Autonomy, Authenticity, Authorship and Intention in Computer Generated Art
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The creative industries have witnessed the advent of generative AI programs of various kinds due to the rapid development of multilayered machine learning architectures.
“In recent times, due to the rapid development of multilayered machine learning (ML) architectures such as Deep Learning (DL) and its increasing application in the field of artificial intelligence (AI) technology [52], the creative industries of modern human society have borne witness to the advent of generative AI programs of various kinds.”
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Understanding and creating art with AI: Review and outlook
Cetinic, E., & She, J. (2022) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3475799 · Cited by 579 · see citing works
The Role of AI Attribution Knowledge in the Evaluation of Artwork
Gangadharbatla, H. (2022) · Empirical Studies of the Arts · doi:10.1177/0276237421994697 · Cited by 132 · see citing works
Diffusion-Based Visual Art Creation: A Survey and New Perspectives
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Emerging human-technology relationships in a co-design process with generative AI
Vartiainen, H., Liukkonen, P., & Tedre, M. (2025) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2024.101742 · Cited by 28 · see citing works
He, Q., Zheng, W., Bao, H., Chen, R., & Tong, X. (2023) · Proceedings of the Eleventh International Symposium of Chinese CHI · doi:10.1145/3629606.3629675 · Cited by 15 · see citing works
- Authors
- McCormack, J., Gifford, T., & Hutchings, P.
- Affiliations
- Monash University (AU)
- Corresponding author
- McCormack, Jon
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 35-50
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2919674582
- Cited by
- 218
- References
- 0
- Citations by year
- 2026: 70 · 2025: 83 · 2024: 30 · 2023: 9 · 2022: 14 · 2021: 6 · 2020: 5 · 2019: 1
- FWCI
- 93.04
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Social Sciences › Political Science and International Relations › Literary and Philosophical Studies
- Keywords
- computer art, AI-generated art, autonomy of art, authenticity, authorship, artistic intention, deep learning, generative adversarial networks, art and technology
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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