
Show notes
Today's guest Mariana Mazzucato is one of our most requested. Mazzucato, a professor of economics at University College London and the founding director of its Institute for Innovation and Public Purpose, specializes in the political economy of technological development and public sector investment. In our conversation, recorded in Madrid while at the Bloomberg CityLab conference, she explains her concept of the "mission economy," her definition of state capacity, how to prevent top talent from fleeing to the private sector, and whether consultants or governments should be blamed for inefficiencies and civic failures. It's a wide-ranging interview, one that covers everything from the initial public financing of Silicon Valley algorithms to the history of moonshots. Subscribe to the Odd Lots Newsletter Join the conversation: discord.gg/oddlots See omnystudio.com/listener for privacy information.
Highlighted moments
“The loans to the steel sector were conditional, that the sector lower the material content of production, which they did in their own way. Had government told them how to do it, you kill innovation. But strong direction, conditional loans, and they ended up now having the greenest steel in the world.”
“They changed it to outcomes-oriented procurement, and they started to ask themselves, what are the outcomes that we need? We need to figure out how are the astronauts going to go to the bathroom, right? Which, by the way, was just a problem again with Artemis, the toilet.”
“these massive economic rents, and I call them rents, not profits. So excess profits and excess of what these companies actually did, because we privatized all the rewards from this massive social and collectively created value in this area. They have so much money, right? Trillions, not billions, trillions, the salaries they are paying to the top researchers in universities, both public and private universities, and to people who used to work in the NASAs, the DARPAs, the COFOS in Chile, they are going now to work in these companies. And that hemorrhaging of talent, of top research expertise, I don't think people are talking about this enough.”
“the biggest conflict of interest being that they have no incentive really to make government better later because they wouldn't have no contracts. It'd be like having a therapist your whole life. That therapist is probably not very good.”
Transcript
Introduction to Odd Thoughts
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Bloomberg Audio Studios
2:08Bloomberg Audio Studios. Podcasts. Radio. News. Hello, and welcome to another episode of the Odd Lots podcast. I'm Jill Weisenthal. And I'm Tracy Allaway. We're still here in Madrid, Tracy. How are you? Still here. You having a good time? I am. I've eaten a lot of ham and cheese. And me too. That's pretty much all I can say. Yeah, I'm going to turn into a jamon by the time I leave. I'm certain of that.
Bloomberg City Lab Conference
2:42So we are at the Bloomberg City Lab Conference. You know, it's funny, like, the mayoral level of politics is not something we spend a ton of time typically on. But I would say, like, it definitely, you know, when I think about it, when I'm, like, here and, like, listening to a lot of the conversations, it's just so obviously, like, connected to a lot of the themes we talk about, because so much of our discussions have to do with something related to, you know, innovation or technology or implementation of policy and how it spans both the public and private sector.
3:13Yeah. I mean, also, when I think about a lot of Odd Lots topics like AI or housing affordability or inequality, like cities, I think City Lab actually used this phrase at one point, but cities are really at the front line of all of those challenges, right? And trying to implement policy in that local level in a way that's, like, very easy to see and observe and also to judge. Totally. Yeah. No, it's exactly right. And I think maybe there's something like, you know, I don't, it feels like to some extent, the mayoral level of any governance is sort of maybe the least
3:46ideological and the most like, you know, we talked to the Baltimore mayor, for example, and so much of his theme was just like talking to other mayors, like what's working in your town, what's working in your city and what's not working and so forth. They all have such similar challenges. So many things have been, like, repeated, you know, one time after another that, like, they all can sort of speak the same language and all have the same issues. Yeah. It's funny. You kind of get that local idea swapping at a mayoral level that I cannot imagine necessarily happening in national politics. Like, can you imagine Trump and Xi Jinping getting
4:18together and be like, oh, we implemented this really cool, like, national transportation program. Have you tried it? Yeah. You know, you hear, like, these stories, right, of a governor, a governor sometimes or a mayor will go to, like, another country. It's like, oh, we can, like, learn from what the city did on transit or whatever. But no, you don't really hear that the same way at the real national level, which is where a lot of our discussions tend to sit.
Guest Introduction
4:40Absolutely. Anyway, I'm really excited about today's episode. We're going to be speaking with a guest who I would say, like, since we've been doing Odd Lods is actually one of the more frequently requested. Long requested. And so it's sort of a failure on our part that, like, we just, like, never made it happen before. But yeah, someone who, like, really, like, whose whole career is, like, dedicated to a lot of Odd Lods-y fame. Well, we waited until we could do it at Madrid. We didn't want to just, like, do it at any other random venue. Yes, it was all very strategically designed. So we really do have the perfect guest, someone that a lot of guests have wanted to
5:14listen to, hear from for a long time. We're going to be speaking with Mariana Mazzucato, professor at University College London, founder of the Institute for Public Purpose, author of several books sort of touching on these themes of technology, public sector, private sector, the roots of innovation, how these things actually get deployed. So, Professor
Professor Mazzucato Interview
5:33Mazzucato, thank you so much for coming on Odd Lods. Thrilled to finally have you on. Yeah. Finally. Finally. Our, completely our fault for not having made it happen sooner. But what are you just starting, like, what are you doing here? What, what brings you to this particular conference? What, what attracts you here? Well, first of all, I'm here also because the government of Spain is really kind of leading the way in many areas that I'm very interested in, especially the kind of new economic thinking that needs to underpin how we rethink government. And so I was meeting with both the prime minister
6:05and the minister for the economy, Carlos Cuerpo, who I'm on a panel today with, about a council that we've just set up. It's called the Global Council for a Common Good Economy. Anyway, and besides that, I'm also here to speak at the Bloomberg City Labs event about this new public sector capability index that we've been developing with them as a partner, which is really about reinvesting inside the civil service so that they can really tackle those wicked, complex problems instead of, you know, hiring Deloitte during COVID and giving them 1.5 million a
6:35day to do test and trace, which they failed at in the UK.
Consultants and State Capacity
6:39I definitely want to get you to go off on consultants. But before we do, like when you meet with someone like the prime minister of Spain, what is it that they want to know from you? Like what information or expertise are they seeking? Right. Well, I'm actually quite lucky that my books actually get read by the prime minister. So usually what happens is that they've, especially the entrepreneurial state, which I, you know, wrote in 2013 that had quite a bit of an effect here. They even wrote a report called El Estado Emprendedor en España. And they really want to ask me, you know, what does that mean? What does it mean for actually even being able to fail, for example, right? So venture capitalists are always
7:14bragging about all the failures that they had in order to get a success, you know, whereas as soon as a civil servant or a minister fails or a prime minister fails, front page of the papers. So they're very interested in the kind of narrative change, but also, well, the cultural change, but especially the theoretical underpinning within, say, a finance ministry or an economics ministry that needs to then accompany rethinking government. Because otherwise, if you continue to have the old economic models where we judge things by cost-benefit analysis, net present value, all these really static metrics, we would have never even bothered going to the moon, okay, first of all, in the 1960s,
7:48had we thought of it as a cost-benefit calculation. And so what should replace that, right? So you mentioned the entrepreneurial state being published in 2013. And I feel like I need to emphasize this because, like, there has been this mind shift since the 2020 pandemic on industrial policy. And we kind of take it almost as a given, especially on this show, that there is a role for governments to play when it comes to innovation and entrepreneurialism. But you were there very early. Did you feel vindicated by the 2020 shift?
8:19Well, I think there's a bit of a misunderstanding that just because government's spending a lot of money investing a lot of money, whether it's the IRA or the next-gen EU, $2 trillion recovery plan in Europe, that that means that industrial strategy is back or that, you know, government is being really strategic. It depends. And I mean, that's the whole point, right? You know, how are we actually framing it? Is it just a lot of tax incentives? Are we focused too much on sectors? To what degree is industrial strategy actually helping to create a more inclusive, sustainable, innovation-driven, you know, economy? Or is it just another wave of handouts and subsidies to particular sectors? And
8:55then we end up socializing risks and privatizing rewards. And also, I mean, I used to joke that the U.S. government has always had an industrial strategy, but, you know, pretended not to. And they've always talked the Jefferson talk, but acted the Hamilton talk or the Hamiltonian kind of more, you know, proactive government strategy. But by pretending that wasn't there, they kept a lot of things under the radar. And the joke bit is just that finally people understood what the hell it was talking about because of the musical, before the musical came out. Anyway, so I think that's
9:27really important to recognize that industrial strategy has always been there, except that in certain phases, including now in some countries, it's not really strategy in terms of being driven by public purpose, which, as you said, is the title in this Institute for Innovation and Public Purpose that I Direct. It's been just kind of vertical strategies, focus on sectors, technologies, types of firms, right? The whole focus on small, medium enterprises. So what I've been trying to do is to say, stop focusing on sectors, technologies and firms, focus on big problems, right? As bold as
9:59going to the moon and back at a short amount of time. This is the mission idea. The missions that then require sectoral support, but you're not getting support because you are a particular sector. You're getting support if you're willing. So moving away from picking winners to picking the if you're willing to work with government around these very difficult challenges, which could be as, I don't want to say simple, but as concrete as making sure that every child in a country has healthy, tasty, sustainable school lunch, right? Not just school lunch. That was the Reagan thing where he said ketchup is a vegetable so we can reduce the cost. We all had t-shirts of Reagan and
10:31ketchup, which was the vegetable is what the t-shirt said. So having moonshots, even on something as simple as a cafeteria, that then requires innovation across many different areas. It requires government to wake up and not just have that be done, for example, from the Department of Education, you know, Department of Agriculture, Health, Education, Finance would work together on a moonshot of healthy, tasty, sustainable school lunch. So that inter-ministerial coordination, which we saw during COVID, right? So we had the war room, the situation room, you know, the military, education, health,
11:04and so on together because we had these really difficult challenges. But as soon as COVID stops, we go back to very siloed ways of thinking. As someone with two kids in the New York City public schools, I can absolutely confirm that the degree to which they associate the mayor with school lunch policy is extremely real. And they like talk about like, oh, we used to have these like really nice waffles or something. And then Eric Adams got rid of them or something. Like they're really like keyed in. Single issue voters on waffles. They're like really pay attention to the degree to which
11:37school lunch policy shifts with administration. Like this is like, they're really, they really think, what is state capacity? We've been using this term for years on the podcast. And we were like, during COVID, we're like, you know, it took a, it took, you know, a long time to stand up testing facilities for a sense on people's like, oh, we lack state capacity. But what is it? What's the definition? So we actually distinguish between the word capacity, routines, kind of administrative routines, and then capabilities. Okay. So what states are often, what governments are often lacking
12:08are those kind of dynamic capabilities. So capacity partly is like literally do you even have fiscal space? Do you have a budget? Okay. But also how are you thinking about that budget in terms of, do you, well, put it this way, capacity is, you know, number of people working in your administration, the budget that's been allocated, perhaps also the training, you know, that the civil service actually has, but capabilities are what you actually then do with it. Are you agile? Are you flexible? Are you able to pivot during COVID and actually start working in this more, again, interministerial way? Do you know how to work with others, right? You know, do you set up
12:41good partnerships or are they problematic partnerships? And also you were talking before about what you're learning here, which is fantastic about how mayors can learn from each other, right? Have you invested in your ability to learn, to adapt? And so I think that ladder, you know, this concept of dynamic capabilities is a much more complex area to be investing in. And the only reason you would do it is if you actually have a theory about government that is more than what traditional economists think about government, which is at best, well, at worst, get out of the way, at best, fix the market
13:11failure. So as soon as you say, actually, it's about shaping and co-creating a different type of economy and society that works for people and planet, then the question is, what does that mean for the capabilities that you need? If you're just fixing, then you just need a lot of bandages. And that's, in fact, what we get. We get very reactive, kind of filling the gap kind of policies. Yeah, the pendulum constantly swinging back and forth. Exactly. Exactly. But I mean, capacity, of course, is essential. Without, you know, a budget and fiscal space, you can do nothing. That third category that I mentioned quickly, administrative routines, that's, you know, are you also, you know, do you have a stable environment
13:44where you can learn by doing? Because if you're constantly changing what you're doing, it's going to be hard to have a learning by doing dynamic. So those kind of administrative routines, I even see this in my university, where as soon as you get a lot of turnover, even those kind of basic routines aren't there. But capabilities, so these three areas, capacity, routines, and capabilities are equally important, but the capabilities are really what I find are lacking. And it goes back, as I was mentioning before, to the underlying economic dogma that has underpinned the way that we think about policy, government at different levels, that by design, not by coincidence, is reactive.
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AI and Government
17:30Have consultants become a substitute for state capacity slash routine slash administrative ability? Right. I always wonder how we got to the point where consultants are so big anyway, because it feels like every time you hire a consultant, it's almost an admission of failure on your part to be able to do something right. And nevertheless, it's a widely accepted practice across governments. So my last book actually was called The Big Con. So Con for Consulting. And the subtitle was How We've Weakened Businesses, Infantilized Our Governments,
18:03and Warped Our Economies, basically due to this consultification. I wouldn't blame the consultants. I mean, I actually blame governments, right? Like, why are you opening the door so wide to consultants? And it's fine to have advisors and some consultants. The problem is when they are actually doing the core tasks that government should do. Again, test and trace during COVID was a core task. And so I think it really stems from, I'd say, the 80s when we, you know, the kind of Reagan-Thatcher years, if you want. It always goes back to Reagan.
18:34Yeah. But actually in the UK, for example, it even increased more during the labor government. So it's not, you know, one party, but it did begin, I'd say, in the 80s with this kind of downsizing of governments, which then ironically cost them more. Because as soon as you start downsizing, without really strategically thinking what you need and what you don't need. Of course, you should trim the fat. There's no reason to have a, you know, a bloated government structure. But when it's done for ideological reasons and not strategic reasons, then, you know,
19:04ironically, then you end up not having those capabilities that you need as soon as you have a flood or, you know, Brexit or COVID. And so I think then what happens with the consultants is it's not their fault that they're invited in. I do think it's very problematic what they end up doing once they're in. So there's huge conflicts of interest. Well, the biggest conflict of interest being that they have no incentive really to make government better later because they wouldn't have no contracts. It'd be like having a therapist your whole life. That therapist is probably not very good. Which is how the therapy model probably works.
19:36Well, do you remember this came up in the episode we did about construction in New York and this idea that like one of the reasons it's so expensive and takes so long for like public funded projects is because consultants have no incentive to actually get the project done. Yes. But also they're often working on both sides of the street. Right. So there'll be, for example, consulting for, I don't know, a state owned enterprise like Eskom in South Africa, as well as the Treasury, which should be regulating Eskom. Or in Australia, there was a famous case with PwC where they were consulting for a medical device company, as well as the regulators of the
20:09medical device companies. Like, come on. So that should just be illegal. Right. And again, you know, getting the right kind of regulation that makes sure that we don't have these kind of scams. So what we also argued was, you know, the first thing is start investing back inside government so you don't need so much consulting. But also when you do bring in the consultants, make sure the contracts actually embed learning within them and that you are also bringing in the right people. You know, if you have an oncology strategy, of course, you should get the top doctors and consultants and cancer to advise. So the other huge problem is that these consultants,
20:40when they're coming in, they often actually don't know very much and they end up really bothering the poor public servants that they end up emailing. Oh, would you mind telling me what you think about or sending me your, you know, plan that we can study? It's like, why are you even working with government if you don't have within the consulting companies that deep expertise, which, you know, I'm not saying this just because I'm an academic, but I don't think academics are used enough. You know, if you have a research center that's been thinking about climate change for the last 40 years, use them. Don't ask McKinsey, as Australia did, to design your climate strategy,
21:13which ended up, by the way, being terrible. So there is a bit of why is it that governments, A, don't invest in their own capacity and capabilities, and B, when they do go out there and look for the advisors and consultants are kind of getting the ones that simply kind of provide a rubber stamp, right, that makes them feel more secure. They haven't even done the homework to make sure they are getting the top people in the world to help advise them on doing, you know,
AI Regulation
21:36difficult tasks. Just to take the other side of the coin. So recently in New York City, it was, I don't know, I think scandal is too strong a word, but there were a lot of headlines about how much the city had paid consultants for working on redesigning the trash collection system in the city. And on the one hand, it's like trash collection, core city function, why do you have to bring in a consultant? On the other hand, reimagining the trash collection system is like, that's a one-time thing. So maintaining it, implementing it, servicing it, okay, that's like a permanent government function.
22:07But the actual, like, okay, we have to do a redesign. Is that necessarily something that, like, we need to have in-house, in government, the capacity? Because do you want to permanently have that muscle? Because that's a one-shot thing. Doesn't that, like, to me, that makes sense as a time to bring in a consultant? People also argue for something like that, there's a value to having an external viewpoint, right? Yeah, like, that makes sense. Like, the redesign, that's a one-time job. Like, to me, I was like, all right, that doesn't seem crazy to bring in a third party to, like, help figure out what that plan is. Exactly. So that's
22:41the myth, right? That somehow we're talking about either government does everything, right? Or even nationalize everything, or it does nothing and it privatizes and brings in the consultants. So the truth is obviously somewhere in the middle. So of course, you're absolutely right. Government doesn't have to have all those skills. It definitely needs the skills to know who to work with outside of government. But it also needs to even understand that kind of outside landscape to even think about what might we need, how might we start developing a strategy that reimagines,
23:11say, the trash collection process. So that's why I talk about missions. So when, you know, NASA wanted to go to the moon and back in a short amount of time, they didn't say, we're going to do it all by ourselves. And they also didn't say, we're just going to do it with the aerospace sector, right? They said, we're going to have to work with so many different private sector people. They ended up working with something like 400,000 people in the private sector. They said, we have a lot of problems, but we don't know the solutions, but we're going to set very clearly a direction for working with the private sector in a problem-oriented way. So the first thing they did was change procurement. Procurement, you know, government purchasing is often like 30%
23:45of a government's budget. It's a very important part of their budget, whether it's Barbados, a small island state, or the U.S., a very large government. Procurement is there. How are we using it? So they realized they had the wrong type of procurement. It was just, again, minimizing costs. It was cost plus procurement. They changed it to outcomes-oriented procurement, and they started to ask themselves, what are the outcomes that we need? We need to figure out how are the astronauts going to go to the bathroom, right? Which, by the way, was just a problem again with Artemis, the toilet. Oh, is a problem up in space. What are they going to eat? What are they going to wear?
24:16How will we communicate with them? And it was the solutions to those problems that happened within mainly, not only private sector institutions, with NASA's also kind of leading investment, but especially leading kind of thought process of what the problems were that ended up getting us camera phones, foil blankets, home installation, software, so many different innovations across many different sectors, aerospace, nutrition, materials, electronics. That itself is what we're talking about, right? So whether it's going to the moon, whether it's trash collection, whether it's school
24:47meals, whether it's, you know, getting prepared for the next pandemic, which unfortunately the science tells us will happen. How are we even thinking within government in a problem-oriented way, a solutions-oriented way? And this, by the way, is why the CityLab conference is so wonderful, and Bloomberg's government innovation team is so important for so many cities, is because they then share their experiences of solving problems. And then they ask, and we're trying to help them do this with this public sector capability index, what did we learn along the way that we were missing?
25:17Where were the bottlenecks? What can we do better? But especially in terms of that flexibility, adaptability, willingness to experiment, right? Remember what Kennedy said, we're doing it because it's hard, not because it's easy. Yet all the words and policy papers are about making things easier. Facilitating. I'm Italian. Facile. We're in Spain. Facile. Right? So if you're facilitating someone, it's not going to be a good contract. If you're de-risking someone, it's not going to be a good contract. If you're simply enabling, facilitating, fixing, it's going to be a very bad public-private relationship. Just going back to consultants for a second, and I think this is
25:50actually relevant to the discussion of having cooperation among, like, different parts of the government on big projects. But how much of the consultancy fetish just has to do with diffusing responsibilities? So I always think back to the old saying about the purchasing manager thing, you'll never get fired for buying IBM, right? Like, how much of it is just like, well, you know, I did my best. I hired McKinsey. What more can I do if it goes wrong? It's McKinsey's fault. Accountability. Absolutely. So that's a really important point because, you know, one problem is
26:22when government doesn't have those capabilities for the reasons we said before. Another is even when they have it, why are they not using it? Australia, again, is an interesting example because they had really interesting capability within government with their innovation agency, CSIRO, and yet they gave this massive contract to McKinsey to do their climate strategy. And it's absolutely about diffusing that responsibility, but also because of the culture we have, again, within government where if they do make mistakes, unlike in the entrepreneurial ecosystems and, you know, VC and so on, we don't accept that.
26:53But it's also in the private sector, right? So we also talk in the book about the consultification of management, basically. And there as well, you know, if you're going to be doing a merger or downsizing or a massive share buyback scheme, isn't it great if you have, you know, McKinsey told us to do it. So also just not taking on, I mean, it's kind of cowardly, right? Like you're not kind of owning your decisions. I do think it's different in government. I think that, you know, changing that culture, having more gov labs like they have in Chile, laboratorio de gobierno, everything sounds better in Spanish. You can say anything in Spanish and
27:23Italian. It sounds like an awful lot. I always say that in Italian, every time we have a reforma della pubblica aministrazione, it's public sector reform, it's just cuts, but it sounds nice. It's just some way. La reforma della pubblica aministrazione. It's literally just cuts. And so that idea that what we need is kind of a laboratory within government, but also between governments, I think is really important. By the way, the head of procurement in NASA, Ernest Brackett, in the 60s with the Apollo program, not only did he help change the procurement policy of NASA, but he also said,
27:55we got to watch out. There's too many consultants in these corridors. And his exact quote was, if this continues, we will get captured by brochuremanship, which is kind of endearing because they didn't have PowerPoints at the time, right? So now the idea that you're ruling by PowerPoint, and that's basically all they know how to do. At the time, it was kind of shiny brochures. But he didn't say we don't want to work with the private sector, right? He said, we won't know how to work with the private sector. We won't know how to write the terms of reference if our own brains are becoming weak. So investing within in order to work also outside with others. So it's
28:29not working with others. It's working smartly with them.
AI and Society
28:32So this gets to the sort of one of the big questions of the day, obviously, and that is AI, right? And so you mentioned, okay, school lunches. You said a mission. It doesn't mean like the private sector isn't going to play a role in providing food or whatever, but first you establish what the mission is. Then you talk about the moon. It doesn't mean that the private sector isn't going to play a role. Private sector played a significant role through various technologies of procurement, but there was an overall mission. Well, how are you thinking about AI? Should governments first decide what is our mission for this? What missions could it theoretically enable? Does this feel
29:09different than other endeavors? We obviously know a lot of public sector money is going to wind its way up in AI and already has a lot of innovation. It already has. But how are you, does this fit? Is this different? Talk to us about how you think about this particular moment of extreme sort of technological ambition. Right. I mean, there's so much to say. So first, the investments that went into what we call today, artificial intelligence, including, you know, LLM models, language models, speech recognition dates, you know, decades, and like so many other areas that was led by government. So if you look
29:43at even DARPA, which as you know, was the lead investor in the internet, it came from problems, mainly in the military industrial complex that then required ultimately what we're calling artificial intelligence today. But again, in the entrepreneurial state, I talked about how everything in our smartphones that make them smart are not stupid, internet, GPS, touchscreen, Siri, and so on, were government finance. What's very scary today, what makes today different with AI is that that's not really necessarily going to be true much longer. Why? Because these massive economic rents, and I call them
30:16rents, not profits. So excess profits and excess of what these companies actually did, because we privatized all the rewards from this massive social and collectively created value in this area. They have so much money, right? Trillions, not billions, trillions, the salaries they are paying to the top researchers in universities, both public and private universities, and to people who used to work in the NASAs, the DARPAs, the COFOS in Chile, they are going now to work in these companies. And that
30:47hemorrhaging of talent, of top research expertise, I don't think people are talking about this enough. It literally is the biggest change, right? Because otherwise, just, you know, the fact that we've had, you know, big technological changes, general purpose technologies completely affecting, you know, how we produce, how we distribute, and, you know, from the rise of electrification and so on. The thing, like, at one point, I mean, I don't think it actually panned out that great for them, but didn't Uber hire the entire Carnegie Mellon robotics team in one fell swoop? I think they did. I think when they were doing self-driving car technology, they just wrote a
31:23check for the entire faculty of the CMU robotics team. And it was just like that. But not enough people are talking about this. So it's very hard to govern a process for good, ethically, and so on, if you don't understand it. So if this talent is, in fact, leaving these publicly financed institutions, even private universities, most of the research, as you know, has been funded by NSF and so on. Once they leave, and the knowledge is so concentrated in these few AI companies, I don't think we've thought about that enough. But sorry, just the
31:53other thing is, I mean, just coming back to your question, which I don't think I answered properly. Yes, of course, government should be thinking because of its, at least a democratically elected government, right? This is different for dictatorships, what we would expect from them. But we would expect governments to make sure that any big change, large kind of opportunities around technological change are done in ways that are, again, good for people and planet, right? But that requires not only that capacity that, as I mentioned, is being decimated, but also a certain type of regulation, which is making sure we even understand the process of, for example, how algorithms are
32:29currently being designed, and whether we have a situation like Shoshana Zuboff in her great book, Surreal and Capitalism. She says, you think you're searching Google for free? They're searching you for free. You know, that could have been avoided, right, through the design of the algorithms. And given that the algorithms initially, at least, were publicly financed, there is this issue of how do we, in a pre-distributive way, instead of kind of exposed with redistribution or regulation or market fixing, think about innovation collaborations that have some of these really important ethical concerns, thought about upfront. And an example of this would be during COVID, where,
33:03you know, the vaccines were not the mission. The mission was to allow these vaccines to be produced and available globally, given it was a global health pandemic. We were all better off if the world was, you know, vaccinated. And yet only one of the vaccines, the one that was the collaboration between Oxford University and AstraZeneca, had that kind of conditionality about what good looks like at the start in terms of how they collaborated. So it was the publicly financed researchers, Oxford is a state school, that put that as a condition with their relationship with AstraZeneca, that they would
33:34share the knowledge, that they would join the patent pool, keep costs and prices low. So more of that. Every time I hear, you know, Tracy, like someone talk about studying AI in college and like their professors, I'm like, that's great. But why are those professors not in the private sector making a hundred times? I mean, many of them are. But I'm always like amazed that given how much money is it? People leave money on the table. Yeah. What are you doing at a university? You're probably making 10 times as much. Where did that money come from? This is the issue, right? So this money that's being used to pay these very large salaries that you're talking about, it's very important to recognize that that
34:08didn't come about because of, you know, early on this amazing kind of entrepreneurship and all the knowledge was in these companies. They gathered that knowledge. Now they're using it. Of course, they're pushing the frontier. Of course, they're doing research. But that idea of also making sure that companies are not earning in excess, right? So why did the public purse not benefit in those early days? Why are they evading so much tax? I mean, literally in so many countries paying almost no tax. You know, also labor exploitation and the case of Amazon, you know, you don't hear it from me. You hear it from all sorts of different investigations, even during COVID,
34:42by the way, that they wouldn't even put the ambulances apparently outside the warehouse. I don't know if I've read that. I'm not sure if it's true. But anyway, the point is that they're, you know, what does a good company look like? And how does that then affect the returns that they're earning? And what is a just return versus these excess returns that now are being used to, you know, higher end. You know, you mentioned the black box of the algorithms, which I think is a really interesting point. And we did an episode with the CTO of Goldman Sachs recently, and we asked him like, Goldman Sachs is a highly regulated bank. When you have bank supervisors who go
35:16in and want to understand your AI system, what are they actually understanding? Do they like understand the underlying code that's driving the algorithm? And the answer was, well, no, not really. You can't expect them to understand all that stuff. It's more about having the right controls in place that prevent the algo from running amok. And so my question is with AI, where we have a lot of experts, highly paid experts and engineers in the private sector developing all this new stuff versus a shrinking body of government officials, like what should our expectation be
35:49about how much they understand this technology? Right. Well, it actually comes back also to that previous point. Do you need all that expertise inside? Or also, how do you regulate this in such a way that also stimulates more innovation? Because you don't want to put a cap on the innovation just by over-regulating it. This is where, by the way, I disagree with the abundance theorem, which makes it sound like, you know, there's all these opportunities out there and it was regulation and too much planning and too many conditions that kind of hurt that, which I think actually corporate governance and shareholder value maximization has really actually stifled the opportunities that we have today. So they don't have to, of course,
36:23understand the algorithms, but they do need to do exactly, as you said, like we do with climate, right, where there's climate disclosures. We need to know what it is that we want to be disclosed. In fact, we have a project that we just did, that we just finished with, do you know Tim O'Reilly? Yeah. So it was Tim and myself with a grant from the Amitya Foundation, a project we called Algorithmic Rents and how to reduce these rents and how we're designing algorithms also through disclosures. So we thought about what would be the equivalent of AI related disclosures that could do
36:57exactly, as you said, be almost the equivalent of what banks now have to do, but also companies have to do around kind of ESG kind of metrics. And so, I mean, the project is still underway. And what we want is actually to find kind of a coalition of AI companies that would be willing to think about this with us. But that assumes, right, that there's also enough of the science as there has been with climate change, which said this is an urgent problem. And unless we fix it now, we're going to reach a tipping point where there's no coming back. That's really when things started to change around
37:29the climate disclosures. We haven't, for some reason, reached that yet, even though there's such a link also, by the way, by the way, between AI and climate, like in terms of these data centers guzzling, you know, like for every, you know, chat GPT search you do, apparently it's like using a bottle of water, like the small plastic bottles of water, like that's literally how much we're using. And yet, you know, we're not making that kind of systemic understanding of, you know, AI problems and how they are connected to climate and water problems and so on. And that requires, again, government
38:00not just having an indicator like GDP to think about, but a dashboard, right? When you're driving your car, if you had one number, you know, how much gas you have or how fast you're going, you would crash it. So what does a dashboard look like, you know, for government that would allow it to make sure it's on track to making sure that also with the evolution of technology, it's thinking about these kind of more systemic features and not just thinking about it as innovation policy.
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40:48audio summaries, and a helpful AI assistant to your docs. So if you want to stop the endless follow-ups, do that with Acrobat. Need to make your docs crystal clear? Do that with Acrobat. Want to make sure your clients get everything they need to hear? Do that with Acrobat. Learn more at adobe.com slash do that with Acrobat. Just from a pure sort of history of technology
History of Technology
41:11standpoint, does AI feel different? I think it definitely fits with the kind of characteristics of a general purpose technology in the sense that it really does kind of change everything. However, there's also a lot of kind of myths around that, kind of a bubble in terms of how we're thinking, not only in terms of the financial market bubble around it, but, you know, just like with electricity, it took about 30 years for it to actually really affect how governments were operating. Similarly with the internet, you'll remember when Robert Solo was saying, you know, there's computers everywhere except in the productivity statistics.
41:42I think we're still very early in the phase with AI in terms of it having a really meaningful impact on improving. Again, coming back to the point about problems, right? This ultimately should be helping us solve problems. Which problems is AI really helping us to solve in a systemic way that can scale and that there's learning between governments? We're definitely using AI. Is it actually helping us, you know, solve some of the biggest problems of our time? Again, health problems, climate problems. Surely there's some of that. But until we manage this process, until we govern
42:16it both ethically, but also in a way that is with government instead of kind of, you know, sidetracking government in order to extract these mega rents, then we're going to have a huge problem. Why do you think that hasn't happened yet or governments haven't stepped in faster? Because I do think AI is kind of unusual in the sense that, like, you know, you have people like Sam Altman who will say very publicly in interviews, like, yeah, this creates a lot of negative externalities. And society is going to have to figure out how to deal with this. And governments are going to have to figure out how to actually best deploy this technology. Open AI published a big industrial
42:50policy document, which, again, I think is kind of unusual to previous technological developments. And yet governments seem kind of slow. I don't want to generalize too much, but many governments seem kind of slow to get in and really start shaping what they want to do with AI. Yeah, I mean, I think, again, it seems like I'm saying the same thing, but I really, it's because I believe in it. This technology on its own will not solve anything. If it's accompanied by a strong, for example, health system, that with AI thinking about health problems, then I can see that
43:22being absolutely revolutionary. And in fact, I once heard a really interesting discussion between Nandan Nilekani, you know, it's an incredible entrepreneur of computer systems. He was one of the co-founders of Infosys in India. And Eric Schmidt at one of these dialogues we have in Bellagio, this beautiful villa in Lake Como run by the Rockefeller Foundation. And we had kind of Eric Schmidt on the one hand saying, you know, in the future, all we're going to really need is an app, a health app, and that's going to be fine. And Nanda Nilekani, who really is one of the biggest innovators around computing,
43:54was like, what? Like, let me tell you, in India, without a proper health system, no matter how many apps you have, we will continue to have misery. And so it's not one or the other, but what you need is more people like Nandan who think about what is the relationship between, you know, the power of AI and the structure of a health system, and who's thinking about that. And if we do have at the same time, not just austerity, but this, you know, kind of dumbing down of what we think government is for. So even the health systems we have are not kind of, you know, fit for purpose, then I don't see
44:27any sort of future of AI kind of helping us with, with health problems. And by the way, just look at water. I mean, like 55% of the global food system right now is at risk because of how we're treating the global hydrological cycle. You know, biodiversity loss also in the Amazon is affecting droughts and floods in other parts of the world. That's a huge problem. To what degree are we really using AI to, you know, fix that problem? Yeah. Not much. So it's also about where we're putting kind of the emphasis. And for that, I think we do need these moonshots, government-led
44:58working with the private sector. And again, using the power of AI well-regulated to solve very concrete problems. Yeah. Joe, I was thinking about this specifically related to healthcare recently, because I've seen a bunch of startups that are saying they're going to simplify the billing process for hospitals. And then you also know that there are a bunch of insurance companies that are also using AI. And it's like, well, if we're just going to have more- We're just going to have computers debating with computers. Yeah, exactly. And like, if the system itself doesn't change, nothing's going to improve. Right. No, I've totally thought about the same thing where it just like,
45:32feels like we're going to have this arms race where it's like, my bot will argue with your bot. And then the only entities that make any money are the bot makers, the bot makers. Do you know that Ada Colau, who was the mayor of Barcelona, another city here in Spain that you know well, she, when she was mayor, she came from a housing movement. So she was really, really concerned with housing issues, but also, you know, public transport, public schools and so on. And her thing was, why is it that when the citizens of Barcelona, you know, like click on Uber or
46:04CityMapper, this data that's created from that, right? Because every time we click on something, data is created. She said, why aren't we in the city using that data to improve our decisions and understanding of our public transport and public housing challenges? And so she ended up hiring computer hackers into the city government and made it a really cool place to work. And I think that, again, kind of insourcing back in those kind of, you know, cool hackers that currently are working in these companies, but to come and work with the city administration that says, we want you to come in, fail, but help, you know, like, don't worry about
46:37failing, sorry, not fail, but, you know, take risks to help us, though, kind of really target our big, you know, challenges around housing, transport, and so on, inequality in terms of access. So obviously, we're talking about the public sector, we're talking about the government's role in facilitating or guiding various technologies. But there's also just like politics, right? Winning elections. And the fact that, you know, as you mentioned, failures become a scandal, and they're on the paper, and maybe like politicians lose their jobs, then someone comes in,
47:08when you just in your own personal work, when you like think about this stuff, like, how much do you have to calculate the reality that one big job of politicians is to win reelection? And that a loss of election has the potential to just take the government in 90 or 180 degree turn from whatever the previous administration at any level in any country does. And how much do you like think about that reality when you're thinking about strengthening government?
Politics and Government
47:37So the first time I started to work on missions wasn't on mission oriented policy, it was on mission oriented organizations, right? To better understand the DARPA kind of organization, right? Corfo in Chile is similar, Citra in Finland, MindLab in Denmark, Vinova in Sweden, these are innovation agencies that are in fact making these big bets that are mission oriented. But my question was, how are they organized? Are they also unstable due to the electoral cycle? And they have thought about this. I mean, it's not a coincidence that DARPA, for example, people come in for five years,
48:08but it's not the four year electoral cycle. They're actually told, come in and do take risks. That's how you'll be evaluated, you know, not by just if you're succeeding all the time, that means you're not taking those risks, but also the impact that your successes have. And so that kind of cultural shift, but also the fact that people are coming in kind of on secondment, you know, they're not there to be a civil service, civil servant their whole life. So we started studying. Well, for some, for some areas, I think that's fine, especially around innovation, right? You want to coming back to the idea
48:38that we want to bring in and crowd in the top talent into government, you know, having like a five year period that you're going to help as a civil servant paid by the government, not as a consultant, you know, working with not at the civil service. I do think there's lots of kind of room for that. So that idea that because we value the private sector, there has been, for example, think of Harvard Business School, where they have this case study methodology of businesses, we've never really done that with government entities, because we don't value basically government as a value creator.
49:09It's just seen as a redistributor, a fixer, a facilitator, and enabler of the private sector. And that's, of course, where then we expect creativity and value to be created, which is not right. And so one of the things that we do in the Institute, which is actually a department, so we train up civil servants around the world, also, you know, through our own MPA, Masters in Public Administration, but also through applied learning programs, was to start developing these cases. You know, what do we know about the BBC? You know, how is it different from other public broadcasters? How do they measure what they call public value? What is public value?
49:39So even having, you know, comparison learning between, say, a public bank, the BBC, a government digital agency on what it means to crowd in or crowd out the private sector, what it means to shape markets, not fix them, what does it mean to have a culture of experimentation versus this huge risk averseness that, as we said before, is a cause for the consultification. So I think a lot about that. But it's not, you know, there's so much instability, obviously, also in the private sector. So there is a bit of a myth that it's all unstable in the public sector because of electoral turnover. We can't shape these bureaucracies to be creative bureaucracies, resilient bureaucracies,
50:12they don't have to be vertical, and so inertial. But the other point, I think that's sort of stemming, I think, in your question, tell me if this is not related, is literally winning the election. What are we learning globally? You know, why is it that Biden, whose economic policies were actually quite successful in the red states, at least starting to be quite successful? Why in those states did he not win? And I think there's something going on in a lot of countries, definitely also in Italy, in the UK, where people who have been, let's just use the concept, left behind on terms of
50:45the economic benefits, at least in the past, even when new economic policies work, that's not enough if people don't feel valued, if they don't have their dignity back, if they continue to feel condescended upon. So one of the really cool things I've been working on with city governments, but even councils, so my neighborhood in London is called Camden, it's about 250,000 people. I worked with the council on mission-oriented procurement for adult social care across 10 housing estates, what you call projects in the US. And we brought the carers and the caries to the table to design that policy. So working with people, really valuing their lived experience
51:22to help design policies that are meaningful and will improve their lives, I think it's just so important, firstly, to get those policies to be designed right, but also to give people, again, dignity and self-worth. And I've seen it also, you know, because we have so much inequality in the UK. Unfortunately, we have food banks, which is barbaric, if you think about it, in the 21st century, food banks, like, you know, we should not have that. People should have food, you know, on the table, enough and healthy food. We don't have that. So transforming food banks into food cooperatives, green food cooperatives, where the people benefiting
51:56from what was a food bank are now also in the place of governing, of having real deliberation, of thinking together. I can tell you, the people I saw working in the food banks, who are also receiving the food, the facial expression, the dignity, just even how people are standing, is completely different from a system where, you know, you... Here's someone's expired, like, pumpkin from last Thanksgiving. No, but even if it's good food, you know, having, again, you know, bringing back dignity and value, it's so important, I think, to fight populism.
52:29I'm going to ask what is potentially an unfair and loaded question, but I think it might be quite
Industrial Policy Examples
52:33illustrative of everything that we've been discussing. When you look across the world, are there particular countries or cities that you think are doing industrial policy right in the sense that they're taking maybe a holistic approach with a defined strategy slash mission? So I tend to also look at, like, very specific things that a government did instead of just saying the whole government's perfect, right? So, for example, in Brazil, something they've done that I think has been very positive is that they've put what I call missions at the center of government. So the ecological transition is at the center. And that then required the Department of
53:07Finance, for example, to rethink its own tools. For example, a public bank, right? So BNDS, which is one of the largest public banks in the world, it can either just, again, give money out to, say, the agrobusiness industry or save the steel industry when it's going bust, or because there's an ecological transition, it can think about how these sectors themselves need to change in order also to access the loans that the bank is giving. Germany, by the way, did that when they had the energy vending policy, their public bank, the KFW, the way they provided support to the steel sector,
53:38which in the US and the UK and so many countries, steel is under pressure. The loans to the steel sector were conditional, that the sector lower the material content of production, which they did in their own way. Had government told them how to do it, you kill innovation. But strong direction, conditional loans, and they ended up now having the greenest steel in the world. It might not be competitive yet, and that's a scale issue that has also to do with regulation. But repurpose, reuse, recycle technology in steel only happened because the public bank that was mission aligned.
54:11So I'm very interested in procurement, public loans, state-owned enterprises, digital public infrastructure, examples where they're not just things that are there, but they're used to really transform and help development. Sweden is also really interesting because they had a high-level challenge, right? Missions are somewhere between a challenge, like the space race, and a sector, like aerospace, right? So the moon mission required lots of different sectors, but it was very concrete with the challenge of, say, climate change or all the sustainable development goals. Those are kind of very broad. So transforming them into missions. And their challenge was, I think they said they wanted
54:44a fossil-free welfare state. And that's why then they said, well, what are the missions? We were working with them on this. So we were kind of stimulating some of this thought through Vinnova, their innovation agency. What are the missions that will help us achieve that? And that's where then the healthy, tasty, sustainable school meals policy came from. We worked with them on that also in Brazil. We just actually put out a report about this with the World Food Program. But what was interesting, again, was that then that required government to work in a different way. Again, interministerially, you know, catalyzing bottom-up experimentation, local manufacturing,
55:17but through also the redesign of the tools themselves. The UK, which I don't think is a very good example right now. I mean, there's lots of instability. There's also been 14 years of austerity. Some things that were really interesting, and this is why I look more at the organizational kind of examples, was government digital services, GDS, which basically began by government back in the early 2000s saying, why does everyone have to go to, say, Google to download a white paper? Why don't we have our own kind of digital platform? They did what most governments do, outsourced it to a
55:49company called Circo, which is not a very innovative company at all, gets lots of government contracts. They failed miserably. And then people from the iPlayer team and the BBC said, we'll do it. So they went over to the cabinet office, set up government digital services, came up with this incredible digital platform called Gov.uk, which won an international design award. But what was interesting to me from that example was that the first thing they did was look out the window and said, with arrows pointing out the window, those are not clients and customers.
56:19Let's stop talking about people as clients and customers. They're users with human rights and how they will access their driver's license, their passport, their voter registration has to enhance their souls and not make them want to die. If you see the Ken Loach movies where people literally want to die when they're accessing their welfare payments because of just the complications around it. And so having kind of like a user-friendly government digital platform that changes the experience of a citizen with those rights that they have through the technology just requires a
56:51very different kind of mind shift. And it became the coolest place to work. So if you were a top, you know, software engineer or even, you know, whatever, these hackers that Adekolao wanted to hire, that's where they wanted to work to the point that lots of private companies were having a hard time finding the top talent because they all wanted to work in GDS. So again, those are the examples I think we need to look for, not like which is the government that's doing everything perfectly. All right. Professor Matsukato, thank you so much. Great to finally catch up with you. It took us all like randomly being in the same location in Madrid, but thank you so much. Thank you so much for coming
57:24on OddLog. Thank you so much for having me.
57:38Tracy, I'm glad we finally caught up with Professor Matsukato. But this was the place to do it. This is definitely the place to do it. I think it really did. Her framing makes a lot of sense. This idea that like outsourcing is not per se bad, that obviously any major mission is going to have to have significant private sector involvement and innovation, even if it's somehow publicly led, but that there's no like chance of going anywhere if there's, you know, if the public sector doesn't
58:08have the internal muscle of like who to talk to or who to talk to at the right time. Or how to judge performance. How to judge performance seems absolutely a key question. And that kind of gets back to the mission idea, which I do. I really I like the idea of focusing on what you're trying to achieve rather than just how you're actually going about achieving it. Like that makes a lot of sense to me if you're dealing with a vast bureaucracy with lots of different silos. And also, I think like getting back to that expertise point does mean that you do develop
58:40that muscle internally within the organization rather than just like, okay, we're going to hire McKinsey to figure out how we're going to do something. Instead, you say, well, we want to do X. Let's all get together and figure out how to do it. You know, AI seems like a weird thing as a technology because, all right, on the one hand, you could say like, all right, we want to massively improve our health care system. We want to massively improve health care outcomes. And I think you could like very easily say, well, AI is going to be a really big part of that. Right. And maybe make things a lot more
59:14efficient, maybe give information access to a lot of people, identify experts, et cetera. There's all develop new medicines. Yeah, totally. It's so great. So maybe the mission has something to do with health and AI plays an important component of it. I guess what's strange, though, is that AI itself creates its own potential pitfalls. I mean, the industry, as you mentioned, is obsessed with the pitfalls of its own making. Right. And so there is almost no way that AI can just be a tool in service of some other mission, because almost everyone who knows something about
59:48AI sees potential for extreme exacerbation of inequality, potentially AI robots that will be misaligned and want to kill us all when they have sufficient capability. Just little things. Yeah, right. And so on the one hand, yes, as a technology, it might fit into some of these other big missions. But on the other hand, it sort of feels like there has to be some AI-specific goal of where do we want this technology to go or how do we curb it or whatever it is that seems very
1:00:21distinct. No, totally. And I do think the unusual part of this moment in time, and a lot of people will argue that maybe it's marketing or whatever, but you do see the big tech CEOs basically going on TV and saying, like, we as a whole society need to figure out what we want to do here. And I don't think it is marketing or just marketing, because, A, there's already this very big tech backlash. Right. So, like, it's not working. You know, if the idea is, oh, we want to plump our valuations. And so we do that by saying the TAM is all human labor and human life.
1:00:55Yeah. Well, you're really upsetting a lot of people by saying this. It's not that's not obviously good. And B, you know, as we've written about or talked about, you know, some of these big labs, like they were founded from day one with the premise that this is not normal technology, which is why it's like housed in a nonprofit or something like this. So I tend to think that when the CEOs of these companies talk about this stuff, they kind of mean what they say. They too are they too are concerned. I mean, I also worry without some sort of government intervention or
1:01:26government strategy here. We are going to get to that situation where we deploy AI and because we're not fixing the underlying system, we're just sort of nippling at the edges and making it worse per that idea of like, OK, the insurance bot is going to talk to the hospital bot. And both of them are going to say that they're streamlining the billing process for medical services. But because we're all doing the same thing without actually fixing how medical bills work and who pays for what in the U.S., like it's just going to be bots fighting bots. No one's going to benefit from
1:01:59that. No. And most likely there'll be sort of, you know, just ongoing increased complexity. It's bots all the way. Bots all the way down. All right. Shall we leave it there? Let's leave it there. OK, this has been another episode of the All Thoughts podcast. I'm Tracy Allaway. You can follow me at Tracy Allaway. And I'm Joe Weisenthal. You can follow me at The Stalwart. Follow our guest, Mariana Matsucato at Matsucato M. Follow our producers, Carmen Rodriguez at Kerman Armand-Dashel Bennett at Dashpot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And for more OddLots content, go to Bloomberg.com slash OddLots. We have a daily
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