"It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language Models
Qian Wan, Siying Hu, Yu Zhang, Piaohong Wang, Bo Wen, Zhicong Lu

TL;DR
This study explores how humans and large language models collaborate during prewriting tasks, revealing a three-stage iterative process that emphasizes human dominance and shifting AI initiative, with insights into collaboration challenges and design implications.
Contribution
It introduces the concept of a three-stage Human-AI Co-creativity process in prewriting, highlighting dynamics, roles, and challenges in collaborative idea development with LLMs.
Findings
Identified three stages: Ideation, Illumination, Implementation.
Humans maintain a dominant role in collaboration.
Collaboration breakdowns and user perceptions were analyzed.
Abstract
Prewriting is the process of discovering and developing ideas before a first draft, which requires divergent thinking and often implies unstructured strategies such as diagramming, outlining, free-writing, etc. Although large language models (LLMs) have been demonstrated to be useful for a variety of tasks including creative writing, little is known about how users would collaborate with LLMs to support prewriting. The preferred collaborative role and initiative of LLMs during such a creativity process is also unclear. To investigate human-LLM collaboration patterns and dynamics during prewriting, we conducted a three-session qualitative study with 15 participants in two creative tasks: story writing and slogan writing. The findings indicated that during collaborative prewriting, there appears to be a three-stage iterative Human-AI Co-creativity process that includes Ideation,…
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Taxonomy
TopicsMachine Learning in Materials Science · Software Engineering Research · Design Education and Practice
