[MM/AI] 人机交互中的心智模型：生成式与智能体AI时代的方法与挑战（研讨会）
[MM/AI] Mental Models in Human-AI Interaction: Methods and Challenges in the Generative and Agentic AI Era (Workshop)
- Ludwig Maximilian University（路德维希-马克西米利安大学）
- ETH Zürich（苏黎世联邦理工学院）
- CSAIL, Massachusetts Institute of Technology（麻省理工学院计算机科学与人工智能实验室）
- Technical University of Munich（慕尼黑工业大学）
- Research Center Trust, University Duisburg-Essen（杜伊斯堡-埃森大学信任研究中心）
- HCII, Carnegie Mellon University（卡内基梅隆大学人机交互研究所）
- Microsoft（微软）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
该研讨会旨在批判性重新评估人机交互中的心智模型概念，应对生成式与智能体AI带来的形成与引出挑战，通过闪电演讲、动手练习和结构化讨论促进理论方法论交流并规划未来研究方向。
中文摘要 AI 辅助
心智模型这一概念在人机交互（HCI）领域被广泛使用，指人们为了推理计算系统并与之交互而持有的知识结构。然而，它常常被凭直觉操作化：该概念常与相关概念（如民间理论、意义建构）互换使用，且研究它的方法（如通过引出法）多种多样，每种方法都基于关于心智模型构成的不同假设。生成式和智能体AI系统可能进一步使心智模型的形成和引出复杂化，因为此类系统在设计上是不透明的，并且越来越多地代表用户在文件、应用程序和网页上采取行动。这些挑战共同可能阻碍关于人们对AI系统心智模型研究的可比较性。MM/AI研讨会呼吁对人机交互研究中我们如何理解和研究心智模型进行批判性重新评估。它旨在促进人机交互中心智模型的理论和方法论交流，识别开放挑战，并为未来研究制定方向。我们邀请关于用户或利益相关者对AI系统心智模型的短文投稿，特别是反思该概念的概念和方法论基础的贡献。为期半天的研讨会结合了闪电演讲、动手引出练习和关于心智模型在人机交互研究中未来关键问题的结构化讨论。
英文摘要
The mental model construct is widely used in HCI to refer to the knowledge structure people hold in order to reason about and interact with computing systems. Yet it is often operationalized intuitively: the construct is often used interchangeably with related concepts (e.g., folk theories, sensemaking) and methods of studying it (e.g., through elicitation) are many and diverse, with each method resting on distinct assumptions about what counts as a mental model. Generative and agentic AI systems may further complicate mental model formation and elicitation as such systems are opaque by design and increasingly act on users' behalf across files, applications, and on the web. Together, these challenges may hinder the commensurability of research on people's mental models of AI systems. The MM/AI workshop calls for a critical reassessment of how we understand and study mental models in human-AI interaction research. It aims to foster theoretical and methodological exchange on mental models in human-AI interaction, identify open challenges, and develop directions for future research. We invite short papers on users' or stakeholders' mental models of AI systems, particularly contributions that reflect on the conceptual and methodological foundations of the construct. The half-day workshop combines lightning talks, hands-on elicitation exercises, and structured discussions on key questions concerning the future of the mental model for human-AI interaction research.
