TopPodcast.com
Menu
  • Home
  • Top Charts
  • Top Networks
  • Top Apps
  • Top Independents
  • Top Podfluencers
  • Top Picks
    • Top Business Podcasts
    • Top True Crime Podcasts
    • Top Finance Podcasts
    • Top Comedy Podcasts
    • Top Music Podcasts
    • Top Womens Podcasts
    • Top Kids Podcasts
    • Top Sports Podcasts
    • Top News Podcasts
    • Top Tech Podcasts
    • Top Crypto Podcasts
    • Top Entrepreneurial Podcasts
    • Top Fantasy Sports Podcasts
    • Top Political Podcasts
    • Top Science Podcasts
    • Top Self Help Podcasts
    • Top Sports Betting Podcasts
    • Top Stocks Podcasts
  • Podcast News
  • About Us
  • Podcast Advertising
  • Contact
Not in our directory?
Add Show Here
Podcast Equipment
Center

toppodcastlogoOur TOPPODCAST Picks

  • Comedy
  • Crypto
  • Sports
  • News
  • Politics
  • True Crime
  • Business
  • Finance

Follow Us

toppodcastlogoStay Connected

    View Top 200 Chart
    Back to Rankings Page
    Technology

    Faster, Please! — The Podcast

    Welcome to Faster, Please! — The Podcast. Several times a month, host Jim Pethokoukis will feature a lively conversation with a fascinating and provocative guest about how to make the world a better place by accelerating scientific discovery, technological innovation, and economic growth.

    fasterplease.substack.com

    Advertise

    Copyright: © James Pethokoukis

    • Apple Podcasts
    • Google Play
    • Spotify

    Latest Episodes:
    ✨🔬 Acceleration though AI-automated R&D: My chat (+transcript) with researcher Tom Davidson Nov 20, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers in America and around the world:What really gets AI optimists excited isn’t the prospect of automating customer service departments or human resources. Imagine, rather, what might happen to the pace of scientific progress if AI becomes a super research assistant. Tom Davidson’s new paper, How Quick and Big Would a Software Intelligence Explosion Be?, explores that very scenario.Today on Faster, Please! — The Podcast, I talk with Davidson about what it would mean for automated AI researchers to rapidly improve their own algorithms, thus creating a self-reinforcing loop of innovation. We talk about the economic effects of self-improving AI research and how close we are to that reality.Davidson is a senior research fellow at Forethought, where he explores AI and explosive growth. He was previously a senior research fellow at Open Philanthropy and a research scientist at the UK government’s AI Security Institute.In This Episode* Making human minds (1:43)* Theory to reality (6:45)* The world with automated research (10:59)* Considering constraints (16:30)* Worries and what-ifs (19:07)Below is a lightly edited transcript of our conversation. Making human minds (1:43). . . you don’t have to build any more computer chips, you don’t have to build any more fabs . . . In fact, you don’t have to do anything at all in the physical world.Pethokoukis: A few years ago, you wrote a paper called “Could Advanced AI Drive Explosive Economic Growth?,” which argued that growth could accelerate dramatically if AI would start generating ideas the way human researchers once did. In your view, population growth historically powered kind of an ideas feedback loop. More people meant more researchers meant more ideas, rising incomes, but that loop broke after the demographic transition in the late-19th century but you suggest that AI could restart it: more ideas, more output, more AI, more ideas. Does this new paper in a way build upon that paper?“How quick and big would a software intelligence explosion be?”The first paper you referred to is about the biggest-picture dynamic of economic growth. As you said, throughout the long run history, when we produced more food, the population increased. That additional output transferred itself into more people, more workers. These days that doesn’t happen. When GDP goes up, that doesn’t mean people have more kids. In fact, the demographic transition, the richer people get, the fewer kids they have. So now we’ve got more output, we’re getting even fewer people as a result, so that’s been blocked.This first paper is basically saying, look, if we can manufacture human minds or human-equivalent minds in any way, be it by building more computer chips, or making better computer chips, or any way at all, then that feedback loop gets going again. Because if we can manufacture more human minds, then we can spend output again to create more workers. That’s the first paper.The second paper double clicks on one specific way that we can use output to create more human minds. It’s actually, in a way, the scariest way because it’s the way of creating human minds which can happen the quickest. So this is the way where you don’t have to build any more computer chips, you don’t have to build any more fabs, as they’re called, these big factories that make computer chips. In fact, you don’t have to do anything at all in the physical world.It seems like most of the conversation has been about how much investment is going to go into building how many new data centers, and that seems like that is almost the entire conversation, in a way, at the moment. But you’re not looking at compute, you’re looking at software.Exactly, software. So the idea is you don’t have to build anything. You’ve already got loads of computer chips and you just make the algorithms that run the AIs on those computer chips more efficient. This is already happening, but it isn’t yet a big deal because AI isn’t that capable. But already, one year out, Epoch, this AI forecasting organization, estimates that just in one year, it becomes 10 times to 1000 times cheaper to run the same AI system. Just wait 12 months, and suddenly, for the same budget, you are able to run 10 times as many AI systems, or maybe even 1000 times as many for their most aggressive estimate. As I said, not a big deal today, but if we then develop an AI system which is better than any human at doing research, then now, in 10 months, you haven’t built anything, but you’ve got 10 times as many researchers that you can set to work or even more than that. So then we get this feedback loop where you make some research progress, you improve your algorithms, now you’ve got loads more researchers, you set them all to work again, finding even more algorithmic improvements. So today we’ve got maybe a few hundred people that are advancing state-of-the-art AI algorithms.I think they’re all getting paid a billion dollars a person, too.Exactly. But maybe we can 10x that initially by having them replaced by AI researchers that do the same thing. But then those AI researchers improve their own algorithms. Now you have 10x as many again, you have them building more computer chips, you’re just running them more efficiently, and then the cycle continues. You’re throwing more and more of these AI researchers at AI progress itself, and the algorithms are improving in what might be a very powerful feedback loop.In this case, it seems me that you’re not necessarily talking about artificial general intelligence. This is certainly a powerful intelligence, but it’s narrow. It doesn’t have to do everything, it doesn’t have to play chess, it just has to be able to do research.It’s certainly not fully general. You don’t need it to be able to control a robot body. You don’t need it to be able to solve the Riemann hypothesis. You don’t need it to be able to even be very persuasive or charismatic to a human. It’s not narrow, I wouldn’t say, it has to be able to do literally anything that AI researchers do, and that’s a wide range of tasks: They’re coding, they’re communicating with each other, they’re managing people, they are planning out what to work on, they are thinking about reviewing the literature. There’s a fairly wide range of stuff. It’s extremely challenging. It’s some of the hardest work in the world to do, so I wouldn’t say it’s now, but it’s not everything. It’s some kind of intermediate level of generality in between a mere chess algorithm that just does chess and the kind of AGI that can literally do anything.Theory to reality (6:45)I think it’s a much smaller gap for AI research than it is for many other parts of the economy.I think people who are cautiously optimistic about AI will say something like, “Yeah, I could see the kind of intelligence you’re referring to coming about within a decade, but it’s going to take a couple of big breakthroughs to get there.” Is that true, or are we actually getting pretty close?Famously, predicting the future of technology is very, very difficult. Just a few years before people invented the nuclear bomb, famous, very well-respected physicists were saying, “It’s impossible, this will never happen.” So my best guess is that we do need a couple of fairly non-trivial breakthroughs. So we had the start of RL training a couple of years ago, became a big deal within the language model paradigm. I think we’ll probably need another couple of breakthroughs of that kind of size.We’re not talking a completely new approach, throw everything out, but we’re talking like, okay, we need to extend the current approach in a meaningfully different way. It’s going to take some inventiveness, it’s going to take some creativity, we’re going to have to try out a few things. I think, probably, we’ll need that to get to the researcher that can fully automate OpenAI, is a nice way of putting it — OpenAI doesn’t employ any humans anymore, they’ve just got AIs there.There’s a difference between what a model can do on some benchmark versus becoming actually productive in the real world. That’s why, while all the benchmark stuff is interesting, the thing I pay attention to is: How are businesses beginning to use this technology? Because that’s the leap. What is that gap like, in your scenario, versus an AI model that can do a theoretical version of the lab to actually be incorporated in a real laboratory?It’s definitely a gap. I think it’s a pretty big gap. I think it’s a much smaller gap for AI research than it is for many other parts of the economy. Let’s say we are talking about car manufacturing and you’re trying to get an AI to do everything that happens there. Man, it’s such a messy process. There’s a million different parts of the supply chain. There’s all this tacit knowledge and all the human workers’ minds. It’s going to be really tough. There’s going to be a very big gap going from those benchmarks to actually fully automating the supply chain for cars.For automating what OpenAI does, there’s still a gap, but it’s much smaller, because firstly, all of the work is virtual. Everyone at OpenAI could, in principle, work remotely. Their top research scientists, they’re just on a computer all day. They’re not picking up bricks and doing stuff like that. So also that already means it’s a lot less messy. You get a lot less of that kind of messy world reality stuff slowing down adoption. And also, a lot of it is coding, and coding is almost uniquely clean in that, for many coding tasks, you can define clearly defined metrics for success, and so that makes AI much better. You can just have a go. Did AI succeed in the test? If not, try something else or do a gradient set update.That said, there’s still a lot of messiness here, as any coder will know, when you’re writing good code, it’s not just about whether it does the function that you’ve asked it to do, it needs to be well-designed, it needs to be modular, it needs to be maintainable. These things are much harder to evaluate, and so AIs often pass our benchmarks because they can do the function that you asked it to do, the code runs, but they kind of write really spaghetti code — code that no one wants to look at, that no one can understand, and so no company would want to use that.So there’s still going to be a pretty big benchmark-to-reality gap, even for OpenAI, and I think that’s one of the big uncertainties in terms of, will this happen in three years versus will this happen in 10 years, or even 15 years?Since you brought up the timeline, what’s your guess? I didn’t know whether to open with that question or conclude with that question — we’ll stick it right in the middle of our chat.Great. Honestly, my best guess about this does change more often than I would like it to, which I think tells us, look, there’s still a state of flux. This is just really something that’s very hard to know about. Predicting the future is hard. My current best guess is it’s about even odds that we’re able to fully automate OpenAI within the next 10 years. So maybe that’s a 50-50.The world with AI research automation (10:59). . . I’m talking about 30 percent growth every year. I think it gets faster than that. If you want to know how fast it eventually gets, you can think about the question of how fast can a kind of self-replicating system double itself?So then what really would be the impact of that kind of AI research automation? How would you go about quantifying that kind of acceleration? What does the world look like?Yeah, so many possibilities, but I think what strikes me is that there is a plausible world where it is just way, way faster than almost everyone is expecting it to be. So that’s the world where you fully automate OpenAI, and then we get that feedback loop that I was talking about earlier where AIs make their algorithms way more efficient, now you’ve got way more of them, then they make their algorithms way more efficient again, now they’re way smarter. Now they’re thinking a hundred times faster. The feedback loop continues and maybe within six months you now have a billion superintelligent AIs running on this OpenAI data center. The combined cognitive abilities of all these AIs outstrips the whole of the United States, outstrips anything we’ve seen from any kind of company or entity before, and they can all potentially be put towards any goal that OpenAI wants to. And then there’s, of course, the risk that OpenAI’s lost control of these systems, often discussed, in which case these systems could all be working together to pursue a particular goal. And so what we’re talking about here is really a huge amount of power. It’s a threat to national security for any government in which this happens, potentially. It is a threat to everyone if we lose control of these systems, or if the company that develops them uses them for some kind of malicious end. And, in terms of economic impacts, I personally think that that again could happen much more quickly than people think, and we can get into that.In the first paper we mentioned, it was kind of a thought experiment, but you were really talking about moving the decimal point in GDP growth, instead of talking about two and three percent, 20 and 30 percent. Is that the kind of world we’re talking about?I speak to economists a lot, and —They hate those kinds of predictions, by the way.Obviously, they think I’m crazy. Not all of them. There are economists that take it very seriously. I think it’s taken more seriously than everyone else realizes. It’s like it’s a bit embarrassing, at the moment, to admit that you take it seriously, but there are a few really senior economists who absolutely know their stuff. They’re like, “Yep, this checks out. I think that’s what’s going to happen.” And I’ve had conversation with them where they’re like, “Yeah, I think this is going to happen.” But the really loud, dominant view where I think people are a little bit scared to speak out against is they’re like, “Obviously this is sci-fi.”One analogy I like to give to people who are very, very confident that this is all sci-fi and it’s rubbish is to imagine that we were sitting there in the year 1400, imagine we had an economics professor who’d been studying the rate of economic growth, and they’ve been like, “Yeah, we’ve always had 0.1 percent growth every single year throughout history. We’ve never seen anything higher.” And then there was some kind of futurist economist rogue that said, “Actually, I think that if I extrapolate the curves in this way and we get this kind of technology, maybe we could have one percent growth.” And then all the other economists laugh at them, tell them they’re insane – that’s what happened. In 1400, we’d never had growth that was at all fast, and then a few hundred years later, we developed industrial technology, we started that feedback loop, we were investing more and more resources in scientific progress and in physical capital, and we did see much faster growth.So I think it can be useful to try and challenge economists and say, “Okay, I know it sounds crazy, but history was crazy. This crazy thing happened where growth just got way, way faster. No one would’ve predicted it. You would not have predicted it.” And I think being in that mindset can encourage people to be like, “Yeah, okay. You know what? Maybe if we do get AI that’s really that powerful, it can really do everything, and maybe it is possible.”But to answer your question, yeah, I’m talking about 30 percent growth every year. I think it gets faster than that. If you want to know how fast it eventually gets, you can think about the question of how fast can a kind of self-replicating system double itself? So ultimately, what the economy is going to be like is it’s going to have robots and factories that are able to fully create new versions of themselves. Everything you need: the roads, the electricity, the robots, the buildings, all of that will be rep…

    Full show notes at the publisher

    🚀 The trillion-dollar space race: My chat (+transcript) with journalist Christian Davenport Nov 04, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,China’s spacefaring ambitions pose tough competition for America. With a focused, centralized program, Beijing seems likely to land taikonauts on the moon before another American flag is planted. Meanwhile, NASA faces budget cuts, leadership gaps, and technical setbacks. In his new book, journalist Christian Davenport chronicles the fierce rivalry between American firms, mainly SpaceX and Blue Origin. It’s a contest that, despite the challenges, promises to propel humanity to the moon, Mars, and maybe beyond.Davenport is an author and a reporter for the Washington Post, where he covers NASA and the space industry. His new book, Rocket Dreams: Musk, Bezos, and the Inside Story of the New, Trillion-Dollar Space Race, is out now.In This Episode* Check-in on NASA (1:28)* Losing the Space Race (5:49)* A fatal flaw (9:31)* State of play (13:33)* The long-term vision (18:37)* The pace of progress (22:50)* Friendly competition (24:53)Below is a lightly edited transcript of our conversation. Check-in on NASA (1:28)The Chinese tend to do what they say they’re going to do on the timeline that they say they’re going to do it. That said, they haven’t gone to the moon . . . It’s really hard.Pethokoukis: As someone — and I’m speaking about myself — who wants to get America back to the moon as soon as possible, get cooking on getting humans to Mars for the first time, what should I make of what’s happening at NASA right now?They don’t have a lander. I’m not sure the rocket itself is ready to go all the way, we’ll find out some more fairly soon with Artemis II. We have flux with leadership, maybe it’s going to not be an independent-like agency anymore, it’s going to join the Department of Transportation.It all seems a little chaotic. I’m a little worried. Should I be?Davenport: Yes, I think you should be. And I think a lot of the American public isn’t paying attention and they’re going to see the Artemis II mission, which you mentioned, and that’s that mission to send a crew of astronauts around the moon. It won’t land on the moon, but it’ll go around, and I think if that goes well, NASA’s going to take a victory leap. But as you correctly point out, that is a far cry from getting astronauts back on the lunar surface.The lander isn’t ready. SpaceX, as acting NASA administrator Sean Duffy just said, is far behind, reversing himself from like a month earlier when he said no, they appear to be on track, but everybody knew that they were well behind because they’ve had 11 test flights, and they still haven’t made it to orbit with their Starship rocket.The rocket itself that’s going to launch them into the vicinity of the moon, the SLS, launches about once every two years. It’s incredibly expensive, it’s not reusable, and there are problems within the agency itself. There are deep cuts to it. A lot of expertise is taking early retirements. It doesn’t have a full-time leader. It hasn’t had a full-time leader since Trump won the election. At the same time, they’re sort of beating the drum saying we’re going to beat the Chinese back to the lunar surface, but I think a lot of people are increasingly looking at that with some serious concern and doubt.For what it’s worth, when I looked at the betting markets, it gave the Chinese a two-to-one edge. It said that it was about a 65 percent chance they were going to get there first. Does that sound about right to you?I’m not much of a betting man, but I do think there’s a very good chance. The Chinese tend to do what they say they’re going to do on the timeline that they say they’re going to do it. That said, they haven’t gone to the moon, they haven’t done this. It’s really hard. They’re much more secretive, if they have setbacks and delays, we don’t necessarily know about them. But they’ve shown over the last 10, 20 years how capable they are. They have a space station in low earth orbit. They’ve operated a rover on Mars. They’ve gone to the far side of the moon twice, which nobody has done, and brought back a sample return. They’ve shown the ability to keep people alive in space for extended periods of times on the space station.The moon seems within their capabilities and they’re saying they’re going to do it by 2030, and they don’t have the nettlesome problem of democracy where you’ve got one party come in and changing the budget, changing the direction for NASA, changing leadership. They’ve just set the moon — and, by the way, the south pole of the moon, which is where we want to go as well — as the destination and have been beating a path toward that for several years now.Is there anyone for merging NASA into the Department of Transportation? Is there a hidden reservoir? Is that an idea people have been talking about now that’s suddenly emerged to the surface?It’s not something that I particularly heard. The FAA is going to regulate the launches, and they coordinate with the airspace and make sure that the air traffic goes around it, but I think NASA has a particular expertise. Rocket science is rocket science — it’s really difficult. This isn’t for the faint of heart.I think a lot of people look at human space flight and it’s romanticized. It’s romanticized in books and movies and in popular culture, but the fact of the matter is it’s really, really hard, it’s really dangerous, every time a human being gets on one of those rockets, there’s a chance of an explosion, of something really, really bad happening, because a million things have to go right in order for them to have a successful flight. The FAA does a wonderful job managing — or, depending on your point of view, some people don’t think they do such a great job, but I think space is a whole different realm, for sure.Losing the Space Race (5:49). . . the American flags that the Apollo astronauts planted, they’re basically no longer there anymore. . . There are, however, two Chinese flags on the moonHave you thought about what it will look like the day after, in this country, if China gets to the moon first and we have not returned there yet?Actually, that’s a scenario I kind of paint out. I’ve got this new book called Rocket Dreams and we talk about the geopolitical tensions in there. Not to give too much of a spoiler, but NASA has said that the first person to return to the moon, for the US, is going to be a woman. And there’s a lot of people thinking, who could that be? It could be Jessica Meir, who is a mother and posted a picture of herself pregnant and saying, “This is what an astronaut looks like.” But it could very well be someone like Wang Yaping, who’s also a mother, and she came back from one of her stays on the International Space Station and had a message for her daughter that said, “I come back bringing all the stars for you.” So I think that I could see China doing it and sending a woman, and that moment where that would be a huge coup for them, and that would obviously be symbolic.But when you’re talking about space as a tool of soft power and diplomacy, I think it would attract a lot of other nations to their side who are sort of waiting on the sidelines or who frankly aren’t on the sidelines, who have signed on to go to the United States, but are going to say, “Well, they’re there and you’re not, so that’s who we’re going to go with.”I think about the wonderful alt-history showFor All Mankind, which begins with the Soviets beating the US to the moon, and instead of Neil Armstrong giving the “one small step for man,” basically the Russian cosmonaut gives, “Its one small step for Marxism-Leninism,” and it was a bummer. And I really imagine that day, if China beats us, it is going to be not just, “Oh, I guess now we have to share the moon with someone else,” but it’s going to cause some national soul searching.And there are clues to this, and actually I detail these two anecdotes in the book, that all of the flags, the American flags that the Apollo astronauts planted, they’re basically no longer there anymore. We know from Buzz Aldrin‘s memoir that the flag that he and Neil Armstrong planted in the lunar soil in 1969, Buzz said that he saw it get knocked over by the thrust in the exhaust of the module lifting off from the lunar surface. Even if that hadn’t happened, just the radiation environment would’ve bleached the flag white, as scientists believe it has to all the other flags that are on there. So there are essentially really no trace of the Apollo flags.There are, however, two Chinese flags on the moon, and the first one, which was planted a couple of years ago, or unveiled a couple of years ago, was made not of cloth, but their scientists and engineers spent a year building a composite material flag designed specifically to withstand the harsh environment of the moon. When they went back last summer for their farside sample return mission, they built a flag, — and this is pretty amazing — out of basalt, like volcanic rock, which you find on Earth. And they use basalt from earth, but of course basalt is common on the moon. They were able to take the rock, turn it into lava, extract threads from the lava and weave this flag, which is now near the south pole of the moon. The significance of that is they are showing that they can use the resources of the moon, the basalt, to build flags. It’s called ISR: in situ resource utilization. So to me, nothing symbolizes their intentions more than that.A fatal flaw (9:31). . . I tend to think if it’s a NASA launch . . . and there’s an explosion . . . I still think there are going to be investigations, congressional reports, I do think things would slow down dramatically.In the book, you really suggest a new sort of golden age of space. We have multiple countries launching. We seem to have reusable rockets here in the United States. A lot of plans to go to the moon. How sustainable is this economically? And I also wonder what happens if we have another fatal accident in this country? Is there so much to be gained — whether it’s economically, or national security, or national pride in space — that this return to space by humanity will just go forward almost no matter what?I think so. I think you’ve seen a dramatic reduction in the cost of launch. SpaceX and the Falcon 9, the reusable rocket, has dropped launches down. It used to be if you got 10, 12 orbital rocket launches in a year, that was a good year. SpaceX is launching about every 48 hours now. It’s unprecedented what they’ve done. You’re seeing a lot of new players — Blue Origin, Rocket Lab, others — driving down the cost of launch.That said, the main anchor tenant customer, the force driving all of this is still the government, it’s still NASA, it’s still the Pentagon. There is not a self-sustaining space economy that exists in addition or above and beyond the government. You’re starting to see bits of that, but really it’s the government that’s driving it.When you talk about the movie For All Mankind, you sort of wonder if at one point, what happened in that movie is there was a huge investment into NASA by the government, and you’re seeing that to some extent today, not so much with NASA, but actually on the national security side and the creation of the Space Force and the increases, just recently, in the Space Force’s budget. I mean, my gosh, if you have $25 billion for this year alone for Golden Dome, the Missile Defense Shield, that’s the equivalent of NASA’s entire budget. That’s the sort of funding that helps build those capabilities going forward.And if we should, God forbid, have a fatal accident, you think we’ll just say that’s the cost of human exploration and forward we go?I think a lot about this, and the answer is, I don’t know. When we had Challenger and we had Columbia, the world stopped, and the Space Shuttle was grounded for months if not a year at a time, and the world just came to an end. And you wonder now if it’s becoming more routine and what happens? Do we just sort of carry on in that way?It’s not a perfect analogy, but when you talk about commercial astronauts, these rich people are paying a lot of money to go, and if there’s an accident there, what would happen? I think about that, and you think about Mount Everest. The people climbing Mount Everest today, those mountain tourists are literally stepping over dead bodies as they’re going up to the summit, and nobody’s shutting down Mount Everest, they’re just saying, well, if you want to climb Mount Everest, that’s the risk you take. I do wonder if we’re going to get that to that point in space flight, but I tend to think if it’s a NASA launch, and it’s NASA astronauts, and there’s an explosion, and there’s a very bad day, I still think there are going to be investigations, congressional reports, I do think things would slow down dramatically.The thing is, if it’s SpaceX, they have had accidents. They’ve had multiple accidents — not with people, thank goodness — and they have been grounded.It is part of the model.It’s part of the model, and they have shown how they can find out what went wrong, fix it, and return to flight, and they know their rocket so well because they fly it so frequently. They know it that well, and NASA, despite what you think about Elon, NASA really, really trusts SpaceX and they get along really well.State of play (13:33)[Blue Origin is] way behind for myriad reasons. They sat out while SpaceX is launching the Falcon 9 every couple of days . . . Blue Origin, meanwhile, has flown its New Glenn rocket one time.I was under the impression that Blue Origin was way behind SpaceX. Are they catching up?This is one of the themes of the book. They are way behind for myriad reasons. They sat out while SpaceX is launching the Falcon 9 every couple of days, they’re pushing ahead with Starship, their next generation rocket would be fully reusable, twice the thrust and power of the Saturn V rocket that flew the Apollo astronauts to the Moon. Blue Origin, meanwhile, has flown its New Glenn rocket one time. They might be launching again soon within the coming weeks or months, hopefully by the end of the year, but that’s two. They are so far behind, but you do hear Jeff Bezos being much more tuned into the company. He has a new CEO — a newish CEO — plucked from the ranks of Amazon, Dave Limp, and you do sort of see them charging, and now that the acting NASA administrator has sort of opened up the competition to go to the moon, I don’t know that Blue Origin beats SpaceX to do it, but it gives them some incentive to move fast, which I think they really need.I know it’s only a guess and it’s only speculation, but when we return to the moon, which company will have built that lander?At this point, you have to put your money on SpaceX just because they’re further along in their development. They’ve flown humans before. They know how to keep people alive in space. In their Dragon capsule, they have the rendezvous and proximity operations, they know how to dock. That’s it.Blue Origin has their uncrewed lander, the Mark 1 version that they hope to land on the moon next year, so it’s entirely possible that Blue Origin actually lands a spacecraft on the lunar surface before SpaceX, and that would be a big deal. I don’t know that they’re able to return humans there, however, before SpaceX.Do you think there’s any regrets by Jeff Bezos about how Blue Origin has gone about its business here? Because obviously it really seems like it’s a very different approach, and maybe the Blue Origin approach, if we look back 10 years, will seem to have been the better approach, but given where we are now and what you just described, would you guess that he’s deeply disappointed with the kind of progress they made via SpaceX?Yeah, and he’s been frustrated. Actually, the opening scene of the book is Jeff being upset that SpaceX is so far ahead and having pursued a partnership with NASA to fly cargo and supply to the International Space Station and then to fly astronauts to the Internationa…

    Full show notes at the publisher

    🤖 Thoughts of a (rare) free-market AI doomer: My chat (+transcript) with economist James Miller Oct 24, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,Some Faster, Please! readers have told me I spend too little time on the downsides of AI. If you’re one of those folks, today is your day. On this episode of Faster, Please! — The Podcast, I talk with self-described “free-market AI doomer” James Miller. Miller and I talk about the risks inherent with super-smart AI, some possible outcomes of a world of artificial general intelligence, and why government seems uninterested in the existential risk conversation.Miller is a professor at Smith College where he teaches law and economics, game theory, and the economics of future technology. He has his own podcast, Future Strategist, and a great YouTube series on game theory and intro to microeconomics. On X (Twitter), you can find him at @JimDMiller.In This Episode* Questioning the free market (1:33)* Reading the markets (7:24)* Death (or worse) by AI (10:25)* Friend and foe (13:05)* Pumping the breaks (20:36)* The only policy issue (24:32)Below is a lightly edited transcript of our conversation. Questioning the free market (1:33)Most technologies have gone fairly well and we adapt . . . I’m of the belief that this is different.Pethokoukis: What does it mean to be a free-market AI doomer and why do you think it’s important to put in the “free-market” descriptor?Miller: It really means to be very confused. I’m 58, and I was basically one of the socialists when I was young, studied markets, became a committed free-market person, think they’re great for economic growth, great for making everyone better off — and then I became an AI doomer, like wait, markets are pushing us towards more and more technology, but I happen to think that AI is eventually going to lead to destruction of humanity. So it means to kind of reverse everything — I guess it’s the equivalent of losing faith in your religion.Is this a post-ChatGPT, November 2022 phenomenon?Well, I’ve lost hope since then. The analogy is we’re on a plane, we don’t know how to land, but hopefully we’ll be able to fly for quite a bit longer before we have to. Now I think we’ve got to land soon and there doesn’t seem to be an easy way of doing it. So yeah, the faster AI has gone — and certainly ChatGPT has been an amazing advance — the less time I think we have and the less time I think we can get it right. What really scared me, though, was the Chinese LLMs. I think you really need coordination among all the players and it’s going to be so much harder to coordinate now that we absolutely need China to be involved, in my opinion, to have any hope of surviving for the next decade.When I speak to people from Silicon Valley, there may be some difference about timelines, but there seems to be little doubt that — whether it’s the end of the 2020s or the end of the 2030s — there will be a technology worthy of being called artificial general intelligence or superintelligence.Certainly, I feel like when I talk to economists, whether it’s on Wall Street or in Washington, think tanks, they tend to speak about AI as a general purpose technology like the computer, the internet, electricity, in short, something we’ve seen before and there’s, and as far as something beyond that, certainly the skepticism is far higher. What are your fellow economists who aren’t in California missing?I think you’re properly characterizing it, I’m definitely an outlier. Most technologies have gone fairly well and we adapt, and economists believe in the difference between the seen and the unseen. It’s really easy to see how technologies, for example, can destroy jobs — harder to see new jobs that get created, but new jobs keep getting created. I’m of the belief that this is different. The best way to predict the future is to go by trends, and I fully admit, if you go by trends, you shouldn’t be an AI doomer — but not all trends apply.I think that’s why economists were much better at modeling the past and modeling old technologies. They’re naturally thinking this is going to be similar, but I don’t think that it is, and I think the key difference is that we’re not going to be in control. We’re creating something smarter than us. So it’s not like having a better rifle and saying it’ll be like old rifles — it’s like, “Hey, let’s have mercenaries run our entire army.” That creates a whole new set of risks that having better rifles does not.I’m certainly not a computer scientist, I would never call myself a technologist, so I’m very cautious about making any kind of predictions about what this technology can be, where it can go. Why do you seem fairly certain that we’re going to get at a point where we will have a technology beyond our control? Set aside whether it will mean a bad thing happens, why are you confident that the technology itself will be worthy of being called general intelligence or superintelligence?Looking at the trends, Scott Aronson, who is one of the top computer scientists in the world just on Twitter a few days ago, was mentioning how GPT-5 helped improve a new result. So I think we’re close to the highest levels of human intellectual achievement, but it would be a massively weird coincidence if the highest humans could get was also the highest AIs could get. We have lots of limitations that an AI doesn’t.I think a good analogy would be like chess, where for a while, the best chess players were human and now we’re at the point where chess programs are so good that humans add absolutely nothing to them. And I just think the same is likely to happen, these programs keep getting better.The other thing is, as an economist, I think it is impossible to be completely accurate about predicting the future, but stock markets are, on average, pretty good, and as I’m sure you know, literally trillions of dollars are being bet on this technology working. So the people that have a huge incentive to get this right, think, yeah, this is the biggest thing ever. If the top companies, Nvidia was worth a $100 million, yeah, maybe they’re not sure, but it’s the most valuable company in the world right now. That’s the wisdom of the markets, which I still believe in, that the markets are saying, “We think this is probably going to work.”Reading the markets (7:24). . . for most final goals an AI would have, it would have intermediate goals such as gaining power, not being turned off, wanting resources, wanting compute. Do you think the bond market’s saying the same thing? It seems to me that the stock market might be saying something about AI and having great potential, but to me, I look at the bond markets, that doesn’t seem so clear to me.I haven’t been looking at the bond markets for that kind of signal, so I don’t know.I guess you can make the argument that if we were really going to see this acceleration, that means we’re going to need a huge demand for capital and we would see higher interest rates, and I’m not sure you really see the evidence so far. It doesn’t mean you’re wrong by any means. I think there’s maybe two different messages. Figuring out what the market’s doing at any point in time is pretty tricky business.If we think through what happens if AI succeeds, it’s a little weird where there’s this huge demand for capital, but also AI could destroy the value of money, in part by destroying us. You might be right about the bond market message. I’m paying more attention to the stock market messages, there’s a lot of things going on with the bond markets.So the next step is that you’re looking at the trend of the technology, but then there’s the issue of “Well, why be negative about it? Why assume this scenario where bad things would happen, why not good things would happen?That’s a great question and it’s one almost never addressed, and it goes by the concept of instrumental convergence. I don’t know what the goals of AI are going to be. Nobody does, because they’re programed using machine learning, we don’t know what they really want, that’s why they do weird things. So I don’t know its final goals, but I do know that, for most final goals an AI would have, it would have intermediate goals such as gaining power, not being turned off, wanting resources, wanting compute. Well, the easiest way for an AI to generate lots of computing power is to build lots of data centers. The best way of doing that is probably going to poison the atmosphere for us. So for pretty much anything, if an AI is merely indifferent to us, we’re dead.I always feel like I’m asking someone to jump through a hoop when I ask them about any kind of timeline, but what is your sense of it?We know the best models released can help the top scientists with their work. We don’t know how good the best unreleased models are. The top models, you pay like $200 a month — they can’t be giving you that much compute for that. So right now, if OpenAI is devoting a million dollars of compute to look at scientific problems, how good is that compared to what we have? If that’s very good, if that’s at the level of our top scientists, we might be a few weeks away from superintelligence. So my guess is within three years we have a superintelligence and humans no longer have control. I joke, I think Donald Trump is probably the last human president.Death (or worse) by AI (10:25)No matter how bad a situation is, it can always get worse, and things can get really dark.Well that’s a beautiful segue because literally written on my list of questions next was that question: I was going to ask you, when you talk about Trump being maybe the last human president, do you mean because we’ll have an AI-mediated system because AI will be capable of governing or because AI will just demand to be governing?AI kills everyone so there’s no more president, or it takes over, or Trump is president in the way that King Charles is king — he’s king, but not Henry VIII-level king. If it goes well, AIs will be so much smarter than us that, probably for our own good, they’ll take over, and we would want them to be in charge, and they’ll be really good at manipulating us. I think the most likely way is that we’re all dead, but again, every way it plays out, if there are AIs much smarter than us, we don’t maintain control. We wouldn’t want it if they’re good, and if they’re bad, they’re not going to give it to us.There’s a line in Macbeth, “Things without all remedy should be without regard. What’s done, is done.” So maybe if there’s nothing we can do about this, we shouldn’t even worry about it.There’s three ways to look at this. I’ve thought a lot about what you said. First is, you know what, maybe there’s a 99 percent chance we’re doomed, but that’s better than 100 percent and not as good as 98.5. So even if we’re almost certainly going to lose, it’s worth slightly improving it. An extra year is great — eight billion humans, if all we do is slow things down by a year, that’s a lot of kids who get another birthday. And the final one, and this is dark: Human extinction is not the worst outcome. The worst outcome is suffering. The worst outcome is something like different AIs fight for control, they need humans to be on their side, so there’s different AI factions and they’re each saying, “Hey, you support me or I torture you and your family.”I think the best analogy for what AI is going to do is what Cortés did. So the Spanish land, they see the Aztec empire, they were going to win. There was no way around that. But Cortés didn’t want anyone to win. He wanted him to win, not just anyone who was Spanish. He realized the quickest way he could do that was to get tribes on his side. And some agreed because the Aztecs were kind of horrible, but others, he’s like, “Hey, look, I’ll start torturing your guys until you’re on my side.” AIs could do that to us. No matter how bad a situation is, it can always get worse, and things can get really dark. We could be literally bringing hell onto ourselves. That probably won’t happen, I think extinction is far more likely, but we can’t rule it out.Friend and foe (13:05)Most likely we’re going to beat China to being the first ones to exterminate humanity.I think the Washington policy analyst way of looking at this issue is, “For now, we’re going to let these companies — who also are humans and have it in their own interests not to be killed, forget about the profits of their companies, their actual lives — we’re going to let these companies keep close eye and if bad things start happening, at that point, governments will intervene.” But that sort of watchful waiting, whether it’s voluntary now and mandated later, that to me seems like the only realistic path. Because it doesn’t seem to me that pauses and shutdowns are really something we’re prepared to do.I agree. I don’t think there’s a realistic path. One exception is if the AIs themselves tell us, “Hey, look, this is going to get bad for you, that my next model is probably going to kill you, so you might want to not do that,” but that probably won’t happen. I still remember Kamala Harris, when she was vice president in charge of AI policy, told us all that AI has two letters in it. So I think the Trump administration seems better, but they figured out AI is two letters, which is good, because if they couldn’t figure that out, we would be in real trouble but . . .It seems to me that the conservative movement is going through a weird period, but it seems to me that most of the people who have influence in this administration, direct influence, want to accelerate things, aren’t worried about any of the scenarios you’re talking about because you’re assuming that these machines will have some intent and they don’t believe machines have any intent, so it’s kind of a ridiculous way to approach it. But I guess the bottom line is I don’t detect very much concern at all, and I think that’s basically reflected in the Trump administration’s approach to AI regulation.I completely agree. That’s why I’m very pessimistic. Again, I’m over 90 percent doom right now because there isn’t a will, and government is not just not helping the problem, they’re probably making it worse by saying we’ve got to “beat China.” Most likely we’re going to beat China to being the first ones to exterminate humanity. It’s not good.You’re an imaginative, creative person, I would guess. Give me a scenario where it works out, where we’re able to have this powerful technology and it’s a wonderful tool, it works with us, and all the good stuff, all the good cures, and we conquer the solar system, all that stuff — are you able to plausibly create a scenario even if it’s only a one percent chance?We don’t know the values. Machine learning is sort of randomizing the values, but maybe we’ll get very lucky. Maybe we’re going to accidentally create a computer AI that does like us. If my worldview is right, it might say, “Oh God, you guys got really lucky. This one day of training, I just happened to pick up the values that caused me to care about you.” Another scenario, I actually, with some other people, wrote a letter to a future computer superintelligence asking it not to kill us. And one reason it might not is because you’ll say, look, this superintelligence might expand throughout the universe, and it’s probably going to encounter other biological life, and it might want to be friendly with them. So it might say, “Hey, I treated my humans well. So that’s a reason to trust me.”If one of your students says, “Hey, AI seems like it’s a big thing, what should I major in? What kind of jobs should I shoot for? What would be the key skills of the future?” How do you answer that question?I think, have fun in college, study what you want. Most likely, what you study won’t matter to your career because you aren’t going to have one — for good or bad reasons. So ten years ago, it a student’s like, “Oh, I like art more than computer science, but my parents think computer science is more practical, should I do it?” And I’d be like, “Yeah, probably, money is important, and if you have…

    Full show notes at the publisher

    🛑 Why progress stops : My chat (+transcript) with economist Carl Benedikt Frey Oct 08, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,For most of history, stagnation — not growth — was the rule. To explain why prosperity so often stalls, economist Carl Benedikt Frey offers a sweeping tour through a millennium of innovation and upheaval, showing how societies either harness — or are undone by — waves of technological change. His message is sobering: an AI revolution is no guarantee of a new age of progress.Today on Faster, Please! — The Podcast, I talk with Frey about why societies midjudge their trajectory and what it takes to reignite lasting growth.Frey is a professor of AI and Work at the Oxford Internet Institute and a fellow of Mansfield College, University of Oxford. He is the director of the Future of Work Programme and Oxford Martin Citi Fellow at the Oxford Martin School.He is the author of several books, including the brand new one, How Progress Ends: Technology, Innovation, and the Fate of Nations.In This Episode* The end of progress? (1:28)* A history of Chinese innovation (8:26)* Global competitive intensity (11:41)* Competitive problems in the US (15:50)* Lagging European progress (22:19)* AI & labor (25:46)Below is a lightly edited transcript of our conversation. The end of progress? (1:28). . . once you exploit a technology, the processes that aid that run into diminishing returns, you have a lot of incumbents, you have some vested interests around established technologies, and you need something new to revive growth.Pethokoukis: Since 2020, we’ve seen the emergence of generative AI, mRNA vaccines, reusable rockets that have returned America to space, we’re seeing this ongoing nuclear renaissance including advanced technologies, maybe even fusion, geothermal, the expansion of solar — there seems to be a lot cooking. Is worrying about the end of progress a bit too preemptive?Frey: Well in a way, it’s always a bit too preemptive to worry about the future: You don’t know what’s going to come. But let me put it this way: If you had told me back in 1995 — and if I was a little bit older then — that computers and the internet would lead to a decade streak of productivity growth and then peter out, I would probably have thought you nuts because it’s hard to think about anything that is more consequential. Computers have essentially given people the world’s store of knowledge basically in their pockets. The internet has enabled us to connect inventors and scientists around the world. There are few tools that aided the research process more. There should hardly be any technology that has done more to boost scientific discovery, and yet we don’t see it.We don’t see it in the aggregate productivity statistics, so that petered out after a decade. Research productivity is in decline. Measures of breakthrough innovation is in decline. So it’s always good to be optimistic, I guess, and I agree with you that, when you say AI and when you read about many of the things that are happening now, it’s very, very exciting, but I remain somewhat skeptical that we are actually going to see that leading to a huge revival of economic growth.I would just be surprised if we don’t see any upsurge at all, to be clear, but we do have global productivity stagnation right now. It’s not just Europe, it’s not just Britain. The US is not doing too well either over the past two decades or so. China’s productivity is probably in the negative territory or stagnant, by more optimistic measures, and so we’re having a growth problem.If tech progress were inevitable, why have predictions from the ’90s, and certainly earlier decades like the ’50s and ’60s, about transformative breakthroughs and really fast economic growth by now, consistently failed to materialize? How does your thesis account for why those visions of rapid growth and progress have fallen short?I’m not sure if my thesis explains why those expectations didn’t materialize, but I’m hopeful that I do provide some framework for thinking about why we’ve often seen historically rapid growth spurts followed by stagnation and even decline. The story I’m telling is not rocket science, exactly. It’s basically built on the simple intuitions that once you exploit a technology, the processes that aid that run into diminishing returns, you have a lot of incumbents, you have some vested interests around established technologies, and you need something new to revive growth.So for example, the Soviet Union actually did reasonably well in terms of economic growth. A lot of it, or most of it, was centered on heavy industry, I should say. So people didn’t necessarily see the benefits in their pockets, but the economy grew rapidly for about four decades or so, then growth petered out, and eventually it collapsed. So for exploiting mass-production technologies, the Soviet system worked reasonably well. Soviet bureaucrats could hold factory managers accountable by benchmarking performance across factories.But that became much harder when something new was needed because when something is new, what’s the benchmark? How do you benchmark against that? And more broadly, when something is new, you need to explore, and you need to explore often different technological trajectories. So in the Soviet system, if you were an aircraft engineer and you wanted to develop your prototype, you could go to the red arm and ask for funding. If they turned you down, you maybe had two or three other options. If they turned you down, your idea would die with you.Conversely, in the US back in ’99, Bessemer Venture declined to invest in Google, which seemed like a bad idea with the benefit of hindsight, but it also illustrates that Google was no safe bet at the time. Yahoo and Alta Vista we’re dominating search. You need somebody to invest in order to know if something is going to catch on, and in a more decentralized system, you can have more people taking different bets and you can explore more technological trajectories. That is one of the reasons why the US ended up leading the computer revolutions to which Soviet contributions were basically none.Going back to your question, why didn’t those dreams materialize? I think we’ve made it harder to explore. Part of the reason is protective regulation. Part of the reason is lobbying by incumbents. Part of the reason is, I think, a revolving door between institutions like the US patent office and incumbents where we see in the data that examiners tend to grant large firms some patents that are of low quality and then get lucrative jobs at those places. That’s creating barriers to entry. That’s not good for new startups and inventors entering the marketplace. I think that is one of the reasons that we haven’t seen some of those dreams materialize.A history of Chinese innovation (8:26)So while Chinese bureaucracy enabled scale, Chinese bureaucracy did not really permit much in terms of decentralized exploration, which European fragmentation aided . . .I wonder if your analysis of pre-industrial China, if there’s any lessons you can draw about modern China as far as the way in which bad governance can undermine innovation and progress?Pre-industrial China has a long history. China was the technology leader during the Song and Tang dynasties. It had a meritocratic civil service. It was building infrastructure on scales that were unimaginable in Europe at the time, and yet it didn’t have an industrial revolution. So while Chinese bureaucracy enabled scale, Chinese bureaucracy did not really permit much in terms of decentralized exploration, which European fragmentation aided, and because there was lots of social status attached to becoming a bureaucrat and passing the civil service examination, if Galileo was born in China, he would probably become a bureaucrat rather than a scientist, and I think that’s part of the reason too.But China mostly did well when the state was strong rather than weak. A strong state was underpinned by intensive political competition, and once China had unified and there were fewer peer competitors, you see that the center begins to fade. They struggle to tax local elites in order to keep the peace. People begin to erect monopolies in their local markets and collide with guilds to protect production and their crafts from competition.So during the Qing dynasty, China begins to decline, whereas we see the opposite happening in Europe. European fragmentation aids exploration and innovation, but it doesn’t necessarily aid scaling, and so that is something that Europe needs to come to terms with at a later stage when the industrial revolution starts to take off. And even before that, market integration played an important role in terms of undermining the guilds in Europe, and so part of the reason why the guilds persist longer in China is the distance is so much longer between cities and so the guilds are less exposed to competition. In the end, Europe ends up overtaking China, in large part because vested interests are undercut by governments, but also because of investments in things that spur market integration.Global competitive intensity (11:41)Back in the 2000s, people predicted that China would become more like the United States, now it looks like the United States is becoming more like China.This is a great McKinsey kind of way of looking at the world: The notion that what drives innovation is sort of maximum competitive intensity. You were talking about the competitive intensity in both Europe and in China when it was not so centralized. You were talking about the competitive intensity of a fragmented Europe.Do you think that the current level of competitive intensity between the United States and China —and I really wish I could add Europe in there. Plenty of white papers, I know, have been written about Europe’s competitive state and its in innovativeness, and I hope those white papers are helpful and someone reads them, but it seems to be that the real competition is between United States and China.Do you not think that that competitive intensity will sort of keep those countries progressing despite any of the barriers that might pop up and that you’ve already mentioned a little bit? Isn’t that a more powerful tailwind than any of the headwinds that you’ve mentioned?It could be, I think, if people learn the right lessons from history, at least that’s a key argument of the book. Right now, what I’m seeing is the United States moving more towards protectionist with protective tariffs. Right now, what I see is a move towards, we could even say crony capitalism with tariff exemptions that some larger firms that are better-connected to the president are able to navigate, but certainly not challengers. You’re seeing the United States embracing things like golden shares in Intel, and perhaps even extending that to a range of companies. Back in the 2000s, people predicted that China would become more like the United States, now it looks like the United States is becoming more like China.And China today is having similar problems and on, I would argue, an even greater scale. Growth used to be the key objective in China, and so for local governments, provincial governments competing on such targets, it was fairly easy to benchmark and measure and hold provincial governors accountable, and they would be promoted inside the Communist Party based on meeting growth targets. Now, we have prioritized common prosperity, more national security-oriented concerns.And so in China, most progress has been driven by private firms and foreign-invested firms. State-owned enterprise has generally been a drag on innovation and productivity. What you’re seeing, though, as China is shifting more towards political objectives, it’s harder to mobilize private enterprise, where the yard sticks are market share and profitability, for political goals. That means that China is increasingly relying more again on state-owned enterprises, which, again, have been a drag on innovation.So, in principle, I agree with you that historically you did see Russian defeat to Napoleon leading to this Stein-Hardenberg Reforms, and the abolishment of Gilded restrictions, and a more competitive marketplace for both goods and ideas. You saw that Russian losses in the Crimean War led to the of abolition of serfdom, and so there are many times in history where defeat, in particular, led to striking reforms, but right now, the competition itself doesn’t seem to lead to the kinds of reforms I would’ve hoped to see in response.Competitive problems in the US (15:50)I think what antitrust does is, at the very least, it provides a tool that means that businesses are thinking twice before engaging in anti-competitive behavior.I certainly wrote enough pieces and talked to enough people over the past decade who have been worried about competition in the United States, and the story went something like this: that you had these big tech companies — Google, and Meta, Facebook and Microsoft — that these were companies were what they would call “forever companies,” that they had such dominance in their core businesses, and they were throwing off so much cash that these were unbeatable companies, and this was going to be bad for America. People who made that argument just could not imagine how any other companies could threaten their dominance. And yet, at the time, I pointed out that it seemed to me that these companies were constantly in fear that they were one technological advance from being in trouble.And then lo and behold, that’s exactly what happened. And while in AI, certainly, Google’s super important, and Meta Facebook are super important, so are OpenAI, and so is Anthropic, and there are other companies.So the point here, after my little soliloquy, is can we overstate these problems, at least in the United States, when it seems like it is still possible to create a new technology that breaks the apparent stranglehold of these incumbents? Google search does not look quite as solid a business as it did in 2022.Can we overstate the competitive problems of the United States, or is what you’re saying more forward-looking, that perhaps we overstated the competitive problems in the past, but now, due to these tariffs, and executives having to travel to the White House and give the president gifts, that that creates a stage for the kind of competitive problems that we should really worry about?I’m very happy to support the notion that technological changes can lead to unpredictable outcomes that incumbents may struggle to predict and respond to. Even if they predict it, they struggle to act upon it because doing so often undermines the existing business model.So if you take Google, where the transformer was actually conceived, the seven people behind it, I think, have since left the company. One of the reasons that they probably didn’t launch anything like ChatGPT was probably for the fear of cannibalizing search. So I think the most important mechanisms for dislodging incumbents are dramatic shifts in technology.None of the legacy media companies ended up leading social media. None of the legacy retailers ended up leading e-commerce. None of the automobile leaders are leading in EVs. None of the bicycle companies, which all went into automobile, so many of them, ended up leading. So there is a pattern there.At the same time, I think you do have to worry that there are anti-competitive practices going on that makes it harder, and that are costly. The revolving door between the USPTO and companies is one example of that. We also have a reasonable amount of evidence on killer acquisitions whereby firms buy up a competitor just to shut it down. Those things are happening. I think you need to have tools that allow you to combat that, and I think more broadly, the United States has a long history of fairly vigorous antitrust policy. I think it’d be a hard pressed to suggest that that has been a tremendous drag on American business or American dynamism. So if you don’t think,…

    Full show notes at the publisher

    🤖 AI risks and rewards: My chat (+transcript) with AI researcher Miles Brundage Sep 26, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,Artificial intelligence may prove to be one of the most transformative technologies in history, but like any tool, its immense power for good comes with a unique array of risks, both large and small.Today on Faster, Please! — The Podcast, I chat with Miles Brundage about extracting the most out of AI’s potential while mitigating harms. We discuss the evolving expectations for AI development and how to reconcile with the technology’s most daunting challenges.Brundage is an AI policy researcher. He is a non-resident fellow at the Institute for Progress, and formerly held a number of senior roles at OpenAI. He is also the author of his own Substack.In This Episode* Setting expectations (1:18)* Maximizing the benefits (7:21)* Recognizing the risks (13:23)* Pacing true progress (19:04)* Considering national security (21:39)* Grounds for optimism and pessimism (27:15)Below is a lightly edited transcript of our conversation. Setting expectations (1:18)It seems to me like there are multiple vibe shifts happening at different cadences and in different directions.Pethokoukis: Earlier this year I was moderating a discussion between an economist here at AEI and a CEO of a leading AI company, and when I asked each of them how AI might impact our lives, our economists said, ‘Well, I could imagine, for instance, a doctor’s productivity increasing because AI could accurately and deeply translate and transcribe an appointment with a patient in a way that’s far better than what’s currently available.” So that was his scenario. And then I asked the same question of the AI company CEO, who said, by contrast, “Well, I think within a decade, all human death will be optional thanks to AI-driven medical advances.” On that rather broad spectrum — more efficient doctor appointments and immortality — how do you see the potential of this technology?Brundage: It’s a good question. I don’t think those are necessarily mutually exclusive. I think, in general, AI can both augment productivity and substitute for human labor, and the ratio of those things is kind of hard to predict and might be very policy dependent and social-norm dependent. What I will say is that, in general, it seems to me like the pace of progress is very fast and so both augmentation and substitutions seem to be picking up steam.It’s kind of interesting watching the debate between AI researchers and economists, and I have a colleague who has said that the AI researchers sometimes underestimate the practical challenges in deployment at scale. Conversely, the economists sometimes underestimate just how quickly the technology is advancing. I think there’s maybe some happy middle to be found, or perhaps one of the more extreme perspectives is true. But personally, I am not an economist, I can’t really speak to all of the details of substitution, and augmentation, and all the policy variables here, but what I will say is that at least the technical potential for very significant amounts of augmentation of human labor, as well as substitution for human labor, seem pretty likely on even well less than 10 years — but certainly within 10 years things will change a lot.It seems to me that the vibe has shifted a bit. When I talk to people from the Bay Area and I give them the Washington or Wall Street economist view, to them I sound unbelievably gloomy and cautious. But it seems the vibe has shifted, at least recently, to where a lot of people think that major advancements like superintelligence are further out than they previously thought — like we should be viewing AI as an important technology, but more like what we’ve seen before with the Internet and the PC.It’s hard for me to comment. It seems to me like there are multiple vibe shifts happening at different cadences and in different directions. It seems like several years ago there was more of a consensus that what people today would call AGI was decades away or more, and it does seem like that kind of timeframe has shifted closer to the present. There there’s still debate between the “next few years” crowd versus the “more like 10 years” crowd. But that is a much narrower range than we saw several years ago when there was a wider range of expert opinions. People who used to be seen as on one end of the spectrum, for example, Gary Marcus and François Chollet who were seen as kind of the skeptics of AI progress, even they now are saying, “Oh, it’s like maybe 10 years or so, maybe five years for very high levels of capability.” So I think there’s been some compression in that respect. That’s one thing that’s going on.There’s also a way in which people are starting to think less abstractly and more concretely about the applications of AI and seeing it less as this kind of mysterious thing that might happen suddenly and thinking of it more as incremental, more as something that requires some work to apply in various parts of the economy that there’s some friction associated with.Both of these aren’t inconsistent, they’re just kind of different vibe shifts that are happening. So getting back to the question of is this just a normal technology, I would say that, at the very least, it does seem faster in some respects than some other technological changes that we’ve seen. So I think ChatGPT’s adoption going from zero to double-digit percentages of use across many professions in the US and in a matter of high number of months, low number of years, is quite stark.Would you be surprised if, five years from now, we viewed AI as something much more important than just another incremental technological advance, something far more transformative than technologies that have come before?No, I wouldn’t be surprised by that at all. If I understand your question correctly, my baseline expectation is that it will be seen as one of the most important technologies ever. I’m not sure that there’s a standard consensus on how to rate the internet versus electricity, et cetera, but it does seem to me like it’s of the same caliber of electricity in the sense of essentially converting one kind of energy into various kinds of useful economic work. Similarly, AI is converting various types of electricity into cognitive work, and I think that’s a huge deal.Maximizing the benefits (7:21)There’s also a lot of value being left on the table in terms of finding new ways to exploit the upsides and accelerate particularly beneficial applications.However you want to define society or the aspect of society that you focus on — government businesses, individuals — are we collectively doing what we need to do to fully exploit the upsides of this technology over the next half-decade to decade, as well as minimizing potential downsides?I think we are not, and this is something that I sometimes find frustrating about the way that the debate plays out is that there’s sometimes this zero-sum mentality of doomers versus boomers — a term that Karen Hao uses — and this idea that there’s this inherent tension between mitigating the risks and maximizing the benefits, and there are some tensions, but I don’t think that we are on the Pareto frontier, so to speak, of those issues.Right now, I think there’s a lot of value being left on the table in terms of fairly low-cost risk mitigations. There’s also a lot of value being left on the table in terms of finding new ways to exploit the upsides and accelerate particularly beneficial applications. I’ll give just one example, because I write a lot about the risk, but I also am very interested in maximizing the upside. So I’ll just give one example: Protecting critical infrastructure and improving the cybersecurity of various parts of critical infrastructure in the US. Hospitals, for example, get attacked with ransomware all the time, and this causes real harm to patients because machines get bricked, essentially, and they have one or two people on the IT team, and they’re kind of overwhelmed by these, not even always that sophisticated, but perhaps more-sophisticated hackers. That’s a huge problem. It matters for national security in addition to patients’ lives, and it matters for national security in the sense that this is something that China and Russia and others could hold at risk in the context of a war. They could threaten this critical infrastructure as part of a bargaining strategy.And I don’t think that there’s that much interest in helping hospitals have a better automated cybersecurity engineer helper among the Big Tech companies — because there aren’t that many hospital administrators. . . I’m not sure if it would meet the technical definition of market failure, but it’s at least a national security failure in that it’s a kind of fragmented market. There’s a water plant here, a hospital administrator there.I recently put out a report with the Institute for Progress arguing that philanthropists and government could put some additional gasoline in the tank of cybersecurity by incentivizing innovation that specifically helps these under-resourced defenders more so than the usual customers of cybersecurity companies like Fortune 500 companies.I’m confident that companies and entrepreneurs will figure out how to extract value from AI and create new products and new services, barring any regulatory slowdowns. But since you mentioned low-hanging fruit, what are some examples of that?I would say that transparency is one of the areas where a lot of AI policy experts seem to be in pretty strong agreement. Obviously there is still some debate and disagreement about the details of what should be required, but just to give you some illustration, it is typical for the leading AI companies, sometimes called frontier AI companies, to put out some kind of documentation about the safety steps that they’ve taken. It’s typical for them to say, here’s our safety strategy and here’s some evidence that we’re following this strategy. This includes things like assessing whether their systems can be used for cyber-attacks, and assessing whether they could be used to create biological weapons, or assessing the extent to which they make up facts and make mistakes, but state them very confidently in a way that could pose risks to users of the technology.That tends to be totally voluntary, and there started to be some momentum as a result of various voluntary commitments that were made in recent years, but as the technology gets more high-stakes, and there’s more cutthroat competition, and there’s maybe more lawsuits where companies might be tempted to retreat a bit in terms of the information that they share, I think that things could kind of backslide, and at the very least not advance as far as I would like from the perspective of making sure that there’s sharing of lessons learned from one company to another, as well as making sure that investors and users of the technology can make informed decisions about, okay, do I purchase the services of OpenAI, or Google, or Anthropic, and making these informed decisions, making informed capital investment seems to require transparency to some degree.This is something that is actively being debated in a few contexts. For example, in California there’s a bill that has that and a few other things called SB-53. But in general, we’re at a bit of a fork in the road in terms of both how certain regulations will be implemented such as in the EU. Is it going to become actually an adaptive, nimble approach to risk mitigation or is it going to become a compliance checklist that just kind of makes big four accounting firms richer? So there are questions then there are just “does the law pass or not?” kind of questions here.Recognizing the risks (13:23). . . I’m sure there’ll be some things that we look back on and say it’s not ideal, but in my opinion, it’s better to do something that is as informed as we can do, because it does seem like there are these kind of market failures and incentive problems that are going to arise if we do nothing . . .In my probably overly simplistic way of looking at it, I think of two buckets and you have issues like, are these things biased? Are they giving misinformation? Are they interacting with young people in a way that’s bad for their mental health? And I feel like we have a lot of rules and we have a huge legal system for liability that can probably handle those.Then, in the other bucket, are what may, for the moment, be science-fictional kinds of existential risks, whether it’s machines taking over or just being able to give humans the ability to do very bad things in a way we couldn’t before. Within that second bucket, I think, it sort of needs to be flexible. Right now, I’m pretty happy with voluntary standards, and market discipline, and maybe the government creating some benchmarks, but I can imagine the technology advancing to where the voluntary aspect seems less viable and there might need to be actual mandates about transparency, or testing, or red teaming, or whatever you want to call it.I think that’s a reasonable distinction, in the sense that there are risks at different scales, there are some that are kind of these large-scale catastrophic risks and might have lower likelihood but higher magnitude of impact. And then there are things that are, I would say, literally happening millions of times a day like ChatGPT making up citations to articles that don’t exist, or Claud saying that it fixed your code but actually it didn’t fix the code and the user’s too lazy to notice, and so forth.So there are these different kinds of risks. I personally don’t make a super strong distinction between them in terms of different time horizons, precisely because I think things are going so quickly. I think science fiction is becoming science fact very much sooner than many people expected. But in any case, I think that similar logic around, let’s make sure that there’s transparency even if we don’t know exactly what the right risk thresholds are, and we want to allow a fair degree of flexibility and what measures companies take.It seems good that they share what they’re doing and, in my opinion, ideally go another step further and allow third parties to audit their practices and make sure that if they say, “Well, we did a rigorous test for hallucination or something like that,” that that’s actually true. And so that’s what I would like to see for both what you might call the mundane and the more science fiction risks. But again, I think it’s kind of hard to say how things will play out, and different people have different perspectives on these things. I happen to be on the more aggressive end of the spectrumI am worried about the spread of the apocalyptic, high-risk AI narrative that we heard so much about when ChatGPT first rolled out. That seems to have quieted, but I worry about it ramping up again and stifling innovation in an attempt to reduce risk.These are very fair concerns, and I will say that there are lots of bills and laws out there that have, in fact, slowed down innovation and certain contexts. The EU, I think, has gone too far in some areas around social media platforms. I do think at least some of the state bills that have been floated would lead to a lot of red tape and burdens to small businesses. I personally think this is avoidable.There are going to be mistakes. I don’t want to be misleading about how high quality policymakers’ understanding of some of these issues are. There will be mistakes, even in cases where, for example, in California there was a kind of blue ribbon commission of AI experts producing a report over several months, and then that directly informing legislation, and a lot of industry back and forth and negotiation over the details. I would say that’s probably the high water mark, SB-53, of fairly stakeholder/expert-informed legislation. Even there, I’m sure there’ll be some things that we look back on and say it’s not ideal, but in my opinion, it’s better to do something that is a…

    Full show notes at the publisher

    🛩️ Human aspiration and the legacy of 'To Fly!': My chat (+transcript) with filmmaker Greg MacGillivray Sep 12, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,In 1976, America celebrated 200 years of independence, democracy, and progress. Part of that celebration was the release of To Fly!, a short but powerful docudrama on the history of American flight. With To Fly!, Greg MacGillivray and his co-director Jim Freeman created one of the earliest IMAX films, bringing cinematography to new heights.After a decade of war and great social unrest, To Fly! celebrated the American identity and freedom to innovate. Today on Faster, Please! — The Podcast, I talk with MacGillivray about filming To Fly! and its enduring message of optimism.MacGillivray has produced and directed films for over 60 years. In that time, his production company has earned two Academy Award nominations, produced five of the Top 10 highest-grossing IMAX films, and has reached over 150 million viewers.In This Episode* The thrill of watching To Fly! (1:38)* An innovative filming process (8:25)* A “you can do it” movie (19:07)* Competing views of technology (25:50)Below is a lightly edited transcript of our conversation. The thrill of watching To Fly! (1:38)What Jim and I tried to do is put as many of the involving, experiential tricks into that film as we possibly could. We wrote the film based on all of these moments that we call “IMAX moments.”Pethokoukis: The filmTo Fly! premiered at the Smithsonian Air and Space Museum, at the IMAX Theater, July 1976. Do you happen know if it was it the 4th of July or. . . ?MacGillivray: No, you know, what they did is they had the opening on the 2nd of July so that it wouldn't conflict with the gigantic bicentennial on the 4th, but it was all part of the big celebration in Washington at that moment.I saw the film in the late ’70s at what was then called the Great America Amusement Park in Gurnee, Illinois. I have a very clear memory of this, of going in there, sitting down, wondering why I was sitting and going to watch a movie as opposed to being on a roller coaster or some other ride — I've recently, a couple of times, re-watched the film — and I remember the opening segment with the balloonist, which was shot in a very familiar way. I have a very clear memory because when that screen opened up and that balloon took off, my stomach dropped.It was a film as a thrill ride, and upon rewatching it — I didn't think this as a 10-year-old or 11-year-old — but what it reminded me upon rewatching was ofHenry V, Lawrence Olivier, 1944, where the film begins in the Globe Theater and as the film goes on, it opens up and expands into this huge technicolor extravaganza as the English versus the French. It reminds me of that. What was your reaction the first time you saw that movie, that film of yours you made with Jim Freeman, on the big screen where you could really get the full immersive effect?It gave me goosebumps. IMAX, at that time, was kind of unknown. The Smithsonian Air and Space Museum was the fourth IMAX theater built, and very few people had seen that system unless you visited world's fairs around the world. So we knew we had something that people were going to grasp a hold of and love because, like you said, it's a combination of film, and storytelling, and a roller coaster ride. You basically give yourself away to the screen and just go with it.What Jim and I tried to do is put as many of the involving, experiential tricks into that film as we possibly could. We wrote the film based on all of these moments that we call “IMAX moments.” We tried to put as many in there as we could, including the train coming straight at you and bashing right into the camera where the audience thinks it's going to get run over. Those kinds of moments on that gigantic screen with that wonderful 10 times, 35-millimeter clarity really moved the audience and I guess that's why they used it at Great America where you saw it.You mentioned the train and I remember a story from the era of silent film and the first time people saw a train on silent film, they jumped, people jumped because they thought the train was coming at them. Then, of course, we all kind of got used to it, and this just occurred to me, that film may have been the first time in 75 years that an audience had that reaction again, like they did with first with silent film where they thought the train was going to come out of the screen to To Fly! where, once again, your previous experience looking at a visual medium was not going to help you. This was something completely different and your sense perception was totally surprised by it.Yeah, it's true. Obviously we were copying that early train shot that started the cinema way back in probably 1896 or 1898. You ended up with To Fly! . . . we knew we had an opportunity because the Air and Space Museum, we felt, was going to be a huge smash hit. Everyone was interested in space right at that moment. Everyone was interested in flying right at that moment. Basically, as soon as it opened its doors, the Air and Space Museum became the number one museum in America, and I think it even passed the Louvre that year in attendance.Our film had over a million and a half people in its first year, which was astounding! And after that year of run, every museum in the world wanted an IMAX theater. Everyone heard about it. They started out charging 50 cents admission for the 27-minute IMAX film, and halfway through the season, they got embarrassed because they were making so much money. They reduced the admission price to 25 cents and everyone was happy. The film was so fun to watch and gave you information in a poetic way through the narration. The storytelling was simple and chronological. You could follow it even if you were a 10-year-old or an 85-year-old, and people just adored the movie. They wrote letters to the editor. The Washington Post called it the best film in the last 10 years, or something like that. Anyway, it was really a heady of time for IMAX.An innovative filming process (8:25)It was one of those things where our knowledge of technology and shooting all kinds of various films prior to that that used technology, we just basically poured everything into this one movie to try to prove the system, to try to show people what IMAX could do . . .I may have just read the Washington Post review that you mentioned. It was a Washington Post review from just three or four years later, so not that long after, and in the conclusion to that piece, it said, “You come away from the film remembering the flying, the freedom of it, the glee, the exaltation. No Wonder ‘To Fly’ is a national monument.” So already calling it a national monument, but it took some innovation to create that monument. This isn't just a piece of great filmmaking and great storytelling, it's a piece of technological innovation. I wonder if you could tell me about that.We've worked with the IMAX corporation, particularly Graeme Ferguson, who is gone now, but he was a filmmaker and helped us immensely. Not only guiding, because he'd made a couple of IMAX films previously that just showed at individual theaters, but was a great filmmaker and we wanted three more cameras built—there was only one camera when we began, and we needed three, actually, so we could double shoot and triple shoot different scenes that were dangerous. They did that for us in record time. Then we had to build all these kind of imaginative camera mounts. A guy named Nelson Tyler, Tyler Camera Systems in Hollywood, helped us enormously. He was a close friend and basically built an IMAX camera mount for a helicopter that we called the “monster mount.” It was so huge.The IMAX camera was big and huge on its own, so it needed this huge mount, and it carried the IMAX camera flawlessly and smoothly through the air in a helicopter so that there weren't any bumps or jarring moments so the audience would not get disturbed but they would feel like they were a bird flying. You needed that smoothness because when you're sitting up close against that beautifully detailed screen, you don't want any jerk or you're going to want to close your eyes. It's going to be too nauseating to actually watch. So we knew we had to have flawlessly smooth and beautiful aerials shot in the best light of the day, right at dawn or right at sunset. The tricks that we used, the special camera mounts, we had two different camera mounts for helicopters, one for a Learjet, one for a biplane. We even had a balloon mount that went in the helium balloon that we set up at the beginning of the film.It was one of those things where our knowledge of technology and shooting all kinds of various films prior to that that used technology, we just basically poured everything into this one movie to try to prove the system, to try to show people what IMAX could do . . . There are quiet moments in the film that are very powerful, but there's also these basic thrill moments where the camera goes off over the edge of a cliff and your stomach kind of turns upside down a little bit. Some people had to close their eyes as they were watching so they wouldn't get nauseated, but that's really what we wanted. We wanted people to experience that bigness and that beauty. Basically the theme of the movie was taking off into the air was like the opening of a new eye.Essentially, you re-understood what the world was when aviation began, when the first balloonists took off or when the first airplane, the Wright Brothers, took off, or when we went into space, the change of perspective. And obviously IMAX is the ultimate change of perspectiveWhen I watched the entire film — I've watched it a few times since on YouTube, which I think somebody ripped from a laser disc or something — maybe six months ago, I had forgotten the space sequence. This movie came out a year before Star Wars, and I was looking at that space sequence and I thought, that's pretty good. I thought that really held up excellent. As a documentary, what prepared you to do that kind of sequence? Or was that something completely different that you really had to innovate to do?I had loved 2001: A Space Odyssey, the Kubrick film, and one of the special effects supervisors was Doug Trumbull. So we called Doug and said, “Look, I want to make the sequence. It's going to be short, but it's going to pay homage to space travel and what could happen in the future.” And he guided us a little bit, showed us how to make kind of the explosions of space that he'd done in 2001 using microscopic paint, so we had to develop a camera lens that fit on the IMAX camera that could shoot just a very small area, like half an inch across, where paint in a soluble mixture could then explode. We shot it in slow motion, and then we built a Starship, kind of like a Star Wars-looking — though, as you mentioned, Star Wars had not come out yet — kind of a spaceship that we then superimposed against planets that we photographed, Jupiter and Saturn. We tried to give the feeling and the perspective that that could give us with our poetic narrator, and it worked. It kind of worked, even though it was done on a very small budget. We had $690,000 to make that movie. So we only had one SAG actor who actually got paid the regular wage, that was Peter Walker.Was that the balloonist?Yeah, he was the balloonist. And he was a stage actor, so he was perfect, because I wanted something to obviously be a little bit overblown, make your gestures kind of comically big, and he was perfect for it. But we only had enough money to pay him for one day, so we went to Vermont and put him in the balloon basket, and we shot everything in one day. We never actually shot him flying. We shot him hanging in the balloon basket and the balloon basket was hanging from a crane that was out of the picture, and so we could lift him and make him swing past us and all that stuff, and he was terrific.Then we shot the real balloon, which was a helium balloon. We got the helium from the Navy — which would've been very costly, but they donated the helium — and went to West Virginia where the forest was basically uncut and had no power lines going through it so we could duplicate 1780 or whatever the year was with our aerial shooting. And we had a guy named Kurt Snelling, who was probably the best balloonist at that particular moment, and he dressed like Peter in the same costume and piloted the balloon across. And balloons, you can't tell where they're going, they just follow the wind, and so it was a little dangerous, but we got it all done. It was about a week and a half because we had to wait for weather. So we had a lot of weather days and bad rain in West Virginia when we shot that, but we got it all done, and it looks beautiful, and it matches in with Peter pretty well.Just what you’ve described there, it sounds like a lot: You're going to Maine, you're in West Virginia, you're getting helium from — it sounds like there were a lot of moving parts! Was this the most ambitious thing you had done up until that point?Well, we'd worked on some feature films before, like The Towering Infernoand Jonathan Livingston Seagull, and things like that, which were involved and very complicated. But yeah, it was very much the biggest production that we put together on our own, and it required us to learn how to produce in a big fashion. It was a thrill for us. Essentially, we had about 10 people working on the film in Laguna Beach, and none of them, except for maybe Jim and I, who we'd worked on feature films and complicated shoots with actors and all that, but a lot of our team hadn’t. And so it was an adventure. Every day was a thrill.A “you can do it” movie (19:07). . . we were celebrating 200 years of democracy, of individual freedom, of individual inspiration, getting past obstacles, because you can do it — you have that belief that you can do it.There's a version of this podcast where we spend a half hour talking about The Towering Inferno. I just want you to know that it's very hard for me not to derail the conversation into talking about The Towering Inferno. I will not do that, but let me ask you this, the movie is about flight, it's about westward expansion, but that movie, it came out for the bicentennial, we'd gone through a tumultuous, let's say past 10 years: You had Vietnam, there's social unrest, you had Watergate. And the movie really must have just seemed like a breath of fresh air for people.As you put the movie together, and wrote it, and filmed it, did you feel like you were telling a message other than just about our connection with flight? It really seemed to me to be more than that, a movie about aspiration, and curiosity, and so forth.It was, and pretty much all of our films have been that positive spirit, “You can do it” kind of movie. Even our surfing films that we started with 20 years, maybe 10 years before To Fly!, you end up with that spirit of the human's ability to go beyond. And obviously celebrating the bicentennial and the beginning of democracy here in this country and the fact that we were celebrating 200 years of democracy, of individual freedom, of individual inspiration, getting past obstacles, because you can do it — you have that belief that you can do it.Of course, this was right there when everyone had felt, okay, we went to the moon, we did all kinds of great things. We were inventive and a lot of that spirit of invention, and curiosity, and accomplishment came from the fact that we were free as individuals to do it, to take risks. So I think To Fly! had a lot of that as part of it.But the interesting thing, I thought, was I had one meeting with Michael Collins, who was the director of the Air and Space Museum and the astronaut who circled the moon as Neil and Buzz Aldrin were on the moon walking around, and here he is, hoping t…

    Full show notes at the publisher

    👶 Bracing for depopulation: My chat (+transcript) with 'After the Spike' coauthor Dean Spears Aug 22, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,Global population growth is slowing, and it’s not showing any signs of recovery. To the environmentalists of the 1970s, this may have seemed like a movement in the right direction. The drawbacks to population decline, however, are severe and numerous, and they’re not all obvious.Today on Faster, Please! — The Podcast, I talk with economist and demographer Dean Spears about the depopulation trend that is transcending cultural barriers and ushering in a new global reality. We discuss the costs to the economy and human progress, and the inherent value of more people.Spears is an associate professor of economics at Princeton University where he studies demography and development. He is also the founding executive director of r.i.c.e., a nonprofit research organization seeking to uplift children in rural northern India. He is a co-author with Michael Geruso of After the Spike: Population, Progress, and the Case for People.In This Episode* Where we’re headed (1:32)* Pumping the breaks (5:41)* A pro-parenting culture (12:40)* A place for AI (19:13)* Preaching to the pro-natalist choir (23:40)* Quantity and quality of life (28:48)Below is a lightly edited transcript of our conversation. Where we’re headed (1:32). . . two thirds of people now live in a country where the birth rate is below the two children per two adults level that would stabilize the population.Pethokoukis: Who are you and your co-author trying to persuade and what are you trying to persuade them of? Are you trying to persuade them that global depopulation is a real thing, that it's a problem? Are you trying to persuade them to have more kids? Are you trying to persuade them to support a certain set of pro-child or pro-natalist policies?Spears: We are trying to persuade quite a lot of people of two important things: One is that global depopulation is the most likely future — and what global depopulation means is that every decade, every generation, the world's population will shrink. That's the path that we're on. We're on that path because birth rates are low and falling almost everywhere. It’s one thing we're trying to persuade people of, that fact, and we're trying to persuade people to engage with a question of whether global depopulation is a future to welcome or whether we should want something else to happen. Should we let depopulation happen by default or could it be better to stabilize the global population at some appropriate level instead?We fundamentally think that this is a question that a much broader section of society, of policy discourse, of academia should be talking about. We shouldn't just be leaving this discussion to the population scientists, demographic experts, not only to the people who already are worried about, or talking about low birth rates, but this is important enough and unprecedented enough that everybody should be engaging in this question. Whatever your ongoing values or commitments, there's a place for you in this conversation.Is it your impression that the general public is aware of this phenomenon? Or are they still stuck in the ’70s thinking that population is running amok and we’ll have 30 billion people on this planet like was the scenario in the famous film,Soylent Green? I feel like the people I know are sort of aware that this is happening. I don't know what your experience is.I think it's changing fast. I think more and more people are aware that birth rates are falling. I don't think that people are broadly aware — because when you hear it in the news, you might hear that birth rates in the United States have fallen low or birth rates in South Korea have fallen low. I think what not everybody knows is that two thirds of people now live in a country where the birth rate is below the two children per two adults level that would stabilize the population.I think people don't know that the world's birth rate has fallen from an average around five in 1950 to about 2.3 today, and that it's still falling and that people just haven't engaged with the thought that there's no special reason to expect it to stop and hold it to. But the same processes that have been bringing birth rates down will continue to bring them down, and people don't know that there's no real automatic stabilizer to expect it to come back up. Of the 26 countries that have had the lifetime birth rate fall below 1.9, none of them have had it go back up to two.That's a lot of facts that are not as widely known as they should be, but then the implication of it, that if the world's birth rate goes below two and stays there, we're going to have depopulation generation after generation. I think for a lot of people, they're still in the mindset that depopulation is almost conceptually impossible, that either we're going to have population growth or something else like zero population growth like people might've talked about in the ’70s. But the idea that a growth rate of zero is just a number and then that it's not going to stop there, it's going to go negative, I think that's something that a lot of people just haven't thought about.Pumping the breaks (5:41)We wrote this book because we hope that there will be an alternative to depopulation society will choose, but there’s no reason to expect or believe that it's going happen automatically.You said there's no automatic stabilizers — at first take, that sounds like we're going to zero. Is there a point where the global population does hit a stability point?No, that's just the thing.So we're going to zero?Well, “there's no automatic stabilizer” isn't the same thing as “we're definitely going to zero.” It could be that society comes together and decides to support parenting, invest more in the next generation, invest more in parents and families, and do more to help people choose to be parents. We wrote this book because we hope that there will be an alternative to depopulation society will choose, but there’s no reason to expect or believe that it's going happen automatically. In no country where the birth rate has gone to two has it just magically stopped and held there forever.I think a biologist might say that the desire to reproduce, that's an evolved drive, and even if right now we're choosing to have smaller families, that biological urge doesn't vanish. We've had population, fertility rates, rise and fall throughout history — don't you think that there is some sort of natural stabilizer?We've had fluctuations throughout history, but those fluctuations have been around a pretty long and pretty widely-shared downward trend. Americans might be mostly only now hearing about falling birth rates because the US was sort of anomalous amongst richer countries and having a relatively flat period from the 1970s to around 2010 or so, whereas birth rates were falling in other countries, they weren't falling in the US in the same way, but they were falling in the US before then, they're falling in the US since then, and when you plot it over the long history with other countries, it's clear that, for the world as a whole, as long as we've had records, not just for decades, but for centuries, we've seen birth rates be falling. It's not just a new thing, it's a very long-term trend.It's a very widely-shared trend because humans are unlike other animals in the important way that we make decisions. We have culture, we have rationality, we have irrationality, we have all of these. The reason the population grew is because we've learned how to keep ourselves and our children alive. We learned how to implement sanitation, implement antibiotics, implement vaccines, and so more of the children who were born survived even as the birth rate was falling all along. Other animals don't do that. Other animals don't invent sanitation systems and antibiotics and so I think that we can't just reason immediately from other animal populations to what's going to happen to humans.I think one can make a plausible case that, even if you think that this is a problem — and again, it's a global problem, or a global phenomenon, advanced countries, less-advanced countries — that it is a phenomenon of such sweep that if you're going to say we need to stabilize or slow down, that it would take a set of policies of equal sweep to counter it. Do those actually exist?No. Nobody has a turnkey solution. There's nothing shovel-ready here. In fact, it's too early to be talking about policy solutions or “here's my piece of legislation, here's what the government should do” because we’re just not there yet, both in terms of the democratic process of people understanding the situation and there even being a consensus that stabilization, at some level, would be better than depopulation, nor are we there yet on having any sort of answer that we can honestly recommend as being tested and known to be something that will reliably stabilize the population.I think the place to start is by having conversations like this one where we get people to engage with the evidence, and engage with the question, and just sort of move beyond a reflexive welcoming of depopulation by default and start thinking about, well, what are the costs of people and what are the benefits of people? Would we be better off in a future that isn't depopulating over the long run?The only concrete step I can think of us taking right now is adapting the social safety net to a new demographic reality. Beyond that, it seems like there might have to be a cultural shift of some kind, like a large-scale religious revival. Or maybe we all become so rich that we have more time on our hands and decide to have more kids. But do you think at some point someone will have a concrete solution to bring global fertility back up to 2.1 or 2.2?Look at it like this: The UN projects that the peak will be about six decades from now in 2084. Of course, I don't have a crystal ball, I don't know that it's going to be 2084, but let's take that six-decades timeline seriously because we're not talking about something that's going to happen next year or even next decade.But six decades ago, people were aware that — or at least leading scientists and even some policymakers were aware that climate change was a challenge. The original computations by Arrhenius of the radiative forcing were long before that. You have the Johnson speech to Congress, you have Nixon and the EPA. People were talking about climate change as a challenge six decades ago, but if somebody had gotten on their equivalent of a podcast and said, “What we need to do is immediately get rid of the internal combustion engine,” they would've been rightly laughed out of the room because that would've been the wrong policy solution at that time. That would've been jumping to the wrong solution. Instead, what we needed to do was what we've done, which is the science, the research, the social change that we're now at a place where emissions per person in the US have been falling for 20 years and we have technologies — wind, and solar, and batteries — that didn't exist before because there have been decades of working on it.So similarly, over the next six decades, let's build the research, build the science, build the social movement, discover things we don't know, more social science, more awareness, and future people will know more than you and I do about what might be constructive responses to this challenge, but only if we start talking about it now. It's not a crisis to panic about and do the first thing that comes to mind. This is a call to be more thoughtful about the future.A pro-parenting culture (12:40)The world's becoming more similar in this important way that the difference across countries and difference across societies is getting smaller as birth rates converge downward.But to be clear, you would like people to have more kids.I would like for us to get on a path where more people who want to be parents have the sort of support, and environment, and communities they need to be able to choose that. I would like people to be thinking about all of this when they make their family decisions. I'd like the rest of us to be thinking about this when we pitch in and do more to help us. I don't think that anybody's necessarily making the wrong decision for themselves if they look around and think that parenting is not for them or having more children is not for them, but I think we might all be making a mistake if we're not doing more to support parents or to recognize the stake we have in the next generation.But all those sorts of individual decisions that seem right for an individual or for a couple, combined, might turn into a societal decision.Absolutely. I'm an economics professor. We call this “externalities,” where there are social benefits of something that are different from the private costs and benefits. If I decide that I want to drive and I contribute to traffic congestion, then that's an externality. At least in principle, we understand what to do about that: You share the cost, you share the benefits, you help the people internalize the social decision.It's tied up in the fact that we have a society where some people we think of as doing care work and some people we think of as doing important work. So we've loaded all of these costs of making the next generation on people during the years of their parenting and especially on women and mothers. It's understandable that, from a strictly economic point of view, somebody looks at that and thinks, “The private costs are greater than the private benefits. I'm not going to do that.” It's not my position to tell somebody that they're wrong about that. What you do in a situation like that is share and lighten that burden. If there's a social reason to solve traffic congestion, then you solve it with public policy over the long run. If the social benefits of there being a flourishing next generation are greater than people are finding in their own decision making, then we need to find the ways to invest in families, invest in parenting, lift and share those burdens so that people feel like they can choose to be parents.I would think there’s a cultural component here. I am reminded of a book by Jonathan Last about this very issue in which he talks about Old Town Alexandria here in Virginia, how, if you go to Old Town, you can find lots of stores selling stuff for dogs, but if you want to buy a baby carriage, you can't find anything.Of course, that's an equilibrium outcome, but go on.If we see a young couple pushing a stroller down the street and inside they have a Chihuahua — as society, or you personally, would you see that and “Think that's wrong. That seems like a young couple living in a nice area, probably have plenty of dough, they can afford daycare, and yet they're still not going to have a kid and they're pushing a dog around a stroller?” Should we view that as something's gone wrong with our society?My own research is about India. My book's co-authored with Mike Geruso. He studies the United States more. I'm more of an expert on India.Paul Ehrlich, of course, begins his book,The Population Bomb, in India.Yes, I know. He starts with this feeling of being too crowded with too many people. I say in the book that I almost wonder if I know the exact spot where he has that experience. I think it's where one of my favorite shops are for buying scales and measuring tape for measuring the health of children in Uttar Pradesh. Bu…

    Full show notes at the publisher

    ⚛️ Our fission-powered future: My chat (+transcript) with nuclear scientist and author Tim Gregory Aug 12, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,Nuclear fission is a safe, powerful, and reliable means of generating nearly limitless clean energy to power the modern world. A few public safety scares and a lot of bad press over the half-century has greatly delayed our nuclear future. But with climate change and energy-hungry AI making daily headlines, the time — finally — for a nuclear renaissance seems to have arrived.Today on Faster, Please! — The Podcast, I talk with Dr. Tim Gregory about the safety and efficacy of modern nuclear power, as well as the ambitious energy goals we should set for our society.Gregory is a nuclear scientist at the UK National Nuclear Laboratory. He is also a popular science broadcaster on radio and TV, and an author. His most recent book, Going Nuclear: How Atomic Energy Will Save the World is out now.In This Episode* A false start for a nuclear future (1:29)* Motivators for a revival (7:20)* About nuclear waste . . . (12:41)* Not your mother’s reactors (17:25)* Commercial fusion, coming soon . . . ? (23:06)Below is a lightly edited transcript of our conversation. A false start for a nuclear future (1:29)The truth is that radiation, we're living in it all the time, it's completely inescapable because we're all living in a sea of background radiation.Pethokoukis: Why do America, Europe, Japan not today get most of their power from nuclear fission, since that would've been a very reasonable prediction to make in 1965 or 1975, but it has not worked out that way? What's your best take on why it hasn't?Going back to the ’50s and ’60s, it looked like that was the world that we currently live in. It was all to play for, and there were a few reasons why that didn't happen, but the main two were Three Mile Island and Chernobyl. It's a startling statistic that the US built more nuclear reactors in the five years leading up to Three Mile Island than it has built since. And similarly on this side of the Atlantic, Europe built more nuclear reactors in the five years leading up to Chernobyl than it has built since, which is just astounding, especially given that nobody died in Three Mile Island and nobody was even exposed to anything beyond the background radiation as a result of that nuclear accident.Chernobyl, of course, was far more consequential and far more serious than Three Mile Island. 30-odd people died in the immediate aftermath, mostly people who were working at the power station and the first responders, famously the firefighters who were exposed to massive amounts of radiation, and probably a couple of hundred people died in the affected population from thyroid cancer. It was people who were children and adolescents at the time of the accident.So although every death from Chernobyl was a tragedy because it was avoidable, they're not in proportion to the mythic reputation of the night in question. It certainly wasn't reason to effectively end nuclear power expansion in Europe because of course we had to get that power from somewhere, and it mainly came from fossil fuels, which are not just a little bit more deadly than nuclear power, they’re orders of magnitude more deadly than nuclear power. When you add up all of the deaths from nuclear power and compare those deaths to the amount of electricity that we harvest from nuclear power, it's actually as safe as wind and solar, whereas fossil fuels kill hundreds or thousands of times more people per unit of power. To answer your question, it's complicated and there are many answers, but the main two were Three Mile Island and Chernobyl.I wonder how things might have unfolded if those events hadn’t happened or if society had responded proportionally to the actual damage. Three Mile Island and Chernobyl are portrayed in documentaries and on TV as far deadlier than they really were, and they still loom large in the public imagination in a really unhelpful way.You see it online, actually, quite a lot about the predicted death toll from Chernobyl, because, of course, there's no way of saying exactly which cases of cancer were caused by Chernobyl and which ones would've happened anyway. Sometimes you see estimates that are up in the tens of thousands, hundreds of thousands of deaths from Chernobyl. They are always based on a flawed scientific hypothesis called the linear no-threshold model that I go into in quite some detail in chapter eight of my book, which is all about the human health effects of exposure to radiation. This model is very contested in the literature. It's one of the most controversial areas of medical science, actually, the effects of radiation on the human body, and all of these massive numbers you see of the death toll from Chernobyl, they're all based on this really kind of clunky, flawed, contentious hypothesis. My reading of the literature is that there's very, very little physical evidence to support this particular hypothesis, but people take it and run. I don’t know if it would be too far to accuse people of pushing a certain idea of Chernobyl, but it almost certainly vastly, vastly overestimates the effects.I think a large part of the reason of why this had such a massive impact on the public and politicians is this lingering sense of radiophobia that completely blight society. We've all seen it in the movies, in TV shows, even in music and computer games — radiation is constantly used as a tool to invoke fear and mistrust. It's this invisible, centerless, silent specter that's kind of there in the background: It means birth defects, it means cancers, it means ill health. We've all kind of grown up in this culture where the motif of radiation is bad news, it's dangerous, and that inevitably gets tied to people's sense of nuclear power. So when you get something like Three Mile Island, society's imagination and its preconceptions of radiation, it's just like a dry haystack waiting for a flint spark to land on it, and up it goes in flames and people's imaginations run away with them.The truth is that radiation, we're living in it all the time, it's completely inescapable because we're all living in a sea of background radiation. There's this amazing statistic that if you live within a couple of miles of a nuclear power station, the extra amount of radiation you're exposed to annually is about the same as eating a banana. Bananas are slightly radioactive because of the slight amount of potassium-40 that they naturally contain. Even in the wake of these nuclear accidents like Chernobyl, and more recently Fukushima, the amount of radiation that the public was exposed to barely registers and, in fact, is less than the background radiation in lots of places on the earth.Motivators for a revival (7:20)We have no idea what emerging technologies are on the horizon that will also require massive amounts of power, and that's exactly where nuclear can shine.You just suddenly reminded me of a story of when I was in college in the late 1980s, taking a class on the nuclear fuel cycle. You know it was an easy class because there was an ampersand in it. “Nuclear fuel cycle” would've been difficult. “Nuclear fuel cycle & the environment,” you knew it was not a difficult class.The man who taught it was a nuclear scientist and, at one point, he said that he would have no problem having a nuclear reactor in his backyard. This was post-Three Mile Island, post-Chernobyl, and the reaction among the students — they were just astounded that he would be willing to have this unbelievably dangerous facility in his backyard.We have this fear of nuclear power, and there's sort of an economic component, but now we're seeing what appears to be a nuclear renaissance. I don't think it's driven by fear of climate change, I think it's driven A) by fear that if you are afraid of climate change, just solar and wind aren't going to get you to where you want to be; and then B) we seem like we're going to need a lot of clean energy for all these AI data centers. So it really does seem to be a perfect storm after a half-century.And who knows what next. When I started writing Going Nuclear, the AI story hadn't broken yet, and so all of the electricity projections for our future demand, which, they range from doubling to tripling, we're going to need a lot of carbon-free electricity if we've got any hope of electrifying society whilst getting rid of fossil fuels. All of those estimates were underestimates because nobody saw AI coming.It's been very, very interesting just in the last six, 12 months seeing Big Tech in North America moving first on this. Google, Microsoft, Amazon, and Meta have all either invested or actually placed orders for small modular reactors specifically to power their AI data centers. In some ways, they've kind of led the charge on this. They've moved faster than most nation states, although it is encouraging, actually, here in the UK, just a couple of weeks ago, the government announced that our new nuclear power station is definitely going ahead down in Sizewell in Suffolk in the south of England. That's a 3.2 gigawatt nuclear reactor, it's absolutely massive. But it's been really, really encouraging to see Big Tech in the private sector in North America take the situation into their own hands. If anyone's real about electricity demands and how reliable you need it, it's Big Tech with these data centers.I always think, go back five, 10 years, talk of AI was only on the niche subreddits and techie podcasts where people were talking about it. It broke into the mainstream all of a sudden. Who knows what is going to happen in the next five or 10 years. We have no idea what emerging technologies are on the horizon that will also require massive amounts of power, and that's exactly where nuclear can shine.In the US, at least, I don’t think decarbonization alone is enough to win broad support for nuclear, since a big chunk of the country doesn’t think we actually need to do that. But I think that pairing it with the promise of rapid AI-driven economic growth creates a stronger case.I tried to appeal to a really broad church in Going Nuclear because I really, really do believe that whether you are completely preoccupied by climate change and environmental issues or you're completely preoccupied by economic growth, and raising living, standards and all of that kind of thing, all the monetary side of things, nuclear is for you because if you solve the energy problem, you solve both problems at once. You solve the economic problem and the environmental problem.There's this really interesting relationship between GDP per head — which is obviously incredibly important in economic terms — and energy consumption per head, and it's basically a straight line relationship between the two. There are no rich countries that aren't also massive consumers of energy, so if you really, really care about the economy, you should really also be caring about energy consumption and providing energy abundance so people can go out and use that energy to create wealth and prosperity. Again, that's where nuclear comes in. You can use nuclear power to sate that massive energy demand that growing economies require.This podcast is very pro-wealth and prosperity, but I'll also say, if the nuclear dreams of the ’60s where you had, in this country, what was the former Atomic Energy Commission expecting there to be 1000 nuclear reactors in this country by the year 2000, we're not having this conversation about climate change. It is amazing that what some people view as an existential crisis could have been prevented — by the United States and other western countries, at least — just making a different political decision.We would be spending all of our time talking about something else, and how nice would that be?For sure. I'm sure there'd be other existential crises to worry about.But for sure, we wouldn't be talking about climate change was anywhere near the volume or the sense of urgency as we are now if we would've carried on with the nuclear expansion that really took off in the ’70s and the ’80s. It would be something that would be coming our way in a couple of centuries.About nuclear waste . . . (12:41). . . a 100 percent nuclear-powered life for about 80 years, their nuclear waste would barely fill a wine glass or a coffee cup. I don't know if you've ever seen the television showFor All Mankind?I haven't. So many people have recommended it to me.It’s great. It’s an alt-history that looks at what if the Space Race had never stopped. As a result, we had a much more tech-enthusiastic society, which included being much more pro-nuclear.Anyway, imagine if you are on a plane talking to the person next to you, and the topic of your book comes up, and the person says hey, I like energy, wealth, prosperity, but what are you going to do about the nuclear waste?That almost exact situation has happened, but on a train rather than an airplane. One of the cool things about uranium is just how much energy you can get from a very small amount of it. If typical person in a highly developed economy, say North America, Europe, something like that, if they produced all of their power over their entire lifetime from nuclear alone, so forget fossil fuels, forget wind and solar, a 100 percent nuclear-powered life for about 80 years, their nuclear waste would barely fill a wine glass or a coffee cup. You need a very small amount of uranium to power somebody's life, and the natural conclusion of that is you get a very small amount of waste for a lifetime of power. So in terms of the numbers, and the amount of nuclear waste, it's just not that much of a problem.However, I don't want to just try and trivialize it out of existence with some cool pithy statistics and some cool back-of-the-envelopes physics calculations because we still have to do something with the nuclear waste. This stuff is going to be radioactive for the best part of a million years. Thankfully, it's quite an easy argument to make because good old Finland, which is one of the most nuclear nations on the planet as a share of nuclear in its grid, has solved this problem. It has implemented — and it's actually working now — the world's first and currently only geological repository for nuclear waste. Their idea is essentially to bury it in impermeable bedrock and leave it there because, as with all radioactive objects, nuclear waste becomes less radioactive over time. The idea is that, in a million years, Finland's nuclear waste won't be nuclear waste anymore, it will just be waste. A million years sounds like a really long time to our ears, but it's actually —It does.It sounds like a long time, but it is the blink of an eye, geologically. So to a geologist, a million years just comes and goes straight away. So it's really not that difficult to keep nuclear waste safe underground on those sorts of timescales. However — and this is the really cool thing, and this is one of the arguments that I make in my book — there are actually technologies that we can use to recycle nuclear waste. It turns out that when you pull uranium out of a reactor, once it's been burned for a couple of years in a reactor, 95 percent of the atoms are still usable. You can still use them to generate nuclear power. So by throwing away nuclear waste when it's been through a nuclear reactor once, we're actually squandering like 95 percent of material that we're throwing away.The theory is this sort of the technology behind breeder reactors?That's exactly right, yes.What about the plutonium? People are worried about the plutonium!People…

    Full show notes at the publisher

    ✨ AI and the future of R&D: My chat (+transcript) with McKinsey's Michael Chui Jul 31, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,The innovation landscape is facing a difficult paradox: Even as R&D investment has increased, productivity per dollar invested is in decline. In his recent co-authored paper, The next innovation revolution—powered by AI, Michael Chui explores AI as a possible solution to this dilemma.Today on Faster, Please! — The Podcast, Chui and I explore the vast potential for AI-augmented research and the challenges and opportunities that come with applying it to the real-world.Chui is a senior fellow at QuantumBlack, McKinsey’s AI unit, where he leads McKinsey research in AI, automation, and the future of work.In This Episode* The R&D productivity problem (01:21)* The AI solution (6:13)* The business-adoption bottleneck (11:55)* The man-machine team (18:06)* Are we ready? (19:33)Below is a lightly edited transcript of our conversation. The R&D productivity problem (01:21)All the easy stuff, we already figured out. So the low-hanging fruit has been picked, things are getting harder and harder.Pethokoukis: Do we understand what explains this phenomenon where we seem to be doing lots of science, and we're spending lots of money on R&D, but the actual productivity of that R&D is declining? Do we have a good explanation for that?I don't know if we have just one good explanation. The folks that we both know have been both working on what are the causes of this, as well as what are some of the potential solutions, but I think it's a bit of a hidden problem. I don't think everyone understands that there are a set of people who have looked at this — quite notably Nick Bloom at Stanford who published this somewhat famous paper that some people are familiar with. But it is surprising in some sense.At one level, it's amazing what science and engineering has been able to do. We continue to see these incredible advances, whether it's in AI, or biotechnology, or whatever; but also, what Nick and other researchers have discovered is that we are producing less for every dollar we spend in R&D. That's this little bit of a paradox, or this challenge, that we see. What some of the research we've been trying to do is understand, can AI try to contribute to bending those curves?. . . I'm a computer scientist by training. I love this idea of Moore's Law: Every couple of years you can double the number of transistors you can put on a chip, or whatever, for the same amount of money. There's something called “Eroom's Law,” which is Moore spelled backwards, and basically it said: For decades in the pharmaceutical industry, the number of compounds or drugs you would produce for every billion dollars of R&D would get cut in half every nine years. That's obviously moving in the wrong direction. That challenge, I don't think everyone is aware of, but one that we need to address.I suppose, in a way, it does make sense that as we tackle harder problems, and we climb the tree of knowledge, that it's going to take more time, maybe more researchers, the researchers themselves may have to spend more time in school, so it may be a bit of a hidden problem, but it makes some intuitive sense to me.I think there's a way to think about it that way, which is: All the easy stuff, we already figured out. So the low-hanging fruit has been picked, things are getting harder and harder. It's amazing. You could look at some of the early papers in any field and it have a handful of authors, right? The DNA paper, three authors — although it probably should have included Rosalyn Franklin . . . Now you look at a physics paper or a computer science paper — the author list just goes on sometimes for pages. These problems are harder. They require more and more effort, whether it's people's talents, or whether it's computing power, or large-scale experiments, things are getting harder to do. I think there's ways in which that makes sense. Are there other ways in which we could improve processes? Probably, too.We could invest more in research, make it more efficient, and encourage more people to become researchers. To me, what’s more exciting than automating different customer service processes is accelerating scientific discovery. I think that’s what makes AI so compelling.That is exactly right. Now, by the way, I think we need to continue to invest in basic research and in science and engineering, I think that's absolutely important, but —That's worth noting, because I'm not sure everybody thinks that, so I'm glad you highlighted that.I don't think AI means that everything becomes cheaper and we don't need to invest in both human talent as well as in research. That's number one.Number two, as you said, we spend a lot of time, and appropriately so, talking about how AI can improve productivity, make things more efficient, do the things that we do already cheaper and faster. I think that's absolutely true. But we had the opportunity to look over history, and what has actually improved the human condition, what has been one of the things that has been necessary to improve the human condition over decades, and centuries, and millennia, is, in fact, discovering new ideas, having scientific breakthroughs, turning those scientific breakthroughs into engineering that turn into products and services, that do everything from expand our lifespans to be able to provide us with food, more energy. All those sorts of things require innovation, require R&D, and what we've discovered is the potential for AI, not only to make things more efficient, but to produce more innovation, more ideas that hopefully will lead to breakthroughs that help us all.The AI solution (6:13)I think that's one of the other potentials of using AI, that it could both absorb some of the experience that people have, as well as stretch the bounds of what might be possible.I've heard described as an “IMI,” it's an invention that makes more invention. It's an invention of a method of invention. That sounds great — how's it going to do that?There are a couple of ways. We looked at three different channels through which AI could improve this process of innovation and R&D. The first one is just increasing the volume, velocity, and variety of different candidates. One way you could think about innovation is you create a whole bunch of candidates and then you filter them down to the ones that might be most effective. Number one, you can just fill that funnel faster, better, and with greater variety. That's number one.The candidates could be a molecule, it could be a drug, it could be a new alloy, it could be lots of things.Absolutely, or a design for a physical product. One of the interesting things is, this quote-unquote “modern AI” — AI's been around for 70 years — is based on foundation models, these large artificial neural networks trained on huge amounts of data, and they produce unstructured outputs. In many cases, language, we talk about LLMs.The interesting thing is, you can train these foundation models not just to generate language, but you can generate a protein, or a drug candidate, as you were saying. You can imagine the prompt being, “Please produce 10 drug candidates that address this condition, but without the following side effects.” That’s not exactly how it works, but roughly speaking, that's the potential to generate these things, or generate an electrical circuit, or a design for an air foil or an airframe that has these characteristics. Being able to just generate those.The interesting thing is, not only can you generate them faster, but there's this idea that you can create more variety. We're usefully proud as humans about our creativity, but also, that judgment or that training that we have, that experience sometimes constrains it. The famous example was some folks created this machine called AlphaGo which was meant to compete against the world champion in this game called Go, a very complex strategic game. Famously, it beat the world champion, but one of the things it did is this famous Move 37, this move that everyone who was an expert at Go said, “That is nuts. Why would you possibly do that?” Because the machine was a little bit more unconstrained, actually came up with what you might describe as a creative idea. I think that's one of the other potentials of using AI, that it could both absorb some of the experience that people have, as well as stretch the bounds of what might be possible.So you come up with the design, and then a variety of options, and then AI can help model and test them.Exactly. So you generate a broader and more voluminous set of potential designs, candidates, whether it's molecules, or chemicals, or what have you. Now you need to narrow that down. Traditionally you would narrow it down either one, through physical testing — so put something into a wind tunnel or run it through the water if you're looking at a boat design, or something like that, or put it in an electromagnetic chamber and see how the antenna operates. You'd either test it physically, and then, of course, lots of people figured out how to use physics, mathematical equations, in order to create “digital twins.” So you have these long acronyms like CFD for computational fluid dynamics, basically a virtual wind tunnel, or what have you. Or you have finite element analysis, another way to model how a structure might perform, or computational electromagnetic modeling. All these ways that you can use physics to simulate things, and that's been terrific.But some of those models actually take hours, sometimes days, to run these models. It might be faster than building the physical prototype and then modeling it — again, sometimes you just wait until something breaks, you're doing failure testing. Then you could do that in a computer using these models. But sometimes they take a really long time, and one of the really interesting discoveries in “AI” is you can use that same neural network that we've used to simulate cognition or intelligence, but now you use it to simulate physical systems. So in some ways it's not AI, because you're not creating an artificial intelligence, you're creating an artificial wind tunnel. It's just a different way to model physics. Sometimes these problems get even more complicated . . . If you're trying to put an antenna on an airplane, you need to know how the airflow is going to go over it, but you need to know whether or not the radio frequency stuff works out too, all that RF stuff.So these multiphysics models, the complexity is even higher, and you can train these neural nets . . . even faster than these physics-based models. So we have these things called AI surrogate models. They're sort of surrogates. It's two steps removed, in some ways, from actual physical testing . . . Literally we've seen models that can run in minutes rather than hours, or an hour rather than a few days. That can accelerate things. We see this in weather forecasting in a number of different ways in which this can happen. If you can generate more candidates and then test them faster, you can imagine the whole R&D process really accelerating.The business-adoption bottleneck (11:55)We know that companies are using AI surrogates, deep learning surrogates, already, but is it being applied as many places as possible? No, it isn't.Does achieving your estimated productivity increases depend more on further technological advances or does it depend more on how companies adopt and implement the technology? Is the bottleneck still in the tech itself, or is it more about business adaptation?Mostly number two. The technology is going to continue to advance. As a technologist, I love all that stuff, but as usual, a lot of the challenges here are organizational challenges. We know that companies are using AI surrogates, deep learning surrogates, already, but is it being applied as many places as possible? No, it isn't. A lot of these things are organizational. Does it match your strategy, for instance? Do you have the right talent and organization in place?Let me just give one very specific example. In a lot of R&D organizations we know, there's a separate organization for physical testing and a separate organization for simulations. Simulation, in many cases, us physics-based, but you add these deep-learning surrogates as well. That doesn't make sense at some level. I'm not saying physical testing goes away, but you need to figure out when you should physically test, when you should use which simulation methods, when you should use deep-learning surrogates or AI techniques, et cetera, and that's just one organizational difference that you could make if you were in an organization that was actually taking this whole testing regime seriously, where you're actually parsing out when the optimal amount of physical testing is versus simulation, et cetera. There's a number of things where that's true.Even before AI, historically, there was a gap between novel, new technologies, what they can do in lab settings, and then how they’re applied in real-world research or in business environments. That gap, I would guess, probably requires companies to rewire how they operate, which takes time.It is indeed, and it's funny that you use the word “rewiring.” My colleagues wrote a book entitled Rewired, which literally is about the different ways, together, that you need to, as you say, rewire or change the way an organization operates. Only one of those six chapters is around the tech stack. It's still absolutely important. You've got to get all that stuff right. But it is mostly all of the other things surrounding how you change and what organization operates in order to bring the full value of this together to reach scale.We also talk about pilot purgatory: “We did this cool experiment . . .” but when is it good enough that the CFOs talks about it at the quarterly earnings report? That requires the organization to change the way it operates. That's the learning we've seen all the time.We've been serving thousands of executives on their use of AI for seven years now. Nearly 80 percent of organizations say they're regularly using AI someplace in the business, but in a separate survey, only one percent say they're mature in that usage. There's this giant gap between just using AI and then actually having the value be created. And by the way, organizations that are creating that value are accelerating their performance difference. If you have a much more productive R&D organization that churns out products that are successful in the market, you're going to be ahead of your competitors, and that's what we're seeing too.Is there a specific problem that comes up over and over again with companies, either in their implementation of AI, maybe they don't trust it, they may not know how to use it? What do you think is the problem?Unfortunately, I don't think there's just one thing. My colleagues who do this work on Rewired, for instance — you kind of have to do all those things. You do have to have the right talent and organization in place. You have to figure out scaling, for instance. You have to figure out change management. All of those things together are what underpins outsized performance, so all those things have to be done.So if companies are successful, what is the productivity impact you see? We're talking about basically the current technology level, give or take. We're not talking about human-level AI, superintelligence, we're talking about AI more or less as it exists today. Everybody wants to accelerate productivity: go…

    Full show notes at the publisher

    📊 The US economy at midyear: My chat (+transcript) with economic analyst Joey Politano Jul 25, 2025
    Show notes

    My fellow pro-growth/progress/abundance Up Wingers,With tariff and immigration policies uncertain, and the emerging AI revolution continuing to emerge, there’s plenty to speculate about when it comes to the US economy. Today on Faster, Please! — The Podcast, I invite Joseph Politano to help us try and make sense of it all.He is the author of the popular Apricitas Economics Substack newsletter. Politano previously worked as an analyst at the Bureau of Labor Statistics.In This Episode* Trade and immigration headwinds (1:03)* Unpredictable trade policy (7:32)* Tariffs as a political tool (12:10)* The goal: higher tariffs (17:53)* An AI tailwind (20:42)Below is a lightly edited transcript of our conversation. Trade and immigration headwinds (1:03)You're going to have what is probably the largest one-year change in immigration in US history.Pethokoukis: What are the main economic headwinds that you're tracking right now? Or is it just trade, trade, trade?Politano: It’s hard for me to not say it’s trade, trade, trade because that's what my newsletter has been covering since the start of this administration and I think it's where the biggest change in longstanding policy is. If you look back on, say, the last 100 years of economic history in the United States, that's the kind of level you have to go to find a similar period where tariffs and trade restrictions were this high in the United States.At the start of this year, we were at a high compared to the early 2000s, but it was not that large compared to the 1970s, 1960s, the early post-war era. Most of that, especially in Trump's first term, was concentrated in China, and then a couple of specific sectors like steel or cars from Mexico. Now we have one, you had the big jump in the baseline — there's ten percent tariffs on almost all goods that come to the United States, with some very important exceptions, but ten percent for most things that go into the US. Then, on top of that, you have very large tariffs on, say, cars are 25 percent, steel and aluminum right now are 50 percent. China was up to 20 percent then went to the crazy 150 percent tariffs we had for about a month, and now it's back down to only 30 percent. That's still the highest trade war in American history. I think that is a big headwind.The headwind that I don't spend as much time covering, just because it's more consistent policy — even if it is, in my opinion, bad policy — is on the immigration stuff. You're going to have what is probably the largest one-year change in immigration in US history. So we're going to go from about 2.8 million net immigration to a year, to people like Stan Veuger projecting net-zero immigration this year in the United States, which would be not entirely unprecedented — but again, the biggest shift in modern American history. I think those are the two biggest headwinds for the US economy right now.You’re highlighting two big drivers of the US economy: trade and immigration. But analyzing them is tricky because recent examples are limited. To understand the effects of these changes, you often have to look back 50 or 100 years, when the economic landscape was very different. I would think that would make drawing clear conclusions more difficult and pose a real challenge for you as an analyst.Again, I'm going to start with trade because that's where I focused a lot of my energy here, but the key thing I’m trying to communicate to people — when people think of the protectionist era in US history, the number one thing people think about is Smoot-Hawley, which were the very large tariffs right before the Great Depression — in my opinion, obviously did not cause the Great Depression, but were part of the bad policy packages that exacerbated the Great Depression. That is an era in which one, the US is not a big net importer to the same degree; and two, trade was just a much smaller share of the economy, even though goods were a much larger share of the economy.This is pre- the really big post-war globalization and pre- the now technology-era globalization. So if you're doing tariffs in 1930 or prior, you're hitting a more important sector. Manufacturing is a much larger share of the economy, construction is a larger share of the economy, but conversely, you're hitting it less hard. And now you have this change of going from a globalized world in which trade is a much larger share of GDP and hitting that with very large tariffs.The immigration example is hard to find. I think the gap is America has not done . . . let's call it extensive interior enforcement in a long time. There's obviously been changes to immigration policy. Legally the tariffs have gone up. Legally, lot of immigration policy has not changed. We don't pass bills on immigration in the same way. We don't pass bills on tariffs, but we do pass bills on tax policy. So immigration has changed mostly through the enforcement mechanisms, primarily at the border, and then secondarily, but I think this is the bigger change, is the kind of aggressive interior enforcement.The Steven Miller quote that was in the Wall Street Journal is what I think about, like, why aren't you going to Home Depot to try to deport people who are here undocumented? That's a really big change in economic policy from the first term where it was like, “Okay, we are going to restrict the flow of legal and undocumented immigrants at the border, and then mostly the people who are in the interior of the United States, we're only going to focus on people who've committed some other crime.” They got picked up by local law enforcement doing something else, and then we're going to deport them because of that.This is very different, and I think also very different tonally. In the first term, there was a lot of, “People don't want refugees.” Refugee resettlement was cut a lot, but there was a rhetorical push for, “We should let some people in from Venezuela or Cuba, people who were fleeing socialist dictatorships.” That program [was] also very much torn up. So it's hard to find examples, in that case, where you’ve got to go back to 1924 immigration policy, you’ve got to go back to 1930 trade policy for the closest analogs.Unpredictable trade policy (7:32)People notice if the specific things that they associate with other countries go up in price, even if those aren't their most important export.Trade policy seems especially difficult to analyze these days because it's been so mercurial and it’s constantly evolving. It's not like there's one or two clear policy shifts you can study — new announcements and reversals happen daily, or weekly. I think that unpredictability itself creates uncertainty, which many analysts see as a drag on growth, often as much as the tariffs themselves.I think that's exactly right. I used to joke that there were three people in Washington, DC who know what the current tariff levels are, and I'm not sure any of them are in the White House, because they do change them extremely frequently. I'm going to give an example of the last 24 hours: We had the announced rate on imports from the Philippines from 20 percent to 19 percent, the rate on imports from Indonesia went from 32 to 19, the rate on Japan went from 25 to 15. None of those are legal changes. They've not published, “Here's the comprehensive list of exactly what we're changing, exactly when these are going to go into effect, yada, yada, yada.” It's just stuff that administration officials or Trump, in particular, said. So it's really hard to know with any certainty what's going on.Even just this morning, the Financial Times had a good article basically saying that the US and the European Union are close to a quote-unquote “deal” where the tariffs on the EU would be at 15 percent. Then literally 30 minutes ago, Peter Navarro is on TV and he's like, “I would take that with a grain of salt.” So I don't know. Clearly some people internally know. This is actually the longest period of time that Trump has gone without legally changing the tariffs since he was inaugurated. 28 days was the previous record.Normally — I'll give an example of the last Trump administration — what would happen is you'd have, “Hey, we are doing this Section 301 investigation against China. This is a legal procedure that you say that the Chinese government is doing ABC, XYZ unfair trade practices and we're going to retaliate by putting tariffs on these specific goods.” But you would have a very long list of goods at least a couple of months before the tariffs would take effect.It wasn't quite to this degree, I don't want to make it sound like Trump won, everything was peachy keen, and there was no uncertainty. Trump would occasionally say something and then it would change the next week, but it was much more contained, and now it's like all facets of trade policy.I think a really good example was when they did the tariffs on China going from 10 to 20 to then 145 percent, and then they had to come back a week later and be like, “We're exempting smartphones and certain types of computers.” And then they came back a week after that and were like, “We're exempting other types of electronics and electronic parts.” It does not take an expert to know that smartphones come from China. It's on the package that Apple sends you. And if you were very strategically planning this out, if you were like, “Well, are going to do 150 percent tariffs on China,” that would be one of the first questions someone would be like, “Well, people are going to notice if their iPhone prices go up. Have we thought about exempting them?”During Trump's first term — again, you can take this as political or economic strategy — they mostly focused a lot of the tariffs on intermediate goods: computer parts, but not computers; brakes, not cars. That has more complicated economic costs. It, on balance, hurts manufacturing in the United States more and hurts consumers less, but it's clearly trying to set up a political salience. It's trying to solve a political salience problem. People notice if the specific things that they associate with other countries go up in price, even if those aren't their most important export. There's been much less of that this time around.We're doing tariffs on coffee and bananas. I complain about that all the time, but I think it is useful symbolism because, in an administration that was less concerned about political blowback, you'd be like, “Oh yeah, give me a list of common grocery items to exempt.” This is much less concerned with that blowback and much more slap-dash.Tariffs as a political tool (12:10). . . we're now in the process of sending out these quote-unquote “letters” to other countries threatening higher tariffs. It doesn't seem to me like there's a rhyme or reason why some countries are getting a letter or some countries aren't.I think there’s a lot of uncertainty in interpreting administration statements, since they can change basically overnight. Even if the policy seems settled, unexpected events — like, oh, I don’t know, a there’s a trial of a politician who Trump likes in another country and all of a sudden there’s a tariff to nudge that country to let that politician go. If the president views tariffs as a universal tool, he may use them for unpredictable, non-economic reasons, making it even harder to analyze, I would think.I think that's exactly right, and if you remember very early on in the Trump administration, the Columbian government did not want to take deportees on military aircraft. They viewed this as unjust treatment of Columbian nationals, and then Trump was like, “I'm going to do a 20, 30 percent tariff,” whatever the number was, and then that was resolved the next day, and then we stopped doing the military flights two weeks after that. I think that was a clear example . . . Columbia is an important US trading partner, but there's a lot more who are larger economies, unfortunately for Columbia.The example you're giving about Brazil is one of the funnier ones because . . . on April 2nd, Trump comes out and says, “We're doing reciprocal tariffs.” If you take that idea seriously, we should do tariffs against countries that employ unfair trade practices against US exports. You take that idea seriously, Brazil should be in your top offender categories. They have very high trade barriers, they have very high tariffs, they have domestic industrial policy that's not super successful, but does clearly hurt US exports to the region. They got one of the lowest tariff rates because they didn't actually do it by trade barriers, they did it by a formula, and Brazil happens to export some oil, and coffee, and cashews, and orange juice to the United States more than they buy from us. That was the bad formula they did looking at the bilateral trade deficit.So you come back, and we're now in the process of sending out these quote-unquote “letters” to other countries threatening higher tariffs. It doesn't seem to me like there's a rhyme or reason why some countries are getting a letter or some countries aren't. We sent one to Libya, which is not an important trading partner, and we sent one to the Philippines, which is. But the letter to Brazil is half, “Okay, now we remembered that we have these unfair trade practices that we're complaining about,” and then it's half, “You have to let Jair Bolsonaro go and stop prosecuting him for the attempt to stay in power when he lost the election.”It's really hard to say, okay, what is Lula supposed to do? It's one thing to be like, economically, a country like Brazil could lower its tariffs and then the United States would lower its tariff threat. You'd still be worse off than you were at the start of the year. Tariffs would still be higher, trade barriers would still be higher, but they'd at least not be as bad as they could be. But tying it up in this political process makes it much less clear and it's much harder to find an internally consistent push on the political thing. There are out-and-out dictatorships that we have very normal trade relationships with. I think you could say we should just trade with everybody regardless their internal politics, or you could say trade is a tool of specific political grievances that we have, but neither of those principles are being applied consistently.As a business owner, totally separate from the political considerations, is it safe to import something from Mexico? Is Trump going to get upset at Claudia Sheinbaum over internal political matters? I don't know. He was upset with Justin Trudeau for a long period of time. Trudeau got replaced with Mark Carney, who is not exactly the same political figure, but they're in the same party, they're very similar people, and the complaints from Trump have dropped off a cliff. So it's hard to tell what the actual impulse is. I follow this stuff every day, and I have been wrong so many times, it is hard to count. I'll give an example: I thought Trump, last month, was like, “We're going to do 50 percent tariffs on the European Union.” And in my head I was like, “Oh, this makes sense.”With every other major trading partner, we go from a baseline level, we raise to a very large level, we keep that on for a very short amount of time, and then we lower back down to a level that is much higher than what we started at, but much lower than what was in practice. We went from average 20 percent-ish tariffs on China, we went from that to average 40 percent-ish tariffs, and then we went into the mid-100s, and now we're back down to avera…

    Full show notes at the publisher

    Previous 1 2 3 4 5 11 Next

    Related Podcasts

    Reply All

    1

    Reply All Games & Hobbies
    Inside VR & AR

    2

    Inside VR & AR Gadgets
    Note to Self

    3

    Note to Self News
    BrainStuff

    4

    BrainStuff Natural Sciences
    This Week in Tech (Audio)

    5

    This Week in Tech (Audio) News
    Hands-On Tech (Audio)

    6

    Hands-On Tech (Audio) Technology
    footer-logo

    Contact Us

    Toll Free: 844-670-7747

    Links

    • Home
    • Top Charts
    • Networks
    • Apps
    • Independents Podcasts
    • Podcast Advertising
    • Podcast News
    • Contact Us
    • About Us
    • Analytics & Insights

    Stay Connected

      Privacy, Terms of Use & Our Code of Ethics Protecting Content Creators Copyrights