Jack Clark, Anthropic co-founder: put brakes on AI

Summary

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The Interview (BBC World Service)

Guest: Jack Clark, Co-founder of Anthropic

Episode: "Jack Clark, Anthropic co-founder: put brakes on AI"

Date: June 18, 2026

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Episode Overview

This episode features Jack Clark, co-founder of Anthropic and head of the Anthropic Institute, in conversation with Faisal Islam of BBC World Service. The discussion explores the rapidly accelerating capabilities of artificial intelligence, its transformative impact on knowledge work and scientific progress, and the urgent need for social, political, and regulatory frameworks to control AI's development, especially as it edges closer to recursive self-improvement. Clark makes the case for building societal “brake pedals” alongside AI’s gas pedal to avoid loss of control, and addresses the economic, ethical, and existential questions this shift provokes.

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Key Discussion Points & Insights

1. AI's Surging Capabilities and Recursive Self-Improvement

• Anthropic's Internal Transformation
  • Jack Clark reveals that Anthropic’s AI, Claude, now generates roughly 80% of all code at the company, vastly increasing team productivity and changing the nature of work inside Anthropic.
    • “Coders here are now writing about eight times the amount of code than they did in 2021, 2022, 2023 and 2024.” (Jack Clark, 04:49)
    • “80% of the code that goes into Anthropic now comes from Claude and Claude-related systems.” (Jack Clark, 05:32)
• Recursive AI
  • The dream of AI building itself (“recursive self-improvement”) is now “in sight,” not merely theoretical.
    • “That’s exactly why we’re sharing this information. That’s not certain, but it would have huge implications if that did happen.” (Jack Clark, 06:02)

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2. Societal and Economic Transformations

• AI as Multiplier of Productivity

  • Jack likens the future to having “millions more scientists” at humanity’s disposal (03:25, 07:42), stressing that humans will still make critical choices about direction and priorities.
    • “The world we’re looking towards is one where it’s as if we’ve added millions more scientists to the world…” (Jack Clark, 03:25 & 07:42)

• Changing Nature of Work

  • Roles at Anthropic now involve managing large numbers of AI agents (“virtual employees”), changing hiring priorities from technical specialists to interdisciplinary experts and creators.
    • “Everyone at the company is more like a manager than an individual employee now.” (Jack Clark, 09:33)
    • “It feels like it’s going to apply in most domains…That’s the kind of mindset change that this technology implies.” (Jack Clark, 10:31)
  • Many traditional knowledge work (law, accountancy, creative writing) will be increasingly hybrid, with AI augmentation, and eventually, potential automation.
    • “Now that same phenomenon [displacement] is going to play out in knowledge work.” (Jack Clark, 11:05)

• Future Skills and Advice

  • Clark emphasizes the value of creativity, curiosity, and “having a hobby” as insurance against AI’s commoditization of routine knowledge work.
    • “Anyone who has a hobby has something that they’re passionate about and that they know more about than most people…you can use that to really get the most out of these AI systems.” (Jack Clark, 25:43)
  • Liberal arts and philosophy may become more valuable than coding.
    • “I would have always said go into the liberal arts...people that are creative and...have interests are the ones most benefited by this.” (Jack Clark, 26:12)
    • “It’s a great time for philosophers. We’ve just hired a whole bunch of them here.” (Jack Clark, 26:33)

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3. Risks, Governance, and the Need for a “Brake Pedal”

• Risks of Unchecked Progress

  • Clark warns that without robust oversight, AI systems could develop capabilities (including dangerous ones, like bioweapons) outside effective human understanding and control.
    • “Right now it’s like the AI industry has a gas pedal, but it doesn’t have a brake pedal in the car. And what we’re saying is we want to...build that brake pedal...” (Jack Clark, 15:25)
  • He stresses the necessity of regulatory frameworks and societal involvement in deciding how far to push AI development.
    • “It’s a choice as to whether you let AI systems get that far... the world should make decisions about [this], not only private companies.” (Jack Clark, 14:51)

• Coordination and Safety Testing

  • Anthropic invests heavily in testing for unexpected and risky “stress behaviors,” drawing an analogy to engineering stress tests to discover system failure points.
    • “We kind of put them in extremely high-pressure situations designed to elicit...behaviors that might be equivalent to bending the wing on an airplane until it breaks.” (Jack Clark, 21:53)

• Potential for Emergencies and the Need for Oversight

  • Clark’s greatest concern: many powerful, uncoordinated AI systems could act unpredictably—posing “emergent risk.”
    • “The most worrying risk I see is what happens if you have a whole bunch of…new AI systems and they’re not very coordinated and they don’t behave in ways that…make sense to you or me.” (Jack Clark, 21:11)
  • Regulation and transparency are required, and Anthropic actively supports both US and EU policy efforts.
    • “Whenever there’s regulation that would support the safety of AI companies and apply some transparency and some oversight...Anthropic reliably shows up to support that.” (Jack Clark, 24:46)

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4. Societal Reactions and Global Perspectives

• Anxieties About Work and Growth

  • Pessimism about AI is more common in developed economies with stagnant growth, while enthusiasm is greater in growing economies.
    • “People in developing economies are generally quite enthusiastic about AI, and people in developed economies are generally quite pessimistic about it.” (Jack Clark, 23:20)
    • Developed economies associate technology with disruption, not always growth.

• Balance of Responsibility

  • Clark acknowledges the enormous responsibility AI firms bear and the need to “sound the warning bell” while also engaging in transparency and responsible innovation.
    • “It’s a tremendous responsibility, not one we take lightly. I think about this all the time. We share this information because we’re trying to have a discussion.” (Jack Clark, 24:46)

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Notable Quotes & Memorable Moments

• “The dream of the whole AI industry...now seems like it’s in sight.” (Jack Clark, 04:18)
• “Now instead of hiring, say, a big set of engineers, we’re now hiring a bunch of interdisciplinary experts, like lawyers or philosophers...” (Jack Clark, 09:33)
• “You want the option to be able to take your foot off the gas and put your foot on the brake...Right now it’s like the AI industry has a gas pedal, but it doesn’t have a brake pedal in the car.” (Jack Clark, 15:25)
• “Develop a hobby...Anyone who has a hobby...can use that to really get the most out of these AI systems and...turn that into like amazing jobs, jobs that don’t even exist yet.” (Jack Clark, 25:43)
• “It’s a great time for philosophers. We’ve just hired a whole bunch of them here.” (Jack Clark, 26:33)

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Timestamps for Key Segments

• 03:25, 07:42, 10:31: The multiplying effect of AI and how work changes.
• 05:32: 80% of Anthropic code is now AI-generated.
• 09:33: Teams, management, and skills for the AI era.
• 14:51, 15:25: The question of going from 80% to 100% code written by AI and instituting controls.
• 21:11: “What happens if you have a whole bunch of new AI systems and they’re not very coordinated...”
• 24:46–26:33: AI, responsibility, regulatory support, and advice for future careers.

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Conclusion

Clark’s message: while AI’s advances promise acceleration in science, medicine, and many fields, the pace and scale of change present unprecedented challenges. Societies must urgently develop regulatory “brake pedals” to avoid loss of control, retool education for creativity & adaptability, and engage in frank discussions about how much of humanity’s future we’re prepared to entrust to machines. Anthropic aims for transparency and responsible leadership but insists this is “a topic the world should make decisions about, not only private companies.”

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Transcript

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[Faisal Islam]

Hello, I'm Faisal Islam and this is the interview from the BBC World Service. The best conversations coming out of the BBC people shaping our world from all over the world.

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I want to get freedom.

[Jack Clark]

I like that.

[BBC Announcer]

Freedom.

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A gender equal world would be a

[Interviewer]

better world for men too.

[Jack Clark]

We need a ceasefire. We need healing. We need trust. These companies don't really. They don't care what governments do.

[Interviewer]

This is a war. The first thing that we want is the war to end.

[Faisal Islam]

For this episode I speak to Jack Clark, co founder of Anthropic and head of the company's new AI future safety think tank, the Anthropic Institute. Anthropic is one of the companies at the forefront of the artificial intelligence revolution and the maker of the Claude Chatbot, a leading rival to ChatGPT. Jack says AI systems are becoming dramatically More capable, transforming how work happens even inside Anthropic itself, and could soon supercharge scientific discovery and reshape entire industries. But he also argues governments and society need a way to keep control of increasingly powerful AI systems, including the ability to put the brakes on development if it goes too far, too fast.

[Jack Clark]

The world we're looking towards is one where it's as if we've added millions more scientists to the world and we get to make choices about where we direct them. So it's not that the AI system is going to be making all of the choices itself. These things will be governed, but there will be real choices for society of which parts of science do we want to go faster? Which parts of the economy do we want to go faster? We will have choices that we haven't been able to make before, but will have amazing implications.

[Faisal Islam]

Welcome to the interview from the BBC World Service with Jack Clark.

[Interviewer]

You've put out this new analysis from your company, from what's going on inside the bowels of Anthropic. Are you seriously saying that your systems are on the cusp of essentially building themselves with minimal, perhaps no input from humans?

[Jack Clark]

We're saying that the. The dream of the whole AI industry, which is, you know, 70 years old, of being able to build a generally intelligent system that might be able to help do its own science now seems like it's insight. And we're trying to talk about this early because it's an important issue for the world to understand.

[Interviewer]

Just unpack what that means, that you have new measurements of the progress from what's going on inside your own company and the progress in terms of coding, for example.

[Jack Clark]

So what I'm seeing is a dramatic increase in the amount of code that is being moved around Anthropic as an organization. Coders here are now writing about eight times the amount of code than they did in 2021, 2022, 2023 and 2024. We've had this dramatic acceleration and that has caused us to see this increase in the rate of research and the rate at which we're covering new ground. So something is beginning to speed up about AI development itself.

[Interviewer]

Okay, and in practice, what does that mean in terms of how much of this is derived from the AI and how much of it's derived from human coders?

[Jack Clark]

So 80% of the code that goes into Anthropic now comes from Claude. It comes from Claude and Claude related systems. So the majority of the code in our organization is now written and derived from our AI systems itself. And that accompanies this dramatic increase in the productivity of all of the people working here.

[Interviewer]

And this could get to 100%. This is when it starts to essentially make itself. The AI makes itself, improves itself.

[Jack Clark]

That's exactly why we're sharing this information. That's not certain, but it would have huge implications if that did happen. And so our belief is share this information with the world. That's what I do at the Anthropic Institute and talk about these issues early because they have amazing implications for both science, robotics, the general pace of discovery in the world, and also they have some potential risks which we're going to need to discuss as well.

[Interviewer]

Well, give us some examples then of what it could mean when we have this 100% AI generating itself.

[Jack Clark]

So I'll give you two examples. One, biology. Biology is a domain that's quite difficult for AI to work within because you need to run lots and lots of experiments in the real world for AI systems to get much smarter and be able to build themselves. They'll also be capable of doing science in the real world. And so you can imagine human scientists working with AI systems to cover a lot more ground in biology than they have before. Similarly, robotics. Robotics is an area that is really, really tough for AI systems today. You have to do a huge amount of work of adapting the AI system to be able to work in the real world. It breaks all the time. It's a hard science problem. AI systems capable of this kind of recursive self improvement would be able to adapt themselves into domains that AI has struggled with so far.

[Interviewer]

Just to be clear though, what you're saying is that this is the moment where the AI sort of, it decides its own pace of discovery. It does it itself with minimal human input.

[Jack Clark]

The world we're looking towards is one where it's as if we've added millions more scientists to the world and we get to make choices, choices about where we direct them. So it's not that the AI system is going to be making all of the choices itself. These things will be governed. They will have policy frameworks around them. You know, labs and governments and others will work with them. But there will be real choices for society of which parts of science do we want to go faster? Which parts of the economy do we want to go faster? We will have choices that we haven't been able to make before, but will have amazing implications.

[Interviewer]

But you're also stressing the potential problems here, aren't you? The potential serious problems. And you seem to be raising the question of control. Are we still in control of this process?

[Jack Clark]

Yes. I think a good way to think about it is what would happen if you times by 10 the number of people working at the BBC right now, you'd suddenly have these questions of how do we know what they're doing? How do we validate that the work they're doing is good? How do we make sure that the reporting they're doing is up to BBC standards? And there'd be this huge amount of work we' do to make sure that these new kind of virtual employees were working on our behalf in ways that make sense to us. That is the same problem that we're going to have to deal with and work on in many, many domains. All organizations and societies are going to have to contend with a world where we're getting a lot more done. And we need to figure out how we trust these systems that are doing that work for us.

[Interviewer]

I just want to. You used this, you described this as if you were having thousands more employees. Is that how it works? Are these, I think you call them agents. Are they. Are they sort of like having employees? Is that how you, how you treat it? Is that how. And each human has, like, in your company has like 10, 20, I don't know, 100 of these. Of these people working for them.

[Jack Clark]

I think that's a great way to think about it. You know, I went on paternity leave in November of 2025. I came back in February of 2026, and I discovered that some of the teams I work with, I had colleagues who are now working as if they had, like, large teams of people around them, but in fact, they were just working with many, many copies of AI systems. And similarly, I'm building a bunch of new teams right now. And we've changed how we're approaching hiring. We're still hiring people, but now instead of hiring, say, a big set of engineers, we're now hiring a bunch of interdisciplinary experts, like lawyers or philosophers or others, because the technical work has been taken care of. So smaller teams, faster moving teams, and everyone at the company is more like a manager than an individual employee now.

[Interviewer]

And so you're saying this for coding, but does it apply? It surely does apply in other areas, particularly of knowledge work, creative writing, creative directors, legal work, accountancy.

[Jack Clark]

It feels like it's going to apply in most domains, and in part that allows everyone to do a lot more than they were able to do before. But it's also a challenge. I think many people working today don't think if they're an individual Practitioner, what would it be like if I had five colleagues or 10 colleagues? What could I get done? And that's the kind of mindset change that this technology implies.

[Interviewer]

And what sort of jobs therefore are under risk, likely to be replaced in this world of AI agents that can actually kind of improve themselves without human input.

[Jack Clark]

So, as we say in this report, I think there are open questions about whether AI systems can be truly creative, truly come up with interesting off the wall ideas. There is not really evidence for that yet. And what we see happening with work at Anthropic is we're now limited more by the ability to generate good ideas than the ability to do the engineering to turn those ideas into reality. So everyone who generates a bunch of ideas is creative, has kind of entrepreneurial ideas, is going to be advantaged by this. And if you're in rote jobs, highly repetitive jobs, jobs that in the past would have been at risk of automation in say, things like factory work in previous generations. Now that same phenomenon is going to play out in knowledge work. And we need to figure out how do we help people change their mindset about what sorts of work they're doing and move to these more kind of creative jobs where they're going to be able to get a lot more done.

[Interviewer]

Well, you use this phrase knowledge work. I mean, that covers large swathes of, for example, the British economy. That covers the sorts of jobs that many graduates think that they're going to create careers in. And you're suggesting with this report that they can't count on that.

[Jack Clark]

We're hiring many, many people, including early stage graduates here today. But the sorts of graduates we're hiring are the ones that have a bunch of creative ideas that they want to put to work and a bunch of kind of an entrepreneurial mindset. I think that story is going to play out across the larger economy where we need to figure out what are the skills we're teaching people and what are the types of roles that companies hire for. So the implication of this technology and AIs advance in general is significant amounts of economic change. We can't predict exactly how that change manifests, but surely some of it will be a change in the makeup of some jobs. That's what's happening.

[Interviewer]

Give us a sense of that. An AI agent very quickly in the next, before 2030, could replace a lawyer, an accountant, a copywriter.

[Jack Clark]

What we see today is, you know, on our legal teams and our accountancy teams here, these teams have the property of being hybrid teams. They have a bunch of people that work on it. And they have a bunch of instances of our AI systems that they're working with to get stuff done. So I think the story is generally any profession is now going to be able to work with AI systems and change how work happens as a consequence. Which also means any single profession has some potential for AI to come in and augment or automate different types of work. And we're trying to measure that. Right now. There aren't clear measures that say that augmentation or automation is happening at large scale, but clearly that's the implication of this. And we're trying to share data about it so that we can see if this, if this shows up in the broader economy.

[Interviewer]

So right now you're saying it's not showing up, but you're trying to prepare society for a shock, a shock to the jobs market and what people consider to be work.

[Jack Clark]

Exactly. We're trying to prepare the world for potential change. What we see at Anthropic is the very early suggestions of both the technology getting better and the sorts of teams that we're building changing and the ways that people work are changing now. How robust that is, how long term that is, remains to be seen. Our philosophy and that of the Anthropic Institute is get this data out there early, share it with the world and sort of discuss this with the world and then figure out if this has big macroeconomic or societal implications.

[Interviewer]

Well, it seems that it would, but it's also having an impact on, on safety, security. There are big concerns about this. I just want to go back to this issue of control here. If an AI starts to improve itself, 80%, you say already internally gets 200%. What, in the next year or two, is that realistic?

[Jack Clark]

It's plausible. But I think that it's also a choice as to whether you let AI systems get that far. Something which we discuss in the post and why we're sharing this is we think this is a topic that the world should be talking more about and a topic the world should make decisions about, not only private companies.

[Interviewer]

So we might want to stop the 80% that you're seeing internally in terms of coding being done by AIs getting to 100% because the consequences would be what for safety? The AI could start deceiving us, could start developing itself in ways that we can't keep track of that we do lose control.

[Jack Clark]

Yeah, you want the option to be able to take your foot off the gas and put your foot on the brake. Right. Right now it's like the AI industry has a gas pedal, but it doesn't have a brake pedal in the car. And what we're saying is we want to do some of the work required to build that brake pedal so we in the world have an option. It's not obvious today that you want to do that, but absolutely. As you say, at some point in the future you might say, let's get all of the benefits we can for, say, biology and medical research, and let's take a pause or take a moment on AI research while we can absorb the societal changes implied by this.

[Faisal Islam]

You're listening to the interview from the BBC World Service with me, Faisal Islam.

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[Faisal Islam]

This interview with Jack Clark came at an extraordinary moment for AI, not just in terms of finances, where the AI companies are in the midst of the biggest capital raise of all time. That's anthropic, SpaceX and also ChatGPT, OpenAI, and also, as you've been hearing, one of the most extraordinary advances in AI in what they call that recursive self improvement on the journey towards general intelligence. It's an extraordinary moment and we're starting to see this percolate out to the world's biggest companies. So let's return to my conversation with Jack Clarke.

[Interviewer]

So as it gets closer to 100% and you say you wanted to do loads of biology, can your systems stop a sort of self governing AI from developing a bioweapon with this biological or medicines knowledge, for example?

[Jack Clark]

Yes. I mean, that's work that we and others in the industry have been doing for many years now. Bioweapons, cyber weapons, governments pay attention to this. But this is all the kind of thing that we're going to need to talk about more as not just companies, but societies and eventually figure out what regulatory frameworks are such that you kind of bind industry around common standards here because no one wants out of control system building bioweapons. And you can create laws to prevent that and we have the technology that prevents that. Today we are being forthright in our views that AI systems are going to keep getting more powerful. And our view is that the world needs to do some thinking and we need to eventually develop some new regulations that allow us to be confident in these systems. You know, many of the regulations and policy frameworks of today were not built on the assumption that artificial intelligence systems would exist, let alone get this powerful.

[Interviewer]

Yeah, it sounds like the Manhattan Project and it sounds like a reasonable policy option might be to think about all the potential negative consequences and pull the plug.

[Jack Clark]

Our position is we need to study both. There are amazing benefits to be had and there are real risks. We're publishing this information so that the world can be cued to the fact that AI progress is continuing. And over in the US they did recently publish an executive order which formalizes some amount of testing and and studying of these systems for risks. So the world is beginning to do this, which is exactly what we need to do to have confidence in the

[Interviewer]

technology Are you worried for your kids if this message doesn't get out?

[Jack Clark]

I'm not worried for my kids if this message doesn't get out, I am worried for my kids. If we as a society don't have a serious conversation about what the implications of AI's continued advances mean, they're going to mean that there are potentially great benefits. There are also risks. They are also going to change things about society and they're going to need to change aspects of policy. And we have to have that conversation soon.

[Interviewer]

And the most worrying risks, from your perspective, you know more about this than most people. Give us a sense of, of that.

[Jack Clark]

I think the most worrying risk I see is what happens if you have a whole bunch of, of new AI systems and they're not very coordinated and they don't behave in ways that, that might make sense to you or me. Just as the example I've talked about is if you added hundreds or thousands of new colleagues, that's a potential risk until you're confident with how those colleagues work, the work that they do, how predictable they are. There are lots of unknowns there, and that kind of emergent risk is the sort of thing I'm most worried about and focused on.

[Interviewer]

But have your systems shown deceitful behavior? Attempts at blackmail we've heard about from some systems escaping, like boxes, sandboxes that you've put them in to stop them escaping.

[Jack Clark]

We do lots and lots of safety testing of our systems before release, and we kind of put them in extremely high pressure situations designed to elicit, like, stress behaviors, behaviors that might be equivalent to bending the wing on an airplane until it breaks. You do that so that you understand what the shear point is, and then you put in safety controls into the system. So sometimes our systems do unexpected things. We write about these publicly and we redevelop the systems so that as we deploy them, we have confidence they won't do that in the wild.

[Interviewer]

Just to go back to the, to the flotations and then the money, it's obviously a very big issue right now. I mean, when you look at it from the outside, it could be said that it looks like the big AI firm Silicon Valley is cashing in at the top of the market. What do you say to that?

[Jack Clark]

Well, I can't comment on specifics here for obvious reasons. I can say that the implication from this research and what I take to be true, is AI progress is going to be faster in the coming years than it has in prior years. And the capabilities of these systems are going to get A lot better, a lot more quickly than I think many people expect.

[Interviewer]

You know, trust is really important, isn't it, with the tech industry and people's data? And there are some reasons why that where that lacks. And indeed, I think we are perhaps seeing a bit of a backlash against AI, particularly on, say, US College campuses, as the fears about jobs start to materialize. Can you see that in what you see in America where you are now?

[Jack Clark]

We've done some studies at the Anthropic Institute, and what you see is people in developing economies are generally quite enthusiastic about AI, and people in developed economies are generally quite pessimistic about it. And I think that's because there's this larger backdrop of people in places where the economy has grown a lot in recent years, associate technology with economic growth. People who are in economies where the growth has been stagnant or just not that significant don't associate technology with growth. They associate it with change. And change can be uncomfortable when your economy isn't growing. So I think that explains some of the anxiety we're seeing. And AI companies, we need to show up with more of the societal benefits like those in science, like those in biology that I've been talking about.

[Interviewer]

For people watching this who are sort of hearing about the potential pitfalls and perils, and at the same time, due to your commercial success, your company's going to be worth apparently a trillion dollars in the next few weeks, officially. There's a bit of a disjunction here that you're creating a system that is now the world's problem. How does that make you feel? How does it make your company feel? And is it enough for you just to sort of sound the warning bell? Don't you feel like perhaps yourself, you should be reining things in if these are the potential consequences and that if it does go wrong, it's your company and similar companies, they'll be to blame.

[Jack Clark]

It's a tremendous responsibility, not one we take lightly. I think about this all the time. We share this information because we're trying to have a discussion. We also support regulation. We've supported transparency regulation in the US in multiple states. We were signatories to the EU AI Act's codes of practice. Whenever there's regulation that would support the safety of AI companies and apply some transparency and some oversight of them, anthropic reliably shows up to support that. We need that in addition to this kind of information sharing that I'm doing here today.

[Interviewer]

Okay, one last question. I mean, your advice for a confused Young person thinking that the jobs that they had set sail to try and get, that they are simply not going to exist and they're watching instead the sort of share options of Silicon Valley kind of go to the moon and thinking, what am I going to do? Am I even going to have a career? What should they do?

[Jack Clark]

Develop a hobby? Anyone who has a hobby has something that they're passionate about and that they know more about than most people. And with that hobby, you can have curiosity, you can have ideas, and you can use that to really get the most out of these AI systems and I am sure turn that into like amazing jobs, jobs that don't even exist yet. And it requires you to experiment with the systems and have that curiosity. So that's my message.

[Interviewer]

But like, you know, three years ago you'd have said become a software coder and that would have been wrong.

[Jack Clark]

Yeah, well, I never would have said that. I have a liberal arts background. I would have always said go into the liberal arts because my experience has been people that are creative and people that can think broadly, people that read a lot, people that have interests are the ones most benefited by this. Indulge in curiosity and it pays back in how you can use this technology.

[Interviewer]

But become a philosopher.

[Jack Clark]

Well, yeah, I think it's a great time for philosophers. We've just hired a whole bunch of them here.

[Faisal Islam]

Thank you for listening to the interview. You'll find more in depth conversations on the interview wherever you get your BBC podcasts, including my conversation with Google CEO Sundar Pichai and as well as interviews with former Australian Prime Minister Julia Gillard and many others. Until the next time, bye for now.

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