探索智能助手的用户体验设计，提出可落地的原型工具与实践框架。
Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypes
- 构建21个维度的助手体验设计分类体系。
- 提炼出5类核心任务与6项关键能力需求。
- 开发AgentUXlab工具，支持浏览器内原型体验验证。
计算机使用代理（或称“代理”）是生成式AI，能根据用户指令在用户界面中自动执行操作。当前研究聚焦于底层模型的训练与评估，而对代理用户体验（UX）的关注不足。本文通过两项研究，探索代理用户体验的设计空间（RQ1）及原型开发所需支持（RQ2）。首先，构建了包含21个子类别的代理用户体验设计考量分类体系；其次，通过对12名参与者（含6名代理专家）的需求挖掘研究，识别出5类活动与6项期望能力，用于支持工具开发。基于上述发现，我们设计并实现了AgentUXlab——一个设计探针工具，使开发者可在浏览器中为特定网站设计不同用户体验策略，并执行原型进行评估。14名参与者的用户研究进一步揭示了工具使用洞见，并推导出代理用户体验原型工具的设计启示。
原文摘要 · Abstract (English)
Computer use agents (or "agents") are generative AI that automates actions within user interfaces from user commands. Current research focuses on training and evaluating the underlying models, leaving these agents' user experience (UX) understudied. We conducted two studies to understand the design space of agent UX (RQ1) and the support required to prototype it (RQ2). First, we develop a taxonomy of design considerations for agent UX, comprising 21 subcategories of UX considerations. Then, through a requirements elicitation study with 12 participants---including six agent experts---we identify five Activities and six Desired Capabilities needed in tools prototyping agent UX. Informed by these results, we created AgentUXlab, a design probe that enables developers to design agents with different UX approaches for a website and evaluate those experiences by executing prototypes in a browser. From a user study with 14 participants, we elucidate tooling insights and derive design implications for agent UX prototyping tools.
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