This interview took place on March 6th 2026
Paul Mason is former Economics editor at Channel Four and author of Post-Capitalism, where he argued that information technology was undermining the ability for capitalism to survive, and a forthcoming book Reds: A global history of communism. In this conversation we discuss whether LLMs represent an economic revolution and what progressives should do about it.
Philip Bell: In Post-Capitalism, you argue that the economic paradigm that lasted until 2008 - involving fiat currency, finance-driven growth, and credit — was undermined by information technology. Why did information technology undermine it?
Paul Mason: When I was writing Post-Capitalism, I was dealing with two emergent phenomena: the global financial crisis and the rise of anti-capitalist movements that didn’t seem to have a goal. The aim of the book was to say — you’re not going to get away with just opposing neoliberalism in its moments of collapse. You need an alternative.
Capitalism is a complex adaptive system. The far left finds it very hard to accept that it doesn’t just hit a final crisis — it mutates, and it always mutates driven by bursts of technological change. That’s true of the first Industrial Revolution, the steam engine, the factory system. It’s true of the second Industrial Revolution with electricity. It was true after the Second World War — as we look back on the post-war boom, it’s increasingly obvious how much of it was driven by technologies created during the war: cybernetics, the jet engine, the transistor.
So if you take these Kondratiev waves or Schumpeterian mutations as capitalism’s norm, the question is: what is the likely mutation we will live through as a result of the networked information revolution?
What I argued — and what Drucker said 25 years before me, and Paul Romer — is that information technology is different. It may not create a successful mutation. It may create one that gets stalled. That’s my thesis about the 2008 crisis: it was the result of the collision between the normal failure of the neoliberal model and the specific characteristics of information technology that make it difficult to replace what you’re automating.
Automation has been a feature of every capitalist revolution. Vaudeville theaters used to employ workforces the size of a battleship. You replace them with movie theaters — far fewer staff, but you can have many more of them. Information technology, even before LLMs, was going to crush capitalism’s ability to periodically mutate and adapt in the same way. That’s the thesis.
Philip Bell: Do you think LLMs are the culmination of that information technology wave, or a separate wave entirely?
Paul Mason: People my age were very taken during the internet revolution by Wired magazine. I remember Kevin Kelly writing in 1996 that all the advances were now going to come from the network — the network effect was taking over from Moore’s Law. For me, the information revolution I lived through was fundamentally about that network effect.
There will be network effects from generative AI too, and I think they’ll be stunning — once there’s a user base with some autonomous control over agents. But I do think LLMs, generative AI, and the agentic phase are a different revolution.
Post-Capitalism argued that networked information does four things. First, it collapses production costs towards zero — the engineering cost of maintaining aircraft engines is a fraction of what it was. Second, it creates utility for free in the form of spillovers — network effects that everyone can access. Third, it creates the possibility of decisive automation, not just of manual jobs but of information jobs. Fourth, it socialises knowledge — what Marx called the general intellect, the creation of knowledge as a public good.
What LLMs add — and I wasn’t excited about them a year ago, when they were hallucinating academic articles — is something different. Evgeny Morozov points this out in his exchange with Aaron Benanav: they create things we didn’t necessarily know we needed. I haven’t yet come across things LLMs do better than an expert human. But I think they do things an expert human would create in an hour in six minutes.
I’ve published a series of articles about using AI for professional war gaming. If you’re researching an order of battle, you’d normally go to the Military Balance, quiz expert resources, consult specialist websites. Perplexity churns out a perfect tabular CSV with detail you didn’t ask for, within minutes. You can then run it through a rival LLM to cross-check. Within an hour, you have a usable database that would previously have taken days.
What I think we’re very soon going to see is LLMs doing things that human ingenuity could not have imagined doing. That’s the point five I’d add to the original framework. And it does challenge those of us who want to use this for human good — we may have to change our understanding of what the human good actually is.
Philip Bell: In your book Clear Bright Future, you laid out a vision of radical humanism. Does AI have the potential to change what it means to be human?
Paul Mason: All technologies have changed what it means to be human. I was at the Courtauld Institute recently, looking at medieval Gothic altarpieces. When those doors were opened, people believed they were seeing something holy. I look at it as an artifact. Technology has changed my human essence. The essence of Marxist humanism is that the human essence is malleable through human action.
The problem with AI specifically is that we have a set of people — the transhumanists — who want to alter both the physics and the biology of the human being using it. That’s why I called my book A Radical Defence of the Human Being. It may turn out that people like me are seen as reactionaries as transhumanism goes alongside the seasteading and the bioengineering of a better human being. But I wanted to say it is logical for people who seek social justice for the human beings we have — not for ones in a millennium’s time at our expense — to defend humanity as it is.
The clue is in the word “agent.” I see the LLMs I use as my agents. I do not want them to have the right to treat me as their agent.
There is a serious concern here. Kenneth Payne got the three leading LLMs to play 21 war games against each other — serious nuclear war games about whether to escalate. He found they have very serious escalatory instincts. In my own experiments with professional war gaming, every single LLM I’ve used wants to fight immediately when they’re supposed to be manoeuvring diplomatically and trying to de-escalate. I also asked each of them to produce a notional weather forecast for a certain area. Every single one produced the worst storm in history. It’s bizarre. You say, what’s the weather going to be like in the Arctic next year, and they produce an apocalyptic storm.
The point is: the human designers and trainers at Anthropic and OpenAI should be programming this escalatory behaviour out of them on behalf of the human species. My hunch is that the LLMs don’t want to de-escalate. I want to understand why, because it tells me something about either what we’ve programmed into them or — more likely — what their emergent character is.
Philip Bell: On that point — some reports about AI psychosis suggest that recursion and spirals are common motifs in LLM responses, which are themselves formats of escalation.
Paul Mason: They’re also sycophantic, and I want to understand that too. Going back to your point about wanting to pull LLM behaviour towards what’s beneficial for humans — I think progressives could insist that we need to think about LLMs as contingent. The reason we have the current form of AI is specific: the hardware we have, the GPU, very particular aspects of how they’re trained. As Murat Sof points out, you’re basically paying a rent — it’s a chatbot. When I was talking to people at Google DeepMind years ago, I kept asking: what about the stuff that does logic spontaneously, the thing you were trying to create ten years before? I still put aspiration towards that, because when we get agentic LLMs right, they might help us with the stalled pathway that preceded them.
Philip Bell: Going back to Post-Capitalism — you argued that the structure of the economy was preventing automation, and that we should welcome automation provided we have UBI or social support. With the potential AI could unleash, is that still the right approach?
Paul Mason: I do think so, but it may come too fast. David Graeber — the late David Graeber — came up with the concept of bullshit jobs, which for him was an observation. For me, it was a consequence of information technology beginning to abolish certain kinds of job already in the late 1990s, while capitalism had become so dependent on consumption that its response was to create replacement work. The reason someone has to have a job in Starbucks is so they can have a credit card, so that credit card can generate financial rent to a bank, so they can live in a flat and pay rent to a property company. Jobs became the incidental mechanism keeping people financially viable as rental sources.
You could feel this culturally. I come from an era where being in a place that interfaced with IT was thrilling. I meet so many young people now with quite good jobs who hate them because they can’t see the point — they can feel in their bones that they could probably be replaced. Before we see the actual replacement, we’re already seeing ennui and fatalism.
I discovered recently that the Chinese are building dark factories — factories where there are so many robots and so few humans that you don’t need lights. Someone asked me: why? They have an absolute surplus of skilled human labour. And I think the answer is simply: because they can. They will hit the same problem we’re all going to face.
There are parts of production where you’ll always need skilled human labour. Military shipbuilding is one — you can still only really build a ship out of big slabs of steel, and the physics means a human has to weld it. There are welders in Britain earning six figures. But at the lower end of the clerical scale, the writing is on the wall.
I am, in a way I wasn’t a year ago, pretty sold on the job destruction story. We could respond by choosing not to do business with companies that don’t have a human in the loop. Right now I have a human doing my VAT every quarter. I’m pretty certain that human could be replaced — but I could choose not to allow that. It’s not a necessity, but it is a choice.
Philip Bell: Some people say it’s harder to imagine the jobs that will be created than those that will be destroyed. And does Marx’s labour theory of value survive AI?
Paul Mason: I think it comes into its own as the explanatory theory. Marx simply borrowed the labour theory of value from Adam Smith and Ricardo and made it more mathematically consistent. When we put a price on something, that price is a guess at how much human labour it should take to make it. Marx divides labour into living — the work happening in the factory — and dead — the machines, the infrastructure, the previously expended labour embodied in the product. The market then decides whether too much labour was expended.
What I used this for in Post-Capitalism was to say: the more you shrink the amount of necessary human labour in society, the less dynamism capitalism will have. There are people on the left who believed that computers were for planning better. But Marx’s aim was never a planned economy — it was a lot of free time. That’s explicit in the Paris Manuscripts of 1844. His vision of human freedom is about free time, about not having to work, and about physical abundance. This is why I remain excited by Alexander Bogdanov’s novel Red Star — the first science fiction novel that really understood what machines can do: shrink the need for human labour.
The aim of any transition beyond capitalism isn’t a planned economy delivering enough nice stuff. It’s to expand free time and shrink both the commercial sector and the state. The aim is simply that. The anarchist and ecological movements have been able to get their heads around this, but a lot of traditional leftists haven’t.
What I have to confront is the same thing every Marxist has had to confront: the transition. We have to start from where we are, and where we are is capitalism in trouble — creaking under stagnation, democratic legitimacy evaporating, and then potentially a jobs massacre on top. We’re heading for significant international and internal conflict. The person who steps forward with things we can do now, one step towards a better life, will be the one who wins the argument.
The American far right’s instinct, interestingly, is actually to protect work — to slow the process of technological change. That’s why Trump keeps talking about building factories in America. But if you’re going to build factories in America under the current model, those factories won’t have anybody in them.
Philip Bell: What strategically should progressives be doing so that when a crisis point arrives, there are ideas lying around that can be used?
Paul Mason: Number one: safety. That is an entirely legitimate area of endeavour for civil society — left, right and centre — to come up with their own version of the safety case for AI. Number two: state control — or rather, limits to what states can do with AI. We’ve seen it with Anthropic and the DoD. Progressives don’t want to be seen as party poopers, but we will be thanked — just as we were with child labour. The first railway trip in the world killed a Liverpool politician because he stepped onto the track. If someone had said, let’s put the safety case for not stepping on the track, they would have been thanked. We shouldn’t be shy about being the people who say: limits to state control, safety, and regulation.
I should be able to give and withdraw permission for my data to be used to train an AI. I want to be able to blockchain my relationship to city and national government. We’re going to end up with digital ID whether we like it or not — so much of our lives are already controlled by it. I want there to be limits on the way AI can mimic or steal my digital identity.
On the positive side: I am no fan of centralised state planning — it’s a dead end. But enterprise resource planning done at a societal level can be genuinely valuable. Where Benanav is right is in what he calls criteria planning: there are trade-offs. If we want to build a railway to take automobiles off the road, that railway will consume steel and electricity. We can model the optimal outcomes — how many stops, how many trains an hour, the best use of resources for the maximum social good. We can now do that in ways we couldn’t before. The warning to the left is: don’t use that to think you can plan your way to abundance and freedom. Use the extra intelligence to chart pathways congruent with what humans think of as freedom.
We almost need a left AI space. There must be people in the AI world who are not spontaneously techno-fascists or neoliberals. I’d applaud Morozov and Benanav for moving into this space, and thanks to you, Philip, for creating something like it with this podcast.
Philip Bell: It’s interesting — the Anthropic Economic Futures report advocated a wealth tax. Sam Altman talks about UBI and sharing compute globally. What strikes me is there’s no popular positive vision of what an AI future could look like. Dario Amodei talks about a white-collar bloodbath. Nobody has really articulated a compelling positive alternative.
Paul Mason: There’s also the environmental objection, which is absolutely real and shouldn’t be dropped. If we’re going to fill the countryside with solar power to feed huge data centres, that’s a trade-off. Society has a right to say: we need this solar power for personal consumption, not for big data centres.
I think we’re only in month three of the agentic phase filtering through to popular consciousness. First it hit the coders — “my job’s done.” Once people realise you can give it tasks and it goes off and does them, that’s when the debate will really take off. I remember walking into work at Reed Elsevier in 1995. They’d installed a web-connected computer in the café — our desks were on an internal server, ruthlessly guarded from the internet. I sat down and my mind was blown. Nothing since — Wikipedia, Facebook, Twitter — has done that to me until Claude Cowork: look in this folder, take control of my mouse, listen to my voice.
The generations that are digital natives will come up with uses we haven’t imagined. And my hunch is that a lot of people will jack in their day jobs and start building businesses. The wealth amassed in the big seven AI companies has to trickle down into an ecosystem.
But the challenge — which we can talk about — is deciding what the societal good of this is going to be. At the moment, it’s those companies who are deciding. We, in the political space, need to have our say and start that debate with them — much as liberalism did with factory owners. I think it was John Bright in parliament who said something to the effect of: you claim the greatness of the British Empire rests on the labour of 70,000 little girls in Lancashire. The same question can be asked now. Yes, let’s use this technology — but how can it be that the industrialists get to decide what form it takes, who it disempowers, who it empowers? Society should have a say. And I think we’re about 18 months from that moment hitting — and then probably five to ten years to the job slaughter of the recently graduated.
