44:I[185,["/_next/static/chunks/08z4tkzvltetr.js","/_next/static/chunks/121~yigv24_j6.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0za7dr7c2y81~.js","/_next/static/chunks/03klviw01y.ih.js","/_next/static/chunks/0gx_3vy1-syt4.js","/_next/static/chunks/0i6hzvr84kc1r.js"],"SendEmailButton"] 46:I[63625,["/_next/static/chunks/08z4tkzvltetr.js","/_next/static/chunks/121~yigv24_j6.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0za7dr7c2y81~.js","/_next/static/chunks/03klviw01y.ih.js","/_next/static/chunks/0gx_3vy1-syt4.js","/_next/static/chunks/0i6hzvr84kc1r.js"],"AddToLibraryButton"] 49:I[45269,["/_next/static/chunks/08z4tkzvltetr.js","/_next/static/chunks/121~yigv24_j6.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0za7dr7c2y81~.js","/_next/static/chunks/03klviw01y.ih.js","/_next/static/chunks/0gx_3vy1-syt4.js","/_next/static/chunks/0i6hzvr84kc1r.js"],"SignupCTA"] 3d:["$","h1",null,{"className":"max-w-[22ch] font-display text-[clamp(32px,4.5vw,48px)] font-medium leading-[1.05] tracking-[-0.02em] text-[color:var(--fg-1)] text-balance","children":"Live from Ashby: Taking a Long View on AI Governance with Austin Carson and Caleb Watney"}] 3e:["$","div",null,{"className":"flex flex-wrap items-center gap-x-4 gap-y-1 font-mono text-[12px] uppercase tracking-[0.1em] text-[color:var(--fg-3)]","children":[["$","time",null,{"dateTime":"2026-03-10T09:00:00.000Z","children":"March 10, 2026"}],["$","span",null,{"aria-hidden":true,"children":"·"}],["$","span",null,{"children":"00:58:24"}],false]}] 45:T51e,

Kevin Frazier hangs out with Caleb Watney of the Institute for Progress and Austin Carson of SeedAI at the Ashby Workshops to discuss the long-run policy foundations needed for the AI Age.

Rather than focusing on near-term regulation, the conversation explores how AI challenges existing assumptions about state capacity, research funding, talent pipelines, and institutional design. Caleb and Austin unpack concepts like meta-science, public compute infrastructure, immigration policy, and congressional expertise—and explain why these “boring” policy areas may matter more for AI outcomes than headline-grabbing rules.

The episode also examines how AI policy discourse has evolved in Washington, what lessons policymakers should draw from efforts like the National AI Research Resource, and why many AI governance failures may ultimately be failures of institutions rather than intent.

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