# Copying style, Extracting value: Illustrators' Perception of AI Style Transfer and its Impact on Creative Labor

arXiv: https://arxiv.org/abs/2409.17410 · HTML: https://mlsanity.com/paper/2409.17410/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Sep 2024.

## Built on by (most cited first, 8 of 8)

- [AI Safety Should Prioritize the Future of Work](https://mlsanity.com/paper/2504.13959/) (2025)
- [Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books](https://mlsanity.com/paper/2601.18353/) (2026)
- [CHOIR: A Chatbot-mediated Organizational Memory Leveraging Communication in University Research Labs](https://mlsanity.com/paper/2509.20512/) (2025)
- [AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration](https://mlsanity.com/paper/2511.17906/) (2025)
- [Rewriting Video: Text-Driven Reauthoring of Video Footage](https://mlsanity.com/paper/2601.08565/) (2026)
- ["Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Work](https://mlsanity.com/paper/2603.07459/) (2026)
- [Hist2Style: Histogram-Guided Stylization with Bilateral Grids](https://mlsanity.com/paper/2606.01819/) (2026)
- [From Style Replication to Style Exploration: Enabling Art Style Exploration with Analyze-Experiment-Resituate Framework](https://mlsanity.com/paper/2608.14405/) (2026)

## Abstract (arXiv)

Generative text-to-image models are disrupting the lives of creative professionals. Specifically, illustrators are threatened by models that claim to extract and reproduce their style. Yet, research on style transfer has rarely focused on their perspectives. We provided four illustrators with a model fine-tuned to their style and conducted semi-structured interviews about the model's successes, limitations, and potential uses. Evaluating their output, artists reported that style transfer successfully copies aesthetic fragments but is limited by content-style disentanglement and lacks the crucial emergent quality of their style. They also deemed the others' copies more successful. Understanding the results of style transfer as "boundary objects," we analyze how they can simultaneously be considered unsuccessful by artists and poised to replace their work by others. We connect our findings to critical HCI frameworks, demonstrating that style transfer, rather than merely a Creativity Support Tool, should also be understood as a supply chain optimization one.