[AI CoLab] Beyond the Black Box: A Statistical View of AI

AI is increasingly shaping how we design policy, deliver services and engage with communities. Yet for many people working in government and across sectors, it can still feel like a “black box” best left to technical teams. This session will take participants behind the curtain by employing a different approach to AI literacy. Facilitators will ground the content in concepts many policy, economics and social science professionals already use in their everyday work - reframing generative AI models, including transformers, in the familiar language of statistics and econometrics.

​The workshop will connect mathematical foundations to practical governance questions: how to interpret a model’s probability of error, how bias emerges from training data, and how to ask meaningful questions about where a system’s insights come from and where its limits sit. By building shared understanding across policy, governance, technical and community perspectives, the session will help shift teams from passive consumption of tools to active, evidence-based stewardship — ensuring AI adoption strengthens public trust, sovereignty and long-term public value.

​AI CoLab events are intentionally open and collaborative. For this session we may capture photos to share publicly. This is done in line with the Charter’s values; transparent, ethical innovation and knowledge sharing to accelerate collective learning (see join.aicolab.org). By participating in this event, you agree to being photographed and for those images to be shared in accordance with this policy.