# Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books

arXiv: https://arxiv.org/abs/2601.18353 · HTML: https://mlsanity.com/paper/2601.18353/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 74 references that are in the map.
- First posted on arXiv 26 Jan 2026.

## Builds on (most cited first, 30 of 30)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals](https://mlsanity.com/paper/2209.14958/) (2022)
- [Art or Artifice? Large Language Models and the False Promise of Creativity](https://mlsanity.com/paper/2309.14556/) (2023)
- [Generative artificial intelligence enhances creativity but reduces the diversity of novel content](https://mlsanity.com/paper/2312.00506/) (2023)
- [Homogenization Effects of Large Language Models on Human Creative Ideation](https://mlsanity.com/paper/2402.01536/) (2024)
- [Mapping the Increasing Use of LLMs in Scientific Papers](https://mlsanity.com/paper/2404.01268/) (2024)
- [Sparks: Inspiration for Science Writing using Language Models](https://mlsanity.com/paper/2110.07640/) (2021)
- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [A Design Space for Intelligent and Interactive Writing Assistants](https://mlsanity.com/paper/2403.14117/) (2024)
- [Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers](https://mlsanity.com/paper/2211.05030/) (2022)
- [Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models](https://mlsanity.com/paper/2402.11723/) (2024)
- [The Widespread Adoption of Large Language Model-Assisted Writing Across Society](https://mlsanity.com/paper/2502.09747/) (2025)
- [Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Edits](https://mlsanity.com/paper/2409.14509/) (2024)
- [People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://mlsanity.com/paper/2501.15654/) (2025)
- [The Effects of Generative AI on Design Fixation and Divergent Thinking](https://mlsanity.com/paper/2403.11164/) (2024)
- [A Robot Walks into a Bar: Can Language Models Serve as Creativity Support Tools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians](https://mlsanity.com/paper/2405.20956/) (2024)
- [PostMark: A Robust Blackbox Watermark for Large Language Models](https://mlsanity.com/paper/2406.14517/) (2024)
- [From Pen to Prompt: How Creative Writers Integrate AI into their Writing Practice](https://mlsanity.com/paper/2411.03137/) (2024)
- ["It was 80% me, 20% AI": Seeking Authenticity in Co-Writing with Large Language Models](https://mlsanity.com/paper/2411.13032/) (2024)
- [Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation](https://mlsanity.com/paper/2502.18357/) (2025)
- [Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond](https://mlsanity.com/paper/2501.11457/) (2025)
- [How Does the Disclosure of AI Assistance Affect the Perceptions of Writing?](https://mlsanity.com/paper/2410.04545/) (2024)
- [Copying style, Extracting value: Illustrators' Perception of AI Style Transfer and its Impact on Creative Labor](https://mlsanity.com/paper/2409.17410/) (2024)
- [Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers](https://mlsanity.com/paper/2510.13939/) (2025)
- [Making the Write Connections: Linking Writing Support Tools with Writer's Needs](https://mlsanity.com/paper/2502.13320/) (2025)
- [Creative Writers' Attitudes on Writing as Training Data for Large Language Models](https://mlsanity.com/paper/2409.14281/) (2024)
- [Phraselette: A Poet's Procedural Palette](https://mlsanity.com/paper/2503.06335/) (2025)
- [Public Opinions About Copyright for AI-Generated Art: The Role of Egocentricity, Competition, and Experience](https://mlsanity.com/paper/2407.10546/) (2024)
- [Who Owns the Text? Design Patterns for Preserving Authorship in AI-Assisted Writing](https://mlsanity.com/paper/2601.10236/) (2026)

## Built on by (most cited first, 9 of 9)

- [Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models](https://mlsanity.com/paper/2603.20957/) (2026)
- [AI Fiction in the Wild](https://mlsanity.com/paper/2606.22748/) (2026)
- [Generative AI floods and dilutes the market for books](https://mlsanity.com/paper/2607.20349/) (2026)
- [The Ultimate Tutorial for AI-driven Scale Development in Generative Psychometrics: Releasing AIGENIE from its Bottle](https://mlsanity.com/paper/2603.28643/) (2026)
- [Ex Ante Evaluation of AI-Induced Idea Diversity Collapse](https://mlsanity.com/paper/2605.06540/) (2026)
- [Narrative Flattening: How Post-Training Compresses Thematic, Affective, and Stylistic Variation in LLM Fiction](https://mlsanity.com/paper/2605.27878/) (2026)
- [Do Large Language Models Always Tell The Same Stories?](https://mlsanity.com/paper/2606.17350/) (2026)
- [Characterizing Cultural Localization in AI-Generated Stories](https://mlsanity.com/paper/2606.14626/) (2026)
- [Weightless Fine-Tuning: Personalizing LLMs via Logit-Space Transport](https://mlsanity.com/paper/2608.11342/) (2026)

## Abstract (arXiv)

Creative writing has long been considered a uniquely human endeavor, requiring voice and style that machines could not replicate. This assumption is challenged by Generative AI that can emulate thousands of author styles in seconds with negligible marginal labor. To understand this better, we conducted a behavioral experiment where 28 MFA writers (experts) competed against three LLMs in emulating 50 critically acclaimed authors. Based on blind pairwise comparisons by 28 expert judges and 131 lay judges, we find that experts preferred human writing in 82.7% of cases under the in-context prompting condition but this reversed to 62% preference for AI after fine-tuning on authors' complete works. Lay judges, however, consistently preferred AI writing. Debrief interviews with expert writers revealed that their preference for AI writing triggered an identity crisis, eroding aesthetic confidence and questioning what constitutes "good writing." These findings challenge discourse about AI's creative limitations and raise fundamental questions about the future of creative labor.