The Use of Wikipedia, Wikimedia, and Open Access Content for Artificial Intelligence and Text and Data Mining

The role of Wikimedia platforms and the broader Digital Commons in developing artificial intelligence (AI) models remains significant yet underexplored. Wikimedia content, licensed under Creative Commons (CC) licenses, constitutes a primary source of training data for many large language models (LLMs), with implications for both the sustainability of the Digital Commons and compliance with copyright law. This article examines the compatibility of CC licenses with AI training, particularly under the European Union’s Copyright Directive on the Digital Single Market (CDSM Directive), which introduced new exceptions for text and data mining (TDM). It identifies scenarios where CC-licensed content can be legally used for AI training and discusses unresolved questions about reproduction, derivation, adaptation, attribution, and share-alike requirements under these licenses. The analysis highlights how stakeholders within the Digital Commons — Wikimedia, GLAM institutions, educational organizations, and intergovernmental organizations (IGOs)—influence the quality and ethical use of AI models. It also examines risks posed by AI usage, such as reduced visibility of source platforms, a decline in volunteer contributions, and diminished sustainability of open knowledge ecosystems. Strategies to uphold the Digital Commons include enforcing share-alike obligations, fostering collaboration among stakeholders, and engaging with AI developers to ensure compliance with CC licenses. The findings underscore the dual potential of open access to enhance AI model quality while maintaining the integrity of digital commons ecosystems. Digital Commons stakeholders must be open in a way that promotes qualitative AI development while maintaining sustainable open knowledge dissemination.