Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond
Open accessAbstract
Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these accounts of harm is that generative AI models are trained on workers' creative output without their consent and without giving credit or compensation to the original creators. This paper reports findings from 20 interviews with creative workers in three domains: visual art and design, writing, and programming. We investigate the gaps between current AI governance strategies, what creative workers want out of generative AI governance, and the nuanced role of creative workers' consent, compensation and credit for training AI models on their work. Finally, we make recommendations for how generative AI can be governed and how operators of generative AI systems might more ethically train models on creative output in the future.
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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).”
From Fanfiction in the Age of AI: Community Perspectives on Creativity, Authenticity and Adoption (2026) · cites this paper as Kyi et al., 2025
Cites
Clarke, V., & Braun, V. (2017) · The Journal of Positive Psychology · doi:10.1080/17439760.2016.1262613 · Cited by 6,543 · see citing works
Sample sizes for saturation in qualitative research: A systematic review of empirical tests
Hennink, M., & Kaiser, B. N. (2022) · Social Science & Medicine · doi:10.1016/j.socscimed.2021.114523 · Cited by 6,311 · see citing works
Artificial intelligence and illusions of understanding in scientific research
Messeri, L., & Crockett, M. J. (2024) · Nature · doi:10.1038/s41586-024-07146-0 · Cited by 707 · see citing works
The Value, Benefits, and Concerns of Generative AI-Powered Assistance in Writing
Li, Z., Liang, C., Peng, J., & Yin, M. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642625 · Cited by 81 · see citing works
Is Resistance Futile?: Early Career Game Developers, Generative AI, and Ethical Skepticism
Boucher, J. D., Smith, G., & Telliel, Y. D. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641889 · Cited by 30 · see citing works
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How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriters
Tang, Y., Zhou, J., Li, H., Xie, X., Ma, X., & Qu, H. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790300 · Cited by 5 · see citing works
“Creatorsemphasizetheneedtopreservetheirauthenticvoice[30], andmanystressthatAIshouldnotusetheirworkwithoutpermis-sionorcredit[27,34].”
Fanfiction in the Age of AI: Community Perspectives on Creativity, Authenticity and Adoption
Alfassi, R., Cooper, A., Mitchell, Z., Calabro, M., Shaer, O., & Mokryn, O. (2026) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2025.2531272 · Cited by 4 · see citing works
“Thereby, encouraging the preservation of core community values such as creativity and appreciation for human labor.”
How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriters
Tang, Y., Zhou, J., Li, H., Xie, X., Ma, X., & Qu, H. (2026) · arXiv · Cited by 5
- Authors
- Kyi, L., Mahuli, A., Silberman, M. S., Binns, R., Zhao, J., & Biega, A. J.
- Affiliations
- Max Planck Institute for Security and Privacy (DE)
- University of Oxford (GB)
- Venue
- Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2025-04-25
- Pages
- 1-16
- OpenAlex
- W4409747794
- Cited by
- 28
- References
- 5
- Citations by year
- 2026: 26 · 2025: 2
- FWCI
- 26.69
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Funders
- European Research Council (947806)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- generative AI, AI governance, creative work, consent, authorship, credit, compensation, AI-generated content, intellectual property
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