Writing is a well-established practice to support ideation and creativity. While Large Language Models (LLMs) have become ubiquitous in providing different kinds of writing assistance to different writers, LLM-powered writing systems often fall short in capturing the nuanced personalization and control necessary for effective support and creative exploration. To address these challenges, we introduce GhostWriter, an AI-enhanced writing design probe that enables users to exercise enhanced agency and personalization. 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 for editing and creative tasks, observing that it helps users craft personalized text and empowers them by providing multiple ways to steer system output. Based on this study, we present insights on people's relationships with AI-assisted writing and offer design recommendations to promote user agency in similar co-creative systems.
View on arXiv@article{yeh2025_2402.08855,
title={ GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency },
author={ Catherine Yeh and Gonzalo Ramos and Rachel Ng and Andy Huntington and Richard Banks },
journal={arXiv preprint arXiv:2402.08855},
year={ 2025 }
}