Algorithmic transparency is a key principle of responsible AI. Relating directly to the right of access to information, compliance with algorithmic transparency principles includes a range of reactive and proactive instruments. This joint project between the Responsible AI and Data Governance working groups aims to support governments in promoting and complying with algorithmic transparency principles, standards, and rules. The project studies the strengths and weaknesses of transparency instruments, exploring the challenges of building them, their diverse uses and users, costs, and potential contributions to transparency including explainability and accountability but also to public value creation. In Spring of 2024, the project produced an analysis of 69 active repositories from around the world. Building on these findings the project aims to produce recommendations for governments to move towards algorithmic transparency in their own contexts.

 Algorithmic Transparency in the Public Sector: A state of the art report of algorithmic transparency instruments (November 2024)

 Algorithmic Transparency in the Public Sector: Case studies of repositories of public algorithms in Chile, the EU and the UK (November 2024)

 Algorithmic Transparency in the Public Sector: Recommendations for Governments to Enhance the Transparency of Public Algorithms (November 2024)

 Scaling responsible AI solutions: Building an international community of practice and knowledge-sharing (November 2024)

Digital Ecosystems that Empower Communities: Exploring case studies to develop theory and templates for technology stacks (November 2024)

 Pandemic resilience case studies of an AI-calibrated ensemble of models to inform decision-making (November 2024)

‌ Algorithmic transparency in the public sector: Why it is important and a key aspect of responsible AI and data governance (project summary brief)

‌ Algorithmic transparency in the public sector: A state-of-the-art report of algorithmic transparency instruments (May 2024)