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Creative Ownership in the Age of AI

Author

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  • Annie Liang
  • Jay Lu

Abstract

Copyright law focuses on whether a new work is "substantially similar" to an existing one, but generative AI can closely imitate style without copying content, a capability now central to ongoing litigation. We argue that existing definitions of infringement are ill-suited to this setting and propose a new criterion: a generative AI output infringes on an existing work if it could not have been generated without that work in its training corpus. To operationalize this definition, we model generative systems as closure operators mapping a corpus of existing works to an output of new works. AI generated outputs are \emph{permissible} if they do not infringe on any existing work according to our criterion. Our results characterize structural properties of permissible generation and reveal a sharp asymptotic dichotomy: when the process of organic creations is light-tailed, dependence on individual works eventually vanishes, so that regulation imposes no limits on AI generation; with heavy-tailed creations, regulation can be persistently constraining.

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  • Annie Liang & Jay Lu, 2026. "Creative Ownership in the Age of AI," Papers 2602.12270, arXiv.org.
    • Handle: RePEc:arx:papers:2602.12270
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    References listed on IDEAS

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    1. Drugov, Mikhail & Ryvkin, Dmitry, 2020. "Tournament rewards and heavy tails," Journal of Economic Theory, Elsevier, vol. 190(C).
    2. Arthur De Vany & W. Walls, 1999. "Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 23(4), pages 285-318, November.
    3. Joshua S. Gans, 2024. "Copyright Policy Options for Generative Artificial Intelligence," NBER Working Papers 32106, National Bureau of Economic Research, Inc.
    4. Chung, Kee H & Cox, Raymond A K, 1994. "A Stochastic Model of Superstardom: An Application of the Yule Distribution," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 771-775, November.
    5. S. Alex Yang & Angela Huyue Zhang, 2024. "Generative AI and Copyright: A Dynamic Perspective," Papers 2402.17801, arXiv.org, revised Dec 2025.
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