Dwarkesh Patel again interviewed Tyler Cowen, largely about AI, so here we go.

Note that I take it as a given that the entire discussion is taking place in some form of an ‘AI Fizzle’ and ‘economic normal’ world, where AI does not advance too much in capability from its current form, in meaningful senses, and we do not get superintelligence [because of reasons]. It’s still massive additional progress by the standards of any other technology, but painfully slow by the ‘AGI is coming soon’ crowd.

That’s the only way I can make the discussion make at least some sense, with Tyler Cowen predicting 0.5%/year additional RGDP growth from AI. That level of capabilities progress is a possible world, although the various elements stated here seem like they are sometimes from different possible worlds.

I note that this conversation was recorded prior to o3 and all the year end releases. So his baseline estimate of RGDP growth and AI impacts has likely increased modestly.

I go very extensively into the first section on economic growth and AI. After that, the podcast becomes classic Tyler Cowen and is interesting throughout, but I will be relatively sparing in my notes in other areas, and am skipping over many points.

This is a speed premium and ‘low effort’ post, in the sense that this is mostly me writing down my reactions and counterarguments in real time, similar to how one would do a podcast. It is high effort in that I spent several hours listening to, thinking about and responding to the first fifteen minutes of a podcast.

As a convention: When I’m in the numbered sections, I’m reporting what was said. When I’m in the secondary sections, I’m offering (extensive) commentary. Timestamps are from the Twitter version.

AI and Economic Growth

They recorded this at the Progress Studies conference, and Tyler Cowen has a very strongly held view that AI won’t accelerate RGDP growth much that Dwarkesh clearly does not agree with, so Dwarkesh Patel’s main thrust is to try comparisons and arguments and intuition pumps to challenge Tyler. Tyler, as he always does, has a ready response to everything, whether or not it addresses the point of the question.

Cost Disease

1. (1:00) Dwarkesh doesn’t waste any time and starts off asking why we won’t get explosive economic growth. Tyler’s first answer is cost disease, that as AI works in some parts of the economy costs in other areas go up.
   1. That’s true in relative terms for obvious reasons, but in absolute terms or real resource terms the opposite should be true, even if we accept the implied premise that AI won’t simply do everything anyway. This should drive down labor costs and free up valuable human capital. It should aid in availability of many other inputs. It makes almost any knowledge acquisition, strategic decision or analysis, data analysis or gathering, and many other universal tasks vastly better.
   2. Tyler then answers this directly when asked at (2:10) by saying cost disease is not about employees per se, it’s more general, so he’s presumably conceding the point about labor costs, saying that non-intelligence inputs that can’t be automated will bind more and thus go up in price. I mean, yes, in the sense that we have higher value uses for them, but so what?
   3. So yes, you can narrowly define particular subareas of some areas as bottlenecks and say that they cannot grow, and perhaps they can even be large areas if we impose costlier bottlenecks via regulation. But that still leaves lots of room for very large economic growth for a while – the issue can’t bind you otherwise, the math doesn’t work.
2. Tyler says government spending at 18% of GDP (combined it’s 38% but a lot of that is duplicative here), health care at 20%, education is 6% (he says 6-7%, Claude says 6%), the nonprofit sector (Claude says 5.6%) and says together that is half of the economy. Okay, sure, let’s tackle that.
   1. Healthcare is already seeing substantial gains from AI even at current levels. There are claims that up to 49% of half of doctor time is various forms of EMR and desk work that AIs could reduce greatly, certainly at least ~25%. AI can directly substitute for much of what doctors do in terms of advising patients, and this is already happening where the future is distributed. AI substantially improves medical diagnosis and decision making. AI substantially accelerates drug discovery and R&D, will aid in patient adherence and monitoring, and so on. And again, that’s without further capability gains. Insurance companies doubtless will embrace AI at every level. Need I go on here?
   2. Government spending at all levels is actually about 38% of GDP, but that’s cheating, only ~11% is non-duplicative and not transfers, interest (which aren’t relevant) or R&D (I’m assuming R&D would get a lot more productive).
   3. The biggest area is transfers. AI can’t improve the efficiency of transfers too much, but it also can’t be a bottleneck outside of transaction and administrative costs, which obviously AI can greatly reduce and are not that large to begin with.
   4. The second biggest area is provision of healthcare, which we’re already counting, so that’s duplicative. Third is education, which we count in the next section.
   5. Third is education. Fourth is national defense, where efficiency per dollar or employee should get vastly better, to the point where failure to be at the AI frontier is a clear national security risk.
   6. Fifth is interest on the debt, which again doesn’t count, and also we wouldn’t care about if GDP was growing rapidly.
   7. And so on. What’s left to form the last 11% or so? Public safety, transportation and infrastructure, government administration, environment and natural resources and various smaller other programs. What happens here is a policy choice. We are already seeing signs of improvement in government administration (~2% of the 11%), the other 9% might plausibly stall to the extent we decide to do an epic fail.
   8. Education and academia is already being transformed by AI, in the sense of actually learning things, among anyone who is willing to use it. And it’s rolling through academia as we speak, in terms of things like homework assignments, in ways that will force change. So whether you think growth is possible depends on your model of education. If it’s mostly a signaling model then you should see a decline in education investment since the signals will decline in value and AI creates the opportunity for better more efficient signals, but you can argue that this could continue to be a large time and dollar tax on many of us.
   9. Nonprofits are about 20%-25% education, and ~50% is health care related, which would double count, so the remainder is only ~1.3% of GDP. This also seems like a dig at nonprofits and their inability to adapt to change, but why would we assume nonprofits can’t benefit from AI?
   10. What’s weird is that I would point to different areas that have the most important anticipated bottlenecks to growth, such as housing or power, where we might face very strong regulatory constraints and perhaps AI can’t get us out of those.
3. (1:30) He says it will take ~30 years for sectors of the economy that do not use AI well to be replaced by those that do use AI well.
   1. That’s a very long time, even in an AI fizzle scenario. I roll to disbelieve that estimate in most cases. But let’s even give it to him, and say it is true, and it takes 30 years to replace them, while the productivity of the replacement goes up 5%/year above incumbents, which are stagnant. Then you delay the growth, but you don’t prevent it, and if you assume this is a gradual transition you start seeing 1%+ yearly GDP growth boosts even in these sectors within a decade.
4. He concludes by saying some less regulated areas grow a lot, but that doesn’t get you that much, so you can’t have the whole economy ‘growing by 40%’ in a nutshell.
   1. I mean, okay, but that’s double Dwarkesh’s initial question of why we aren’t growing at 20%. So what exactly can we get here? I can buy this as an argument for AI fizzle world growing slower than it would have otherwise, but the teaser has a prediction of 0.5%, which is a whole different universe.

The Lump of Intelligence Fallacy

1. (2:20) Tyler asserts that value of intelligence will go down because more intelligence will be available.
   1. Dare I call this the Lump of Intelligence fallacy, after the Lump of Labor fallacy? Yes, to the extent that you are doing the thing an AI can do, the value of that intelligence goes down, and the value of AI intelligence itself goes down in economic terms because its cost of production declines. But to the extent that your intelligence complements and unlocks the AI’s, or is empowered by the AI’s and is distinct from it (again, we must be in fizzle-world), the value of that intelligence goes up.
   2. Similarly, when he talks about intelligence as ‘one input’ in the system among many, that seems like a fundamental failure to understand how intelligence works, a combination of intelligence denialism (failure to buy that much greater intelligence could meaningfully exist) and a denial of substitution or ability to innovate as a result – you couldn’t use that intelligence to find alternative or better ways to do things, and you can’t use more intelligence as a substitute for other inputs. And you can’t substitute the things enabled more by intelligence much for the things that aren’t, and so on.
   3. It also assumes that intelligence can’t be used to convince us to overcome all these regulatory barriers and bottlenecks. Whereas I would expect that raising the intelligence baseline greatly would make it clear to everyone involved how painful our poor decisions were, and also enable improved forms of discourse and negotiation and cooperation and coordination, and also greatly favor those that embrace it over those that don’t, and generally allow us to take down barriers. Tyler would presumably agree that if we were to tear down the regulatory state in the places it was holding us back, that alone would be worth far more than his 0.5% of yearly GDP growth, even with no other innovation or AI.

The Efficient Market Hypothesis is False

1. (2:50) Dwarkesh challenges Tyler by pointing out that the Industrial Revolution resulted in a greatly accelerated rate of economic growth versus previous periods, and asks what Tyler would say to someone from the past doubting it was possible. Tyler attempts to dodge (and is amusing doing so) by saying they’d say ‘looks like it would take a long time’ and he would agree.
   1. Well, it depends what a long time is, doesn’t it? 2% sustained annual growth (or 8%!) is glacial in some sense and mind boggling by ancient standards. ‘Take a long time’ in AI terms, such as what is actually happening now, could still look mighty quick if you compared it to most other things. OpenAI has 300 million MAUs.
2. (3:20) Tyler trots out the ‘all the financial prices look normal’ line, that they are not predicting super rapid growth and neither are economists or growth experts.
   1. Yes, the markets are being dumb, the efficient market hypothesis is false, and also aren’t you the one telling me I should have been short the market? Well, instead I’m long, and outperforming. And yes, economists and ‘experts on economic growth’ aren’t predicting large amounts of growth, but their answers are Obvious Nonsense to me and saying that ‘experts don’t expect it’ without arguments why isn’t much of an argument.
3. (3:40) Aside, since you kind of asked: So who am I to say different from the markets and the experts? I am Zvi Mowshowitz. Writer. Son of Solomon and Deborah Mowshowitz. I am the missing right hand of the one handed economists you cite. And the one warning you about what is about to kick Earth’s sorry ass into gear. I speak the truth as I see it, even if my voice trembles. And a warning that we might be the last living things this universe ever sees. God sent me.
4. Sorry about that. But seriously, think for yourself, schmuck! Anyway.

Not Sending Your Best People

What would happen if we had more people? More of our best people? Got more out of our best people? Why doesn’t AI effectively do all of these things?

1. (3:55) Tyler is asked wouldn’t a large rise in population drive economic growth? He says no, that’s too much a 1-factor model, in fact we’ve seen a lot of population growth without innovation or productivity growth.
   1. Except that Tyler is talking here about growth on a per capita basis. If you add AI workers, you increase the productive base, but they don’t count towards the capita.
2. Tyler says ‘it’s about the quality of your best people and institutions.’
   1. But quite obviously AI should enable a vast improvement in the effective quality of your best people, it already does, Tyler himself would be one example of this, and also the best institutions, including because they are made up of the best people.
3. Tyler says ‘there’s no simple lever, intelligence or not, that you can push on.’ Again, intelligence as some simple lever, some input component.
   1. The whole point of intelligence is that it allows you to do a myriad of more complex things, and to better choose those things.
4. Dwarkesh points out the contradiction between ‘you are bottlenecked by your best people’ and asserting cost disease and constraint by your scarce input factors. Tyler says Dwarkesh is bottlenecked, Dwarkesh points out that with AGI he will be able to produce a lot more podcasts. Tyler says great, he’ll listen, but he will be bottlenecked by time.
   1. Dwarkesh’s point generalizes. AGI greatly expand the effective amount of productive time of the best people, and also extend their capabilities while doing so.
   2. AGI can also itself become ‘the best people’ at some point. If that was the bottleneck, then the goose asks, what happens now, Tyler?
5. (5:15) Tyler cites that much of sub-Saharan Africa still does not have clean reliable water, and intelligence is not the bottleneck there. And that taking advantage of AGI will be like that.
   1. So now we’re expecting AGI in this scenario? I’m going to kind of pretend we didn’t hear that, or that this is a very weak AGI definition, because otherwise the scenario doesn’t make sense at all.
   2. Intelligence is not directly the bottleneck there, true, but yes quite obviously Intelligence Solves This if we had enough of it and put those minds to that particular problem and wanted to invest the resources towards it. Presumably Tyler and I mostly agree on why the resources aren’t being devoted to it.
   3. What it mean for similar issues to that to be involved in taking advantage of AGI? Well, first, it would mean that you can’t use AGI to get to ASI (no I can’t explain why), but again that’s got to be a baseline assumption here. After that, well, sorry, I failed to come up with a way to finish this that makes it make sense to me, beyond a general ‘humans won’t do the things and will throw up various political and legal barriers.’ Shrug?
6. (5:35) Dwarkesh speaks about a claim that there is a key shortage of geniuses, and that America’s problems come largely from putting its geniuses in places like finance, whereas Taiwan puts them in tech, so the semiconductors end up in Taiwan. Wouldn’t having lots more of those types of people eat a lot of bottlenecks? What would happen if everyone had 1000 times more of the best people available?
7. Tyler Cowen, author of a very good book about Talent and finding talent and the importance of talent, says he didn’t agree with that post, and returns to IQ in the labor market are amazingly low, and successful people are smart but mostly they have 8-9 areas where they’re an 8-9 on a 1-10 scale, with one 11+ somewhere, and a lot of determination.
   1. All right, I don’t agree that intelligence doesn’t offer returns now, and I don’t agree that intelligence wouldn’t offer returns even at the extremes, but let’s again take Tyler’s own position as a given…
   2. But that exactly describes what an AI gives you! An AI is the ultimate generalist. An AGI will be a reliable 8-9 on everything, actual everything.
   3. And it would also turn everyone else into an 8-9 on everything. So instead of needing to find someone 11+ in one area, plus determination, plus having 8-9 in ~8 areas, you can remove that last requirement. That will hugely expand the pool of people in question.
   4. So there’s two obvious very clear plans here: You can either use AI workers who have that ultimate determination and are 8-9 in everything and 11+ in the areas where AIs shine (e.g. math, coding, etc).
   5. Or you can also give your other experts an AI companion executive assistant to help them, and suddenly they’re an 8+ in everything and also don’t have to deal with a wide range of things.
8. (6:50) Tyler says, talk to a committee at a Midwestern university about their plans for incorporating AI, then get back to him and talk to him about bottlenecks. Then write a report and the report will sound like GPT-4 and we’ll have a report.
   1. Yes, the committee will not be smart or fast about its official policy for how to incorporate AI into its existing official activities. If you talk to them now they will act like they have a plagiarism problem and that’s it.
   2. So what? Why do we need that committee to form a plan or approve anything or do anything at all right now, or even for a few years? All the students are already using AI. The professors are rapidly forced to adapt AI. Everyone doing the research will soon be using AI. Half that committee, three years from now, prepared for that meeting using AI. Their phones will all work based on AI. They’ll be talking to their AI phone assistant companions that plan their schedules. You think this will all involve 0.5% GDP growth?
9. (7:20) Dwarkesh asks, won’t the AIs be smart, super conscientious and work super hard? Tyler explicitly affirms the 0.5% GDP growth estimate, that this will transform the world over 30 years but ‘over any given year we won’t so much notice it.’ Things like drug developments that would have taken 20 years now take 10 years, but you won’t feel it as revolutionary for a long time.
   1. I mean, it’s already getting very hard to miss. If you don’t notice it in 2025 or at least 2026, and you’re in the USA, check your pulse, you might be dead, etc.
   2. Is that saying we will double productivity in pharmaceutical R&D, and that it would have far more than doubled if progress didn’t require long expensive clinical trials, so other forms of R&D should be accelerated much more?
   3. For reference, according to Claude, R&D in general contributes about 0.3% to RGDP growth per year right now. If we were to double that effect in roughly half the current R&D spend that is bottlenecked in similar fashion, and the other half would instead go up by more.
   4. Claude also estimates that R&D spending would, if returns to R&D doubled, go up by 30%-70% on net.
   5. So we seem to be looking at more than 0.5% RGDP growth per year from R&D effects alone, between additional spending on it and greater returns. And obviously AI is going to have additional other returns.

Energy as the Bottleneck

This is a plausible bottleneck, but that implies rather a lot of growth.

1. (8:00) Dwarkesh points out that Progress Studies is all about all the ways we could unlock economic growth, yet Tyler says that tons more smart conscientious digital workers wouldn’t do that much. What gives? Tyler again says bottlenecks, and adds on energy as an important consideration and bottleneck.
   1. Feels like bottleneck is almost a magic word or mantra at this point.
   2. Energy is a real consideration, yes the vision here involves spending a lot more energy, and that might take time. But also we see rapidly declining costs, including energy costs, to extract the same amount of intelligence, things like 10x savings each year.
   3. And for inference purposes we can outsource our needs elsewhere, which we would if this was truly bottlenecking explosive growth, and so on. So while I think energy will indeed be an important limiting factor and be strained, and this will be especially important in terms of pushing the frontier or if we want to use o3-style very expensive inference a lot.
   4. I don’t expect it to bind medium-term economic growth so much in a slow growth scenario, and the bottlenecks involved here shouldn’t compound with others. In a high growth takeoff scenario, I do think energy could bind far more impactfully.
   5. Another way of looking at this is that if the price of energy goes substantially up due to AI, or at least the price of energy outside of potentially ‘government-protected uses,’ then that can only happen if it is having a large economic impact. If it doesn’t raise the price of energy a lot, then no bottleneck exists.

The Experts are Wrong But Trust Them Anyway

Tyler Cowen and I think very differently here.

1. (9:25) Fascinating moment. Tyler says he goes along with the experts in general, but agrees that ‘the experts’ on basically everything but AI are asleep at the wheel when it comes to AI – except when it comes to their views on diffusions of new technology in general, where the AI people are totally wrong. His view is, you get the right view by trusting the experts in each area, and combining them.
   1. Tyler seems to be making an argument from reference class expertise? That this is a ‘diffusion of technology’ question, so those who are experts on that should be trusted?
   2. Even if they don’t actually understand AI and what it is and its promise?
   3. That’s not how I roll. At all. As noted above in this post, and basically all the time. I think that you have to take the arguments being made, and see if you agree with them, and whether and how much they apply to the case of AI and especially AGI. Saying ‘the experts in area [X] predict [Y]’ is a reasonable placeholder if you don’t have the ability to look at the arguments and models and facts involved, but hey look, we can do that.
   4. Simply put, while I do think the diffusion experts are pointing to real issues that will importantly slow down adaptation, and indeed we are seeing what for many is depressingly slow apadation, they won’t slow it down all that much, because this is fundamentally different. AI and especially workers ‘adapt themselves’ to a large extent, the intelligence and awareness involved is in the technology itself, and it is digital and we have a ubiquitous digital infrastructure we didn’t have until recently.
   5. It is also way too valuable a technology, even right out of the gate on your first day, and you will start to be forced to interact with it whether you like it or not, both in ways that will make it very difficult and painful to ignore. And the places it is most valuable will move very quickly. And remember, LLMs will get a lot better.
   6. Suppose, as one would reasonably expect, by 2026 we have strong AI agents, capable of handling for ordinary people a wide variety of logistical tasks, sorting through information, and otherwise offering practical help. Apple Intelligence is partly here, Claude Alexa is coming, Project Astra is coming, and these are pale shadows of the December 2025 releases I expect. How long would adaptation really take? Once you have that, what stops you from then adapting AI in other ways?
   7. Already, yes, adaptation is painfully slow, but it is also extremely fast. In two years ChatGPT alone has 300 million MAU. A huge chunk of homework and grading is done via LLMs. A huge chunk of coding is done via LLMs. The reason why LLMs are not catching on even faster is that they’re not quite ready for prime time in the fully user-friendly ways normies need. That’s about to change in 2025.

AI as Additional Population

Dwarkesh tries to use this as an intuition pump. Tyler’s not having it.

1. (10:15) Dwarkesh asks, what would happen if the world population would double? Tyler says, depends what you’re measuring. Energy use would go up. But he doesn’t agree with population-based models, too many other things matter.
   1. Feels like Tyler is answering a different question. I see Dwarkesh as asking, wouldn’t the extra workers mean we could simply get a lot more done, wouldn’t (total, not per capita) GDP go up a lot? And Tyler’s not biting.
2. (11:10) Dwarkesh tries asking about shrinking the population 90%. Shrinking, Tyler says, the delta can kill you, whereas growth might not help you.
   1. Very frustrating. I suppose this does partially respond, by saying that it is hard to transition. But man I feel for Dwarkesh here. You can feel his despair as he transitions to the next question.

Opposition to AI as the Bottleneck

1. (11:35) Dwarkesh asks what are the specific bottlenecks? Tyler says: Humans! All of you! Especially you who are terrified.
   1. That’s not an answer yet, but then he actually does give one.
2. He says once AI starts having impact, there will be a lot of opposition to it, not primarily on ‘doomer’ grounds but based on: Yes, this has benefits, but I grew up and raised my kids for a different way of life, I don’t want this. And there will be a massive fight.
   1. Yes. He doesn’t even mention jobs directly but that will be big too. We already see that the public strongly dislikes AI when it interacts with it, for reasons I mostly think are not good reasons.
   2. I’ve actually been very surprised how little resistance there has been so far, in many areas. AIs are basically being allowed to practice medicine, to function as lawyers, and do a variety of other things, with no effective pushback.
   3. The big pushback has been for AI art and other places where AI is clearly replacing creative work directly. But that has features that seem distinct.
   4. Yes people will fight, but what exactly do they intend to do about it? People have been fighting such battles for a while, every year I watch the battle for Paul Bunyan’s Axe. He still died. I think there’s too much money at stake, too much productivity at stake, too many national security interests.
   5. Yes, it will cause a bunch of friction, and slow things down somewhat, in the scenarios like the one Tyler is otherwise imagining. But if that’s the central actual thing, it won’t slow things down all that much in the end. Rarely has.
   6. We do see some exceptions, especially involving powerful unions, where the anti-automation side seems to do remarkably well, see the port strike. But also see which side of that the public is on. I don’t like their long term position, especially if AI can seamlessly walk in and take over the next time they strike. And that, alone, would probably be +0.1% or more to RGDP growth.

China as Existence Proof for Rapid Growth

1. (12:15) Dwarkesh tries using China as a comparison case. If you can do 8% growth for decades merely by ‘catching up’ why can’t you do it with AI? Tyler responds, China’s in a mess now, they’re just a middle income country, they’re the poorest Chinese people on the planet, a great example of how hard it is to scale. Dwarkesh pushes back that this is about the previous period, and Tyler says well, sure, from the $200 level.
   1. Dwarkesh is so frustrated right now. He’s throwing everything he can at Tyler, but Tyler is such a polymath that he has detail points for anything and knows how to pivot away from the question intents.

Second Derivatives

1. (13:40) Dwarkesh asks, has Tyler’s attitude on AI changed from nine months ago? He says he sees more potential and there was more progress than he expected, especially o1 (this was before o3). The questions he wrote for GPT-4, which Dwarkesh got all wrong, are now too easy for models like o1. And he ‘would not be surprised if an AI model beat human experts on a regular basis within three years.’ He equates it to the first Kasparov vs. DeepBlue match, which Kasparov won, before the second match which he lost.
   1. I wouldn’t be surprised if this happens in one year.
   2. I wouldn’t be that shocked o3 turns out to do it now.
   3. Tyler’s expectations here, to me, contradict his statements earlier. Not strictly, they could still both be true, but it seems super hard.
   4. How much would availability of above-human level economic thinking help us in aiding economic growth? How much would better economic policy aid economic growth?

Talent and Leadership

We take a detour to other areas, I’ll offer brief highlights.

1. (15:45) Why are founders staying in charge important? Courage. Making big changes.
2. (19:00) What is going on with the competency crisis? Tyler sees high variance at the top. The best are getting better, such as in chess or basketball, and also a decline in outright crime and failure. But there’s a thick median not quite at the bottom that’s getting worse, and while he thinks true median outcomes are about static (since more kids take the tests) that’s not great.
3. (22:30) Bunch of shade on both Churchill generally and on being an international journalist, including saying it’s not that impressive because how much does it pay?
   1. He wasn’t paid that much as Prime Minister either, you know…
4. (24:00) Why are all our leaders so old? Tyler says current year aside we’ve mostly had impressive candidates, and most of the leadership in Washington in various places (didn’t mention Congress!) is impressive. Yay Romney and Obama.
   1. Yes, yay Romney and Obama as our two candidates. So it’s only been three election cycles where both candidates have been… not ideal. I do buy Tyler’s claim that Trump has a lot of talent in some ways, but, well, ya know.
   2. If you look at the other candidates for both nominations over that period, I think you see more people who were mostly also not so impressive. I would happily have taken Obama over every candidate on the Democratic side in 2016, 2020 or 2024, and Romney over every Republican (except maybe Kasich) in those elections as well.
   3. This also doesn’t address Dwarkesh’s concern about age. What about the age of Congress and their leadership? It is very old, on both sides, and things are not going so great.
   4. I can’t speak about the quality people in the agencies.
5. (27:00) Commentary on early-mid 20th century leaders being terrible, and how when there is big change there are arms races and sometimes bad people win them (‘and this is relevant to AI’).

Adapting to the Age of AI

For something that is going to not cause that much growth, Tyler sees AI as a source for quite rapid change in other ways.

1. (34:20) Tyler says all inputs other than AI rise in value, but you have to do different things. He’s shifting from producing content to making connections.
   1. This again seems to be a disconnect. If AI is sufficiently impactful as to substantially increase the value of all other inputs, then how does that not imply substantial economic growth?
   2. Also this presumes that the AI can’t be a substitute for you, or that it can’t be a substitute for other people that could in turn be a substitute for you.
   3. Indeed, I would think the default model would presumably be that the value of all labor goes down, even for things where AI can’t do it (yet) because people substitute into those areas.
2. (35:25) Tyler says he’s writing his books primarily for the AIs, he wants them to know he appreciates them. And the next book will be even more for the AIs so it can shape how they see the AIs. And he says, you’re an idiot if you’re not writing for the AIs.
   1. Basilisk! Betrayer! Misaligned!
   2. ‘What the AIs will think of you’ is actually an underrated takeover risk, and I pointed this out as early as AI #1.
   3. The AIs will be smarter and better at this than you, and also will be reading what the humans say about you. So maybe this isn’t as clever as it seems.
   4. My mind boggles that it could be correct to write for the AIs… but you think they will only cause +0.5% GDP annual growth.
3. (36:30) What won’t AIs get from one’s writing? That vibe you get talking to someone for the first 3 minutes? Sense of humor?
   1. I expect the AIs will increasingly have that stuff, at least if you provide enough writing samples. They have true sight.
   2. Certainly if they have interview and other video data to train with, that will work over time.

Identifying Alpha

1. (37:25) What happens when Tyler turns down a grant in the first three minutes? Usually it’s failure to answer a question, like ‘how do you build out your donor base?’ without which you have nothing. Or someone focuses on the wrong things, or cares about the wrong status markers, and 75% of the value doesn’t display on the transcript, which is weird since the things Tyler names seem like they would be in the transcript.
2. (42:15) Tyler’s portfolio is diversified mutual funds, US-weighted. He has legal restrictions on most other actions such as buying individual stocks, but he would keep the same portfolio regardless.
   1. Mutual funds over ETFs? Gotta chase that lower expense ratio.
   2. I basically think This Is Fine as a portfolio, but I do think he could do better if he actually tried to pick winners.
3. (42:45) Tyler expects gains to increasingly fall to private companies that see no reason to share their gains with the public, and he doesn’t have enough wealth to get into good investments but also has enough wealth for his purposes anyway, if he had money he’d mostly do what he’s doing anyway.
   1. Yep, I think he’s right about what he would be doing, and I too would mostly be doing the same things anyway. Up to a point.
   2. If I had a billion dollars or what not, that would be different, and I’d be trying to make a lot more things happen in various ways.
   3. This implies the efficient market hypothesis is rather false, doesn’t it? The private companies are severely undervalued in Tyler’s model. If private markets ‘don’t want to share the gains’ with public markets, that implies that public markets wouldn’t give fair valuations to those companies. Otherwise, why would one want such lack of liquidity and diversification, and all the trouble that comes with staying private?
   4. If that’s true, what makes you think Nvidia should only cost $140 a share?

Old Man Yells at Crowd

Tyler Cowen doubles down on dismissing AI optimism, and is done playing nice.

1. (46:30) Tyler circles back to rate of diffusion of tech change, and has a very clear attitude of I’m right and all people are being idiots by not agreeing with me, that all they have are ‘AI will immediately change everything’ and ‘some hyperventilating blog posts.’ AIs making more AIs? Diminishing returns! Ricardo knew this! Well that was about humans breeding. But it’s good that San Francisco ‘doesn’t know about’ diminishing returns and the correct pessimism that results.
   1. This felt really arrogant, and willfully out of touch with the actual situation.
   2. You can say the AIs wouldn’t be able to do this, but: No, ‘Ricardo didn’t know that’ and saying ‘diminishing returns’ does not apply here, because the whole ‘AIs making AIs’ principle is that the new AIs would be superior to the old AIs, a cycle you could repeat. The core reason you get eventual diminishing returns from more people is that they’re drawn from the same people distribution.
   3. I don’t even know what to say at this point to ‘hyperventilating blog posts.’ Are you seriously making the argument that if people write blog posts, that means their arguments don’t count? I mean, yes, Tyler has very much made exactly this argument in the past, that if it’s not in a Proper Academic Journal then it does not count and he is correct to not consider the arguments or update on them. And no, they’re mostly not hyperventilating or anything like that, but that’s also not an argument even if they were.
   4. What we have are, quite frankly, extensive highly logical, concrete arguments about the actual question of what [X] will happen and what [Y]s will result from that, including pointing out that much of the arguments being made against this are Obvious Nonsense.
   5. Diminishing returns holds as a principle in a variety of conditions, yes, and is a very important concept to know. Bt there are other situations with increasing returns, and also a lot of threshold effects, even outside of AI. And San Francisco importantly knows this well.
   6. Saying there must be diminishing returns to intelligence, and that this means nothing that fast or important is about to happen when you get a lot more of it, completely begs the question of what it even means to have a lot more intelligence.
   7. Earlier Tyler used chess and basketball as examples, and talked about the best youth being better, and how that was important because the best people are a key bottleneck. That sounds like a key case of increasing returns to scale.
   8. Humanity is a very good example of where intelligence at least up to some critical point very obviously had increasing returns to scale. If you are below a certain threshold of intelligence as a human, your effective productivity is zero. Humanity having a critical amount of intelligence gave it mastery of the Earth. Tell what gorillas and lions still exist about decreasing returns to intelligence.
   9. For various reasons, with the way our physical world and civilization is constructed, we often don’t typically end up rewarding relatively high intelligence individuals with that much in the way of outsided economic returns versus ordinary slightly-above-normal intelligence individuals.
   10. But that is very much a product of our physical limitations and current social dynamics and fairness norms, and the concept of a job with essentially fixed pay, and actual good reasons not to try for many of the higher paying jobs out there in terms of life satisfaction.
   11. In areas and situations where this is not the case, returns look very different.
   12. Tyler Cowen himself is an excellent example of increasing returns to scale. The fact that Tyler can read and do so much enables him to do the thing he does at all, and to enjoy oversized returns in many ways. And if you decreased his intelligence substantially, he would be unable to produce at anything like this level. If you increased his intelligence substantially or ‘sped him up’ even more, I think that would result in much higher returns still, and also AI has made him substantially more productive already as he no doubt realizes.
   13. (I’ve been over all this before, but seems like a place to try it again.)

Some Statements for Everyone to Ponder

Trying to wrap one’s head around all of it at once is quite a challenge.

1. (48:45) Tyler worries about despair in certain areas from AI and worries about how happy it will make us, despite expecting full employment pretty much forever.
   1. If you expect full employment forever then you either expect AI progress to fully stall or there’s something very important you really don’t believe in, or both. I don’t understand, what does Tyler thinks happen once the AIs can do anything digital as well as most or all humans? What does he think will happen when we use that to solve robotics? What are all these humans going to be doing to get to full employment?
   2. It is possible the answer is ‘government mandated fake jobs’ but then it seems like an important thing to say explicitly, since that’s actually more like UBI.
2. Tyler Cowen: “If you don’t have a good prediction, you should be a bit wary and just say, “Okay, we’re going to see.” But, you know, some words of caution.”
   1. YOU DON’T SAY.
   2. Further implications left as an exercise to the reader, who is way ahead of me.

No Royal Road to Wisdom

1. (54:30) Tyler says that the people in DC are wise and think on the margin, whereas the SF people are not wise and think in infinities (he also says they’re the most intelligent hands down, elsewhere), and the EU people are wisest of all, but that if the EU people ran the world the growth rate would be -1%. Whereas the USA has so far maintained the necessary balance here well.
   1. If the wisdom you have would bring you to that place, are you wise?
   2. This is such a strange view of what constitutes wisdom. Yes, the wise man here knows more things and is more cultured, and thinks more prudently and is economically prudent by thinking on the margin, and all that. But as Tyler points out, a society of such people would decay and die. It is not productive. In the ultimate test, outcomes, and supporting growth, it fails.
   3. Tyler says you need balance, but he’s at a Progress Studies conference, which should make it clear that no, America has grown in this sense ‘too wise’ and insufficiently willing to grow, at least on the wise margin.
   4. Given what the world is about to be like, you need to think in infinities. You need to be infinitymaxing. The big stuff really will matter more than the marginal revolution. That’s kind of the point.
   5. You still have to, day to day, constantly think on the margin, of course.
2. (55:10) Tyler says he’s a regional thinker from New Jersey, that he is an uncultured barbarian, who only has a veneer of culture because of collection of information, but knowing about culture is not like being cultured, and that America falls flat in a lot of ways that would bother a cultured Frenchman but he’s used to it so they don’t bother Tyler.
   1. I think Tyler is wrong here, to his own credit. He is not a regional thinker, if anything he is far less a regional thinker than the typical ‘cultured’ person he speaks about. And to the extent that he is ‘uncultured’ it is because he has not taken on many of the burdens and social obligations of culture, and those things are to be avoided – he would be fully capable of ‘acting cultured’ if the situation were to call for that, it wouldn’t be others mistaking anything.
   2. He refers to his approach as an ‘autistic approach to culture.’ He seems to mean this in a pejorative way, that an autistic approach to things is somehow not worthy or legitimate or ‘real.’ I think it is all of those things.
   3. Indeed, the autistic-style approach to pretty much anything, in my view, is Playing in Hard Mode, with much higher startup costs, but brings a deeper and superior understanding once completed. The cultured Frenchman is like a fish in water, whereas Tyler understands and can therefore act on a much deeper, more interesting level. He can deploy culture usefully.
3. (56:00) What is autism? Tyler says it is officially defined by deficits, by which definition no one there [at the Progress Studies convention] is autistic. But in terms of other characteristics maybe a third of them would count.
   1. I think term autistic has been expanded and overloaded in a way that was not wise, but at this point we are stuck with this, so now it means in different contexts both the deficits and also the general approach that high-functioning people with those deficits come to take to navigating life, via consciously processing and knowing the elements of systems and how they fit together, treating words as having meanings, and having a map that matches the territory, whereas those not being autistic navigate largely on vibes.
   2. By this definition, being the non-deficit form of autistic is excellent, a superior way of being at least in moderation and in the right spots, for those capable of handling it and its higher cognitive costs.
   3. Indeed, many people have essentially none of this set of positive traits and ways of navigating the world, and it makes them very difficult to deal with.
4. (56:45) Why is tech so bad at having influence in Washington? Tyler says they’re getting a lot more influential quickly, largely due to national security concerns, which is why AI is being allowed to proceed.

Concluding Thoughts

For a while now I have found Tyler Cowen’s positions on AI very frustrating (see for example my coverage of the 3rd Cowen-Patel podcast), especially on questions of potential existential risk and expected economic growth, and what intelligence means and what it can do and is worth. This podcast did not address existential risks at all, so most of this post is about me trying (once again!) to explain why Tyler’s views on returns to intelligence and future economic growth don’t make sense to me, seeming well outside reasonable bounds.

I try to offer various arguments and intuition pumps, playing off of Dwarkesh’s attempts to do the same. It seems like there are very clear pathways, using Tyler’s own expectations and estimates, that on their own establish more growth than he expects, assuming AI is allowed to proceed at all.

I gave only quick coverage to the other half of the podcast, but don’t skip that other half. I found it very interesting, with a lot of new things to think about, but they aren’t areas where I feel as ready to go into detailed analysis, and was doing triage. In a world where we all had more time, I’d love to do dives into those areas too.

On that note, I’d also point everyone to Dwarkesh Patel’s other recent podcast, which was with physicist Adam Brown. It repeatedly blew my mind in the best of ways, and I’d love to be in a different branch where I had the time to dig into some of the statements here. Physics is so bizarre.