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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 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 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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