AI development is concentrated in corporate hands, but community-controlled alternatives ‒ open, efficient, and democratically governed ‒ are already proving viable.
Latin America's data centre boom reveals that digital sovereignty depends less on legal declarations than on states' operational control over energy, water, and exit rights.
China is recasting artificial intelligence as a tool of infrastructure diplomacy, a strategic shift that confronts the innovation-led paradigm and navigates the risks of fragmented global governance.
Europe is losing its war on poverty because it is ignoring the new front: digital poverty.
The struggles of African professionals shut out of LinkedIn reveal how digital identity systems, if poorly designed, can erode rights and opportunities anywhere, even in Europe.
Codifying “by design” principles into policies may lead to contradictions.
What big tech’s latest sustainability reports say (and don’t say) about the true environmental cost of AI.
This op-ed explores how blockchain could catalyse a global, open alternative to the current scientific system.
If transparency is the solution, are we really addressing the problems of automated decision-making?
While transparency is often championed as the key to addressing the risks of automated decision-making (ADM) in public governance, this op-ed argues that a narrow focus on explainability overlooks deeper systemic issues such as power imbalances, commercial influence, and weakened accountability. To address these issues, mechanisms that promote transparency must operate alongside efforts to enhance citizen engagement and other methods of oversight and accountability to better protect democratic values.
Article 10 of the EU’s AI Act puts data governance at the heart of bias mitigation in high-risk AI systems but offers little guidance on implementation. Delegating these challenges to technical standardisation bodies raises both feasibility and legitimacy concerns, posing a significant test for the institutions now tasked with defining AI fairness in practice.