Publications
From Open Access to Collective Governance
This research report analyzes the EU's policy evolution from early open access initiatives to current digital infrastructure governance and offers recommendations for future policy direction.
Data Governance in Open Source AI
The paper defines a shared position on data sharing and data governance in Open Source AI development. Collective action is needed to establish shared standards for training data and datasets.
AI Speaks Polish
This report analyzes the development of Polish small language models and the ecosystem in which this happens. The case studies show alternatives to large commercial models that are built as Digital Commons, and can help fight concentrations of power in AI.
Demonopolizing the European Public Domain
This report examines the legal status of datasets created as a result of European libraries' participation in the Google Books project under agreements for the digitization of public domain books.
Open movement’s common(s) causes
This report maps current threats and opportunities facing the open movement, based on an advocacy event organized at Wikimania 2024.
Digital Commons as Providers of Public Digital Infrastructures
This paper examines literature on public digital infrastructures and current global debates. It presents five case studies demonstrating how Digital Commons can support and improve these infrastructures.
The Digital Innovation We Need
This policy brief highlights lessons drawn from an analysis of the EU’s current digital funding framework and provides recommendations to improve it.
Democratizing AI for the Public Good
This policy brief considers open-source AI as a digital public good and provides recommendations for progressing toward AI democratization and accelerating the attainment of the SDGs.
Investing in Public Digital Infrastructure
This paper outlines four key actions to fund public-driven innovation, safeguard digital rights and reduce Europe's reliance on private, extractive digital infrastructure.
Towards Robust Training Data Transparency
This paper and the accompanying blueprint of the transparency template that the AI office is tasked to develop is a collaborative effort of Open Future and Mozilla Foundation, drawing on input from experts.
The Impact of Share Alike/CopyLeft Licensing on Generative AI
The study explores the impact of Share Alike/CopyLeft licensing on machine learning and generative AI.
