Despite the potential of Large Language Models (LLMs) as writing assistants, they are plagued by issues like coherence and fluency of the model output, trustworthiness, ownership of the generated content, and predictability of model performance, thereby limiting their usability. In this position paper, we propose to adopt Norman's seven stages of action as a framework to approach the interaction design of intelligent writing assistants. We illustrate the framework's applicability to writing tasks by providing an example of software tutorial authoring. The paper also discusses the framework as a tool to synthesize research on the interaction design of LLM-based tools and presents examples of tools that support the stages of action. Finally, we briefly outline the potential of a framework for human-LLM interaction research.

翻译：尽管大型语言模型（LLMs）作为写作助手的潜力巨大，但它们也存在一些问题，如模型输出的连贯性和流畅性、生成内容的可信度、所有权以及模型性能的可预测性，从而限制了它们的可用性。在本文中，我们建议采用诺曼七个行动阶段作为智能写作助手交互设计的框架。我们通过提供一个软件教程撰写的例子来说明该框架在写作任务中的适用性。本文还讨论了该框架作为综合研究LLM-based工具交互设计的工具，并提供了支持行动阶段的工具示例。最后，我们简要概述了该框架作为人-LLM交互研究工具的潜力。