such systems impose, the strategies people adopt in response, and propose considerations for designing beyond off-the-shelf interfaces to reduce these demands and support better user experiences and affordances in health information seeking.
Problem
Research questions and friction points this paper is trying to address.
metacognitive demands
conversational agents
health information seeking
AI
user experience
Innovation
Methods, ideas, or system contributions that make the work stand out.
metacognitive demands
conversational AI
health information seeking
think-aloud study
user experience design
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