Keyword: Copyright
Copyright and Generative AI: Opinion of the European Copyright Society external link
Copyright Liability and Generative AI: What’s the Way Forward? external link
Abstract
This paper examines the intricate relationship between copyright liability and generative AI, focusing on legal challenges at the output stage of AI content generation. As AI technology advances, questions regarding copyright infringement and attribution of liability have become increasingly pressing and complex, requiring a revision of existing rules and theories. The paper navigates the European copyright framework and offers insights from Swedish copyright law on unharmonized aspects of liability, reviewing key case law from the Court of Justice of the European Union and Swedish courts. Considering the liability of AI users first, the paper emphasizes that while copyright exceptions are relevant in the discussion, national liability rules nuance a liability risk assessment above and beyond the potential applicability of a copyright exception. The analysis centers in particular on the reversed burden of proof introduced by the Swedish Supreme Court in NJA 1994 s 74 (Smultronmålet / Wild strawberries case) and the parameters of permissible transformative or derivative use (adaptations of all sorts), especially the level of similarity allowed between a pre-existing and transformative work, examining in particular NJA 2017 s 75 (Svenska syndabockar / Swedish scapegoats). Moreover, the paper engages in a discussion over the harmonization of transformative use and the exclusive right of adaptation through the right of reproduction in Article 2 InfoSoc Directive. Secondly, the paper examines copyright liability of AI system providers when their technology is used to generate infringing content. While secondary liability remains unharmonized in the EU, thus requiring consideration of national conceptions of such liability and available defences, expansive interpretations of primary liability by the Court of Justice in cases like C-160/15 GS Media, C-527/15 Filmspeler, or C-610/15 Ziggo require a consideration of the question whether AI providers indeed could also be held primarily liable for what users do. In this respect, the analysis considers both the right of communication to the public as well as the right of reproduction. The paper concludes with a forward-looking perspective, arguing in light of available litigation tactics that clarity must emerge through litigation rather than premature legislative reform. It will provide an opportunity for courts to systematize existing rules and liability theories and provide essential guidance for balancing copyright protection with innovation.
Artificial intelligence, Copyright, liability
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Bibtex
Generative AI, Copyright and the AI Act external link
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.
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AI Act, Content moderation, Copyright, Digital Services Act (DSA), Generative AI, Text and Data Mining (TDM), Transparency
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Bibtex
DPG Media et al vs. HowardsHome – A national ruling on DSM’s press publishers’ rights and TDM exceptions external link
EU copyright law roundup – fourth trimester of 2024 external link
Generative AI and Creative Commons Licences – The Application of Share Alike Obligations to Trained Models, Curated Datasets and AI Output external link
Abstract
This article maps the impact of Share Alike (SA) obligations and copyleft licensing on machine learning, AI training, and AI-generated content. It focuses on the SA component found in some of the Creative Commons (CC) licences, distilling its essential features and layering them onto machine learning and content generation workflows. Based on our analysis, there are three fundamental challenges related to the life cycle of these licences: tracing and establishing copyright-relevant uses during the development phase (training), the interplay of licensing conditions with copyright exceptions and the identification of copyright-protected traces in AI output. Significant problems can arise from several concepts in CC licensing agreements (‘adapted material’ and ‘technical modification’) that could serve as a basis for applying SA conditions to trained models, curated datasets and AI output that can be traced back to CC material used for training purposes. Seeking to transpose Share Alike and copyleft approaches to the world of generative AI, the CC community can only choose between two policy approaches. On the one hand, it can uphold the supremacy of copyright exceptions. In countries and regions that exempt machine-learning processes from the control of copyright holders, this approach leads to far-reaching freedom to use CC resources for AI training purposes. At the same time, it marginalises SA obligations. On the other hand, the CC community can use copyright strategically to extend SA obligations to AI training results and AI output. To achieve this goal, it is necessary to use rights reservation mechanisms, such as the opt-out system available in EU copyright law, and subject the use of CC material in AI training to SA conditions. Following this approach, a tailor-made licence solution can grant AI developers broad freedom to use CC works for training purposes. In exchange for the training permission, however, AI developers would have to accept the obligation to pass on – via a whole chain of contractual obligations – SA conditions to recipients of trained models and end users generating AI output.
Artificial intelligence, Copyright, creative commons, Licensing, machine learning
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Annotatie bij Hof van Justitie EU 9 maart 2021, Hof van Justitie EU 22 juni 2021 & Hoge Raad 27 januari 2023 download
Copyright, the AI Act and extraterritoriality external link
Opinion of the European Copyright Society on CG and YN v Pelham GmbH and Others, Case C-590/23 (Pelham II) external link
Abstract
In its questions for preliminary ruling, the German Federal Court of Justice asked for clarification as regards the definition of pastiche under EU copyright law; and, in essence, whether and how this concept applies to musical sampling. In the present Opinion, the European Copyright Society takes the view that pastiche is an autonomous concept of EU law. Article 5(3)(k) InfoSoc Directive (ISD) should be read as an overarching provision including three forms of permitted use that share their underlying nature but shall be judged differently. The meaning of pastiche cannot be understood as a mere imitation of an artistic style and it need not entail an explicit interaction with the original work. The presence of humour or mockery is not a necessary requirement for the application of the pastiche exception. Also, the expression resulting from the exercise of the pastiche exception need not itself be an original work. Finally, the intention of the user to create pastiche plays no role in the review of the legality of any given use. At the same time, legitimate forms of pastiche need to have their own features that are distinguishable from the copyrighted expression in pre-existing works used as source materials. Overall the use of the pastiche exception for purposes of musical sampling, as in the underlying Metall auf Metall case, complies with all the three steps of Article 5(5) ISD.
Copyright