Economist Tyler Cowen guest-hosted an episode of the New York Times podcast, using the platform for an extended interview with Dwarkesh Patel. In a post announcing the conversation on Marginal REVOLUTION, published on October 16, 2026, Cowen wrote, “Here is the audio, video, and transcript”, directing readers to the full episode hosted on the Times’s website.

Cowen, a professor of economics at George Mason University and longtime co-author of Marginal REVOLUTION, is a frequent commentator on technology and economics. Patel is best known as the host of the Dwarkesh Podcast, where he interviews researchers, founders, and policymakers on artificial intelligence; the Times episode placed him in the guest’s chair instead.

Excerpt: Unreleased Models and What Insiders Know

The published excerpt centered on unreleased A.I. models — systems developed inside major laboratories that never reach the public, whether because releasing them would cost too much or because they are not yet considered safe. The topic opens a window on the question running beneath the whole exchange: how much the public can know about the pace of A.I. progress when the most telling evidence stays inside the labs.

Cowen: “Unreleased models — why are they important?”

Patel: “As in the ones that are internal to the companies?”

Cowen: “Well, many companies have unreleased models. Maybe it would cost too much to release them or they’re not safe yet, but the public doesn’t see them.”

Patel: “Yeah.”

Cowen: “You’re an insider. Whether or not you see them, you hear about them; you know something about them. How should we think about unreleased models, and how does that change our picture of what’s going on?”

Patel: “I think there’s a very frustrating element to the current situation right now, where people inside the A.I. labs claim to have evidence that makes them more worried, and they are not allowed to talk about it. This makes it a very difficult situation on the outside to evaluate how worried we should be.”

Patel then offered a recent private exchange to illustrate the problem. “Maybe two days ago, I was talking to somebody at Anthropic, and they were like: Look, I expect A.I.s to beat humans at A.I. research within nine months,” he said. “And I’m like: Why do you believe that? They’re like: It’s not just vibes, but I have information on the inside.” When Patel pressed further — “What is it? Is it a new model? Is it some evaluation you ran?” — the response, he recounted, was: “I can’t talk about it.”

“I think it’s a terrible state of affairs,” Patel said, adding: “If they really believe this, if they think that we’re in a situation where we’re less than a year away from automating A.I. research and radically speeding it up, they should make this evidence public.”

A Widening Information Gap

Patel also outlined a scenario in which the distance between what laboratories know and what the public knows grows over time. “I especially worry about the following scenario, whereas A.I.s get better and better at making A.I. progress faster and automating it, they will be inclined not to keep releasing models that are even close to their smartest models externally, because then if they release those externally, it would help others make smart models,” he said. “And it’s just kind of a schlep to release models externally. You need all these safeguards and everything.”

Cowen drew out the consequence for outsiders: “So the gap between what they know and what we know would get bigger and bigger under that scenario. We’d end up more in the dark, more surprised when things happen. It would be harder for regulators, policymakers, members of Congress, everyone.” In that framing, the choices labs make about which models to release — weighed against cost, safety, and the safeguards Patel described — shape how much regulators, policymakers, and the public can actually see.

Alongside the exchange on unreleased models, Cowen pointed readers to the pair’s “discussion of AI psychosis, among other topics” covered in the episode. He closed his announcement by writing, “Kudos to Dwarkesh for taking the other side of the microphone.”n
This article is based on the original post, I guest host the NYT podcast and interview Dwarkesh, on Marginal REVOLUTION.