As the Open Knowledge Foundation turned 15 years old, we took the time to look at the changing landscape of challenges faced by society.
The tumultuous debate around algorithms and artificial intelligence (AI) appeared to us as an opportunity to mobilise our unique experience with open data and data literacy and create positive change. After all, the issues of transparency, accountability, ethics and civic empowerment that we’ve addressed while working on open data are also present in the civic and political debate around algorithms and AI. Even more, it appears to us that our experience building communities, defining shared concepts, and raising data literacy translate directly to this new field.
This is why today the Open Knowledge Foundation is making a new commitment – to apply our unique skills and network to the emerging issues of AI and algorithms.
We are aware of the existing work around these issues by celebrated academics, civic organisations and even private companies and do not intend to reinvent the wheel.
Nonetheless, the conversations we have been having with multiple stakeholders for the past year have convinced us that our experience can strengthen existing communities, projects and research on the topic, with the help of our existing and future partners around the world.
Working with partners across civil society, academia and governments, we’ll apply to AI and algorithms each of the building blocks that we believe made the open data movement impactful:
- Shared definitions (what kind of algorithms are we talking about?)
- Standard tools and resources (to facilitate transparency around algorithm and AI use)
- Literacy among stakeholders (citizens, but also lawyers, civil servants and others)
Cutting across those building blocks will be three themes which will guide our action:
- Accountability: training lawyers and journalists to make sure that problematic algorithms can be investigated and challenged
- Monitoring: training journalists, CSOs and citizens to monitor the impact of algorithms, which is sometimes the only way to really understand their effects
- Improvement: we will train public and private organisations, and the lawyers advising them, to push them toward a better use of this technology
The table below shows some of the activities we are researching:
|Shared definitions||Standard resources||Literacy|
|Accountability||Mobilising thematic communities of researchers, activists, civil servants, private organisations and other stakeholders to define common concepts and methods||Participation in public policy debates to embed accountability in upcoming regulations||Creating learning content and guides on legal and non-legal ways to enforce transparency and accountability around algorithmic usage|
|Monitoring||Mapping algorithm & AI usage across government (and delegated agencies)||Training journalists in algorithm impact monitoring|
|Improvement||Training watchdog civic organisations on legal frameworks and best practices||Training government lawyers on algorithmic risk|
Stay tuned for more on the topic! For comments, contributions, or if you want to collaborate on this programme, you can get in touch with us at email@example.com.