Problem
Research questions and friction points this paper is trying to address.
Human-Computer Interaction
On-Demand UI Generation
Large Language Models
HCI Design Principles
Accessibility
Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCI
🤖 AI Summary
This study addresses the limitation that user interfaces generated by large language models typically satisfy functional requirements while lacking constraints derived from high-quality design principles. To overcome this, we construct a shared human-machine cognitive space and pioneer the translation of classical HCI design knowledge into version-controlled, executable declarative skill files. By integrating structured prompt engineering with software skill modularization techniques, these design principles are encoded as machine-readable skills and injected directly into the generation process. Consequently, this work enables the on-demand generation of specification-compliant user interfaces, advancing design compliance from static checklists toward a dynamic, executable, and open automated paradigm.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
On-Demand UI Generation
HCI Principles Automation
Machine-Readable Skills
Space to Think
Large Language Models
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