个性化
代理(哲学)
计算机科学
万维网
知识管理
数据科学
社会学
社会科学
作者
Catherine Vance Yeh,Gonzalo Ramos,Rachel Ng,Annette Huntington,Richard C. Banks
出处
期刊:Cornell University - arXiv
日期:2024-02-13
标识
DOI:10.48550/arxiv.2402.08855
摘要
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.
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