GhostWriter：通过个性化与自主性增强人机协作写作体验
GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency
AI总结：
GhostWriter通过隐式学习用户写作风格并提供显式风格优化与反思机制，在AI辅助写作中增强用户个性化与控制力，基于18人用户研究验证其有效性并提出设计建议。
摘要：
大型语言模型（LLMs）在为不同写作者提供各种形式的写作辅助方面已变得无处不在。然而，基于LLM的写作系统往往难以捕捉有效支持用户所需的细致个性化与控制能力——尤其是对于那些缺乏提示工程经验的用户。为应对这些挑战，我们引入了GhostWriter，这是一个AI增强的设计探针，使用户能够在写作过程中行使更强的自主性和个性化能力。GhostWriter利用LLMs隐式学习用户预期的写作风格以实现无缝个性化，同时提供显式的教学时刻用于风格优化与反思。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，观察到它帮助用户生成个性化的文本内容，并通过提供多种控制该系统写作风格的方式赋予用户能力。基于这项研究，我们提出了关于特定设计选择如何在AI辅助写作中促进更大用户自主性的见解，并讨论了人们与此类系统之间不断演变的关系。最后，我们为未来工作提供了设计建议。
英文摘要：
Large language models (LLMs) have become ubiquitous in providing different forms of writing assistance to different writers. However, LLM-powered writing systems often fall short in capturing the nuanced personalization and control needed to effectively support users -- particularly for those who lack experience with prompt engineering. To address these challenges, we introduce GhostWriter, an AI-enhanced design probe that enables users to exercise enhanced agency and personalization during writing. GhostWriter leverages LLMs to implicitly learn the user's intended writing style for seamless personalization, while exposing explicit teaching moments for style refinement and reflection. We study 18 participants who use GhostWriter on two distinct 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. Based on this study, we present insights on how specific design choices can promote greater user agency in AI-assisted writing and discuss people's evolving relationships with such systems. We conclude by offering design recommendations for future work.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
