Understanding Visual Artists’ Values and Attitudes towards Collaboration, Technology, and AI
Abstract
Artificial Intelligence (AI) tools have recently gained widespread interest for image creation, but tool developers have largely focused on technical capabilities or specialized domain uses, rather than visual artists as users. We collected survey data from 89 practising visual artists and conducted follow-up interviews with 30 of them, to better understand their diverse needs and values. Through reflexive thematic analysis, we explored visual artists’ attitudes towards collaboration in art creation both with human artists and with AI- and other technology-based support systems. Our results suggest that the focus of popular AI tools on high-quality, finished images does not meet the needs of visual artists. Instead, they wanted reference images, ideation support, and variant exploration. We identified similarities and differences between how visual artists view collaboration with other artists or with machine support, enabling designers of new tools to adopt a more user-centered approach.
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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].”
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Self-citation
- Authors
- Johnston, H., & Thue, D.
- Affiliations
- Carleton University (CA)
- Venue
- Graphics Interface
- Publisher
- ACM
- Published
- 2024-06-03
- Pages
- 1-9
- OpenAlex
- W4402721924
- Cited by
- 12
- References
- 21
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 1
- FWCI
- 42.14
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Graphics Interface (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada (NSERC) (2020-06502)
- 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
- visual artists, artificial intelligence in art, generative AI tools, human-AI collaboration, reference images, user-centered design
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