  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.
