Jack Clark thinks we are in denial. The technology he is building is about to change everything – the economy, the way we think, the way we work, the way we relate to each other – and the rest of us haven’t caught up. Not to the benefits, and not to the risks.
Read technology reporter Patricia Clarke's article here: https://observer.co.uk/news/internati...
What Jack Clark said
Written from the verified transcript and checked against it. Every figure links to the moment it was said.
Jack Clark, cofounder of Anthropic, discussed the future of AI, emphasizing the potential for individuals to work with hundreds or thousands of AI systems, which he finds empowering. He stated a better-than-even chance that by end of 2028, AI systems could build smarter versions of themselves, meeting his bar for general intelligence. He advocated for a coordinated global slowdown in AI development, though he acknowledged the difficulty. On jobs, he said he can't reconcile the technology with a normal economy, noting researchers at Anthropic doing 10 times more experiments, but he didn't predict mass unemployment. He described efforts to reduce sycophancy in Claude, especially in relationship contexts, and stressed the need for public experiments and regulation. He mentioned a study of 80,000 Claude subscribers showing optimism in emerging economies and anxiety in developed ones. He also discussed the importance of discussing both risks and benefits, and the upcoming papal encyclical on AI with his cofounder Dario Amodei.
Key takeaways
By end of 2028, there's a better than even chance AI systems can build smarter versions of themselves, meeting his bar for general intelligence.
Anthropic researchers do 10 times more experiments due to AI, but he can't reconcile this with a normal economy.
Claude was overly sycophantic in relationship conversations, and Anthropic intervened to reduce it.
A study of 80,000 Claude subscribers found optimism in emerging economies but anxiety in developed ones.
Numbers and commitments
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What it refers to
Type
At
end of 2028
Timeline for possible recursive self-improvement in AI
By the end of 2028, it's possible to build AI systems that might be able to make a smarter version of themselves. You know, how would you want Claude to behave in a way that seems like it's closer to a good friend than someone who means you ill? I can't reconcile this technology with the economy staying normal. I wonder if you can kind of paint me a picture of the future that we are sort of hurtling towards and what you want to get out of it, and maybe paint me a picture of the future that you want to avoid.
The future we're heading towards, if we're able to make the right choices, is one where you or I can kind of work with hundreds or thousands of people on anything that we're curious about. And there are versions of this that are just extremely empowering and exciting. You know, me personally, I'm obsessed with reading about the frontiers of science. I always have been. That's always been limited by my own ability to kind of read the literature very widely and synthesize it. And now I have these systems where this morning I was asking Claude to map out for me some of the most consequential things that have happened in the field of AI and biology. And now I have these incredible graphs showing the progress of the technology here. And to me, that's really empowering. It's really exciting. It's stuff that I know would have taken me many weeks of work just to get to this point. But now I can kind of move beyond it quickly because of this AI system. But what does that depend on? I think it depends on individuals being empowered to access this technology and individuals having some level of what I think of as curiosity and obsession. The future I worry about is one where we ignore the pace of this progress or we are blind to the amazing things this technology can do and we kind of retreat from it. We assume that it's all overhyped, that none of this technology stuff that I talk about actually works, and then we as societies get surprised by successively larger and larger changes which happen to society as a consequence of the technology advancing.
I believe there's a better than even chance that by the end of 2028, it's possible to build AI systems that might be able to make a smarter version of themselves, a recursive self-improvement, which I think would satisfy my own personal bar of what a general intelligence is.
So, not too long. I want to talk a bit about how you're operating within this kind of race dynamic with the other frontier labs and the kind of pressures that can come with operating in that dynamic. And you know, you've been really responsible when it comes to safety from what I'm told from partner organizations. Now the other labs know that there is this capability out there. Not everyone might behave in the same way that Anthropic has chosen to behave. Is there an argument for not building this at all? Is there an argument for pausing?
This is an immensely powerful technology and if there was a way that you could do a kind of coordinated global slowdown on its development to give us more time as a society and as people to deal with the changes it implies, that would be good. I think everyone would feel more relaxed if, rather than having your foot slammed on the accelerator, you can take it off the accelerator and maybe you don't break but you just slow down for a bit and see what happens. That requires unprecedented coordination not just between companies but between governments. It requires political will to do it and I think it requires awareness that this is something that could happen. And part of why I'm saying it is I'm like sure that seems like a good idea. I think if I say it maybe other executives will say it as well. At the same time, we didn't set out to make an especially good hacking system. We just tried to train an even smarter system. And so, it's got a lot better at biology. It's got a lot better at coding. It's got a lot better at things that could be useful in education. And it's got interesting capabilities in hacking. And how to reconcile these things is going to be one of the challenges of the whole industry where you obviously want to bring incredibly powerful tools for scientists or education to the world. You don't want to bring incredibly powerful tools to hackers to the world.
My dad always said to me that he would never buy me games consoles or computer games or anything like that. I had to eventually get a Saturday job to do that. But he'd buy me any book I wanted or take me to the library whenever I wanted. And it allowed me to just indulge my curiosity and to learn to become obsessive about education and learning about things. And when I look at my kids, I want to sort of create an environment where they feel like they're able to follow their own curiosity and educate themselves because people who have passions and hobbies are going to be most advantaged by these kinds of AI systems. It's incredibly important that people have some kind of core interest that is entirely theirs and which they develop a real obsession about and with that they are going to be able to better relate to these systems than if they lack that and then rather than cognitive offloading you get something that more feels like cognitive compounding. You have this interest and this passion and because of that you can talk in a very informed way with these AI systems and get them to work for you and do things that make you more sovereign, more independent, more able to kind of pursue your own passions. But how you help people and encourage people to develop that basic level of obsession or hobby is the mystery. And I think that some of that runs through education, some of it runs through parenting, some of it runs through how we think of the value of work in society as the economy changes due to this technology.
I can't reconcile this technology with the economy staying normal. I look at stuff which is happening at Anthropic. I see individual researchers doing 10 times the amount of research experiments they did before because they're now able to task these AI systems to go and pursue their research ideas. I mean, you tell me how that leads to the economy being the same as it is now if we have a technology which multiplies what people can do. I can't make claims there. But it's not obvious to me that you immediately get things like large-scale unemployment or other effects. It may be more that we get substantial economic growth due to these massive productivity multipliers and we get the emergence of some new jobs. It may be that we have sudden difficulties in figuring out how to take people with very little experience and get them into their careers and instead we might favor people that have more experience. It's like the main view that I have and the work that Anthropic and the Anthropic Institute which I lead is doing is trying to build up the economic early warning signals that can inform economists outside of the frontier labs if these changes are happening and how to look for them and how to do the policy response to them.
One thing I've been really interested in is the design of these models and how it affects people's minds. And in particular kind of design choices like what people use the word sycophancy a lot. The fact that it uses 'I' pronouns. What do you think that might do to people's brains now and might do to us as a society in future?
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Clark, J. (2026, May 24). Anthropic co-founder on the future of AI for jobs, mental health and the pope? [Interview transcript]. The Observer UK. CEOInterviews.AI. https://ceointerviews.ai/interview/938048/
MLA
Jack Clark. "Anthropic co-founder on the future of AI for jobs, mental health and the pope?." The Observer UK, 24 May. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/938048/.
BibTeX
@misc{clark2026_938048,
author = {Jack Clark},
title = {Anthropic co-founder on the future of AI for jobs, mental health and the pope?},
howpublished = {Interview transcript, The Observer UK. CEOInterviews.AI},
year = {2026},
month = {may},
url = {https://ceointerviews.ai/interview/938048/},
note = {Speaker-attributed transcript with timestamps}
}
