Kevin Werbach speaks with Joshua Tan, CTO of Current AI, about the case for public AI: The idea that AI can and should be public infrastructure, like highways, libraries, or the internet. Tan traces his path from theoretical machine learning at Oxford to starting the reseaerch group Metagov. He explains what work on decentralized and collective organizations can offer AI governance. He also discusses autonomous organizations run by AI agents, the safety questions that arise when agents hold bank accounts and manage human employees, and why incentives shift once these experiments reach real scale.
Tan positions public AI as a third way between closed proprietary AI and open-weight models, which are struggling to keep pace with frontier-scale capital costs. Current AI focuses on everything beyond the model, aiming to build a fully open source stack on top of fully open models, a Linux for AI. He describes this as a Honda Civic strategy: not at the frontier, but close enough, cheaper, and reliable. The conversation also covers the role of government funding, a new Swiss cooperative, a community-owned data center effort in Maine, and what it would take for Europe and other middle powers to compete.
Joshua Tan is CTO at Current AI. He also leads product and strategy for the public AI movement and leads Stanford AO, an incubator and lab for autonomous organizations at Stanford OpenLab. He previously co-founded Metagov, a lab for engineering institutions, completed his PhD and postdoc in computer science at Oxford, and held fellowships at Stanford, Princeton, and MIT. He founded and led DAOstar.
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