Large language models (LLMs) are becoming more prevalent and have found a ubiquitous use in providing different forms of writing assistance. However, LLM-powered writing systems can frustrate users due to their limited personalization and control, which can be exacerbated when users lack experience with prompt engineering. We see design as one way to address these challenges and introduce GhostWriter, an AI-enhanced writing design probe where users can exercise enhanced agency and personalization. GhostWriter leverages LLMs to learn the user's intended writing style implicitly as they write, while allowing explicit teaching moments through manual style edits and annotations. We study 18 participants who use GhostWriter on two different writing tasks, observing that it helps users craft personalized text generations and empowers them by providing multiple ways to control the system's writing style. From this study, we present insights regarding people's relationship with AI-assisted writing and offer design recommendations for future work.

翻译：大型语言模型（LLMs）正日益普及，并被广泛应用于提供各种形式的写作辅助。然而，基于LLM的写作系统可能因个性化和控制能力有限而让用户感到挫败，当用户缺乏提示工程经验时，这一问题会进一步加剧。我们将设计视为应对这些挑战的一种方法，并引入GhostWriter这一AI增强型写作设计原型，使用户能够拥有更强的自主性和个性化能力。GhostWriter利用LLMs在用户写作时隐式学习其期望的写作风格，同时通过手动风格编辑和注释提供显式的教学时刻。我们研究了18名参与者在两项不同写作任务中使用GhostWriter的情况，观察到该工具帮助用户生成个性化文本，并通过提供多种控制系统写作风格的方式赋予他们更强的能力。基于此研究，我们提出了关于人机辅助写作关系的见解，并为未来工作提供了设计建议。