Writing in Symbiosis: Mapping Human Creative Agency in the AI Era

Vivan Doshi, Mengyuan Li

Track: Paper

Keywords: human-AI coevolution, creative writing, stylometric analysis, authorship, large language models, perplexity analysis, AI detection, clustering analysis, linguistic adaptation, creative agency

TL;DR: Human writers exhibit adaptation patterns such as Adopters, Resistors, and Pragmatists, revealing the "Dual-Track Evolution" where thematic convergence coexists with stylistic divergence in the LLM era.

Abstract: The proliferation of Large Language Models (LLMs) raises a critical question about what it means to be human when we share an increasingly symbiotic relationship with persuasive and creative machines. This paper examines patterns of human-AI coevolution in creative writing, investigating how human craft and agency are adapting alongside machine capabilities. We challenge the prevailing notion of stylistic homogenization by examining diverse patterns in longitudinal writing data. Using a large-scale corpus spanning the pre- and post-LLM era, we observe patterns suggestive of a "Dual-Track Evolution": thematic convergence around AI-related topics, coupled with structured stylistic differentiation. Our analysis reveals three emergent adaptation patterns: authors showing increased similarity to AI style, those exhibiting decreased similarity, and those maintaining stylistic stability while engaging with AI-related themes. This Creative Archetype Map illuminates how authorship is coevolving with AI, contributing to discussions about human-AI collaboration, detection challenges, and the preservation of creative diversity.

Submission Number: 217