# The Prompt Artists

arXiv: https://arxiv.org/abs/2303.12253 · HTML: https://mlsanity.com/paper/2303.12253/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Mar 2023.

## Built on by (most cited first, 21 of 21)

- [Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Prompts](https://mlsanity.com/paper/2308.03921/) (2023)
- [Scientists' Perspectives on the Potential for Generative AI in their Fields](https://mlsanity.com/paper/2304.01420/) (2023)
- [Interactive AI Alignment: Specification, Process, and Evaluation Alignment](https://mlsanity.com/paper/2311.00710/) (2023)
- [Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming](https://mlsanity.com/paper/2311.06237/) (2023)
- [Using Text-to-Image Generation for Architectural Design Ideation](https://mlsanity.com/paper/2304.10182/) (2023)
- [User Experience Design Professionals' Perceptions of Generative Artificial Intelligence](https://mlsanity.com/paper/2309.15237/) (2023)
- [Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching](https://mlsanity.com/paper/2501.18588/) (2025)
- [The Dearth of the Author in AI-Supported Writing](https://mlsanity.com/paper/2404.10289/) (2024)
- [Un-Straightening Generative AI: How Queer Artists Surface and Challenge the Normativity of Generative AI Models](https://mlsanity.com/paper/2503.09805/) (2025)
- [POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation](https://mlsanity.com/paper/2504.13392/) (2025)
- [Disability Representations: Finding Biases in Automatic Image Generation](https://mlsanity.com/paper/2406.14993/) (2024)
- [Reusing Computation in Text-to-Image Diffusion for Efficient Generation of Image Sets](https://mlsanity.com/paper/2508.21032/) (2025)
- [Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration](https://mlsanity.com/paper/2509.10652/) (2025)
- [Comparison-based Active Preference Learning for Multi-dimensional Personalization](https://mlsanity.com/paper/2411.00524/) (2024)
- [Computational Scaffolding of Composition, Value, and Color for Disciplined Drawing](https://mlsanity.com/paper/2509.17268/) (2025)
- [The Algorithmic Gaze of Image Quality Assessment: An Audit and Trace Ethnography of the LAION-Aesthetics Predictor](https://mlsanity.com/paper/2601.09896/) (2026)
- [Are Semantic Networks Associated with Idea Originality in Artificial Creativity? A Comparison with Human Agents](https://mlsanity.com/paper/2602.02048/) (2026)
- [Beyond the Desk: Barriers and Future Opportunities for AI to Assist Scientists in Embodied Physical Tasks](https://mlsanity.com/paper/2603.19504/) (2026)
- [Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review](https://mlsanity.com/paper/2408.00613/) (2024)
- [On Semiotic-Grounded Interpretive Evaluation of Generative Art](https://mlsanity.com/paper/2604.08641/) (2026)
- [Man, Machine, and Masterpiece: Artistic Ownership in the AI Era](https://mlsanity.com/paper/2607.15027/) (2026)

## Abstract (arXiv)

This paper examines the art practices, artwork, and motivations of prolific users of the latest generation of text-to-image models. Through interviews, observations, and a user survey, we present a sampling of the artistic styles and describe the developed community of practice around generative AI. We find that: 1) the text prompt and the resulting image can be considered collectively as an art piece prompts as art and 2) prompt templates (prompts with ``slots'' for others to fill in with their own words) are developed to create generative art styles. We discover that the value placed by this community on unique outputs leads to artists seeking specialized vocabulary to produce distinctive art pieces (e.g., by reading architectural blogs to find phrases to describe images). We also find that some artists use "glitches" in the model that can be turned into artistic styles of their own right. From these findings, we outline specific implications for design regarding future prompting and image editing options.