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：尽管大语言模型（LLM）作为写作助手具有巨大潜力，但其仍受到模型输出的连贯性与流畅性、可信度、生成内容的所有权以及模型性能的可预测性等问题的困扰，从而限制了其可用性。在本立场论文中，我们提出采用诺曼的七阶段行动框架来指导智能写作助手的交互设计。通过提供软件教程编写的示例，我们展示了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LLM工具交互设计研究的工具，并列举了支持各行动阶段的具体工具实例。最后，我们简要概述了该框架在人机交互研究中的潜在应用前景。