Abstract
We are living in the era of art-making being transformed by rapidly advancing generative AI technologies. With these technologies, what are some approaches to design and build AI-powered art-making tools?
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References
9
[1]
Chung, J.J., He, S., and Adar, E. Artist support networks: Implications for future creativity support tools. In Designing interactive Systems Conference [DIS '22]. ACM, New York, 2022, 232--246.
[5]
Bansal, A., Borgnia, E., Chu, H., Li, J., Kazemi, H., Huang, F., Goldblum, M., Geiping, J., and Goldstein, T. Cold diffusion: Inverting arbitrary image transforms without noise. arXiv:2208.09392 [cs.CV]. 2022.
[7]
Zhang, L. and Agrawala, M. Adding conditional control to text-to-image diffusion models. arXiv:2302.05543 [cs.CV] 2023.
[9]
Resnick, M., Myers, B.A., Nakakoji, K., Shneiderman, B., Pausch, R.F., Selker, T., and Eisenberg, M. Design principles for tools to support creative thinking. 2005.
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AI: An Active and Innovative Tool for Artistic Creation

Charis Avlonitou, Eirini Papadaki · 2025

Arts
Metrics
4
Citations
9
References
Details
Published
Jun 01, 2023
Vol/Issue
29(4)
Pages
14-19
License
View
Cite This Article
John Joon Young Chung (2023). Designing AI-Powered Art-Making Tools. XRDS: Crossroads, The ACM Magazine for Students, 29(4), 14-19. https://doi.org/10.1145/3596925
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