Keyword: Auteursrecht
The Obligations of Providers of General-Purpose AI Models external link
Abstract
During the legislative process, the EU Artificial Intelligence (AI) Act was amended to include provisions related to general-purpose AI (GPAI) models. These broadly relate to transparency towards downstream users and relevant regulators, in addition to obligations connected to intellectual property. In this paper, we provide detailed analysis of these new provisions in the context of current technological applications and emerging trajectories, connecting them to computing literature and practice, and the broader context of connected and adjacent legal regimes, in particular copyright and relevant emerging case law. We find that there are a significant number of inclarities, tensions and contradictions both within the text, between the text and other legal regimes, and between the text and guideline documents, such as the Code of Practice on General-Purpose AI and recent guidelines by the European Commission. We identify a range of issues with the scoping of the provisions which may undermine its policy goals and create loopholes for regulatory avoidance, such as those relating to non-commercial models, open-source models, and model finetuning along the value chain. We find that the Code of Practice contains significant omissions and misstatements, some of which may present a compliance risk for an entity choosing to rely on the Code. We do not consider the provisions on GPAI models which present a systemic risk, which are dealt with elsewhere in the volume which this work will form a part of.
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AI Act, code of practice, Copyright, Transparency
RIS
Bibtex
Thuiskopieheffing is nog niet op haar retour external link
Article 3: The Untapped Legal Basis for Europe’s Public AI Ambitions external link
EU copyright law roundup – second and third trimester of 2025 external link
Are the European TDM Exceptions Applicable to GenAI Training? Despite the Three-Step Test? external link
Angemessene Vergütung insbesondere im Bereich Streaming und Plattform-Ökonomie/Reform des Vergütungssystems für gesetzlich erlaubte Nutzungen im Urheberrecht download
An EU Copyright Framework for Research: Opinion of the European Copyright Society external link
Abstract
Research and academic freedom are at the core of the EU project. Yet, the relationship between EU copyright law and research is intricate. Research and education interests have traditionally been recognized within copyright law to some degree, however, the current EU copyright acquis is not really conducive to an effective research environment. This jeopardises the fulfilment of the EU’s ambitions in the field.
Building on the pillars of action of the European Research Area (ERA) Policy Agenda 2022-2024 and its follow-up, the ECS emphasises the need for a copyright framework that fosters research, and supports the call for immediate action on the EU copyright framework to address the most pressing challenges it raises for European researchers and their institutions.
This Opinion stresses the need to ensure a proper balance between IP rights, protected under Article 17(2) CFREU, and the freedom of art and science (Article 13 CFREU), coupled with the ‘right to research’, as enshrined in international legal instruments (UDHR and ICESCR), the objectives of the EU treaties, and the CFREU and ECHR. Various EU and national legal instruments are in place that facilitate access and reuse of scientific works, but these have several shortcomings. They weaken the effective balance between copyright, research policy needs, and the fulfilment of ERA policy goals, including the EU Open Science agenda.
This opinion focuses on the flaws in key provisions aimed at balancing copyright and research needs: the general InfoSoc Directive research exception, the text and data mining exception of the CDSM Directive and national secondary publication rights. It also briefly assesses the interface between copyright and (research) data regulation. We propose several policy interventions to address the identified shortcomings. These include the introduction of an EU-wide secondary publication right with specific characteristics; the amendment of text and data mining exceptions; the creation of a general mandatory research exception overcoming the challenges raised by Article 5(3)(d) InfoSoc; and a more careful legislative drafting to reduce legal complexity and ensure consistency across copyright and data legislation.
Copyright, european copyright society, research
RIS
Bibtex
More Information Law Series Volumes Freely Available external link
GenAI and the Copyright Three-Step Test – Do TDM Exceptions for AI Training Conflict With a Work’s Normal Exploitation? external link
Abstract
Text and data mining (TDM) for AI training can be regarded as the starting point of a complex process that impacts the market for human literary and artistic creations in different ways. The machine is only capable of mimicking human content after it had the opportunity to derive patterns for its own productions from myriad human creations that served as training resources. Once AI training has been completed and a generative AI (GenAI) system is brought to the market, AI output may support fruitful human/machine collaboration. However, it may also kill demand for the same human creativity that empowered the AI system to become a competitor in the first place. In the terminology of the ubiquitous three-step test in international and European copyright law, this latter challenge raises the question whether copyright exceptions permitting TDM for AI training cause a conflict with a work’s normal exploitation.
A closer inspection of the normal exploitation test shows that the chances of demonstrating a relevant conflict are slim in the case of AI training. Rightsholders seeking compensation for displacement effects caused by GenAI systems must resort to the final criterion of the three-step test and argue that the use for AI development unreasonably prejudices their legitimate interests. In practice, this means that copyright holders can hardly employ the three-step test as a tool to erode TDM exemptions altogether. They can only insist on the introduction of appropriate remuneration schemes to avoid unreasonable prejudice in cases of commercial AI training.
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Copyright, exploitation, GenAI, Text and Data Mining (TDM), three-step test