Rebooting Democracy in the Age of AI

A mayor presents a plan, residents push back, and everyone leaves frustrated, not because people weren’t heard, but because listening and engagement happened at the wrong moment. This piece reframes participation as a cycle: listening to set the agenda, engagement to shape decisions, and follow-through to prove input mattered. The example of St. Louis shows how sequencing these stages turns public input into real outcomes, with AI enabling reflection on input at scale.

Lots of numbers in this week's News that Caught Our Eye: Beth Simone Noveck interviews Matti Schneider of OpenFisca about why we may be over-investing in "100 interns on cocaine" aka GenAI when what we need are more computational legal systems. Yan Zhu maps over 1,000 AI governance documents, revealing proliferating policies but major gaps. Summer Mothwood explains how California used AI to make sense of suggestions from 1500 state workers about how to improve government. Beyond Reboot, Brookings finds federal AI use rising but uneven across agencies, while New York scales AI training to over 100,000 workers. Elsewhere, reporting on ICE’s geotracking system and proposed limits on license plate data underscores growing scrutiny of surveillance, while research on AI “personalities” and worker pushback in China points to emerging risks in decision-making and labor.

What happens when governments rely on systems that sound right instead of being right? Drawing on OpenFisca’s spread from France to governments across Europe, Africa, and Oceania, Beth Simone Noveck’s interview with Matti Schneider makes the case for public infrastructure that computes the law, as well as the risks of sidelining it as generative AI scales globally.