Proactive AI as a Catalyst for Creativity? Balancing Human Agency and AI Contribution in Collaborative Story Writing

要旨

Large Language Models (LLMs) hold promise in supporting creative writing, yet the role of proactive AI in collaborative writing remains underexplored due to concerns around human agency and disruption. To investigate effective strategies for proactive AI support, we conducted a Wizard-of-Oz study simulating two suggestion styles: intrusive suggestions (next-sentence completions) and non-intrusive suggestions (exploratory proposals), where participants completed two story outlining tasks under each style, receiving real-time proactive suggestions from a human wizard acting as the AI. Both quantitative and qualitative results show that proactive AI can enhance creativity and accelerate writing. However, we observed a trade-off between AI involvement and perceived human agency. This trade-off was moderated by how strongly AI stimulated users—greater inspiration led to stronger perceived agency even under high AI involvement. Based on wizards' behavior, we offer guidance on suggestion style and timing to better balance creativity and agency for future proactive AI writing systems.

著者
Yiwen Yin
Tsinghua University, Beijing, China
Mingze Wu
Institute for Human-centered AI, Stanford, California, United States
Ruijie Huang
Beijing University of Posts and Telecommunications, beijing, China
Xin Tong
University of Michigan Ann Arbor, Ann Arbor, Michigan, United States
Junyu Zhou
University of Science and Technology of China, Hefei, China
Chun Yu
Tsinghua University, Beijing, China
Yuanchun Shi
Tsinghua University, Beijing, China

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI and Interactive Tools for the Arts

Auditorium
7 件の発表
2026-04-16 18:00:00
2026-04-16 19:30:00