Cited by 33Ethics and Social Impacts of AILaw, AI, and Intellectual PropertyArt, Technology, and Culture

Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art

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Lovato, Juniper, Zimmerman, Julia Witte, Smith, Isabelle, Dodds, Peter, Karson, Jennifer L.·2024·Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Abstract

Generative AI tools are used to create art-like outputs and sometimes aid in the creative process. These tools have potential benefits for artists, but they also have the potential to harm the art workforce and infringe upon artistic and intellectual property rights. Without explicit consent from artists, Generative AI creators scrape artists' digital work to train Generative AI models and produce art-like outputs at scale. These outputs are now being used to compete with human artists in the marketplace as well as being used by some artists in their generative processes to create art. We surveyed 459 artists to investigate the tension between artists' opinions on Generative AI art's potential utility and harm. This study surveys artists' opinions on the utility and threat of Generative AI art models, fair practices in the disclosure of artistic works in AI art training models, ownership and rights of AI art derivatives, and fair compensation. Results show that a majority of artists believe creators should disclose what art is being used in AI training, that AI outputs should not belong to model creators, and express concerns about AI's impact on the art workforce and who profits from their art. We hope the results of this work will further meaningful collaboration and alignment between the art community and Generative AI researchers and developers.

Integrity signals

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Crossref · 10.1609/aies.v7i1.31691

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  • Recent investigations into creative communities have revealed widespread apprehension regarding unauthorized use of artistic works in AI training.

    “Recent investigations into creative communities have revealed widespread apprehension regarding the unauthorized use of artistic works in AI training (Kyi et al., 2025;Lovato et al., 2024).”
  • Questions of agency, visibility, and ownership are not evenly distributed within sociotechnical systems.

    “As Jo and Gebru (2020) and Lovato et al. (2024) note, questions of agency, visibility, and ownership are not evenly distributed within these sociotechnical systems.”

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Authors
Lovato, J., Zimmerman, J. W., Smith, I., Dodds, P., & Karson, J. L.
Affiliations
University of Vermont (US)
Venue
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society
Published
2024-10-16
Volume
7
Pages
905-916
ISSN
3065-8365 (ISSN-L)
OpenAlex
W4404518214
Cited by
33
References
0
Citations by year
2026: 18 · 2025: 13 · 2024: 2
FWCI
15.06
Type
conference paper
Language
en
Open access
Locations
  • Proceedings of the AAAI/ACM Conference on AI Ethics and Society (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
  • arXiv (Cornell University)
Funders
  • National Science Foundation (2242829)
  • Alfred P. Sloan Foundation
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
  • Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
Keywords
AI-generated art, intellectual property, copyright infringement

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