Speaking at the Global Expert Network on Copyright User Rights Symposium on 16 June 2025, Professor Christophe Geiger argues for a simple solution to the AI training debate. Instead of the EU’s current opt-out system, which he says often fails…
On September 18, 2025, the Italian Senate definitively approved the country’s first comprehensive framework law on artificial intelligence (AI). The new law also reflects Italy’s commitment to aligning its domestic legal system with the EU Artificial Intelligence Act (Regulation (EU)…
QUT News, 22 February 2024 22nd February 2024 The role of intellectual property rights in technology transfer to developing countries and least developed countries to achieve the UN Sustainable Development Goals (SDGs) is a major theme of a new international…
By Andres Izquierdo On September 20 and 21, 2023, the World Intellectual Property Organization (WIPO) hosted its Eighth Session of the WIPO Conversation on Intellectual Property (IP) and Frontier Technologies. Central to the discourse was the pivotal role of training…
Creative Commons (CC) has engaged with a wide variety of stakeholders such as artists and content creators, as part of its ongoing community consultation on generative AI, to explore ways of addressing the artists’ concerns. CC has published an open…
[Matthew Sag] ... Although we are still a long way from the science fiction version of artificial general intelligence that thinks, feels, and refuses to “open the pod bay doors”, recent advances in machine learning and artificial intelligence (“AI”) have captured the public’s imagination and lawmakers’ interest. We now have large language models (“LLMs”) that can pass the bar exam, carry on a conversation on almost any topic, create new music, and new visual art. The principal copyright questions that you as law makers must consider relate to (1) the copyrightability of artifacts made with generative AI; and (2) the legality of using copyrighted works to train machine learning models, without express consent.
[Katherine Klosek] This month, the Library Copyright Alliance (LCA) issued principles to guide policymakers in their conversations around copyright law and AI. LCA is the voice of the library community on copyright policy; its members—the American Library Association (ALA) and the Association of Research Libraries (ARL)—represent over 300,000 information professionals and thousands of libraries. The LCA principles hold that US copyright law is fully capable of addressing questions about AI-generated outputs.
[Martin Senftleben] Abstract... The rights reservation option following from the regulation of text and data mining in the EU (Article 4 of the Directive on Copyright in the Digital Single Market) could serve as a basis for a remuneration system focusing on the use of human creations for AI training purposes. Considering legal and practical difficulties arising from this approach, however, it is preferable to follow an alternative path and introduce a levy system that imposes a general payment obligation on providers of generative AI systems.
[Brandon Butler] The past six months or so have seen the seemingly sudden appearance of several startlingly powerful AI tools that create complex new textual and visual works in response to relatively simple prompts. You probably know at least a couple by name: ChatGPT (for text) and Stable Diffusion (for images) are the ones that seem to have taken over my social feeds. These tools are creating a buzz in part because the works they generate are sometimes good enough to pass for or replace the work of humans, at least in some contexts. This raises a laundry list of policy questions, some as old as the story of John Henry (will machines put humans out of work?), others as 21st-century as data sovereignty (how can nations govern data pertaining to their citizens when it flows seamlessly around the globe?).
[Teresa Nobre] As the summer approaches, we are taking stock of the latest developments in copyright policy debates. The scene-stealer “Generative AI” is prompting a copyright comeback in the EU bubble, forcing everyone to take a position (including us). Yet the conversations that deserve the attention of copyright experts in the months to come are not limited to ChatGPT and its peers, or even to Brussels for that matter. Just when our hopes were fading, international copyright policy-making is back in action in Geneva, and the next chapter of the discussions looks promising!
[João Pedro Quintais] Generative AI is one of the hot topics in copyright law today. In the EU, a crucial legal issue is whether using in-copyright works to train generative AI models is copyright infringement or falls under existing text and data mining (TDM) exceptions in the Copyright in Digital Single Market (CDSM) Directive. In particular, Article 4 CDSM Directive contains a so-called “commercial” TDM exception, which provides an “opt-out” mechanism for rights holders. This opt-out can be exercised for instance via technological tools but relies significantly on the public availability of training datasets. This has led to increasing calls for transparency requirements. In response to these calls, the European Parliament is considering adding to its compromise version of the AI Act two specific obligations with copyright implications on providers of generative AI models: on (1) transparency and disclosure; and (2) on safeguards for AI-generated content moderation. There is room for improvement on both.
[Andrés Izquierdo] On April 28th, 2023, the World Intellectual Property Organization's Committee on Development and Intellectual Property (CDIP) approved a pilot project on Text and Data Mining (TDM) to support research and innovation in universities and other research-oriented institutions in Africa. PIJIP has been participating as an observer on this Committee since 2022... The pilot project will begin by mapping the current treaty implementation, legal framework, and licensing schemes, as well as existing materials such as studies and toolkits in the region, to assess the use of TDM in research, particularly by universities and research-oriented institutions. In the second step, the project will collaborate with three pilot universities in Africa, along with input from other regional stakeholders, to develop case studies on the application of TDM in research, using the information and experiences gathered during the mapping process.