发表机构
Virginia Tech（弗吉尼亚理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出将经典HCI设计知识编码为机器可读技能，使生成式AI按需构建用户界面时遵循设计原则，推动HCI从启发式清单走向可执行、开放的未来。
AI 中文摘要
人机交互（HCI）正处于转型中期：大型语言模型现在可以根据自然语言任务描述按需生成功能性用户界面（UI）。用户解释他们试图完成的任务，系统便会物化出一个支持该任务的工作界面。这种能力已存在于Claude和ChatGPT等系统中，并随着底层模型的改进而持续提升保真度。这一轨迹的下一步是从仅仅生成的界面转向生成良好的界面。我们提出一个框架，其中用户与人工智能（AI）之间的对话成为一个思考空间：一个共享的、结构化的认知工作空间，在其中任务分解产生按需用户界面，作为用户思维的延伸而非独立产物。在此范式中，经典HCI设计知识（Nielsen的启发式、Norman的负担性规定、Web内容可访问性指南（WCAG）成功标准、认知负荷约束和混合主动原则）被编码为技能：生成代理在运行时作为软件工程工具加载的机器可读的http URL文件。技能将HCI设计知识转化为声明性、可检查、版本控制和可编辑的工件，由HCI社区本身拥有，从而使可访问性、可学习性和一致性成为生成过程的属性，而非成品的属性。我们概述了一个研究议程，描绘了一个未来，其中HCI领域从今天的设计和知识启发式清单过渡到工艺变得机器可读、可执行和开放的未来。
英文摘要
Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand from natural-language task descriptions. A user explains what they are trying to accomplish, and the system materializes a working interface to support it. This capability already exists in systems such as Claude and ChatGPT and continues to grow in fidelity as the underlying models improve. The next step along this trajectory is to move from interfaces that are merely generated to interfaces that are generated well. We propose a framework in which the dialogue between user and artificial intelligence (AI) becomes a Space to Think: a shared, structured cognitive workspace in which task decomposition produces an on-demand user interface as an extension of the user's thinking rather than as a separate artifact. Within this paradigm, classical HCI design knowledge (Nielsen's heuristics, Norman's affordance prescriptions, Web Content Accessibility Guidelines (WCAG) success criteria, cognitive-load constraints, and mixed-initiative principles) is encoded as skills: machine-readable skill.md files that the generating agent loads at runtime as software engineering tools. Skills turn HCI design knowledge into declarative, inspectable, version-controlled, and editable artifacts owned by the HCI community itself so that accessibility, learnability, and consistency become properties of a generative process rather than properties of a finished product. We outline a research agenda depicting a future where the HCI field transitions from today's design and knowledge heuristic checklist towards a future where the craft becomes machine-readable, executable, and open.
