Faster, Please! — The Podcast

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

  1. 23h ago

    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

  2. Oct 16

    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

  3. Oct 9

    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

  4. Oct 1

    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

  5. Sep 24

    📈 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

  6. Sep 17

    ✨ 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

  7. Sep 9

    ✨ 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

  8. Aug 26

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

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