Faster, Please! — The Podcast

James Pethokoukis

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.

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Friday · 41 min
Next steps for humanity in space: My conversation with Kevin Cannon
Welcome to Faster Please!—The Podcast, the audiovisual companion to my Faster Please! newsletter. I am your host, Jim Pethokoukis. My guest this episode is Dr. Kevin Cannon. Kevin is the principal at Starbench Analysis, a platform that provides research and analysis on space exploration, emerging technologies, and the future of humanity in space. Previously, he was a professor at the Colorado School of Mines, where he taught planetary geology and space resources. Today, we dive into the growing competition between SpaceX and Blue Origin, the possibility of AI data centers in orbit, the race back to the moon, and humanity’s prospects for settling Mars. Hope you enjoy it. In this episode: * Space after the midterms (0:00) * Orbital data centers and the night sky (8:47) * In search of a killer app (17:35) * The coming launch crunch (20:18) * The race back to the moon (26:53) * Mars and bigger rockets (30:36) * Planetary defense and asteroid mining (35:35) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On space after the midterms… Space itself and NASA has enjoyed very good bipartisan support. It always has. And even under this administration where the OMB has tried to cut back on NASA programs, particularly the science programs, Congress has been very good about restoring that funding. So I think you’re going to see kind of continued broad support for NASA and for the Artemis program. I don’t think we’re going to see any kind of radical shift in direction going back to Mars or asteroids as we did in previous administrations. But I think there are questions about kind of the enthusiasm, like the overall enthusiasm you talked about for kind of settlement, things like that. There’s always a question of how enthusiastic the president and the vice president are, and then also who they put in as administrator, right? So we’ve kind of seen NASA flourish under Jim Bridenstine and now under Jared Isaacman. And so that can really have a huge effect on just the workforce and the overall morale of the agency. On orbital data centers… The other thing though, I think the more interesting debate though is the societal acceptance of these data centers. And this is something that I haven’t seen too many people talking about. The one person who’s been doing really interesting work on this is this guy, Shane Ross, who’s a professor at Virginia Tech. And what he’s been doing is making these very accurate simulations of what these orbital data centers would actually look like to the naked eye in space. So if we take the SpaceX AI-1 satellite, that’s kind of their pathfinder. It’s a 250 kilowatt AI data center satellite. And one of those satellites would be as bright in the sky as Venus is. Now it gets kind of worse from there. So if you want to put these satellites in orbit, there’s really only one type of orbit in low Earth orbit that makes sense, and it’s called a sun-synchronous orbit. So if you have a satellite orbiting around the Earth, it can have a different inclination. So the orbit can be inclined relative to the pole of the Earth. And if you get that inclination up to about kind of 97, maybe 100 degrees, you get into these sun-synchronous orbits that perfectly track the terminator, which is the dividing line between night and day. And they get basically 100% sunlight all the time, which is what you want if you’re doing compute in space. On the search for a killer app… The whole lunar thing. There’s a little bit there, but there’s still not really a lunar economy per se. So yeah, I think that’s why orbital data centers have attracted so much interest from the space industry. The appeal there is that you’re selling into an existing market, right? So there’s already an existing market for compute. We know how much people will pay for inference for AI models. And so if you can kind of get set up, you can just tap into that existing market. That’s kind of the same argument that AstroForge just made for asteroid mining. So there were all these other people saying, well, we’re gonna go out and get water from these asteroids and bring them back and sell it into this kind of water-based orbital economy. And the problem there is that it’s kind of a chicken and egg. Like you don’t really have this kind of cislunar development where you could find a customer to sell water to in space. And so they say, we’re just gonna go get metals from asteroids. There’s already the London metals market. We can just sell our products into an existing market. On the coming launch crunch… So if you’re trying to do any of these other things, tourism, mining, whatever, right? If you don’t have your own rockets, you’re paying the price, and so you’re paying very healthy margins to SpaceX in this case because they don’t really have robust competition. So the price for that Falcon 9 might be 80, 90 million dollars, whereas the internal cost to SpaceX is only 10 or 15. So this is really just a question of when is there going to be robust competition to get those prices down, kind of eat into those margins and start to commoditize launch. I think Blue Origin and ULA with their Vulcan, they’re kind of like the next best hope. Obviously Blue had that very tough incident on the pad. They’re scrambling to try to get back to flight. And then you do have a new slate. I think these high prices, these high margins are going to attract a lot of people coming in with new concepts for medium-lift, heavy-lift vehicles. Some of them are very promising, like Stoke Space. So they’re going straight for a fully reusable rocket. There’s others that are entering the market with medium lift, heavy lift. On the race back to the moon… And then on the flip side, you’ve got Blue Origin, right? They obviously care deeply about this. Jeff really wants to be the one to land American astronauts. But they’ve just kind of been hamstrung by these kind of failures and engineering incidents. So for them it’s more of a technical question: can they kind of get this program together and make things happen? But I would say right now it’s not looking great for a US landing by 2029. So I think there is the potential that China does get there first. The next question though is what happens after? China’s kind of going for this one-off Apollo recreation. There’s a lot of question marks about their ability to kind of build up a sustained presence. So on the US side, I think that’s kind of the hope, is that even if that first landing comes a year or two after the Chinese, that the US is putting into place all of these things: the landers, the CLPS program, power infrastructure, fission surface power, mining, that even if they kinda get there after, they’re kind of setting up for kind of a long-term presence and a long-term success with the moon base. On Mars and bigger rockets… To me the question is how does our technical capability of doing something like Mars missions improve with very, very strong AI? So if we just kind of look at the capabilities and look at the exponential trends it’s starting with coding and math, it’s now kind of moving into the physical sciences, it’s gonna move into hardware engineering, right? Anything an engineer can do on a computer, CAD modeling, simulations. So do we kind of get that kind of exponential uplift in our ability to kind of do these very hard technical things? And does that kind of start to bend that timeline towards something more optimistic? So I think right now if you just have kind of normal NASA incentives, maybe kind of SpaceX more focused on low Earth orbit, data, AI, communications around Earth, then that kind of seems like a reasonable estimate. But if you kind of equip a startup who really cares about this, who really wants to do this, with kind of incredible technical capabilities, then that’s where I could see that kind of come down into maybe the mid-late 2030… This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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November 6 · 43 min
Life before humanity’s Great Acceleration: My interview with Chelsea Follet
My guest this episode is Chelsea Follett. Chelsea is a research fellow at the Cato Institute’s Center for Global Liberty and Prosperity, where she works with HumanProgress.org. She is also the author of the Past Imperfect Substack and her new book, The Grim Old Days: An Introduction to the Preindustrial Past, which challenges our tendency to romanticize the past by revealing the harsh realities of life before industrialization. Today, we’ll discuss the book, exploring a world that technological progress and economic growth have allowed us to escape. In this episode: * Romanticizing the pre-industrial past (0:54) * Life before the great enrichment (5:05) * But what about the royalty? (13:27) * Nostalgia and the case against growth (21:52) * Making the case for growth (26:52) * How we treated people, animals, and nature (32:04) * The beauty of the past without its horrors (36:39) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On misconceptions about the Industrial Revolution… Even if you ignore the extremes and just look at the broad center of the political spectrum, if you ask the average person, what was the effect of the Industrial Revolution on the living standards of an average person? The picture they will paint for you is not a pretty one. They will probably tell you that the Industrial Revolution caused terrible living conditions, worker exploitation, pollution, and all manner of other hardships. Not that long ago, on the Joe Rogan podcast, our vice president JD Vance made the comparison, like everyone else does, it’s cliche at this point, between the AI revolution and the Industrial Revolution. And he claimed that if we want to avoid what was worst, his word, of the Industrial Revolution from recurring during the AI revolution, we need strong labor unions, anti-monopoly measures, essentially more government intervention into the economy. And I don’t think he is expressing an unusual view when he thinks of the Industrial Revolution and his mind immediately goes to these terrible working and living conditions that no modern person would accept. But we have to remember those conditions were largely preexisting. On the improvement of diets… The diets of the past, which are so romanticized both by the MAHA movement and other people, this idea that in the past people ate these wholesome, chemical-free diets, all organic. Unfortunately, this romanticized view would shock our ancestors, whose food was so bland that they fought wars and would kill and die over spices that we now take for granted. And that’s when they had food at all. Every three or four years, a famine could occur and the years of famine were terrible even in the relatively well off areas of the world, such as Western Europe. For example, in Burgundy, France, at one point, a famine occurred that was said to have taken the lives of 10,000 families, and those that survived were said to have turned to eating grass and wild plants in the fields, and even to eating human flesh of those who had already succumbed to malnourishment. In fact, we see again and again accounts of famine-induced cannibalism in different parts of the world. On the hardships of royalty… You alluded to the lives of the wealthy. Even if you were a member of the small elite, and remember again, 80 to 90 percent of the population would have been subsistence farmers. But even if you managed to win the lottery and be born among the nobility, you still would have wine freeze at your table. You still would lose half of your children because being a prince or princess would not spare you from the astronomical rates of childhood death in the past. You would still face a higher mortality rate at every age, indeed. There is another myth that rates of mortality in the past were only so much higher because of high rates of child mortality. In reality, in the pre-industrial past, mortality rates were higher at every age group. Although it is true that children face the worst odds of anyone. And if you were a member of the nobility or even the royalty, we must recall again that even the palace of Versailles lacked restrooms. Human waste would accumulate in the corridors. There is a firsthand account of the Queen’s gentleman usher letting go of her hand to go urinate on a wall hanging. On the case against growth… Sadly, if you look at polling of the general population, you will see that a majority of people, for example, oppose data center construction in their community. And in the DC area where we both reside, regulation has been preventing the entry of self-driving cars that are operating just fine in other areas of the country and that hold the potential to save many of the nearly 40,000 lives that are lost every year to traffic accidents. Progress is being held back by these government barriers because, as you point out, many people do not see economic growth as a particularly important goal. If the AI revolution is a new industrial revolution, that is incredible. What that would mean, if true, is that our descendants, our great-grandchildren, will look back at the 2020s with the same kind of horror and disgust and disbelief with which we look back on the pre-industrial age because their own standard of living will be so much higher. On recent technological jumps… That’s actually going to be my next project, trying to deromanticize the latter half of the 20th century, whether they want to go back to the good old days of the 50s or the 60s or the 70s or the 80s or the 90s in some cases. I think that if you ask the average person, how much money would you have to receive in order to give up every piece of technology that has been invented since 1990? The answer would be quite a high number. You couldn’t use a smartphone, you would have to use a paper map. If you needed to look up someone to come help out around the house, a handyman, you’d have to use an actual phone book. I mean, it was a different era, and the amount of money that people would have to receive in order to give up all of that technology is usually pretty high. On the treatment of animals… Now we may critique modern treatment of animals in various ways, but the fact that people have discussions of animal welfare today at all shows that we live in a completely different world from one where torture was legally required of animals. And we have to remember also before modern transportation, milk would spoil if you tried to transport from the countryside into the city. And so cows were kept in the city for their milk, in these small dark stalls where they could hardly move, and the creature’s milk was called blue milk for its sickly color because these creatures were so mistreated. Farm animals would be kept in the cities, pigs roaming the streets. This was not a healthy situation for the human beings involved either. Environmental degradation was rampant. Deforestation was so severe in parts of Europe that when the colonial era did occur, numerous trees or wood was brought over from North America, from the colonies, because England had deforested itself so much, stripped many of its forests bare, and then there was the pollution of the rivers and the water supply. People were dumping human waste into the same rivers from which they drew their own water and from which they fished. On the beauty of the past… I am not against resurrecting the aesthetics of the past. I am a fan of many of the aesthetics of the past. Old paintings, old styles of architecture. I think that they’re lovely. But today, with our modern prosperity, we are better able to preserve and recreate the artistic and architectural styles of the past than ever before. When Notre Dame Cathedral burned, people thought that we lacked the know-how in this day and age to recreate it and restore it to its former glory. But it turned out that we could. In fact, apparently, because a part… This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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October 30 · 39 min
Bringing Tomorrowland back to the future: My interview with ‘Disneyologist’ Art Tavana
My guest this episode is journalist and author Art Tavana. Art is currently a PhD researcher at the University of Southern California, focusing on Disney and fan studies. He also teaches courses on Disney and technology and serves on the editorial board of the International Journal of Disney Studies. Today’s conversation centers on Tomorrowland, a subject close to my heart. (The introduction to my book is titled “America’s Tomorrowland Problem.”) We’ll talk about its history and Disney’s new plan to reimagine the theme land, which we both hope will make Tomorrowland once again what the plaque at its entrance promised back in 1955: In this episode… * Walt Disney: America’s futurist (0:53) * The evolution of Tomorrowland (4:47) * How Tomorrowland lost its future (9:48) * Bringing tomorrow back to Tomorrowland (16:27) * Balancing Disney’s past and future (26:45) * Disneyland’s hidden gems (33:36) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On the legacy of Walt Disney… He’s definitely a futurist. His innovations in audio-animatronics, his innovations in animation, his innovation in roller coaster technology. We really don’t have the jet-age aesthetic that Disneyland captured in ways that nobody had up until that point. There’s a really good book on this called The Jet Age Aesthetic by Vanessa Schwartz. And she talks about how Disneyland took that mid-century modern, retrofuturistic aesthetic of movement and jets and transportation and turned it into an attraction-centered experience that really changed the way we as Americans view technology and experience. So I think that is a foundational accomplishment: He revolutionized blending technology with experience in a way that I think is literally our society today. On the evolution of Tomorrowland… In the early 70s–mid-70s, Tomorrowland goes away from the practical, realistic future to more of a Jules Verne [style future]. Disney starts narrativizing the future as more fantasy-based. And so that’s when we move from Tomorrowland as a space to exhibit the future to a space to exhibit the fantasies of the future, which sometimes are the future. Like, sci-fi is kind of a prediction of where we’re going in our society often. But anyway, so that happens in the 70s, and it carries over into the 80s and 90s and even the 2000s. And then that’s when IP becomes the feature. So now what we have is, like, IP and a fantasy of a sci-fi future. But I truly believe, the new Tomorrowland that we’ll probably see in the next four to five years is gonna be more of what people saw in the early Tomorrowland, which is a bit more like a technological exhibition hall, World’s Fair-style park. Now, that’s me being optimistic and hoping for things, but I don’t know if that’s gonna happen. On Tomorrowland’s lost techno-optimism… We’ve become a very techno-negative kind of culture. Techno-optimism, I think, should be focused on tomorrow. I don’t think Tomorrowland should be skeptical of technology. I think Tomorrowland should embrace technology and should be narrativizing it into really fun, engaging, and interesting experiences. Now, educational rides—or attractions, sorry, I always say rides, and you’re never supposed to do that in Disney-speak. But seriously, I think that educational attractions don’t necessarily work anymore. I don’t think they really connect with people. But you can narrativize them in interesting ways and build technology and optimistic, sort of, you know, experiences at the parks. And I think Tomorrowland should be focusing on a view of the future that is embracing the things that are interesting right now, which I think a mission to Mars or some sort of Mars-centric experience should be part of Tomorrowland. On using storytelling to showcase innovation… Well, see, Disney’s magic is going to be—and I think they can do this, and they’ve done this before—they have to really be able to narrativize that world without making it sort of feel dystopian or feel like something that needs to be critiqued. A WALL-E sort of—the Olaf animatronic, the free-roaming Olaf in Paris that uses a lot of AI tech. That’s the sort of way you do it, where you bring it in through the kind of characters people love and experiences people really love, and you showcase the sort of innovation without didacticism. The problem is, the moment you do something where we’re trying to teach you or educate you through ideological sort of baseline preferences and things, that’s when it becomes, I think, a problem for the parkgoer. You know, Disney doing didacticism doesn’t work. It doesn’t work in its movies. It sort of worked in the park in the early era of the park, but it doesn’t really work anymore. They can kind of do that with their story department, but they haven’t done a good job. On balancing nostalgia and progress in Tomorrowland… But in terms of nostalgia, I think when you go to Tomorrowland, the first thing I think of, at least, is Space Mountain. And I think that will be there, and it will be there as it is for the most part. Maybe expanded, but yeah, it’s hard. Retrofuturism is part of Disney’s identity, and the jet age and the mid-century sort of... But how do you keep that without being too old-fashioned? Because Tomorrowland has to be the future. That’s the one part of the park, to me, that doesn’t need to be sort of too preservationist. That’s the one part of the park, to me, that needs to move forward aggressively. And of course, Autopia, one of the original attractions. That is not going away, right? On underappreciated Disney attractions… Autopia, to me, is so underappreciated now, especially since it’s sort of become a dated feature of the park. But I think the fact that you can get in an automobile, a small automobile, and drive on a freeway with kind of free rein to do what you want is special. I mean, it’s not complete free rein because you’re on a track, but you’re smelling the gasoline, you’re smelling the freeways. This attraction, to me, is still the closest thing to the original Disneyland feel. I think that’s such an underappreciated attraction. It isn’t on anyone’s list. If you look at a list of favorite attractions, Autopia is rarely on it, but it’s on mine. I love the smell of it. I love the energy of it. I love that it’s in a corner of the park that not everyone really accesses. I think that’s really underappreciated. I hope that when Tomorrowland relaunches, Autopia is centered as an important part of its future, not just a side attraction or an old nostalgia point. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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October 16 · 31 min
The story of how climate worry has turned into AI worry: My interview with Stephanie Wakefield
My guest this episode is Stephanie Wakefield. Stephanie is an assistant professor of Urban Planning and Environmental Design at Florida Atlantic University. She is also the author of a wonderful recent article in Palladium magazine titled “Frontier Panic,” which examines how the apocalyptic thinking surrounding the climate change movement has now been transferred to artificial intelligence. Today’s conversation will discuss this article as well as some of her other scholarship, diving into how an excessive focus on resilience could hold us back from building a world shaped by innovation and adaptation to a changing environment. In this episode * From climate panic to AI panic (0:53) * Who gets to govern AI? (6:15) * Discovery, experimentation, and the frontier (11:06) * Why we fear change (20:28) * Climate adaptation as experiment (23:02) * Aesthetics, infrastructure, and the future (26:17) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On parallels between AI and climate change… It’s as if you took climate change documentaries and transposed them onto AI. It’s very much the same script and lens. You see people saying our children might not make it to high school because of AI, that we’re all going to die. And, like with climate change, this discourse of apocalyptic projections based on models and media is tied to what are then said to be the appropriate responses. So it’s a discourse that authorizes a particular set of voices to make a claim to governing this new phenomenon, this new technology, and this new environment that we’re in. With climate change, that led to this concept of resilience, which we could talk about more. And now it’s underwriting the idea of pacing the frontier or the AI pause—slowing or even forbidding the development of frontier models. On who gets to govern AI… In these moments, it is often the case that some figures step in to be the moral authority and position themselves as the ones with the right answer, to guide the mass of the population. And I personally find that to be a really cynical operation because a lot of these discourses are deployed in the name of humanity and the good of humanity, or even ordinary Americans concerned about data centers or something. And I think they actually play on the fears of these people—that they’re using them as a tool in this broader play for power, rather than actually being concerned with them. On fear surrounding AI… I think there are certain factions within society that are obsessed with that (what can go wrong) and forwarding that way of thinking and trying to spread it. It’s a contagion, it’s a virus, like other ones that we have experienced. It spreads through mimetic contagion, through repetition, through feedback loops. We are in a cybernetic society, and if you are trying to influence the culture and the discourse and the mood, you understand that. And you are an operator of feedback, trying to push the swarm, let’s say, in a particular direction and not others. But I would say I don’t think that’s just us in general. These moments of technological inflection—the same was the case in the early 20th century—always involve multiple factions and perspectives. Every time we’re in this space of upheaval, it’s actually like a war, really, a war situation or a game situation. It’s a contest for putting forward other visions and other attitudes. On the AI frontier… The famous Turner essay on it—it’s kind of cliché to bring it up, but actually reading it again is amazing. What he’s describing is a specific experience in a material world, in a real reality, of certain people that was complex, it was fraught, it involved conflict, yes, but also experimentation—an experience that ultimately reshaped those people who had it, who forged out into the unknown. The frontier spirit is one of an individual who is excited by going into the unknown, wants to explore it, find out what is possible there, test reality there, test the new environmental conditions, but also is willing to be reshaped by it. I think that’s a thing that is lost. On resistance to change… Politically, we’ve gone through the past few decades with an extreme discomfort with political categories and binaries and frames. We’ve just been in this endless series of cascading transformation. And so I think that there is, among some types of people, a desire—a conservative desire—to stop time, stop this movement, hold on to something familiar, to build a wall ultimately against all this change rushing at us, or that we’re rushing toward, however you want to think about it. On climate adaptation… If it really is true that we are going through such a time of massive transformation, including environmental transformation, then wouldn’t that be an occasion to try really audacious, totally new kinds of visions and designs and experiments? Shouldn’t this be a time for a civilization in experiment mode rather than a conservative mode? The seawall kind of becomes a metaphor, like building a wall against that change. On 21st-century aesthetics… Infrastructure and the aesthetics of our environment are actually one of the ways in which we create meaning in our lives and create a sense of where we’re going as a society. And I think that’s a massive project that we could and should be embarking on again. There are a lot of calls for a return to classical architecture, which are fine, but I think this can also be combined with a thrust toward the future. What are the new styles, the new aesthetics? What is the new built environment that we want to make that’s adequate to our time and our momentum at this point in history, the 21st century? On sale everywhere by James Pethokoukis The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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October 9 · 38 min
The AI state of play: My interview with Ramez Naam
My guest this episode is Ramez Naam. Ramez has spent years thinking, writing, and investing around technological progress in energy and artificial intelligence. He is the founder and managing partner of Planetary VC, where he invests in emerging technologies across areas including clean energy, electrification, and AI. He is also the author of The Infinite Resource, More Than Human, and the Nexus science-fiction trilogy. Today’s conversation will focus on the pace of AI progress, the roadblocks that could stand in the way, and what all of this could mean for long-term economic growth. In this episode * The state of AI growth (00:38) * Roadblocks to an intelligence explosion (06:11) * AI in the short term (13:34) * AI’s economic impact (19:00) * Balancing AI safety and exploration (22:04) * What will power the AI economy? (31:04) The state of AI growth (00:38) AI capabilities are likely to be jagged for the foreseeable future. I believe in superintelligence, I believe it’s already here. We already have superintelligence playing Go. We’re crossing into superintelligence in formal math. That doesn’t mean we’ll have super capable persuaders, politicians or city planners. Pethokoukis: Where are we right now? As we’re recording this, OpenAI just released all these mathematical proofs and people are being wowed by that. Wherever you think we are at in the world of AI progress, does that result change your opinion? Naam: It’s amazing. It’s very impressive. I’m not sure I thought we would be here right now. Math is a very special domain. I think about the different types of domains that AI is good or bad at in terms of how highly verifiable they are. And AI first got really good at things like chess and then the game of Go, and now parts of math, formal math, because these have some interesting characteristics. You can generate an unlimited amount of data, and AI is very data hungry. You can get to a very firm yes or no with one-hundred percent accuracy. You can verify it as absolutely correct or not correct. But like human persuasion, politics, policy, and so on you can’t. You can do all of that at the speed of compute. You’re limited only by the speed of your computing to figure out if you won the game of Go or if the math proof is correct, which is not how it is in biological research or new material science, which are messy real world. So math is a domain that is pretty far over on the highly verifiable, symbolic, perfect training data, absolutely correct yes or no. All of it happens in software. Where something like curing aging is messy. We don’t have the training data at all. We’re going to need new instruments, new science, you need experiments, and your lag to verify anything is years, decades. And so that’s something that AI is not going to be as inherently good at, in my view. I made you leap over my first question, which is sort of where we are. There are certainly people who think that, by the end of 2027, there will be no debate that everything is changing in a profound, rapid way that changes all aspects of life. And then there are those who say “that doesn’t seem to be happening right now.” The world is a messy place. The world of carbon based life forms is a messy place. And whatever the capabilities in the lab of this technology, how it emerges into the real world is going to be a much slower and uneven process. On those two poles, where are you? Yeah, I mean I’d say look, I’m an AI optimist and I’m also an AI realist. And I think there’s two separate issues we’re dealing with in your question and the one before that. One is speed of diffusion, right? And if you look at expectations of how much impact AI will have on the economy, and you ask people in AI labs, some of them say it’s going to take us to 20 percent annual growth. I mean there’s one chart out there that says it’ll get us to 100 percent annual growth. Then you ask economists Move the decimal point over. Yeah, just get rid of it even. You ask economists and the consensus to you is that, yeah, maybe it’s half a point of annual GDP growth. The economists have just seen too many past technologies run into friction in being absorbed into real life work. The diffusion rate, the dissemination rate, and the bottlenecking on the long pull on the last thing that can be automated. So in computer science we talk about something called Amdahl’s law, which is usually in terms of performance optimization. And if you have a piece of code and you can take 90 percent of it and speed it up dramatically, well the 10 percent you can’t speed up becomes the bottleneck. And sometimes that means you get very little actual speed up if it’s the thing that you’re waiting on. So in things that AI can do entirely on its own, I think we should expect incredible breakthroughs and incredible speed of progress. In things where the task is messy, as you said, and a human still needs to be involved where judgment is involved, where it’s a relational task, as one of Google’s post AGI economists, Alex Imas has this theory about relational tasks being a growth area for humans. In all of those I think diffusion will be slow. And that’s on top of my view that weekly held, but current view, that AI capabilities are likely to be jagged for the foreseeable future. I believe in superintelligence, I believe it’s already here. We already have superintelligence playing Go. We’re crossing into superintelligence in formal math. That doesn’t mean we’ll have super capable persuaders or super capable politicians or super capable city planners or whatnot. Roadblocks to an intelligence explosion (06:11) New ideas get harder to find. Right? You pick the low hanging fruit first. So I fully believe AI is going to have more and more of a role of helping to build itself, but each step will get more challenging. Certainly there are economists. You mentioned economists who study AGI. There are certain economists who think that’s a ridiculous thing to focus your scholarship on. A science fictional reality which may never occur. And even if it should, it doesn’t need a special economics. We have economics and the tools will be perfectly fine for whatever advances we get. But certainly the technologists will say, “you ain’t seen nothing yet.” You either you don’t understand the technology or you’re willfully blinding yourself that everything is absolutely about to change. Is that what they really think? Have I described what technologists think, even the ones who are worried about “it’s going to kill us all” still think this is going to be an amazingly capable technology and even they think it’s a ten percent chance it’s going to kill us all, the ninety percent will change every aspect of our lives and will be an inflection point in human civilization. Yeah, I mean I think we should expect that AI helps us increase our rate of progress in things that we care about. There are many things that we care about where progress is much slower and much more difficult than we’d like. In pharma, we have this thing called Eroom’s Law. Eroom’s law is the opposite of Moore’s Law. Moore’s Law says computing power doubles roughly per dollar every eighteen months. Eroom’s law says that over some period of time, the amount of money you have to spend to design and develop a new drug gets ten times more costly. So we already have these steep diminishing returns to research. And so AI should help bend some of those curves and accelerate how fast we find cures to diseases, develop new materials, etc. So I see it as finally very good for humanity. But I think there’s a particular assumption in the “my gosh, the singularity is scheduled for next Tuesday” forecast or for, March third, 2027, I can tell you it’s the singularity, whatever viewpoint you have. And that is the generality of AI going to one hundred percent. That is that AI will just be able to do every single thing that humans can do better than humans. And I don’t see strong evidence of that. What we see is more like logistic curves where AI, at… This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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October 1 · 29 min
An update on AI’s economic impact: My interview with Scott Strand of Google’s AI & Economy program
My guest this episode is Scott Strand. Scott is Head of Strategy, Operations, and Special Projects at Google, where he founded the Google AI Economy program as well as Google ATLAS. Recently, Scott co-authored two papers, “Mapping Gemini’s Usage in the Economy” and “AI in Science: Early Insights.” Today’s conversation will discuss these two papers, diving into the role AI could play in benefiting society through everyday life, scientific progress, and long-term economic growth. In this episode: * Is AI a general purpose technology? (0:40) * Gemini’s usage in the economy (4:20) * What will it add up to? (9:44) * AI and entry level jobs (15:34) * AI beyond the workplace (19:13) * AI and the future of science (22:15) Faster Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On the visible impact of AI… I think you could dig the deepest hole you can think of, and it would be hard to find the impact unless you were really, really pushing for it. Look, there are the basic stats that everyone can see right now. Unemployment rates are at 4.1 percent or something like that, on trend with more or less where they’ve been. In the data that we’ve looked at, it’s not consistent with the story of AI creating either widespread—certainly not widespread—unemployment or even unemployment in specific pockets. On AI’s usage… One is that, with past technological innovations, routine tasks are the things that get automated first—the things that are repeatable, where you do them over and over in the same way. That is not what we saw in our data. We saw that most AI usage focuses on non-routine tasks. The types of things like creative design, hypothesis testing, doing something that’s a little bit out of the ordinary from your job description. Those make up about a third of the tasks in the average American worker’s job basket. It represents about 65 percent of their AI usage. So they’re really over-indexing on using AI for this type of work. And that poses an interesting challenge to the routine task intensity model, where you expect every wave of technological innovation to automate the repetitive stuff. But that’s not quite what we see happening. The other thing that really surprised us was the amount of blue-collar and manual occupational usage in the data. We came in honestly just expecting to see not very much. That’s certainly what our peer laboratories found. But we saw a pretty significant amount. We see auto technicians using our models to diagnose engine wear and tear, electricians using it to sketch out wiring diagrams and inspect what might be going on. On micro vs. macro impact… So, in a micro sense, the productivity benefits are very real and observable. As to when they start to show up in the macro, I don’t know. I think it’s gonna require a lot of things. It’s going to require teaching people to use these tools to their maximum potential. It’s gonna require reorganizing businesses around it. When they first introduced electricity, they needed to retool entire factory floors in order to make electricity available throughout the factory, and only then were they really able to make full use of it. So I think we’re probably gonna see something similar with AI. On AI’s effect on entry-level jobs… We found in our data that a lot of the usage was people in high-expertise roles using it for lower-expertise tasks, the types of tasks that entry-level workers often take on. And obviously this is concerning. We can’t confirm or evaluate whether or not it’s dampening entry-level hiring, but I think this is something that we need to look at really closely going forward. One thing that I find to be a useful frame for thinking about this is David Autor’s expertise framework, where, if you think about the expertise requirements for a given job, they sit on a distribution curve across the number of tasks. Some technologies automate away the low-expertise requirements related to that role, which raises the average expertise level required for that job. This is kind of what happened with accountants when spreadsheets were released. You didn’t really need to have people doing tables of numbers anymore; the computer took care of that. But that freed up a lot of time for accountants to specialize in tax strategy and things of that nature. On AI’s impact outside the office… It’s hugely significant. Eighty-six percent of AI interactions are happening outside of work. And we see people using it for really valuable things, things like seeking professional services, navigating legal questions, discussing how to engage with government and civic services. That actually overindexes by 20 times relative to the amount of time people spend there. And about half of that interaction with AI happens on nights and weekends when government offices are closed. So it raises a really interesting idea that AI may be helping to extend civil society in some way and help people get more out of their governments, whether that’s benefits or just clearing up questions on fines, et cetera. I mean, I’m a parent, I’m a really busy parent, and so I just think of tired parents sitting at the kitchen table at 10 at night, trying to figure out how to fix a broken dishwasher or translate some zoning notice from the city into something that they can do and act on. AI is really providing real value there with a real dollar figure attached to it. But it doesn’t get measured. On AI in science… We found that scientists were getting a lot of productivity gains out of this. They’re saving about seven hours per week, which they’re mostly just reinvesting back in more research, which is huge. So it’s not all good news. What’s happening is that scientists are able to generate a lot more hypotheses, which is great, but now there’s a backlog of hypotheses to test, and the bottlenecks on research are starting to shift downstream to things like physical experimentation and clinical validation. So, yeah, lots of exciting stuff, but still lots of work to do. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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September 24 · 31 min
📈 How economic growth can defeat authoritarianism: My interview with Dalibor Rohac, author of ‘Unshackled’
On this episode of Faster Please!—The Podcast, I am joined by Dalibor Rohac. Dalibor is the director of global research at GLOBSEC and a longtime senior research fellow in international relations at the University of Buckingham. Recently, he wrote the book Unshackled, which focuses on how economic power is inseparable from geopolitical strength. In our conversation, Dalibor and I discuss his new book and what growing strains within the Western alliance could mean for its economic and geopolitical future. We also talk about Europe’s defense posture and its struggle to remain competitive in the global technology race, as well as why trade within the Western alliance is critical to maintaining long-term Western prosperity. In this episode: * What defines the West (0:43) * The changing West (6:04) * The disappearing secret ingredient (12:54) * A change in nationalism? (18:25) * European regulation (22:56) * Europe’s economic future (26:10) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But for now here are some of the many highlights from the chat: On defining the West… For me, the West is not defined geographically, it’s not defined in ethnic terms, it’s not defined in cultural terms. It’s defined through adherence to a certain set of institutions that people like Acemoglu and Robinson would call inclusive economic and political institutions, and different scholars would have different names for them. But I think we see as meaningful the distinction between autocracy and liberal democracy, between free markets and state capitalism or a planned economy. And I think countries that do have those sorts of institutions that have enabled the rise of the West—places like the UK and the United States—and the opening up of our political systems, they can be in Asia. There’s Japan, there’s South Korea, there’s Australia, and I think they are very much part of the West as much as we are here in Europe or in the United States. On the potential of a changing West… I think we can deal with troubled democracy in Hungary or democratic backsliding in Turkey. Turkey would be one of those cases where there has been a significant shift away from the Western alliance and away from democracy. But if we see a similar shift sustain itself in the United States, I think the world will be in a lot more trouble, even relative to the status quo. On the West’s trajectory… I see all these controls that you’re looking at blinking in the wrong direction. And I think there is some urgency with which we have to create intellectual, political coalitions to defend some of these things. We might need to learn things, relearn things the hard way, but I very much hope that it won’t be necessary and that people will understand what is at stake. I think the most immediate pressure point is the federal budget. If you are spending more on financing your debt than on the Department of Defense, you’re placing yourself in a very poor position to fight a major conflict. On Europe’s diverging defense mindset… A place like Poland, which has been spending consistently between 3.5 and 5 percent of GDP on defense, which has a dynamically growing economy that has now joined the G20 group of most advanced industrial nations of the world, which surpassed Japan in per capita GDP last year. Unfortunately, the further west you go, I think the more complacency you see. I was recently at a conference in Austria, beautiful place, lots of young German-speaking people, both from Austria and Germany, and I had the sense that people wanted to be left in their illusions. Much of the rhetoric reminded me of the stuff you would hear at conferences 10 years ago about multilateralism and just getting along and solving the climate issue and preserving the advances of the welfare state. There just wasn’t the same sort of urgency that you hear when you go further east. On Europe’s position in the global technology race… That sense that we have to facilitate the diffusion of new technologies if we don’t want to be left at the periphery of the global economy is getting stronger. I think people understand that Europe is not going to have its own frontier AI model and will instead remain reliant on American technology. The transatlantic relationship is not in a good place, but there is no real constituency in Europe for aligning with China when it comes to technology and tech governance. The lack of separation between Chinese corporations and the Chinese state makes people uneasy, irrespective of their politics. On the West’s retreat from trade… The American turn away from trade and efforts at trade liberalization has coincided with an inward turn in Europe. The EU has found it increasingly difficult to get trade deals done, whether with Canada or, more recently, Mercosur. When it comes to trade, though, I think we may be starting to see a reversal in Europe. And when it comes to domestic reforms, the dire international situation could serve as a catalyst for change at the European level. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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September 17 · 34 min
✨ Why verification is AI's real bottleneck: My interview with economist Christian Catalini
On this episode of Faster Please!—The Podcast, I am joined by Christian Catalini. Christian is a research scientist and the founder of the MIT Cryptoeconomics Lab. Recently, Christian co-authored “Some Simple Economics of AGI” In our conversation, we focus on the AI bottleneck of verification, rising safety concerns, and how to address and solve these problems while maintaining growth and the US advantage over China. In this episode: * Red light or green light? (0:37) * AI risk and safety (8:07) * The bottleneck: verification (15:28) * Markets and AI safety (22:48) * AI labs and regulations (26:17) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some of the many highlights from the chat: ✨ On slowing AI industry growth… Definitely not a red light for the entire space. I think that would be a very bad idea. That said, concerns have been raised by the labs themselves. So I think the next natural step is to send some real evaluators in and see what’s actually going on. We’ve seen a report from METR. I think they’re a talented team, but they have a very particular bias and a very particular type of expertise in this. I would love to see traditional security engineers and cyber experts looking at what happened inside OpenAI, what is happening inside Anthropic. Is there something we should be concerned about? Or are these companies just racing and potentially being a little bit reckless with their deployments? ✨ On catastrophic AI risk… Could someone, on the bio side, use the information from an LLM to create something more dangerous than attempts that have been happening over the last few decades, where people were just ill-informed? They got 80 percent of the way. Could they get to 100 percent of the way and hurt a substantial number of people? Yes. Would it be a pandemic? I think that’s the big stretch. Once you do those massive jumps, I think that’s where we’re in the land of science fiction. And honestly, it’s harmful because we keep anthropomorphizing these agents when there are very benign explanations for what they’re doing. In fact, it’s the training that the labs are doing with reinforcement learning that’s leading exactly to the outcomes you’re seeing. ✨ On the verification bottleneck… The act of verification is the actual bottleneck. Because with AI, you can just throw compute at anything that’s been measured and therefore can be automated. But if you can’t trust the output, if there are important unmeasured dimensions of that problem that the AI doesn’t have access to, well, then you’re in trouble. I think companies today, including the labs—and maybe this is why we’re seeing the security incidents—have this temptation to keep advancing and rapidly progressing, potentially not doing all the proper verification. ✨ On regulating AI… I don’t think we need to come up with draconian, very tight regulatory bodies for mature markets, right? Airlines, financial services—how long did it take us to fine-tune that regulation so that we got it right? Decades. And in fact, it’s still a work in progress. I think here we need to be thoughtful. I think we can start with better measurement. Let’s surface the evidence. Let’s have neutral evaluators and inspectors. Again, we have METR, but we need probably 10 different organizations with very different philosophies, different skill sets, that can go in and provide us a neutral third-party assessment. By the way, neutrality also means funding. If the funding for these institutions comes from the labs, well, I don’t know what to make of it, right? Maybe academia has a role to play. I’m not sure, but we really urgently need better measurement. ✨On the labs’ role in AI safety… The antitrust concerns don’t really apply in the format of safety. Of course, if you’re timing model releases and sort of handicapping the industry in different ways, that could be an antitrust concern. But I think many have said this very eloquently over the last few days. Yes, the labs are in full control. If they don’t believe their products are safe to ship, they don’t even need to coordinate, right? In a sense, each one of them can look at their own evidence and make their own risk-based decisions. ✨ On who can benefit from AI growth… The obvious one, of course, is NVIDIA, right? They control the hardware, and so they benefit from more intelligence being used across the economy. But take Meta. I mean, Meta is developing AI that they can put to work into every other line of business. Same with Google. Google doesn’t need to be a frontier lab, right? They can take great AI and apply it to their products and be a lot more effective. Financial services—you have the likes of Stripe and Ramp. What they’re doing is taking the models and making financial services better. So that’s a much more positive view of the future, one where we’re not completely disempowered by this massive supercorporation, but also one where human dignity and the contribution of humans to labor, I think, will be strongly preserved. Faster Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Hey, my book is on sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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September 9 · 32 min
✨ My interview with economist Tyler Cowen on the Age of AI (and more)
On this episode of Faster Please!—The Podcast, I am joined (again) by Tyler Cowen. Tyler is an economics professor at George Mason University and co-founder of the economics blog Marginal Revolution. He is an opinion writer for The Free Press and the author of several books, including The Great Stagnation, Average Is Over, and Stubborn Attachments. During our conversation, Tyler and I discuss AI risk, the extent to which public pushback could slow AI progress and economic growth, different forecasts for AI development and where Tyler stands, and what the technology could mean long term for the American economy. In This Episode: * The Effect of AI Industry Pushback (0:41) * Different AI perspectives (7:37) * The Fear of AI (12:37) * Economic Growth: (17:32) * The Future of Jobs (23:06) * AI on a Global Stage (26:50) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some of the many highlights from the chat: ✨ On potential catastrophic harms from AI… They love to talk in extreme parables of Skynet going live or a bioterror attack where all humans die. But, you know, in the short run, the intermediate term, what share prices should we expect to go down? What variables should we expect to change? Give me a number for what cybersecurity costs will be next year and by what percentage that will go up. There was another estimate I saw. It said cybersecurity insurance costs will double over a five-year time period. This was from experts in the sector. Again, I’m not endorsing that number, but it’s a number, and it puts it in perspective. It’s terrible if those costs double. But again, it’s not an insane scenario that we can’t live with. ✨ On whether AI fears lead to heavy regulation or a pause… The discourse will be ugly and stupid no matter what your point of view, even if you favor a lot more regulation. But it’s very hard to stop fundamental new technologies. There’s also Chinese open source. There’s a national security imperative here. I just think it’s going to happen. It will pain me every day to see the debates and some of the laws that probably end up getting passed, but I just don’t see how it gets stopped. You know, for better or worse—I would say for better. But there’s not a coherent path for telling a story of how this ends. ✨ On how much AI company executives are to blame for the public AI backlash… I don’t know if the word “blame” is the right word here. I think a lot of the PR has not shown enough equanimity, and the people who are motivated to work on this are precisely the same people who think it will have very extreme effects. And those companies have gotten a lot done at a truly incredible pace, even by American or tech-world standards. So the notion that they have semi-religious views of what this all means is a very San Francisco kind of thing. Like, do I blame people in the 1960s who thought that LSD was creating a new world, a new way of living, a new way of life? Well, sort of—but that’s what we are. You know, we’re a little nutty in the head as a country, and this is California, and then it’s San Francisco. So we also need to embrace that nuttiness at the same time. I think that’s the bigger picture I try to keep in mind when maintaining my own equanimity. ✨ On roadblocks to economic growth from AI… The thing (AI) being smarter is not the problem. The things are already very smart. The real issue is, if you're in a mid-size to large organization, reorganizing your systems—HR, finance, whatever, all the things they do at AEI—not just for people on an individual basis to use, say, ChatGPT to augment their labor, but actually building the whole system around AI in a way that's reliable and coherent and everyone there knows how to work with. That's very, very, very hard and slow. And if I saw more progress on that, then I would really think the rates of productivity growth will be much higher soon. ✨ On AI and job displacement… In any foreseeable future, we can achieve full employment if we don’t screw up other policies. Just think of the number of jobs that will be available testing the new ideas that AIs come up with, most of all in the biomedical field. Think of all the new jobs that will be available gathering and processing data for the AIs. It wouldn’t shock me if, in some distant future, that was like a third of the whole labor force—the way today, you know, services are some very high percent of the labor force, something that people in the Industrial Revolution never would have imagined. ✨ On how China thinks about AI and the national security implication… I don't think we understand it. I'm not sure they understand themselves. But it seems to me, as a non-Christian society, they don't have that much of a Book of Revelation scenario, so they don't really have doomers. They do think it's an important technology. I strongly suspect they're afraid it could displace the CCP, and they're much more worried about it in a way that we are not. Those are my hypotheses. I stress the word “hypotheses,” but that would be my best guess. Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. On sale everywhere by James Pethokoukis: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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August 26 · 34 min
🚀 The New Space Age meets the Age of AI: My interview with Phil Metzger
Thanks in large part to the massive drop in the cost of getting a pound or kilogram of stuff into orbit and beyond, many of the boldest Space Age dreams are now possible. The business of space makes economic sense like never before. And here comes the AI Revolution to really give the sector a boost. Today, on Faster Please!—The Podcast, I am joined by Phil Metzger. Phil is a professor of planetary science at the University of Central Florida and director of its Stephen W. Hawking Center for Microgravity Research and Education. Before joining UCF, Phil spent nearly 30 years at NASA, where he worked as a senior research physicist. (I also highly recommend his X account.) In this episode, we talk about why AI has made the economics of space work by providing a “killer app,” what the first off-world industries might look like, what obstacles we still have to overcome to make them viable, and what the long-term future holds. In This Episode: * The economics of space (0:49) * Industries launching in space (7:36) * Cutting space expenses (11:31) * How do we start? (16:55) * Dealing with lunar dust (22:31) * What does the future hold? (29:31) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On orbital and lunar manufacturing… We have a lot of work to do. But it isn’t gonna require any new physics. It’s just gonna be industrial engineering, aerospace engineering, civil engineering on the moon, and a straightforward effort to do it. And so we’ve got to spend the effort building these technologies. But there are already companies getting ready to build commercial space stations in low Earth orbit. There are companies getting ready to start launching data centers in space. I believe that once that begins to expand and grow, the economics of space in every sector of the space industry will be pulled upward by the huge economic value of AI. On how the case for AI is the case for space… We were hoping that Mars settlement would drag up the entire in-space industry. I ran models on Mars settlement, and I believe it’s very doable. But the new thing now is AI. AI swept in like a storm two, three years ago. Suddenly everybody woke up and realized, “No, this is the killer app for space.” Elon immediately started talking about “Mars is gonna have to wait a couple years because we’re gonna do the moon right away.” And it’s all because of AI. So AI has changed our whole assessment of the business case for space. On the economics of orbital data centers… The amount of throughput of spacecraft hardware will be so gigantic that there will be this huge motive to shorten the supply chains and move more industry closer to the launch pads. And then the workforce we’re gonna need is gonna grow gigantically. Maybe we’ll do AI and robotics, but there will be an opportunity for huge growth in the labor force. So I think governments, universities, everybody in industry and in finance needs to get ready for this tidal wave that’s about to sweep through. … So in Elon’s mind, the issue is the demand for AI will keep growing, and it’ll grow so fast that you can’t build the data centers fast enough and you can’t launch them off the earth fast enough. It’ll be a logistics problem and a supply chain problem. [Musk] hasn’t said this, but I will add, it will be an atmospheric protection issue. If you start launching too fast, then it does cause some cumulative damage to the atmosphere. The atmosphere will heal pretty quickly, so it’s not long-term damage from rocket launch. But I believe there will be political pushback when people see gigantic rockets launching every hour, hour after hour, 365 days a year, from 50 launch sites around the world. So Elon’s idea was we’re gonna have to build these AI systems on the moon using lunar resources, and we don’t need to launch them off the moon with rockets because the moon doesn’t have an atmosphere. We can just shoot them off the moon with a railgun. They call it a mass driver in that context. On lowering launch costs… We’re expecting launch costs to go from—right now they’re like $1,500 or $2,000 per kilogram to low Earth orbit—we’re expecting it to go down to like $35 per kilogram in 30 years, and that’s a conservative estimate. On the future of humanity in space… Most people don’t know this, but there are at least 150 planet-sized objects in our solar system. Most of them are dwarf planets far away. But the moons are amazing worlds, and pretty soon we’re going to have buildings being constructed. We’ll have architects designing buildings for the environment of Titan. I can’t imagine what beautiful architecture will be developed. Once we’ve got an abundance of robotics driven by AI, then we’re not gonna be doing things on the cheap. We won’t have to. And so we’ll be able to make beautiful cities on all these worlds. We’ll be bringing beautification to all these planetary bodies throughout the solar system. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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August 18 · 30 min
🏁 The Great AI Race as a clash over compute: my interview with analyst Ryan Fedasiuk
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: The AI race between America and China isn’t just about whose AI models are at the frontier or get adopted most widely. Today on Faster, Please! — The Podcast, I am joined by Ryan Fedasiuk, a fellow at AEI and the author of the Substack Choosing Victory, where he focuses on US-China relations, technology, and national power. He’s also an adjunct assistant professor at Georgetown University. Recently, Fedasiuk has written about the US-China AI race, and while much of the debate has focused on the models themselves, Fedasiuk is focused on the role of compute in shaping the global balance of power, which is also the subject of a new report, Voltcraft: Industrial Competition in the Age of AI. We discuss the speed at which AI capabilities are improving, the dimensions of the US-China AI race, and why Fedasiuk thinks compute will be central to that competition. We also discuss a global US strategy and, as AI abilities increase, what role the American government could play in ensuring safety. In This Episode: * How Fast Is AI Moving? (0:54) * The US-China AI Race (7:08) * The Future of the AI Industry (12:42) * The Compute Race (17:04) * Expanding US AI Infrastructure Abroad (22:05) * Geopolitics and National Security (25:10) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On the pace of AI progress… At least according to definitions circa the late 2010s, we’re living through what I would describe as a fast takeoff. We have, as far as I am concerned, artificial general intelligence capable of meeting the performance of human beings or exceeding it at most tasks. And I think that things are only likely to improve from here. On the US-China AI race… We are obviously living through this uncertainty. When Mythos was unveiled on April 6, I think it sent a real tremor through the Chinese national security apparatus and kind of a moment of, “What is this? What do the Americans have? What is this system capable of achieving? When can we produce our own?” On why compute is critical… The fact is that to make the most out of frontier AI and to run it at scale, you still need tons of devices that turn electricity into tokens. You still need tons of compute. And really, I think the name of the game is going to be who can build and install computational power around the world. On why America needs to export its compute… If compute is the substrate of the global intelligence economy, we want to make sure that it’s US-designed compute that other countries are choosing to buy and install rather than compute manufactured in China. On who should get access to American compute… If we can expect the developer ecosystem in Singapore is going to take off like wildfire and start building and using a lot of AI applications, maybe we want to make sure that Singaporeans are building on American compute ASAP before China’s compute becomes a viable alternative that could serve that market. Maybe we want to make sure that that market is served even before certain constituencies in Des Moines. On government intervention in frontier AI labs… I think that we are already seeing some shadow of this, even if it isn’t declared. I think we will likely see a continued molding and merging of private sector capability with the resources and infrastructure of the national security enterprise. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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August 6 · 35 min
💧⚡🖥️ A deep-dive on data centers: My interview with AI researcher Andy Masley
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: With the massive buildout of data centers has come an equally massive backlash. They’ve been blamed for higher electricity bills, taking up too much water, and pushing out farmland. All this has led to a public outcry and efforts against their construction. But how much of the criticism is warranted? Has one of America’s fastest-growing industries become a political scapegoat? Today on Faster, Please!—The Podcast, I am joined by Andy Masley, an independent writer supported by Coefficient Giving who deep dives into AI research. Recently, he has focused on data centers at his great newsletter and separating facts from myths surrounding them. We discuss what the evidence actually says about data centers’ impact on water, land, and electricity prices—and where Andy thinks people get the facts wrong. We also discuss AI art, Waymo, and America’s willingness to embrace technological change. In This Episode: * AI Art as Curation (0:37) * Waymo and Technological Disruption (4:43) * The Case for Data Centers (9:14) * Water and Land (15:41) * Data Centers and Electricity (21:41) * The Data Center Backlash (28:50) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On AI Art… As you see someone using Midjourney to create images that you are actually much more interested in, and find more subtle or pleasant than the kinds of AI-generated images most people are typically exposed to on their timelines, it can really open people up and make them realize that these tools are much more powerful than they might expect. On Waymo Entering Cities… While there are many industries that I might worry about completely disrupting, the number of deaths caused by driving, and the difficulty people face getting around very dense cities, are such important problems that I am willing to hand the robots this one before we march forward elsewhere. On this issue, I am entirely gung ho: “Let the Waymos have it.” On misconceptions about data centers… If you somehow hid the words “data center” but included all the other information and asked, “Would you accept these specific trade-offs in your community, such as using a certain amount of water and land, in exchange for this amount of tax revenue?” I think that, in most places, with a few exceptions, people would say yes. On the “lack” of land… This has really blown up in the past few months in a way I really didn’t expect. Willie Nelson actually just posted this thing that got like a hundred thousand likes on Twitter about, “Don’t give them an inch of our farmland.” My basic finding is that data centers themselves, the physical buildings, will take up something like one-fifteenth of the land that we currently dedicate to Christmas trees in America, which isn’t nothing, but it’s also incredibly small. On data centers driving up electricity prices… Electricity markets are very complicated and don’t always work in a simple, you increase demand, and the price just immediately goes up for everyone. That’s not really how it works. They have had to slightly raise household electricity prices because of the data center. They’ve reported data centers as being one of several causes, but that’s usually not a significant percentage. On the growing data center backlash It’s hard not to feel like a lot of the anti-data center stuff is also this collective, “I can find this deep meaning in this local struggle against these people who I perceive to be bad.” The general idea that we can all band together as this ragtag team of everyday people and prevent this thing from destroying our local community is a very compelling narrative to people, regardless of the actual specific harms that are expected. I do think general anti-tech sentiment is definitely playing into this. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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July 30 · 34 min
📈 The business of AI: My interview with technology analyst and investor Azeem Azhar
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Artificial intelligence is expected to transform the economy, but what about the AI industry itself? Companies across the AI supply chain are now valued in the trillions of dollars. But do the data and current demand justify such lofty expectations, or are investors getting ahead of reality? And when will the AI economy finally begin to live up to the hype? Today on Faster, Please!—The Podcast, I am joined by Azeem Azhar, a Digital Fellow at Stanford’s Digital Economy Lab, the founder of Exponential View, a research platform focused on helping leaders understand emerging technologies and their impact on society. He is also the author of The Exponential Age and the co-author of The State of the AI Economy, one of the first serious attempts to measure the size and trajectory of the AI economy from the demand side and know what customers are actually paying for. We discuss where the AI economy stands today, why businesses are still struggling to realize AI’s full potential, who stands to capture the greatest gains from the technology, and the roles different countries could play in the “AI Race” between the United States and China. In This Episode: * The AI Economy (0:44) * AI’s Return on Investment (6:40) * Will AI Bring an Entrepreneurial Wave? (12:41) * When AI Hits the Bottom Line (17:53) * Who Wins the AI Economy? (23:48) * Europe in the AI Race (30:20) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On AI’s creation of abundance… It may look like abundance when you’re on the other side before the inflection, but when you’re in it, it really looks like a day-to-day grind where you still have to fight for the things that you care about. The notion of abundance in general, I think, defies the realities of physics. You always need energy to get something done. On why AI adoption has been slower than expected… Companies are going through the similar type of process that Paul David describes around electrification, which is that you can put the light bulbs in the workshop—that is the copilot. But to move to the moving assembly line requires a lot more work and a lot more expertise. On AI’s challenge for businesses… No business was ever about, “Can we summarize an email quicker than before?” The question is: At what point do AI tools meaningfully come in to make those decisions happen more effectively—either at higher quality, at lower cost, or at higher speed? On why AI may not lead to immediate job losses… Companies realize that there was so much tacit knowledge in their workforce that they just let walk out the door. I think CEOs will start to want to understand: What are we losing when we cut an entire function for an LLM? On whether we know who will win the AI race… If you’d asked me two years ago, the winner was OpenAI, and Anthropic was really just playing around doing God knows what. So I don’t think we necessarily know who the biggest winners are. Does Anthropic or OpenAI have a significant role to play in several years time? I’m absolutely sure that will be the case. That doesn’t preclude there being other, bigger winners. On Europe’s AI opportunity… There’s things that states can do, even if they’re smaller states like the UK, because they can clear paths, they can help vertical integration, they can get access to the best specific talent. And this is not all about large language models. It’s also about models that can stimulate physics or models that can discover new materials. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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July 21 · 31 min
✨ Data center distortions: My interview with energy policy analyst Shuting Pomerleau
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: What problem does a data-center moratorium solve, exactly? As these warehouse-sized supercomputers face growing public backlash, they’re blamed for higher electricity bills and strains on the power grid—all while failing to provide enough jobs or tax revenue. But are they actually the problem, or are they exposing problems that have existed for years in America’s electrical grid? Today on Faster, Please!—The Podcast, I am joined by Shuting Pomerleau, the director of energy and environmental policy at the American Action Forum, where she studies electricity markets and energy policy. We discuss New York’s controversial decision to pause construction of large data centers, whether AI is really driving up electricity prices, the economic benefits of data centers, who should pay for expanding the grid, and how states should respond to growing demand for power. In This Episode: * New York’s Data Center Slowdown (0:16) * Dealing with Demand (7:09) * What is the Right Step Forward? (14:24) * Who is Paying Up? (19:27) * Can Regulation Fend Off Data Center Growth? (23:39) * Where Do Data Centers Go from Here (27:44) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On New York’s data center moratorium… My concern is that pausing this will send a very strong signal to investors, data centers and developers, a very chilling signal saying, “you’re not really welcome here.” This is such a fast-moving space. One year is actually a lot of time. On what’s really driving electricity price increases… What has been really driving the electricity increases mostly in the residential sector is the local distribution system—the maintenance, repairs, upgrades that cost a lot of money. It was almost like a coincidence with the AI data center boom and the sentiment against AI. We see that in electricity prices, but if you look into the real price level changes, it’s still quite flat both at the state level and across the country. On the policy challenge of funding AI infrastructure… What is a fair share? That is a question that has always been on my mind. The data centers are not all sitting there across the country doing their own thing separate from the remaining population. They’re providing digital services and great services for us, you and me, using AI. So, what is a fair share? How can they pay exactly how much they use? On the economic benefits of data centers… The opposition to AI data centers is probably one of the biggest pieces of misinformation out there. The right way to look at it is these are businesses that are paying taxes; they’re paying property taxes. If you look at Loudoun County, about 90% of the county’s operating budget comes from data centers. On whether regulation can slow the AI data center boom… I think of the AI data center boom in the United States as a fast-moving train. It’s going to move; it’s going to happen. I think the New York States moratorium, some of the local opposition across the countries may slow down some of the application of development, but not very significantly. I think what will have a material impact on the pace of AI data center development is all the discussion about who’s paying for it. On what needs to happen with data centers… First, permitting reform. It will alleviate the burden off of a lot of people’s minds, and a lot of stakeholders’ minds. Two is, we really need some reform in our grid, in terms of interconnection. I would say interconnection is your keyword, both on the generation side, connecting to generation sources and to large load customers. On sale everywhere: The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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July 14 · 34 min
✨ My interview with Sebastian Mallaby, author of 'The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence'
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: If my podcast guest today is correct, the emergence of generative artificial intelligence "heralds a transformation more profound than anything since Homo sapiens acquired the capacity for abstract thought." That's about as pure a distillation of the San Francisco Consensus view on the importance of this technology as it gets. Today on Faster, Please!—The Podcast, I am joined by Sebastian Mallaby, the Paul A. Volcker Senior Fellow for International Economics at the Council on Foreign Relations and a widely read columnist for The Washington Post. He is also the author of the new best-selling book The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence. (Spoiler: It’s tremendous book about the man, the company, and the technological revolution. I really liked it.) We discuss The Infinity Machine and the life of Demis Hassabis, including how his original vision for artificial superintelligence compares with the propulsive race unfolding today. We also explore how that competitive acceleration has affected the focus on safety, what role government regulation should play, and why many people may still be underestimating how transformative AI will become. The Quest for “Success” (0:27) Inside the Mind of Hassabis (8:29) The Race for Monopoly (12:31) The Economics of AI Anxiety (17:05) Governing the AI Race (24:17) The Biggest Leap Since Abstract Thought (30:13) A lightly edited transcript of our conversation will appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: On where AI is heading… You look backwards; you see how fast the progress has been. To merely extrapolate forwards is probably to undersell the speed at which we’ll accelerate in the future because there’s an accelerating phenomenon here where the more advanced you are, the easier it is to get to the next level. On Hassabis’s belief that AI development would look more like the Manhattan Project than a multi-country, multi-company competition … In retrospect, it’s crazy. All one can say is that ex ante, the atmosphere in the community of AI builders when Demis began his company in 2010 was that this was a thing that simply didn’t work. AI could not recognize the photograph of a cat. AI could do nothing. It was deep AI winter. And so, under those conditions, you could assemble the entirety of the world’s strong AI believers in one conference in San Francisco, and it felt like a single community. So, this sort of Singleton scenario where you just have one lab, it was a natural outgrowth of that moment in time. How AI competition has overwhelmed that vision… Before 2022, Demis had the freedom because he was clearly the leader to define what the next project should be. He chose at one point to go and do this protein folding project. …This is kind of AI with a smiley face painted on it. Whereas once the chatbot went viral at the end of 2022, ChatGPT, then everybody had to pile in and build a competitor and there’s a lot less leeway to define your own path. So, I think the agency of the individual was quite strong until 2022 and thereafter the power of the race dynamic takes over. What skeptics, such as many economists, have gotten wrong and right… The number of improvements before even we talk about Mythos and the cyber capabilities of that one, I mean, it’s been an extraordinary ride in what is actually less than four years. So, I don’t take back anything I say about the speed of the advance of the frontier. Now that’s different to the speed of the deployment. There I have a lot of sympathy with the economist. On the difficulty of AI regulation… I’m actually quite optimistic in terms of the ability of a government agency to regulate… People often think of AI as a bunch of code that flies around cyberspace and you really can’t control it. But actually, it’s also a bunch of data centers which are huge physical installations. The government knows precisely where they are. They can’t be moved or hidden. On his superintelligence timeline… To be honest, I would say it’s already true. I mean, you try using Fable and if people are listening and they’re inclined not to agree with me, I just ask you, spend a couple of hours with Claude Fable and then see if you disagree with me…I think it is smarter than me by quite a long shot on any topic I ask it about. On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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June 25 · 37 min
✨💪 AI, jobs, and productivity: My chat with economist Erik Brynjolfsson
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Will artificial intelligence displace workers or make them more valuable? Probably plenty of both. But how much in either direction, and how fast will all this change happen? Today on Faster, Please!—The Podcast, I am joined by Erik Brynjolfsson, one of the world’s top economists studying how AI is reshaping productivity, jobs, and the American economy. Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI, and Director of the Stanford Digital Economy Lab. He is also the co-author, along with Andrew McAfee, of Machine, Platform, Crowd, The Second Machine Age, and the classic Race Against the Machine. He is a co-founder of Workhelix, which helps large companies measure, track, and maximize the return of their AI investments. We explore what the next decade of AI could mean for workers, businesses, and the broader economy, and what the relationship between humans and intelligent machines may look like. We discuss why views from Silicon Valley and the East Coast differ so sharply on AI’s impact, why the technology has produced dramatically different results across companies, and why some firms and departments are already seeing meaningful productivity gains while others have yet to unlock AI’s full potential. In This Episode: * What AI brings to the table (0:35) * Does AI bring too much? (6:49) * Moving away from the Valley view (10:55) * How perspectives are formed (16:05) * Companies and productivity (23:01) * AI in the foreseeable future (29:21) A lightly edited transcript of our conversation will be appear in my Week in Review issue on Saturday. (Another option is using the Substack auto transcript function.) But here are some edited highlights from the chat: What’s the positive case for workers in an AI future that currently sounds like it only benefits CEOs, tech firms, and data-center builders This is, I think, the best time to be alive if you’re somebody who's got agency and ambition and intention and wants to do something, create new things for themselves and for the world. But that's not the story that's out there. …There's going to be a lot of new jobs created. You got to tell both parts of that story. Of course, you want to lean into the second part of the story about the new stuff that's being created [and not just job disruption and loss], because that's where people should be focusing. There's no point staring at the things that are disappearing… My company, Workhelix, is all about doing that. So I'm doing what I can for my part. I would love to see more people lean into that part of the story. Can someone coherently believe both that AI may become extremely powerful—possibly AGI or superintelligence—and that the future labor market can still be broad, humane, and full of useful work? I think we're going to have several decades worth of humans and machines working together. I'd like to extend that window where we can still have an important role for humans to contribute and for us to expand that pie, not simply automate what's already existing. We should probably be preparing for some further time in the future when there's less of a role for people. But most of my friends here in Silicon Valley, I think their timelines are way too short for when humans no longer have a role. If AI eventually becomes capable of doing almost all economically valuable work, would that actually be a desirable future for humanity, and what would make it a good society rather than a dystopia? We should start preparing for a period where AI can do almost everything and we need to come up with mechanisms so that we still have freedom and power in that kind of world. I don't think that's automatic. And one of my biggest concerns, to be frank, is not that we don't have abundance, I think we will, but it's that we don't have freedom and autonomy. That's something that's not to be taken for granted, and we need to put in place ways that we not only have the wealth, but we also have widely shared prosperity and widely shared decision making rights. Is AI already delivering real business value and productivity gains, or are the impressive lab results still mostly failing to show up in the economy? The returns (AI productivity gains) have been somewhat disappointing. To me, that’s totally natural. That’s totally understandable. As you know, I’ve done a lot of work, we call it the Productivity J Curve on the need for complementary investments for intangible investments in new business process design and new skills for the workforce, even new products and services. Those take time. With past general purpose technologies like the steam engine and electricity, it took literally decades before you got those returns. How should we think about AI’s usefulness when some high-profile business uses have produced embarrassing hallucinations? They (AI) can also do wondrous things that are incredibly valuable. My advice is to keep a human in the loop. Ultimately, you, the person, is responsible for the output. You can identify where the good things are and not the bad things. Can AI progress happen so quickly that society can’t adapt, and should policymakers worry about the speed of change, not just the destination? How fast do we want to go with this? It's not infinitely fast. We want to be able to digest and manage it. Now, the way I would handle that is I would put more resources into speeding up our ability to understand and adapt, and we're not doing enough of that. And that means, for instance, instead of cutting the budget for economic statistics, I would be massively boosting it so we get more visibility. On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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April 28 · 28 min
✨💪 The future of work in an age of AI: My chat with economist Daniel Rock
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Artificial intelligence is undoubtedly poised to change the workplace—the question is, by how much? Key voices in Silicon Valley warn that white-collar jobs will soon be a thing of the past, while others predict more modest economic gains as firms struggle to reorganize workflows. When it comes to the future of work and American business, contradictory forecasts can be difficult to interpret and reconcile. Today on Faster, Please!—The Podcast, Daniel Rock and I attempt to sift through the often-confusing current AI conversation. We cover the distinction between “AI-exposed” fields and those destined for automation, explore the bottlenecks that could slow adoption among businesses, and offer a more realistic outlook for growth. Rock is an assistant professor of operations, information, and decisions at the University of Pennsylvania’s Wharton School. There, his research dives into the economics of AI and digital technologies, as well as the future of work. His paper,The Productivity J-Curve: How Intangibles Complement General Purpose Technologies, is worth a read. In This Episode * The trouble with forecasting (1:40) * The economist’s evaluation (8:09) * The productivity J-curve (11:49) * Exposure vs. automation (18:53) * Growth projection (23:04) (A lightly edited transcript of our conversation will be appear in my Week in Review issue on Saturday. Another option is using the Substack auto transcript function.) On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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April 10 · 19 min
🏗️ A hub for hard-tech startups: My chat with 'American Shenzhen' builder Joshua Farahzad
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: As a college sophomore, Josh Farahzad assembled a group of students from around the country in an attempt to launch a homemade rocket into space. From there, he ditched the traditional route and scoured the country for the perfect place to build a uniquely American mega-project. Disillusioned with the entrepreneurial atmosphere of the Bay Area, he has since broken ground in central Texas. Caldwell County is now home to Proto-Town—a place Farahzad hopes businesses will have the space to engineer and build world-changing hardware. Today on Faster, Please—The Podcast, I chat with Farahzad about his quest to build America’s premier manufacturing town from scratch. In This Episode * Welcome to Proto-Town (1:20) * The Limits of California (5:18) * From the Ground Up (10:46) * The Vision (17:35) (A lightly edited transcript of our conversation will be appear in my Week in Review issue on Saturday. Another option is using the Substack auto transcript function.) On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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March 24 · 42 min
✨ The Age of AI, an update: My chat with policy analyst Dean Ball
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Anxiety is running rampant about the future of artificial intelligence and its place in society. When technology CEOs warn of an impending white-collar jobpocalypse (or jobageddon, if you prefer), it’s no wonder public pessimism is so widespread. Today on Faster, Please!—The Podcast, I chat with tech policy analyst Dean Ball to help us sift through some of the uncertainty. We talk about recursive self-improvement, the role of AI in everything from medicine to defense, and what to think about the possible growing risk of AI company nationalization. (FYI: Our chat occurred just before the White House released new guidelines for AI federal legislation, about which Ball opined on X/Twitter: “The White House’s proposal for a nationwide AI law is a thoughtful document that will serve as an excellent foundation for the legislative work ahead. I would be happy to see these principles, if translated well into statute, become law.”) Ball is a senior fellow at FAI, the Foundation for American Innovation. He recently served as senior policy advisor for Artificial Intelligence and Emerging Technology at the White House Office of Science and Technology Policy, as well as strategic advisor for AI at the National Science Foundation. He was previously a research fellow at the Mercatus Center and a policy fellow at Fathom. He’s also the author of the excellent Hyperdimensional Substack newsletter. In This Episode * Public pessimism (1:37) * Differing narratives (4:21) * The nationalization risk (16:15) * Accountability via audit (25:55) * Productivity projection (34:18) (A lightly edited transcript of our conversation will be appear in my Week in Review issue on Saturday. Another option is using the Substack auto transcript function.) On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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February 19 · 34 min
🌎 Storm watch: My chat with climate policy expert Roger Pielke Jr.
My fellow pro-growth/progress/abundance Up Wingers in America and around the world: Headlines portend rising seas, raging storms, and a planet in crisis. It’s easy to feel like the future is something to fear; however, the key to cooling things down isn’t scaling civilization back. If the world wants to cut back on carbon emissions without sacrificing growth, the answer lies in bold innovation. A sustainable tomorrow requires smart energy investment and long-term thinking today. On this episode of Faster, Please! — The Podcast, I chat with Roger Pielke Jr. about the ever-evolving discussion around climate change. We talk about the benefits of embracing new energy technology and identifying some easy wins. Pielke is a senior fellow at the American Enterprise Institute where his research focuses on science and technology policy. He is also a professor emeritus at University of Colorado Boulder, a distinguished fellow at Japan’s Institute of Energy Economics, a research associate with Risk Frontiers in Australia, and an honorary professor at University College London. Pielke has authored and edited several books, including The Climate Fix: What Scientists and Politicians Won’t Tell You About Global Warming. He also writes The Honest Broker Substack. In This Episode * The Shale Story (1:42) * Unknown Unknowns (7:42) * The Weather Forecast (14:19) * Alternate History (25:23) * The Path Forward (28:25) (A lightly edited transcript of our conversation will be appear in my Week in Review issue on Saturday. Another option is using the Substack auto transcript function.) On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were Promised This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe
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