NEXT Event
The Geneva Workshop on Innovations in Scholarly Communication
From 10-14 November 2025
Prof Yaniv Benhamou
University of Geneva
Yaniv Benhamou 
is Professor of Digital, Information and Media Law at the Faculty of Law of the University of Geneva and is a board member of the Digital Law Center (DLC). His research focuses mainly on emerging technologies (Web3+AI) and the articulation between legal regimes (intellectual property, data protection, and data law). He also focuses on the cultural and creative sector (e.g., impact of digital on the value chain) and on the collective dimension of data (e.g., digital commons,
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open source). Since 2015, he has co-organized the Digital Law Summer School with Prof. Jacques de Werra. Since 2018, he has been mandated as expert by WIPO on Museums and Copyright and by the Swiss authorities on AI regulation. In addition to his academic activities, he practices as an attorney-at-law in a Swiss law firm and is an active member of the Swiss Media Supervisory Authority (AIEP). He is also active in the cultural sector. In particular, he founded Artists Rights, a free legal advisory service for Swiss artists; regularly teaches copyright law to museums as part of AMS.
All Sessions by Prof Yaniv Benhamou
Navigating AI in Open Science
November 12, 2025
Open Source AI: Propagation of Open Source Licenses in the Age of AI
Open source AI models have the potential to foster innovation and technological progress. Nevertheless, the definition of “open source” in the AI space is hotly discussed. A related – yet no less central – issue concerns the propagating effect of copyleft (or ShareAlike) clauses embedded in training data or upstream code. Do these clauses require downstream AI models, systems and their output to be released under the same open source terms, e.g. as copyright derivatives? This has major repercussions as such propagation would render entire AI projects fully open. The presentation will examine this question and find that this is presently unlikely to be the case, save for training data. Further to this finding, and in order to protect the effectiveness of ShareAlike clause, it will thus advocate for a new definition of copyright derivatives specific to the AI-context.