用AI模拟专家视角，激发跨学科研究创意
PersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation
- 用大模型模拟不同领域的专家提供多角度意见
- 用户认为创意更相关、更具创造力，且思维更深入
- 可自定义专家角色，提升掌控感，减少对AI依赖
生成跨学科研究创意需要多元领域知识，但专家及时反馈往往难以获取。本文提出PersonaFlow，一种利用大模型模拟特定领域专家的新系统，以提供多重视角。用户研究显示，该设计1）提升了研究方向的感知相关性和创造性；2）促进了用户的批判性思维活动（如解释、分析、评估、推理与自我调节），且未增加认知负担。此外，用户自定义专家角色的能力显著增强了其主体感，有助于缓解对AI的过度依赖。本工作为增强创意与协作的智能系统设计提供了支持，并为在科研构思及其他领域中使用可定制的AI模拟人格提供了设计启示。
原文摘要 · Abstract (English)
Generating interdisciplinary research ideas requires diverse domain expertise, but access to timely feedback is often limited by the availability of experts. In this paper, we introduce PersonaFlow, a novel system designed to provide multiple perspectives by using LLMs to simulate domain-specific experts. Our user studies showed that the new design 1) increased the perceived relevance and creativity of ideated research directions, and 2) promoted users' critical thinking activities (e.g., interpretation, analysis, evaluation, inference, and self-regulation), without increasing their perceived cognitive load. Moreover, users' ability to customize expert profiles significantly improved their sense of agency, which can potentially mitigate their over-reliance on AI. This work contributes to the design of intelligent systems that augment creativity and collaboration, and provides design implications of using customizable AI-simulated personas in domains within and beyond research ideation.
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