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The best books on Industrial Policy

recommended by Danny Crichton

Government intervention in the economy played a key role in the East Asian economic miracle and, further back, the development of countries that have traditionally championed free markets around the world. As the merit of state leadership in key industries returns to mainstream debate, Danny Crichton of venture capital firm Lux Capital recommends five outstanding books for understanding industrial policy.

Interview by Uri Bram

Before we get to the books, please tell us about industrial policy. What is it, and why is it so relevant now?

Industrial policy was a major area of study in the 1970s and 1980s that crescendoed throughout the Japanese bubble of the 1980s which ultimately crashed in the early 1990s. You had countries like Japan, Taiwan, China, South Korea, Singapore and others which all moved rapidly up the economic development ladder based on heavy government intervention in the economy. You have to remember the intellectual context of the Cold War between the free-trade capitalism epitomised by Margaret Thatcher and Ronald Reagan versus the state-led capitalism that was seen across East Asia and the state-controlled economy behind the Iron Curtain.

With Francis Fukuyama’s book, The End of History and the Last Man, there’s this moment of the end of history: the Berlin Wall falls, and there’s a ‘Washington Consensus’ that comes into vogue in the 1990s. The idea was that free trade, limited intervention in the economy, and open borders would lead to prosperity and was the right economic model for everyone universally going into the new millennium.

Now instead of Japan, it’s China that’s pushing America back toward a reconsideration of industrial policy. Just in the last year, with the CHIPS and Science Act as well as the Inflation Reduction Act, the Biden administration has enacted more than $100 billion of subsidies across semiconductors, green technologies, solar panels, and more to incentivize these industries.

Suddenly, after two decades in the wilderness—at least in U.S. policy circles—industrial policy is back.

What exactly is meant by ‘industrial policy’?

A lot of American policymakers—and certainly a lot of American politicians—believe that industrial policy means picking winners. This is the idea that you are choosing Crest over Colgate. The government is going to say, ‘Crest  is the company that will make toothpaste going forward, and we’re all going to brush our teeth with Crest.’

In reality, industrial policy is about solving a classic chicken-and-egg game-theoretic problem, which is: how do you coordinate complex areas of the economy? I mentioned the CHIPS and Science Act. The United States wants to build leading-edge semiconductor fabs so that it can compete with Taiwan and China going forward.

But to build that industry, you need tens of billions of dollars for the fab. You need thousands of highly-trained workers who are educated in universities, post-grad programs, and graduate schools to be successful. You need infrastructure. You need the electricity and, particularly for chips, you need water facilities that move millions of gallons of water to those fabs in order to produce chips. Then you need the airports and ports to get the finished products to their destinations.

“Industrial policy is back”

Ideally, a free market would connect all those dots together. But let’s say you’re a worker, and you think, ‘Look, I want to learn how to build a chip, but there’s no fab.’ And the fab and the semiconductor companies are saying, ‘Look, I want to build a fab, but there are no workers. By the way, there are also not enough ports and airports and water facilities. How do you coordinate—simultaneously—construction, infrastructure, energy development, workforce development, and financial capital? You’re creating something that didn’t exist before, and that is what industrial policy tries to do.

As an aside, there’s another term that sometimes gets bandied around: ‘innovation policy’. Innovation policy tends to focus more on the actual science and engineering discoveries that happen in universities, and how those get transferred into the commercial economy. So it’s related to industrial policy, but not the same.

Let’s move to our first selection, which is Kicking Away the Ladder: Development Strategy In Historical Perspective by Ha-Joon Chang. Please tell us a little bit about this book.

Ha-Joon Chang is writing in 2002. By then we’ve had a decade of the Washington Consensus of free trade and liberalism going around the world. This is the world that Thomas Friedman would eventually dub The World is Flat.

What Chang is really trying to do is say, not only is that not the right approach, it’s not even the approach that Britain and America took themselves to get rich. So he is taking a historical look—all the way from the 1600s to the present day—to show that, in fact, when we look at major developed countries, they actually used precisely the kinds of industrial policy techniques that countries in East Asia are doing today.

For instance, he shows that Robert Walpole, the de facto first prime minister of Britain in the 1700s, actually developed import substitution policies. He put in place tariffs and blocked other countries from importing goods into Britain so that Britain’s nascent industries could develop, and didn’t have to be competitive with France and other countries at the same time.

America in particular ignored intellectual property. One of the funny things about US-China dynamics today is that there’s this notion that China is stealing American technology and just indigenizing it. But America, at least in Chang’s argument, did the exact same thing to the British and Europeans in the 1800s. We would regularly ignore British patents, and just import products, learn from them, copy them, and steal them. The Industrial Revolution comes and starts in Britain, and we just pilfer! We take away the best techniques, the technologies, the machines, and we rebuild them here.

So his argument is in the title, which is that America built itself up with industrial policy, and now we are putting in place these rules and thus we’re kicking away the ladder. We’re saying to other countries: ‘You can’t do these techniques. They don’t work. They’re not going to make you rich.’ He’s really focusing on the hypocrisy of that.

Is there a non-cynical explanation for this? How did we come to believe these principles for industrial development that we didn’t embody ourselves?

One of the important things that comes up with industrial policy and really all of economics is around allocation. If you have scarce resources, how do you allocate them in the economy in the most effective way?

When you’re rich and wealthy, you can oftentimes allocate to everything. That’s in some ways how modern American fiscal policy works; that’s why we take on so much debt every year. You can simultaneously fund a healthcare system, a university system, a large army, an immense amount of industry, etc. You can do all of the above.

But when you look at Western nations back in the 1700s and 1800s, or look at the developing world today, you have to make choices. There are tradeoffs. You can’t do ‘all of the above.’ One of the arguments is that back in the 1800s, America was a poor, rural nation. It was a hinterland. Almost all people lived on farms and in the wilderness, and the nation did not have the resources to spend on intellectual property and following the rules of the Old World. Now that we do, those rules matter a lot more.

Suppose you were running a small developing country at this exact moment in time, do you have a sense of what you would do? You have these international institutions like the World Bank that are suggesting policies, but they’re not necessarily right. What would you do?

I would take Chang’s argument, which is really excoriating the multinational development institutions—the International Monetary Fund, the World Bank, and others—and saying, ‘Look, a lot of the advice they give is actually correct for well-developed and advanced economies. But it’s absolutely horrendous for developing nations.’ In many cases, you could argue, the World Bank is stuffed with people who are just not sensitive to the needs of the countries that they’re supposedly serving.

As a developing country, what you really have to ask yourself is, ‘What’s right for you? How do you actually go economically from point A to point B?’ Chang’s argument would be: you have to protect local industries; you have to industrialise; you have to build; you have to have factories.

Let’s say you’re India. Outside of government duties, it’s probably cheaper to import a Chinese television than it is to manufacture a local television. The Indian television will have fewer features, it will be more expensive, and it’ll be more labor intensive. But you have to start there and actually work your way up the ladder, as opposed to just importing today and not having an industry at all.

That makes a lot of sense. Next up, we have your best book about defense industry policy: Rebecca S. Lowen’s Creating the Cold War University

As I said with Chang’s book, America does not believe that it has an industrial policy, but where it actually does, and where you really see it, is in defense policy. The United States spends hundreds of billions of dollars on manufacturing weapons, tanks, ships—everything that the military and the Pentagon need. This is where factories get made; this is how universities get funded.

The literature on this is unfortunately fairly light, but it’s really important. What Lowen has done is explore—from the 1930s to the 1970s—why universities expanded the way they did. The thesis is that in the post-World War Two era, universities needed funding. In the 1930s, the entire university system in the United States was impacted by the Great Depression, from their own endowments to the people paying the tuition and also donations. The universities were looking around and saying, how do we grow in this coming era?

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What Lowen finds is that the universities start looking for funding from the federal government. They start asking for more research grants, they start asking for more subsidization of the system, and on top of that, they’re also looking to private industry for the first time for support.

Transport yourself back to a 1930s university—they’re not looking for anything commercial anywhere near their ivy-covered gates. But now, for the first time, they’re willing to open up to industry and say, ‘Who could sponsor a center? Who could sponsor some research? Who could fund a laboratory?’ It’s also in this era that we see the rise of what’s dubbed Big Science, where you move from the individual entrepreneurial scientist to Manhattan Project-scale science teams.

What we see (and she’s actually fairly negative on it) is over the course of about forty years, the university transitions from a bastion of Arcadia—this place where you think, philosophize, and debate the trivium of logic, rhetoric and grammar—to a model of laboratories that make money, that raise funds and, at some point later, spin off companies. Those spin-off companies then sponsor research back at the university, creating what we now think of as Stanford and Silicon Valley.

Do you want to tell us a little bit more about that specific example and the birth of the tech industry—Silicon Valley and the world of technology?

Yes, so the other book along this line is Christophe Lecuyer’s Making Silicon Valley, which was written in the mid-2000s. He writes about an important part of industrial policy that almost everyone gets wrong. which is that while it’s mostly centred on economics—how money gets allocated, how you fund this—ultimately it’s people who build this stuff. People have to create the ecosystems behind it.

Lecuyer’s book is the best I know of that really gets at the sociology of how an innovative industrial ecosystem gets built. Right now in the United States, if we were trying to build a fab in Arizona or in Columbus, Ohio, where do the people come from? How do businesses get started? Who starts them? Who funds them? How does the culture change over time to allow different types of industries to happen?

For instance, fabs require tens of billions of dollars to build and when operated, demand a military-like discipline to stay optimized in order to have the most number of chips produced with the most profitability. That’s very different from an innovative software startup ecosystem that’s building a bunch of different types of companies with small teams and a lot of creativity.

Lecuyer really shows—similar to Lowen, starting in the thirties and going into the eighties—how Silicon Valley itself specifically developed this unique culture of startups and small firms.

There’s resonance there because if you look at other countries, there’s a really wide mix. Taiwan is relatively well known for having a robust small-and-medium enterprise industry, whereas South Korea’s economy is dominated by these huge conglomerates like Samsung which are known as chaebols. Lecuyer does a really great job of opening up a lens on ways of understanding how these kinds of diverse regional economies come to be.

There seems to be an interesting division here between theory and implementation. Some of your recommended books on industrial policy are talking a lot about the theory of development, and some are talking really specifically about the implementation details of specific industries.

You’re getting at one of the challenges with industrial policy, which is: you can study it at a school; you can go to the Kennedy School at Harvard or other places and study it. You have this notion that, okay, you’re in charge of an economy—a job that, by the way, mostly doesn’t exist in America, but does exist in many other more state-directed economies. How do you actually do the job?

Unlike a central bank governor, industrial policy isn’t about looking at the past and trying to modulate and stabilize the economy today. You actually have to create economies, new ones. You’re actually looking forward and saying, ‘Okay, here we are today, where should we go in the next five to ten years, and how can we catalyze that to actually take place?’

For instance, to pick some popular themes in technology these days: artificial intelligence, the metaverse, quantum computing. Shouldn’t the United States try to coordinate action around quantum computing? We did this in the fifties and sixties around semiconductors. We did this around the space program. We went from having no space program to a man on the moon in ten years. That didn’t happen because a bunch of people just suddenly got together randomly and tried to make that work.

All the books we’re talking about today are lenses. They’re ways of understanding the world. They’re not guides. There’s really no guide to go do this. You have to imbibe all these lenses, and then if you’re in a position of trying to catalyze this, hopefully all those lenses add up so you’re able to zoom in on a particular topic and say: ‘Okay, I need this group of people here, another group of people there, this finance has to show up in a certain way at the same time, we have to have the right regulations in place and the right infrastructure. And if all that happens, we’re going to have something amazing.’

It’s a little bit like being a chef. You can read about being a chef, but at some point, you’ve got to cook. I think the way to think of industrial policy is: I need to know which ingredients exist. I also need to know I have fire that I can use, and I know I need to be in a kitchen. A lot of steps have to happen in the right order. But, if I do it all right, I have a soufflé. But if I just told you, ‘we need to have a soufflé’ you would have no idea how to make it.

Let’s talk about your next recommendation for us, the best book about East Asian development, which is Asia’s Next Giant: South Korea and Late Industrialization by Alice H. Amsden. 

East Asia is where industrial policy is being done, and has been done, and where the most number of people are and were focused on it. There have been an immense number of books written on the subject, and it’s actually really hard to choose just one.

Just to give a sense of this, there are multiple books with more than 10,000 citations on the subject. It’s a huge literature, an endless sprawl. But I think Asia’s Next Giant gets you the closest to a book that gets into the weeds, to answer your direct question of, practically, how does this work?

Amsden is an economist, and frankly, it’s not a particularly easy read. It’s an economist’s economics book. If you want to understand why economics is known as a dismal science, this is the book for you: it has dozens of tables of capital and interest rates and loans, and all of the actual mechanics of how South Korea in the 1950s to the 1980s went from being among the poorest countries in the world—making $60 per capita per year after the Korean War—to the country we see today. Annual per capita income is now $35,000 according to the World Bank and last year Korea beat Japan in per capita income at purchasing power parity.

“During the late 1960s and 1970s, Korea was one of the fastest-growing countries in all of history”

The book’s argument is that the Korean government took a very central role in economic planning. They didn’t have a lot of resources and they were very aggressive and strategic in placing every dollar they had in industries that mattered.

Amsden shows how it changed interest rates based on whether a company was in exactly the right industry or not. She also shows the metrics around business performance the government expected: when companies weren’t performing, the government would just transfer the ownership of the business over to someone else and say, ‘Look, you said 12% growth, but you got 10% growth, your business is now going to move over here to someone who can get the job done.’ That’s the terrible part for a free marketeer, but a necessary part for such an immiserated country looking to get ahead quickly.

What miraculously emerges—and the Koreans do dub it the Miracle on the Han River—is Korea transforms into the fastest-growing country in the world for a period of time. During the late 1960s and 1970s, Korea was one of the fastest-growing countries in all of history, with 10% to 15% GDP growth year after year after year. Amsden gets deeply into those weeds to really show how industrial policy happens.

It’s fascinating to me that people talked about the miraculous growth of Japan and China for a long time, but I didn’t hear as much about Korea until a few years ago. Now it seems that Korea has continued that path more successfully than some of its more famous neighbors.

Definitely. I think part of the reason is that China has 1.4 billion people and Japan has over 100 million. Korea is a small country, with 52 million people. It’s surrounded on all sides by water or North Korea, and so is de facto an island. It tends to get short shrift because it’s surrounded by these giant neighbors who receive a lot more attention.

Since you mentioned Japan, I should mention MITI and the Japanese Miracle, the Chalmers Johnson book from 1982 that is by far the most-read book on industrial policy. Japan hits its zenith in the 1980s, and it’s really hard for people to realize if you weren’t there, or don’t read about it, that Japan was buying everything in the United States. It was a bubble, but they bought the Rockefeller Center in New York and choice properties all around America. It felt like they were undefeatable. There was a real fear that Japan Inc. would own the United States by the end of the millennium.

I think the difference with Korea is Japan experienced ‘the Lost Decade,’ as a lot of people call it, in the 1990s. They did not transition well into the digital economy. Whereas in the Korean case—Alice Amsden ends in the 1980s when she was getting this book ready to go, but this is true up until today—Korea just continued with its industrial policy as if nothing happened. So they went from shipbuilding and heavy chemicals into chips and electronics, and taking a lead in smartphones and displays and memory. Samsung generates the majority of worldwide revenue from mobile screens. Despite the obvious competition between Apple and Samsung, the iPhone uses a Samsung screen.

Korea just endures. And Korea, with the Korean Wave, continued to move beyond manufacturing into culture too. Starting in the 1990s, the Korean government has a huge industrial policy around taking Korean culture global. Unlike the Japanese culture industry, which is still mostly domestically focused, K-pop, K-dramas, K-films, etc, all get exported. The government has this goal of, ‘Look, we’re a small economy with a small internal market—how do we get K-pop to have a billion listeners?’

That’s not to diminish the entrepreneurs that did this or cut down the artists that are producing their art, but the reality is that the Korean government put in place heavy incentives around tax, exports, and trade promotion to help those companies expand and reach overseas markets. They’ve continued, so they’re still moving up the value chain as Japan has just stagnated.

The next recommendation you have for us is the best book about the quantitative side of industrial policy. This is The Politics of Large Numbers: A History of Statistical Reasoning by Alain Desrosières.

Industrial policy includes so many different facets, and I’m trying to pick one from every lens you might have to use in order to understand it. Statistics is a really important part of understanding industry and the state.

You may know this, but the word ‘statistics’ actually comes from the Latin statisticum, of the state, and the Italian word statista, which means statesman. The development of the state and statistics are synonymous with each other. You have to know who a population is. Who are these people—we need a census. What is our land—we need a cadastral survey, we need to actually look at the territory and understand it. What do we own, and how do we subdivide that? How do we create parcels so that people can buy a patch of land and give it to someone else?

Alain Desrosières is looking mostly at France, and he is investigating how statistics came to be from around the 1600s into the 1800s. He shows how it reflects the development of the French state at this period of time, which, similar to England and elsewhere in Europe, goes from this rural, feudal society of the Middle Ages into the modernity that we know today.

“The development of the state and statistics are synonymous with each other”

What he argues is that society transforms into an economy of measurement. One of the most striking early passages from the book is around the sheer scale of measurement in the modern economy. You have accounting, you have zoning, you have taxation, you have weights and measures. You have people who check that the gas pump is actually pumping the liter of petrol that you expect. You have to measure public health, like everything we’ve seen with COVID recently. That’s all a form of measurement.

How do we know how many people participate in the economy? And then as we get into the 1900s: how do we measure the GDP? How do we measure employment? We’re obviously focused on inflation these days, but all the inflation data is based around the consumer price index. How do we know that prices are the same for fruit and vegetables and bread compared to last month?

He’s really showing that the modern state could not exist without the development of statistics, and vice versa. The evolution of statistics is triggered by the state. As the state needs more systems in place, statistics come to back it up. Econometrics, as an example, came together in the 1930s as a fusion of economics and statistics, and it was triggered by the American New Deal. Suddenly we had all these new programs that the Roosevelt administration was launching, and we had no way of gauging whether any of them worked. So suddenly economists and statisticians said, ‘Okay, we need new methods to see if when we give farmers a certain amount of money in a certain period of time, that leads to positive gains—or not.’

So Desrosières’s whole book is focused on that evolution, and he has an amazing number of historical examples. It’s one of those completely eye-opening works that is really special.

This raises the question: Can we and should we trust the numbers?

There are obviously a lot of books on this. The sociology of quantification has gotten really, really large in the last decade. As we’ve seen the rise of the algorithm and machine learning, a lot of scholars are starting to ask, ‘What do you do about all these numbers and how much they impact our daily lives?’

One of the canonical works is Trust in Numbers. Theodore Porter, writing back in 1986, shows how it was really a choice for science to become the objective field it is today—physics, biology, etc. are all statistical in nature. People asked for objectivity and statistics offered the methods to get there. While statistics and quantification are not necessarily objective—you can massage the statistics, all statistics lie, “lies, damned lies and statistics” (as Disraeli supposedly said)—we’ve accepted as a culture that it feels like quantification is more objective than qualitative judgment.

That is arbitrary. It’s a cultural decision we have made as a society. One could easily argue that qualitative judgments are actually stronger and better than quantitative judgments. You’re including more facts because the human brain is better able to synthesize disparate pieces of information than a statistic can.

Porter really explains the context and situational development of quantification over the history of science and in public life. Presidents used to be guided by their instincts and by advice from advisors. Now, they look at the GDP numbers and survey polls and ask, ‘Are they up or down?’ Tough and complex decisions get narrowed to a single number that’s enticingly precise and yet limited.

We’ve lost something with the movement toward quantification and that’s really important in the context of industrial policy. On the one hand, there are all these stats available—this is why the Amsden book gets a little tough, you can look at all these spreadsheets and try to decide what to do. Or, we can take a step back and say, ‘What are we trying to accomplish as a nation? What are we trying to do?’ When you get into leadership around the economy, there’s this huge challenge of wanting to lead towards the future, but we obviously don’t know what it will be. Is quantum computing next, or will it be the metaverse?

I think that’s where critical studies of quantification can become a very important lens to say, ‘Look, sometimes spreadsheets are precise but wrong, and to allocate well you have to qualitatively synthesize what you can and make a decision that affects people in the best possible way.’

Your last selection for us is a lens on disasters, The Collapse of Complex Societies by Joseph Tainter. Can you tell us a little bit about this work?

This was hard. What I was trying to do is find a book that gets at the idea of rise and fall, which is intrinsic to economies. You could easily read some economic histories about Japan in the nineties, maybe even of China today and some of the struggles around the real estate industry there, to get a sense of a boom and bust. That comes with industrial policy.

I prefer Joseph Tainter’s work in The Collapse of Complex Societies, because it’s anthropological, a field we haven’t had on this list so far. (Alice Amsden is economics, The Politics of Large Numbers is from a sociology of statistics perspective, Lowen is coming from a historical point of view, and Kicking Away the Ladder is development and institutional economics). Now we’ve got anthropologists and we’re actually looking at individual humans and how they respond to things.

Tainter has a very simple theory, which is that most social systems start very simple, and we benefit a lot when they become complicated. We live in a modern economy where everyone hones a different skill. You are doing this interview, I am reading books. We were talking about a soufflé—a chef is making incredible food. I don’t know how to make a soufflé, but we both benefit from the fact that I make money somehow, you make money somehow, and we’re able to pay someone else to do something we can’t do. There are benefits to complexity. We actually want to create more complexity, more subdivisions of labor, more expertise, because then we’re able to trade it and do something magical.

But Tainter argues that there’s a certain point in almost any of these economic systems, or any society, where we go over the peak of benefits and start getting more and more uselessly complex over time. There’s a popular argument in progress studies and technology circles today that we can’t build anything in the United States. We want to build a subway line in New York and we just opened East Side Access, a 20-year project that was $12 billion in the making—in order to get a couple of suburban trains into Grand Central. It’s the most expensive subway station in the world.

What went so wrong? There are too many planners, too many designers, too many consultants, too many construction engineers. No one knows what they’re doing. No one has experienced building a subway in a generation. So it costs astronomical sums as everyone gropes for an answer.

I think that’s really important, because when we’re setting an industrial policy, a lot of the argument is that you have to be quick. You’ve got to allocate effectively, it’s got to go to the right people. If any of that goes wrong, it doesn’t really work. Tainter is saying: this is what it looks like when it fails. Things get really bureaucratic. They get extremely slow. Money’s not getting allocated well.

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Look at the European Union. Some industrial policy obviously happens there, but a lot of folks would say the European Union has not done well in building up its industry. It’s not a lead in fabs and semiconductors, it doesn’t have a lead in a lot of other industries. East Asia has hollowed out the core of industry in Europe, particularly in Britain and France, less so in Germany.

What went wrong? Well, if you have multiple levels of government, they’re not interacting with each other, there’s all this complexity, and you actually spend more time on the complexity itself than the actual building. That’s a huge problem.

What is the case study in The Collapse of Complex Societies? Which societies is Tainter looking at?

Tainter has a lot of examples. He’s looking at everything from Mesoamerica and the Mayans to Mesopotamia and a lot of the civilizations there, as well as China and some of the dynasties that have collapsed. He has more than a dozen civilizations he’s analyzing.

He’s trying to develop a theory of why these civilizations or societies rise and then fall. And what he tries to show is that too much complexity leads to the decline of a lot of these civilizations. The bureaucracy becomes too intense.

In China, you see this with a lot of the dynasties. They start taxing fairly low, and then it reaches this pinnacle where you’re taxing too much and no one can actually make any money, people underinvest, and then the regime or the dynasty falls. He’s interconnecting a lot of different examples.

It was well received. It’s been popular more recently, for various reasons. Everyone thinks we’re at the end of times, particularly during and after COVID.

I’m not sure it’s a perfect book, but I do think it has a lot of good insights. What I particularly loved was a section where he describes how you really have to do this using statistics. He’s more on the quantitative side. You can always feel, ‘Oh, it’s the worst time, we’re about to collapse,’ and the reality is that, for example, the Romans said that and then it took 400 years. Generations went by and everything was fine. So you just never know unless you’re really looking at the math, and thus he’s arguing for the benefit of statistical work. Quantification rears its head again!

I’m seeing a slight theme on the topic of rising and falling: people do things that seem to work for some period of time. Would you say that the issue is becoming entrenched in doing the things that got you to where you are now, but which are no longer relevant? 

Tainter’s book is probably the best argument against industrial policy. It’s one that’s maybe most relevant to the United States in particular because entrenched interests become really hard to un-entrench when a policy or approach needs to move on.

So if the last decade in technology was the rise of social media, and that was where the action was, now it’s AI. Yes, there are overlaps, and there are people who might be borrowed from one to the next, but every field starts from scratch. In the artificial intelligence world today, you need chips, you need fabs. You need to program these large language models. It’s a totally different industry than the one that we’re just coming from. That means you need an entirely different set of incentives, of approaches, of thinking about it.

What often happens, particularly in the US where lobbying is very effective, is that you can’t beat the fact that the last industry was successful and has money. We keep wanting to print money with the old money machine that we used to make it with in the past. Industrial policy is about being done and saying, ‘Okay, that’s over, you’re on your own now. We need to move on to the next thing.’

If you look at South Korea in particular, the government is really good at moving on. There’s definitely a survival-of-the-fittest mentality. They’re like, ‘Look, you are in place, you are competitive. It’s up to you to keep going. We’re not going to keep subsidizing this. We’re not going to keep protecting you. You must be market driven. At some point, you must compete and win. We’ve gotten you to that point and our job here is done.’ Then they walk away and go on to the next industry.

The challenge in the United States—and less so but also in Europe—is entrenchment. It’s lobbying of Congress. We see this particularly in defense. Defense is a huge part of industrial policy for the United States. We build a fighter jet in 50 states because we want to cover every congressional district. We want to make sure everyone has a little bit of their hand in the till, so to speak, so the program doesn’t get canceled.

This leads to these suboptimal outcomes where the Navy will recommend—this was reported a couple of weeks ago— that the littoral combat ship be decommissioned because it doesn’t work and we don’t need it anymore. But we’re going to maintain it anyway for another 25 years because maintenance jobs are affected in all these different congressional districts. There’s no way to get rid of it.

That’s the challenge for a lot of folks who do industrial policy today in the United States. On the one hand, there are clearly a lot of industries that would benefit from more industrial policy. On the other hand, we have never proven ourselves capable of letting go when we need to let go. So you have a little bit of pragmatism from some folks who say, ‘We should never do it to begin with because we’re always going to end up in some terrible situation at the end’ versus those who are a little bit more idealistic who say, ‘No, we can get it right. There’s a lot of benefit from this.’ I’m a pragmatist, but I wish the idealists would win every now and then—imagine what we could build!

Interview by Uri Bram

April 1, 2023

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Danny Crichton

Danny Crichton

Danny Crichton is head of editorial at venture capital firm Lux Capital. Previously, he was managing editor at TechCrunch.

Danny Crichton

Danny Crichton

Danny Crichton is head of editorial at venture capital firm Lux Capital. Previously, he was managing editor at TechCrunch.