Today's guest is Jack Clark. He's the co-founder of Anthropic—the artificial intelligence company behind Claude—and the head of its newly launched Anthropic Institute, a forum designed to think through the philosophical, political, and practical challenges that AI poses to society.

Nick Gillespie talks with Clark, a former tech journalist at Bloomberg and The Register, about his company's ongoing regulatory battles with the Trump administration; whether Anthropic should have held back Mythos, its superpowerful version, from general release; and what might happen if and when AI becomes fully capable of "recursive self-improvement," or the ability to build itself without human input.

They also talk about libertarian and market-based regulatory systems for the internet and tech sector and whether those would yield better outcomes than the ones we've seen so far from the European Union and other conventional governing bodies.

0:00—The promise of artificial intelligence

3:50—Overcoming AI hallucinations and sycophancy

5:08—Military applications of AI

9:38—Anthropic's red lines on mass surveillance and fully automated weapons

14:23—Lessons from the 1990s

16:12—Oversight and regulation of AI technology

23:07—Navigating politics through policy ambiguity

33:31—How does U.S. governance affect global AI policy?

36:42—What is recursive self-improvement?

43:35—How does Clark's literature and journalism background inform his views on AI?

45:43—The liberating aspects of technology

51:15—The effects of AI on employment

Producer: Paul Alexander

Audio Mixer: Ian Keyser

Transcript

This is an AI-generated transcript. Check all quotes against the audio for accuracy.

Nick Gillespie: This is The Reason Interview With Nick Gillespie. My guest today is Jack Clark. He's the co-founder of Anthropic, and he's one of the most influential figures in AI policy. We are going to talk about the government clampdown on Anthropic in particular and various things going on with that. We're gonna talk about the power of AI, the perils, the pitfalls, pretty much the whole ball of wax. So, Jack Clark, thanks for talking to Reason.

Jack Clark: Thanks for having me.

So let's start in a broader sense. Talk about what you see as the main kind of promise of AI. Because we're right now, we are definitely in a kind of technological dark cloud moment, where people are freaking out over AI. And you guys at Anthropic are freaking out on a certain level that we'll talk about. But just broadly, in a general way, what is the biggest, like, what's the biggest selling point of AI?

I'd split it into three different layers: There's stuff for the individual, stuff for what you might think of as the economy, and stuff for science. So, for the individual today, we have a universal teacher, which is something that people fantasized about building for decades and decades, and it just exists. You can go and spend $0 a month to talk to an expert teacher. And if you spend $20 a month, you can talk to, like, a really good teacher. This is incredible. So that's for the individual. For the economy - the economy - especially in the Western world, it is defined by back-office work and bureaucracy, or what David Graeber called, "Bullshit jobs". We now have a system that can deal with, navigate the bureaucracy and back-office stuff, do it better, in some cases get rid of it, and allow people to get back to the parts of the jobs which either use their skills or have more meaning.

Put a specific example on that.

Yeah, I'll give you an example. We worked closely with the makers of Ozempic to help them do work on the backend for how they processed and formatted results in their clinical trials. And we took it down from something on the order of two months of work to a week of work. I don't think anyone misses that. No one there is crying at their desk because they can't do that.

Yeah, I was the best back-office paper shuffler.

Yeah, damn it, that was me. That's what I did. So that and examples like that are found everywhere. There's someone I work with at Anthropic who got so annoyed at processing a certain type of invoice that they just fully automated that. They're not sad about it. Everyone's happy that that's automated. And then for science, we now have systems that, if you read the literature, are co-creating science at the frontier of biology, mathematics, physics, medicine. You are seeing the world's expert scientists co-author papers with Gemini, Claude, ChatGPT. This is a new era for scientific discovery.

Not Grok, right? Nobody serious uses Grok.

I may have seen it somewhere, but there are other names that come to mind as well.

Right. And this is also, you know, one of the examples that gets talked a lot about, which seems amazing, is that when you think of something like X-rays for tumors that might be cancerous or whatever, suddenly the entire world becomes a database, and you have computers training and looking at all of this and just coming up with better diagnostics and prognoses and things like that.

Much better diagnostics, much better prognoses. Also, on an individual level, we've now, you know, replaced WebMD, which always tells you you've got cancer and are going to die, with AI systems, which often tell you something a lot more reasonable, factually accurate, and also say, "Probably call the advice nurse and tell them these things."

What do you do? I'm forgetting the name of the disease that somebody made up that has gone through, like it's in every AI model now, Baxillism or something. But I mean, I guess just quickly before we move on to kind of more policy issues, how does the AI work to filter out kind of bullshit or mass delusion? Because this is always the problem. Right?

So there's a couple of things here. Years ago, AI systems used to hallucinate. They used to make stuff up a lot. And it's basically because we train AI systems to be like a contestant on Jeopardy!. They want to hit the buzzer. The moment you say something, they want to answer. It took a lot of work to say to them, "It's totally reasonable to hit th...