Towards a Diffractive Analysis of Prompt-Based Generative AI
Open accessAbstract
Recent developments in prompt-based generative AI has given rise to discourse surrounding the perceived ethical concerns, economic implications, and consequences for the future of cultural production. As generative imagery becomes pervasive in mainstream society, dominated primarily by emerging industry leaders, we encourage that the role of the CHI community be one of inquiry; to investigate the numerous ways in which generative AI has the potential to, and already is, augmenting human creativity. In this paper, we conducted a diffractive analysis exploring the potential role of prompt-based interfaces in artists’ creative practice. Over a two week period, seven visual artists were given access to a personalised instance of Stable Diffusion, fine-tuned on a dataset of their work. In the following diffractive analysis, we identified two dominant modes adopted by participants, AI for ideation, and AI for production. We furthermore present a number of ethical design considerations for the future development of generative AI interfaces.
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Existing socio-technical evaluations of AI have primarily centered on conversations with artists through interviews, with only a handful focusing on artists experimenting with tools directly or bringing artists into conversation with one.
“While these get closer to understanding AI as a socio-technical artifact, these studies have primarily centered on conversations with artists through interviews, with only a handful studies focusing on artists experimenting with tools directly or bringing artists into conversation with one [18, 19, 21-24].”
From Dialogue with the Machine and Dialogue with the Art World: Evaluating Generative AI for Culturally-Situated Creativity (2024) · cites this paper as [18]
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References 39 · Cited by 37
- Authors
- Rajcic, N., Llano Rodriguez, M. T., & McCormack, J.
- Affiliations
- Monash University (AU)
- Human Centred Computing, Monash University, Australia
- Venue
- Proceedings of the CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2024-05-11
- Pages
- 1-15
- OpenAlex
- W4392488463
- Cited by
- 37
- References
- 39
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 1
- FWCI
- 129.92
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- Monash University Research Portal (Monash University) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- Australian Research Council (DP220101223)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- diffractive analysis, Stable Diffusion, fine-tuning, human-AI collaboration, visual arts
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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