Can Europe Catch Up on AI? with Carl Frey

Geoff Mulgan has been a key figure in UK innovation for a number of decades. He Chief Executive of Nesta from 2011 to 2019, worked as advisor to Tony Blair and currently professor at UCL and founder of The Institutional Architecture Lab. We discussed his recent article ‘An ARIA for social issues’ where he argues we need a mission-drivem research body aimed at solving the most difficult social problems in society. Philip Bell: Geoff, you’re the founder of Nesta, a former advisor to the UK government, and currently working on institutional innovation in cities. The main reason I wanted to talk to you was your article, “ARIA for Social Issues.” Why don’t we have an ARIA for social issues today? Geoff Mulgan: For probably 80 years there’s been a striking imbalance between science, technology, and innovation on one hand, and social discovery and innovation on the other. After the Second World War, the US under Vannevar Bush created the modern approach to science, massively increasing public funding for R&D. It became assumed that breakthrough discoveries were primarily about physical stuff — aeroplanes, computers, new materials. Today most developed countries spend three, four, maybe five percent of GDP on that kind of research. The social sciences used to do a lot of discovery and exploration. The great 19th century social scientists all combined analysis with prescription. The same was true of people like Keynes in the 20th century. But in the last few decades, social science has increasingly moved towards analysis of the present or past — diagnosis and critique rather than prescription, rather than proposing options for the future. As a result, we’ve had an ever-greater gap between extraordinary technological dynamism and social stagnation, which you can see in phenomena from mental health to trusted institutions to social cohesion. We need more deliberate, systematic funding for exploration, discovery, and imagination focused on the social problems that people say matter most in their lives. Philip Bell: Why do you think social science has become more diagnostic and less prescriptive over time? Geoff Mulgan: There are both good and bad reasons. One quite healthy reason is much more attention to data and empirical facts — computational social science has become a much more exciting field. But anything focused on evidence and data has to be about the present and the past. That should be allied with equally energetic work on design, experiment, and imagination. For various reasons across all the social sciences, there’s been a retreat from that. It’s thought to be too risky. It hasn’t been rewarded in terms of journals, publications, and career progression. And the funding from governments and research bodies hasn’t supported it at all. In the UK, there’s literally no funding support for social exploration. To the extent there is any, it comes from the Arts and Humanities Research Council, not from the Economic and Social Research Council, which overwhelmingly focuses on analysis and diagnosis. That leaves us with a weird deficit of good options, which shows up in every era of politics. Philip Bell: You’ve argued there isn’t a general failure of imagination — it’s more specifically located within particular domains. Science and technology seem to have more leeway to imagine than the social sciences. Is that fair? Geoff Mulgan: There is genuine evidence that novelty is becoming harder in many areas of science — it takes longer, bigger teams, more money. But I’m always cautious of generalisations that say we’ve already used up all the good ideas, because that claim has been made repeatedly over the last 200 years and nearly always shown to be wrong. Many fields are moving incredibly dynamically right now — the combination of AI, chemistry, genomics, and physics is leading to lots of breakthroughs. The Fredric Jameson quote — that it’s easier to imagine the end of the world than the end of capitalism — is really interesting here. Aft

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

David Edgerton is Professor of History at Kings College London. His book Shock of the Old challenged the way we think about innovation, arguing that we systematically overvalue the new and ignore the old (including maintenance). He has also written importantly on the British ‘warfare state’ and his book The Rise and Fall of the British Nation argues Britain became a fundamentally national economy from 1940-1985. In this conversation we discussed the uses of history in understanding AI and society, why the word ‘technology’ might mislead more than clarify and what a detailed material understanding of our world might look like. Philip Bell: David, you are a professor of history at King’s, and I think I’m right in saying you founded the Centre for the History of Science, Technology and Medicine at Imperial College London. In the foreword to Jean-Baptiste Fressoz’s new book, More and More and More, he describes it as coming out of the intellectual environment at Imperial, because I think he was a researcher there as well. It’s an absolute pleasure to have you on the podcast. Thank you for joining. David Edgerton: My pleasure. Philip Bell: The genesis of this conversation was the use of history and historical analogy in understanding what might inadequately be called technology. One thing I’ve found quite interesting about AI is that there seems to be a geopolitical divide in how it’s considered in historical context. The US, and the West generally, tends to compare AI to the atom bomb or the Manhattan Project — an existential threat to be contained. Whereas Chinese companies and policymakers, if you look at the “AI Plus” strategy in China, tend to compare AI to electricity — more of a utility to be diffused. Do you think analogies are helpful in understanding technologies or technical change, or do historical analogies trap us into particular responses? David Edgerton: Clearly some analogies will be helpful and others won’t be. What’s interesting about analogies in this strange area — discussion of technology, where we don’t really know what it is — is that they are often very predictable. Comparing AI with the atomic bomb is just a replica of comparing the Human Genome Project with the Manhattan Project. Desperately unoriginal comparisons. Comparing things with electricity is a bit richer and not quite so common. Suggesting that artificial intelligence will cause an industrial revolution just like the Industrial Revolution of the eighteenth century — that’s a very, very common argument. Not a very helpful one. So we need to beware the analogies. We need to wise up to the small range of analogies that are in play, and to understand why they’re being used and what they’re being used for. Philip Bell: That’s an interesting point about the predictability of the analogies. I’ve looked up a list of different analogies that have been used with regard to AI. Sundar Pichai, the CEO of Google, described AI as “more profound than electricity or fire.” Yann LeCun, until recently head of AI at Meta, said the invention of the printing press is the closest historical parallel to AI. Alex Karp, CEO of Palantir, compared AI to the Manhattan Project. It’s interesting because technologists seem very interested in talking about history. It reminds me of the famous Keynes quote: “Practical men who believe themselves to be quite exempt from any intellectual influences are usually the slaves of some defunct economist.” How would a technologist go about getting a better historical framing? David Edgerton: Well, you say technologists — who are these people? They’re not necessarily technologists. They are figures associated with great enterprises. I think that’s an important distinction to make. Yes, there’s a nice little list of comparisons. It’s always the big ones, isn’t it? They could have said agriculture. They could have said the Neolithic Revolution, but that wouldn’t sound quite right, I guess. They are looking for big ones. And that’s all they’re

The rhythm of social media is frenetic. But what if AI can give us more choice about the speed at which we live our lives? In his article ‘Time Machines’ Nicklas Berild Lundblad outlines the thesis that AI has the potential to be a ‘temporal mediator’, enabling a decoupling of computational and biological time. Nicklas is a writer, investor, and formerly Head of Global Policy and Public Affairs at DeepMind. Philip Bell: You’re an investor, advisor, writer and researcher working across a number of different think tanks and writing a blog which I’m a big fan of—which is why I asked you to come on today. I previously worked at DeepMind on policy, so I loved your article “Time Machines” and it was really thought-provoking. It really made me consider some of the possibilities of how an AI-influenced world might sort of play out. So that’s why I was really keen to talk to you. My first question would be: how will AI influence our experience of time? NBL: The article has this fundamental idea that there are two kinds of time. There’s biological time and computational time. Everything that we’ve done as human beings—our relationships, our institutions, our society, our economies—they all evolved to run in biological time, in our time. Biological time is evolutionary time. It’s the kind of time of seasons. It has this particular pace. But as we developed computers and machines, we were able to create this other pace layer—to use a term from the literature—this computational time that’s much, much faster. We can now do calculations at a speed that no human being could do. We could play a million chess games in a very short time. So we have developed this computational layer of time, and there’s a tension between the two. Many of the institutions that we have developed are not necessarily built to run in computational time. Markets, for example, for a long time struggled with figuring out how to deal with high-frequency trading. My idea in the article is essentially this: maybe we can use artificial intelligence as this mediator that understands biological time because it can communicate with us, but also can operate in computational time. So it can help us prioritize across the many different things that happen in computational time and give us an effective interface. Artificial intelligence becomes a temporal interface between these two different pace layers. That’s the basic idea of the article. Not revolutionary in any sense, but I think it addresses this notion that we have of everything accelerating, everything speeding up, and at the same time, we have this upper limit beyond which we cannot speed up. We have 24 hours a day of attention and that’s it. That’s what we can spend. Philip Bell: One of the really interesting ideas in the article was you put it that perhaps most significantly this bifurcation will enable individualized relationships with time itself. That made me think: if people are able to have individualized relationships with time, that might influence identities themselves. Many scholars have talked about how the experience of time has helped form identities. For example, Benedict Anderson in his famous book about the origins of nationalism describes people reading a newspaper across different parts of—let’s say Germany—for the first time in the late 19th century, which created a kind of simultaneous feeling that you’re inhabiting the same time because everyone would read the newspaper at the same time in the morning. He described this as “national time.” Could this new capability—if people are able to have their own individualized relationship with time—influence identities? Do you think that could allow small communities to have their own identities based around time? How do you see that influencing culture and identity? NBL: That’s a great question. The way to think about this is to think about the way that we constitute our “now.” Essentially what Benedict Anderson is talking about is this notion of a national n

Jonathan White is Professor of Politics at the London School of Economics and author of In the Long Run: The Future as a Political Idea. His research explores how time has been used and thought about politically. I have found his argument that politicians (and the public) feel we are in a situation of ‘temporal claustrephobia’ really useful for understanding our current landscape. Our actions feel both urgent, uncertain and irreversible.Are you feeling a sense of temporal claustrephobia or do you think there are ways to avoid this? Comment below! Phil: Jonathan, you’re a professor of politics at LSE, and I was really keen to speak to you about your book In the Long Run, because your argument that it feels like in politics the future is being foreclosed has really structured the way I think about a lot of issues, including climate breakdown. But also, on an emotional level, I feel this temporal claustrophobia that you talk about in my own personal life. So welcome to the Tech Futures Project. Jonathan: Thanks very much for having me, Phil. Glad you found something interesting in the book. Phil: Could you summarize the argument in In the Long Run and maybe say a little bit about whether you’ve updated any of the ideas since you wrote it a year ago? Jonathan: Sure. The book came out of a course I was teaching at LSE on how the future is used and abused in politics—the ways in which different outlooks on the future get promoted by different types of ideologies and interest groups, and the political implications that come with these. It’s a book with a tortoise on the cover, which indicates something to do with questions of how much time one has—whether there are certain virtues of perseverance and deliberation that presuppose a certain way of approaching political time, and that get extinguished when one approaches it in the register of high-speed emergency. A running theme is how the question of how much future is felt to be available—whether it’s open and abundant, or whether it’s felt to be closing in on the present—varies historically. The book starts with an earlier phase of modernity 200 years ago when revolutionary politics was very much focused on immediate transformation. Then over the course of the 19th into the early 20th century, you get conversely a lot of politics with a sense of abundant time. The slow timescales of evolution made their way into political thinking—incrementalism, gradualism. The Fabians in this country used the tortoise as their emblem. This is quite in contrast to the present moment where, in a range of contexts—you mentioned climate change, ideas of climate deadlines, five years, ten years, twelve years in which to make certain key political decisions—this is clearly how we’ve thought about climate change for some years now. But it’s not just that. There’s also economic inequality and the sense that we have a critical window to arrest runaway concentrations of economic power, or somehow it’ll be too late. That sense of living in a critical moment where what can’t be done now risks going permanently undone. You asked how my thoughts have changed since I wrote the book. Clearly one thing that’s happened is Trump coming to power in the US. I’m perhaps more aware now of the ways in which certain kinds of far-right, potentially fascist forms of politics prosper under these conditions of temporal constraint and the sense of the closed future—that things can’t be otherwise, that we’re living with a limited array of possibilities. So many mainstream political parties seem willing to push this, including Labour in this country at the moment. I think this really creates an opening that Trump made use of in the US and potentially that Farage and Reform will make use of in this country—an opening for that desire to occupy the territory of the future from a far-right perspective with ideas of disruption, of breakdown, of imminent civil wars. We live in a time of temporal claustrophobia, and I think too many p