The DOI matches its Crossref record.
AI Derivatives: the Application to the Derivative Work Right to Literary and Artistic Productions of AI Machines
Abstract
This Article predicts that there will be attempts to use courts to try to broaden the derivative work right in litigation either to prevent the use of, or claim protection for, literary and artistic productions made by Artificial Intelligence (AI) machines. The Article considers the normative valence and the (significant) doctrinal pitfalls associated with such attempts. It also considers a possible legislative alternative, namely attempts to introduce a new sui generis right in AI productions. Finally, the Article explains how, whether such attempts succeed or not, the debate on rights (if any) in productions made by AI machines is distinct from the debate on text and data mining exceptions.
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“Second, if the legally protected aspects or elements of the pre-existing materials appear in the LLM output through indirect adaptations or modifications, always unauthorized, then this output would likely qualify as a derivative creation from the pre-existing materials [56,57].”
From Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity (2024) · cites this paper as [57]
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Cites
No references could be resolved yet.
Research works printed but not linked: 9
- The protection of derivative rights extends beyond mere protection against unauthorized copying, Mirage Editions, 856 F.2d at 1343
- 1984, The current (1976) Copyright Act entered into force on January 1, 1978. The facts of the case (Lone Ranger) predate this entry into force, 722
- 1992, A derivative work must be fixed to be protected under the Act, see 17, 102
- 1009, 63 Galoob, 964 F.2d at 969 (citing Midway Mfg, 1013
- 1983, Lone Ranger, 740 F. 2d, at 721 (quoting Paul Goldstein, Derivative Rights and Derivative Works in Copyright, 30, J. COPYRIGHT SOC'Y U.S.A, 209
- Eleanor Dickson, 2022, ); see also Veale, supra note 18 and accompanying text, Synthesis of Cross-Stakeholder Perspectives on Text Data Mining with Use-Limited Data: Setting the Stage for an IMLS National Forum, 5
- 2019, J. COPYRIGHT SOC'Y. U.S.A, 291, 294
- 2014, There is little doubt in this Author's mind that the main value of this corpus is not in making snippets available (though that is what gave the use its fair nature), but the possibilities afforded by the mining of the data. At this point, only Google and those it partners with can reap that benefit, 207
- On Japan, 2021, The Flexible Copyright Exception for 'Non-Enjoyment' Purposes -Recent Amendment in Japan and Its Implication, 70 GRUR INT, L, 145
Cited by
Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · Computer Law & Security Review · doi:10.1016/j.clsr.2024.106066 · Cited by 124
Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · doi:10.2139/ssrn.4821952 · Cited by 57
Metadata
- Authors
- Gervais, D. J.
- ORCID
- Gervais, Daniel J.
- Publisher
- Elsevier BV
- Published
- 2022
- Cited by
- 12
- References
- 0
- Type
- Preprint
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- Gervais, D. J. (2022). AI Derivatives: the Application to the Derivative Work Right to Literary and Artistic Productions of AI Machines. https://doi.org/10.2139/ssrn.4022665
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
