GhostWriter：透過個性化和代理，增強協作人工智慧寫作體驗

GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency

February 13, 2024

作者: Catherine Yeh, Gonzalo Ramos, Rachel Ng, Andy Huntington, Richard Banks

cs.AI

摘要

大型語言模型（LLMs）正變得越來越普遍，並在提供不同形式的寫作輔助方面得到廣泛應用。然而，由於其有限的個性化和控制，LLM 驅動的寫作系統可能會讓用戶感到沮喪，尤其是當用戶缺乏提示工程方面的經驗時。我們認為設計是解決這些挑戰的一種方式，並介紹了 GhostWriter，一種 AI 增強的寫作設計探針，用戶可以通過其行使增強的代理權和個性化。GhostWriter 利用LLMs在用戶撰寫時隱含地學習用戶的預期寫作風格，同時允許透過手動風格編輯和註釋進行明確的教學時刻。我們研究了18名參與者在兩個不同寫作任務上使用 GhostWriter，觀察到它幫助用戶製作個性化的文本生成，並通過提供多種控制系統寫作風格的方式來賦予用戶權力。通過這項研究，我們提出了關於人們與AI輔助寫作的關係的見解，並為未來工作提供設計建議。

English

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.