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This stream examines whether the EU’s Artificial Intelligence Act will create a new “Brussels Effect.” It argues that, due to external competition and internal design limits, the Act is unlikely to shape global standards broadly, leading instead to a patchwork of partial influence across jurisdictions.
This course explores the legal and regulatory challenges of Generative AI in the European Union, focusing on liability, privacy, intellectual property, and cybersecurity. It analyzes the adequacy of current and proposed EU legislation, including the AI Act, identifies gaps, and offers recommendations for the safe and compliant use of generative models.
This course offers a critical overview of the newly adopted EU Artificial Intelligence Act (Regulation 2024/1689). It examines the regulation’s structure, objectives, and key concepts, as well as its material and territorial scope. The course explores underlying principles such as fairness, transparency, and accountability, and analyzes prohibited AI practices and the regulation of high-risk and general-purpose AI systems. It also addresses transparency obligations, certification, supervision, and sanctions. Finally, the course reflects on the regulation’s complexity and its potential impact on responsible AI innovation in the EU and beyond.
This course explores the anticipated impact of the EU Artificial Intelligence Act on key areas of intellectual property law where AI technologies raise legal and regulatory challenges. Participants will examine issues such as authorship and ownership of AI-generated works, IP protection for the technologies underlying AI systems, and the implications of using IP-protected content to train or operate AI models. The course also discusses how AI systems may infringe third-party rights or act as intermediaries in IP violations, and how traditional legal standards may be influenced by AI developments. Through a critical analysis of the EU AI Act’s scope and potential, the course highlights existing gaps and considers where new IP legislation may be needed in response to the evolving role of AI.
This course explores the complex relationship between artificial intelligence (AI) regulation and innovation. While regulations and standards are essential to minimise risks and maximise benefits, they are often criticised for potentially stifling innovation. Through a critical examination of this debate, the course analyses current trends in AI regulation, with a particular focus on the proposed European AI Act and the standards supporting its implementation. Participants will engage with arguments claiming that regulation hinders innovation, evaluate these perspectives, and consider alternative viewpoints that demonstrate how regulation and standards can, in fact, foster innovation in the AI field.
This course offers a critical exploration of the intersection between the European Union’s Artificial Intelligence (AI) Act and EU copyright law. It examines how AI regulation affects copyright throughout the AI lifecycle — from data input and model training to output generation — highlighting legal ambiguities and gaps that may shape future policy. Key topics include the role of text and data mining (TDM) under the Copyright in the Digital Single Market Directive, transparency and compliance requirements, and the Act’s extraterritorial effects. The course also addresses concerns around fair remuneration for creators, proposing solutions such as collective licensing, statutory licensing, and AI output levies. Participants will gain insights into the evolving relationship between AI governance and copyright protection in the EU.
This course explores copyright challenges related to generative AI, using ChatGPT as a central case study. It examines how AI systems rely on large datasets — often containing copyrighted material — for training, raising questions about fair use, derivative works, and the legality of data use. The course discusses potential copyright infringements and offers strategies to protect rights holders while promoting AI innovation. Special focus is given to how copyright laws may need to evolve to address authorship and ownership in AI-generated content.
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