Generative AI, Copyright and the AI Act
Computer Law & Security Review, Volume 56, 2025, 106107, https://doi.org/10.1016/j.clsr.2025.106107.
17 Pages Posted: 13 Aug 2024 Last revised: 30 Jan 2025
Date Written: January 30, 2025
Abstract
This paper provides a critical analysis of the Artificial Intelligence (AI) Act's implications for the European Union (EU) copyright acquis, aiming to clarify the complex relationship between AI regulation and copyright law while identifying areas of legal ambiguity and gaps that may influence future policymaking. The discussion begins with an overview of fundamental copyright concerns related to generative AI, focusing on issues that arise during the input, model, and output stages, and how these concerns intersect with the text and data mining (TDM) exceptions under the Copyright in the Digital Single Market Directive (CDSMD).
The paper then explores the AI Act's structure and key definitions relevant to copyright law. The core analysis addresses the AI Act's impact on copyright, including the role of TDM in AI model training, the copyright obligations imposed by the Act, requirements for respecting copyright law—particularly TDM opt-outs—and the extraterritorial implications of these provisions. It also examines transparency obligations, compliance mechanisms, and the enforcement framework. The paper further critiques the current regime's inadequacies, particularly concerning the fair remuneration of creators, and evaluates potential improvements such as collective licensing and bargaining. It also assesses legislative reform proposals, such as statutory licensing and AI output levies, and concludes with reflections on future directions for integrating AI governance with copyright protection.
Keywords: Generative AI, AI Act, AI, copyright, text and data mining, transparency, content moderation, DSA, fair remuneration
Suggested Citation: Suggested Citation
Quintais, João Pedro, Generative AI, Copyright and the AI Act (January 30, 2025). Computer Law & Security Review, Volume 56, 2025, 106107, https://doi.org/10.1016/j.clsr.2025.106107.
, Available at SSRN: https://ssrn.com/abstract=4912701
, Available at SSRN: https://ssrn.com/abstract=4912701
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