Diskurs

Generative AI is transforming creative fields by rapidly producing texts, images, music, and videos. These AI creations often seem as impressive as human-made works but require extensive training on vast amounts of data, much of which is copyrighted. This dependency on copyrighted material has sparked legal debates, as AI training involves “copying” and “reproducing” these works, actions that could potentially infringe on copyrights. In defense, AI proponents in the United States invoke “fair use” under Section 107 of the Copyright Act, while in Europe, they cite Article 4(1) of the 2019 DSM Directive, which allows certain uses of copyrighted works for “text and data mining.”

This study challenges the prevailing European legal stance, presenting several arguments:

1. The exception for text and data mining should not apply to AI training because the technologies differ fundamentally - one processes semantic information, while the other extracts syntactic information.

2. There is no suitable copyright exception to justify the massive infringements occurring during AI training. Copyrighted works are copied during data collection, fully or partly replicated inside AI models, and can also be reproduced by end-users.

3. Even if AI training occurs outside Europe, developers cannot avoid European copyright laws. If works are replicated within a model, making it available in Europe could infringe the “right of making available“ under Article 3 of the InfoSoc Directive. Thus, offering AI services to European users ultimately subjects developers to European copyright laws and European courts’ jurisdiction.

This study suggests to rethink copyright issues in the context of AI. Given the technical revolution and socio-economic disruptions generative AI brings, lawmakers should reconsider how to balance protecting human creativity and fostering AI innovation. The current lack of regulation neglects the technical realities and is thus not only legally unsound but also unjust.