AI, the commons and the limits of copyright

This talk explores the impact of generative ML models on the production of digital commons. Traditionally, digital commons such as open source projects, Wikipedia, or the movies released by the Blender Foundation have relied on copyright licenses to ensure openness and protect against unilateral appropriation. With the advent of generative ML models that rely on large amounts of online content for training, some of these arrangements are breaking down.

How can we ensure that large-scale collaborative projects can continue to thrive under these conditions, and are there ways to channel some of the surplus generated by generative ML systems back into the commons?


  • Paul is Director of Policy at Open Future and President of COMMUNIA Association for the Public Domain. For more than 20 years, Paul has been advocating for more open, fair and inclusive digital policies in Europe and beyond. He has worked on building open content licensing systems, increasing access to digitized cultural heritage, reforming EU copyright polices and promoting digital public spaces…

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