Artinter: AI-powered Boundary Objects for Commissioning Visual Arts
Abstract
When commissioning visual art, clients and artists communicate to agree on what is to be created. This often requires bridging a language gap in how they conceive art. To arrive at a mutual understanding, they leverage boundary objects—organized language and artifact instances. However, building and working with such objects is hard due to their innate subjectivity and ambiguity. Moreover, acquiring artifact instances, such as references and sketches, requires effort. We introduce Artinter, an AI-powered commission-support system for sharing, concretizing, and expanding boundary objects. Artinter helps artists and clients develop a mutually understood ‘language’ by allowing them to define concepts with artifacts (e.g., what they mean by ‘happy’). The system provides two AI-powered approaches for expanding commission boundary objects: 1) guided search with user-defined concepts and 2) instance generation by mixing concepts and artifacts. Our studies identify how AI features can support commissions and reveal future directions for AI-powered collaborative art-making.
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People with art skills seem to have more concerns about AI-generated images.
“People with art skills seem to have more concerns about AI-generated images [15, 36].”
From Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI (2024) · cites this paper as [15]
These repetitive cycles of changes are particularly troublesome in the video game industry.
“which is particularly troublesome in the video game industry [15, 16, 35].”
From Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI (2024) · cites this paper as [15]
Several previous studies have explored the role of GenAI in collaborative creativity.
“Several previous studies have explored the role of GenAI in collaborative creativity [15, 16].”
From Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI (2024) · cites this paper as [15]
These studies revealed AI's potential to foster collaboration among users with different roles.
“These studies revealed AI's potential to foster collaboration among users with different roles.”
From Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI (2024) · cites this paper as [15]
Cites
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“Moreover, with more fexibility in grounding concepts, the machine’s mechanism can be more opaque to the end-user [76].”
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“many of these do not necessarily consider the user’s style, which can introduce friction in the art commission setting, as artists would like to maintain their own unique styles, unless they are open to new ideas and styles [14, 40].”
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Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI
Ling, L., Chen, X., Wen, R., Li, T. J.-J., & LC, R. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3677102 · Cited by 52 · see citing works
- Authors
- Chung, J. J. Y., & Adar, E.
- Affiliations
- University of Michigan (US)
- Venue
- Proceedings of the 2023 ACM Designing Interactive Systems Conference
- Publisher
- ACM
- Published
- 2023-07-10
- Pages
- 1997-2018
- OpenAlex
- W4383681529
- Cited by
- 33
- References
- 13
- Citations by year
- 2026: 7 · 2025: 17 · 2024: 8 · 2023: 1
- FWCI
- 89.75
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Designing Interactive Systems Conference (publishedVersion)
- 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
- boundary objects, art commissioning, visual arts, collaborative art making, concept definition, instance generation, guided search, AI-assisted design
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