Caleb Watney - America's Innovation Engine

Okay, today I have the pleasure of speaking with Caleb Watney, who is the Director of Innovation Policy at the Progressive Policy Institute. And he's recently written a piece of The Atlantic arguing that America's innovation engine is slowing.
So before we get into the weeds, Caleb, do you want to describe the main reasons why you think America's innovation engine is slowing? Sure. Yeah, America's innovation engine is, of course, a very broad and multivariate, you know, thing.
But I was trying to focus on three particular trends that I thought were troubling, make major impacts on America's ability to innovate. And just briefly, those are basically high-skill immigration international talent flows.
Number two, our cutting-edge university system that's really the best of the world. And three, the industrial clusters, the agglomerations that we have that are sort of the geographical regions where a lot of this innovation comes from.
And each of those, we're sort of seeing maybe negative trends before the pandemic, but the pandemic might serve as kind of a breaking point in each of them. Okay, so let's start with remote work first, or at least the agglomeration effects first.
Now, what is so important about the physical agglomeration effects of being in these high productivity cities? Why can't remote work make up for that? Sure. Yes, I mean, economists have, you know, for hundreds of years, basically been setting the effect of these close geographically connected networks of entrepreneurs, innovators, scientists,

academics, you know, supply chain managers.

When you have all of those people in a geographical region where they're, you know, running into

each other spontaneously and they're sharing ideas and they're having long conversations,

you know, in the hallway or in their offices that they wouldn't otherwise be able to replicate,

you know, simply online, that ends up leading leading to more creativity, more ideas, more patents. And we have a lot of evidence for that in the real world.
And as you mentioned, some people are starting to counter and say, oh, well, in the last 20 years, we've seen this huge array of online communication platforms kind of pop up, and can't those replicate a lot of the agglomeration effects that we're getting in physical environment. And I think that's certainly true to some extent, but I guess the right comparison here isn't even necessarily physical agglomeration versus digital agglomeration.
But right now, if you're in one of these geographic clusters, you're getting the best of both worlds. You're getting the best that physical agglomeration effects have to offer.
Plus, you know, I have tons of great conversations on Twitter. And so it's really digital and physical agglomeration effects versus just digital.
And I think the difference there is still pretty large, and it would be a shame to lose a lot of the high productivity clusters that we currently have. Okay, let me make the case that remote workers actually going to increase some sort of agglomeration benefit, and you convinced me that it's wrong.
Okay, so first of all, it's just going to connect the entire world into this hyper-productive city that we can't have in the real world, not just because of the limitations of how big cities can be and who can move in there, but just because of the inevitable zoning laws that cities like San Francisco passed that artificially limit how many people can join into the innovation circus there. And, you know, now we're going to have developing countries and the talent there joining into these agglomeration benefits, as well as people in rural areas in America.
Why won't this massively outweigh the loss of physical agglomeration? Yeah, no, I think digital, you know, agglomeration, these digital networks can have huge benefits. And you're exactly right that there are a lot of ways you can arbitrage both bad regulations, you know, like zoning laws, but also, you know, just physical distances.
But again, I think, you know, the relevant alternative here is not where you're just getting physical agglomeration or just digital, you know, right now, living in Washington, DC, or Silicon Valley, or New York, you can have those conversations with people from all over the world, you can even hire remotely. But you do also get, there's a certain kind of like cultural context that you only get by like being in person and sharing conversations.
I mean, I certainly experienced this in my own life. I get a lot of ideas, you know, from having conversations on Twitter, but it's still very different to, you know, have an extended two-hour long conversation with a friend in their office, you know, like making eye contact, having this sort of spontaneous ideas that it's hard to replicate even over Zoom, partially because I think Zoom meetings tend to be a little bit more scheduled.
It's hard to have flexible time. You know, frequently the best conversations that happen in the real world are ones that, you know, aren't intended to start off as conversations.
They just kind of spontaneously arise. You know, you start off just sharing one thing and then it extends into a whole conversation.
But there's also kind of a Zoom fatigue that you see. People, especially right now in this era of remote work, are having so many Zoom calls.
They don't want to stay on longer, you know, just to maybe have a conversation with somebody extra. And so again, I think, yeah, it's good to recognize that these aren't completely contradictory or we can have both.
And that's really what we're getting in the big physical agglomeration effects of today, which kind of gets to the point, I think we need maybe a better taxonomy of what we're talking about in terms of the kinds of interactions that we think lead to innovation, because there's kind of a spontaneity and really in-depth conversation that you can, I think, only get in physical spaces. But there is a, obviously, a huge effect from having just way more people that you can have access to in some of these digital spaces.
So that's one thing I would like to see this conversation get into, is rather than like, oh, which is better, which is more important, let's break down what are the specific attributes of these kinds of interactions that are happening in the physical or the digital space. That's very interesting.
Yeah, you talk in the Atlantic piece about how there might be aspects of remote work that advantage the businesses that are using it, but for the net rate of innovation is actually quite bad. I'm wondering if, can we understand this in the context of like, you can't explicitly say that, listen, I just want to hang out in this coffee place or wherever in my office, just in case somebody wants to help me leave this company and start another company, or maybe I'll find a mate or something here.
But getting on Zoom requires some sort of explicit communication of your motives that you can get away with without not doing in the real world. Yeah, I think that's exactly right.
There's sort of, you know, I think you've seen some workplaces try to experiment this. Like, what if you just left your camera on and it was as if you were like working next to somebody in an office, but people seem to be really uncomfortable with that.
They don't seem to like it. Yeah, it doesn't seem to just like to have the same sort of easy, spontaneous conversation that you can mimic in the real world.
And I'm not sure exactly why. And I also don't want to necessarily rule out the case.
It could be, you know, 30 years from now or maybe sooner. You know, we have some sort of virtual reality technology that's really blossomed.
And now everybody, regardless of where you're living, is kind of working in these virtual workspaces. And if that's the case, then maybe, you know, physical agglomeration effects really start to diminish in importance.
But I certainly don't think we're there yet. And regardless, it seems like we're kind of, or there's a big experiment being taken.
So I'll be very curious to see kind of what are the effects of all of these, you know, big tech companies, Facebook, Twitter, others, you know, that are moving to all remote work for the foreseeable future. And again, I think you kind of pinpointed something in your earlier comment.
There's both productivity within the firm that I'm sort of concerned about, but in some ways you could say that that's internalized. If the companies themselves are seeing lower productivity measures, lower idea generation, then they should be able to internalize that themselves.
But the thing I'm particularly concerned about from a public policy perspective is the public spillovers, the fact that you have fewer new firms being formed. And of course, Facebook doesn't internalize that cost.
And so they have no reason to consider that. But as a matter of public policy, we do care about new firm generation and the kind of idea spillovers that are generated in these public externalities.
Is there a reason why agglomeration effects are so salient, even today when we have online courses or open source code? I would expect these sorts of more public and transparent displays would like reduce the effect of having to be in the right cluster at the right time. Yeah, I mean, I think they have reduced it to some extent, but at base, I think humans are extremely pro-social animals.
We just do all of our thinking and idea generation sort of in groups. I mean, of course, you have some lone geniuses that are introverts or something, but I think that's a pretty small minority of the population.
Another way to maybe think about this is how long Silicon Valley has lasted already and how high the rent costs have gotten. The fact that everybody continues to live in Silicon Valley and pay these exorbitant rent fees, despite the fact that all of this online technology has gotten so good, is perhaps evidence that the benefits, the productivity benefits of being in those clusters is actually really quite high.
Although we're seeing the rent prices crater recently, so we'll see what happens in the future. Yeah, we'll see.
Oh, so let's talk about the big picture before we get into these different points about why it even matters if America's innovation engine slows and somebody else takes over. So why can't it make the case that, listen, whatever country in the future is the innovation hub will be the one that is, you know, free, prosperous, has adopted the policies you're advocating.
Otherwise, it wouldn't be the innovation hub. So why does it matter if somebody else takes the mantle of the innovation hub? Great question.
I think one thing you've seen, and this last generation of communications technologies is actually an interesting example here, that there are a lot of cultural values that are conveyed in the building of especially technology platforms that end up becoming the underlying infrastructure that are used in the rest of the world. And the technology has a great degree of path dependence.
You know, sometimes it's easy to be a technological determinist and say like, oh, whatever is the best technology will always win out. And that's true, you know, obviously within some bounds.
But it's also the case that sometimes we can get really, you know, caught in a particular infrastructure. And that can be either like a physical or digital infrastructure or even like a cultural infrastructure.
And so if you look at a lot of the social media platforms, you know, the big ones internationally are primarily American firms. And they've built into those platforms certain kinds of cultural mores around, say, free speech or the separation between the private and the government sector, about intellectual property law, about a huge number of different sort of choices that you end up baking into your platforms.
And so I think if we were in an alternative universe where all of the main social media companies being used globally were Chinese or run by the Chinese Communist Party, especially, there would be very different values embedded in those platforms. And that would end up really shaping the direction the technology plays.
And so, especially as we're starting to look into the future of technologies that might even be more monumental, like artificial intelligence, I think it is worth thinking very carefully about where the leading firms are geographically and what kind of cultural attitudes or social infrastructures you end up building in. And I, for one, would much prefer that the United States and their broadly liberal democratic values are the ones ending up building into the emerging technologies of tomorrow than the Chinese Communist Party.
Okay, but then what about the claim that's kind of turned into a truism at this point, which is that liberal democratic countries are just necessarily going to have higher rates of innovation. So as long as the Chinese Communist Party stays authoritarian, they're not going to be the next innovation hub for the things we care about.
I don't, I mean, I hope that's true, but we certainly can't have, you know, complete confidence in that. I think if you were comparing a lot of predictions of liberal democratic economists from 20 years ago about what China's expected development path is, they've certainly outplayed, I think, the vast majority of predictions.
And some of that might be catch-up growth, but they've had much higher rates of catch-up growth than almost any other country. They've been much bigger, and they've maybe had other issues that they've been able to overcome kind of surprisingly.
The other thing is I wouldn't underestimate our ability to kind of shoot ourselves in the foot. So I would say that absent actively bad policy, this sort of free liberal democratic model should work or should out-compete.
I think especially because the nature of innovation kind of relies on free thinking and iterative thought that's different from the consensus that tends to, I think, work better with these sorts of cultural values. But that doesn't, you know, that only works so long as, say, policy is equally conducive in both kind of cultural environments.
And I would say that right now the United States is certainly not playing into its not playing into its role as the global R&D hub of the world. And we're shooting ourselves in the foot in many ways that end up undermining our own ability to play that role.
But there's been questions raised about the effectiveness of Chinese R&D. Patrick Collison has a question up on his website about like, why aren't the leading, given how much China spends on R&D, why aren't there any influential papers in the field that come from China? So is there something about the way they're doing science there that's not that productive? Yeah, no, I share some of those same concerns.
Again, I would kind of look at this in like an expected value model, right? So there's like some probability that China, you know, kind of stagnates or can't really, you know, maybe they're really good at catching up to the technological frontier, but it's just an entirely different kind of question than actively pushing out the technological frontier. That's actually where I'd say like maybe the majority likelihood is, but we can't completely rule out the chance that they're going to continue, you know, making progress in the way they have.
But to that point, I do think that there are a number of, I think it's called Goodhart's law, you know, the idea that when a metric becomes a target, it ceases to be a useful metric. And you do see, I think, lots of examples of that in China.
One of my favorite examples is, you know, they made a big push recently for AI, and they were saying, you know, we're going to have 50 world-class leading AI textbooks and 50 world-class leading AI online classes, which kind of seems to like miss the point of like, what a good textbook or what a good online class is supposed to do. I mean, after you have the first, you know, five really good ones, I don't know what the other 45 are really getting you.
And so I yeah, I do think you see sort of issues like that. But I think the other point here is that regardless of whether or not China stagnates, it's good on the merits by itself for the United States to try to play this role.
And so it's sort of like a, it's good if China does end up playing the threat that we fear, but it's also good even if they end up stagnating and don't. You know, it's kind of a win-win either way.
Okay, so let me give you my optimistic scenario, which is that maybe the U.S. shoots itself in the foot, but like China takes over or starts to take over as the innovation hub, and the U.S., innovation is the sort of thing that you only recognize its importance when you can see saliently its lack, right? So you see China's making innovations, we're not.
And then we reverse the mistakes that we made that led us to less innovation. And we also already have go to universities.
We have a history of innovation. So then we'll become the innovation hub.
If we start to lose our edge, we'll correct course and we'll become the innovation hub in the future uh is this a persuasive model uh yeah i think it's again certainly within the the range of of possibilities it is it sort of does ring true that uh the united states um seems to uh sort of coast for long periods of time and then when they feel particularly threatened by another great power they kind of kick into a whole nother gear that a lot of the world kind of forgets that we have. You look at how galvanizing it was for the US when the USSR was able to launch Sputnik and get into orbit before the US was.
That kind of was a great political awakening. And there is something to, I don't know, you could use the term techno-hegemony.
the idea that the United States is traditionally, or at least maybe since the 1940s or so, the sort of clear unrivaled leader in science and technological development. And that when we have the chance, we'll kind of coast in that role.
But as soon as somebody explicitly takes up the mantle as a challenger in that, that does kind of kick us into another gear. So we'll see if that can happen.
But I think the counter concern, or the case for concern would be that American, you know, governance institutions are much more sclerotic than they used to be. If you look at, you know, would the Van Auer Bushes of today, you know, be willing to work in the NSF? And I think you could have a pretty compelling case that they wouldn't, you know, there's just so many more roadblocks to wanting to be an inventive, you know, interesting person who is trying to push out the frontier in useful ways and also working in government.
That I think means that even if maybe we get our cultural attitudes right, maybe our institutions are just too sclerotic to really be able to kick into high gear in the way that they once were. Okay, and as far these institutions go, there's, I know there's always been a debate about like whether you reform these institutions or you try to create new institutions that are better.
When it comes to institutions that are funding science, political institutions, whatever else, do you think the best course to increase innovation is just to make them less bureaucratic and have less red tape? Or is it just to start alternative institutions? Yeah. I mean, I don't know that I have strong priors on that.
I think it's going to be for some of these questions, it's really a matter of like political opportunism, you kind of have to like play with the cards you're dealt. And so I would certainly guess that reform seems much more likely than, you know, outright, you know, abolishing these institutions or creating new ones.
But if the chance presents itself to, you know, create new ones, then that might certainly be worthwhile. Part of it, I think, is we're almost trying to create like a governance infrastructure that can easily scale to the kinds of problems that we see ourselves facing or to the kinds of, you know, new roadblocks that existing institutions are running into.
So, for example, with science funding, I think one of the easiest, lowest cost things we could start doing

is to introduce more like almost randomized control trials within science funding.

So you saw, I think it was New Zealand did an interesting experiment recently

where instead of going through this lengthy science funding application process,

they just randomly distributed funds to projects that met some qualified metric. And I think so far, they found it to be pretty successful.
And, you know, they were trying to randomly distribute it, so it would have some sort of external validity. But you can imagine, you know, running 10 different versions of that experiment in the United States, where you're tweaking little variables within the current science funding apparatus, and seeing how each of those, you know, randomizations end up making the results better or worse.
And then you can then take those results and depending on how willing the current bureaucracy is to incorporate these results, then decide whether you want to reform or tear it down. Yeah, the concern there is that the people who would be running the experiments are the ones that have vested interest in preserving the current structure.
It reminds me like a story that Thomas Sowell always tells, he used to be Marxist, and then he worked at the labor department for a summer. And he had this idea of studying whether the minimum wage actually increased employment.
And he was just completely reputed by this department, because they were saying, this guy's just going to make us all lose our jobs. So yeah, it's interesting how you go about instituting those kinds kinds of studies.
For sure. Yeah, there's I mean, yeah, there's the whole meta problem here of can you even, you know, break through the current sclerosis enough to be able to do things that would test the level of sclerosis.
And it comes almost circular in some sense. Yeah, yeah.
Okay, so let's talk about immigration now. Yeah, I just want to bounce some anti high school immigration arguments off of you and see how you respond.
Okay. So Senator Tom Cohn has proposed limiting Chinese students from coming to US and studying in STEM fields.
This is a direct quote. If Chinese students want to come here and study Shakespeare and the Federalist Papers, that's what they need to learn from America.
They don't need to learn quantum computing and artificial intelligence from America. And the case here is, you know, is it just some sort of arbitrage where they'll learn the information that taxpayers have subsidized in the U.S.
and get that innovation and just move it to China? Why is it a bad argument? Yeah, I think it's a pretty foolish argument, and it would be even worse if we ended up, you know, actually running some version of that. I think that there's a number of factors here.
One, it's good to recognize what does the CCP themselves recognize as their biggest barriers to actually achieving some sort of, you know, technological leadership role. And they've consistently pointed to their lack of talent acquisition.
You know, they've said multiple times that their really innovation strategy is a talent first strategy because one of their single biggest problems in the regime is that all of their best and brightest don't want to stay in China and said, you know, go to the US, go to Australia, go to other foreign universities, and then want to stay and work there. So if you look at something, say, AI PhD students from China that study in the United States, when given the opportunity, you know, 90 plus percent of them end up staying in the United States.
And that's a really big problem for China if you're then trying to develop the cutting edge AI companies of the future. So they've been pretty explicit

in the fact that, yeah, talent retention is their biggest issue. They're undertaking a bunch of

programs to try to fix that. They have the 1000 Talents Program and the 1000 Foreign Talents

Program that are both aimed at trying to recruit both Chinese nationals that are brought back home and even just generally talented scientists from abroad and recruit them back home. And so in some sense, if we took extremely broad measures to just shut down all Chinese students from coming here to learn STEM, we'd be really doing them a huge favor, because that's exactly what they're in a sense hoping for.
Great, now we can keep all of these smart Chinese STEM students here in China rather than in the United States. So I think one, yeah, it would sort of play into the CCP's hands there.
Two, I don't want to downplay and say that, you know, Chinese industrial espionage isn't a problem, because yeah, there are certainly many examples of it. One problem is we don't have a good sense of like how big or small the problem actually is.
You hear tons of you know anecdotes or or tangential stories but it's hard to know systematically kind of by the nature of espionage you know how widespread this is. And so I would certainly be supportive of you know more narrowly targeted ways of trying to say you know do more background checks before Chinese nationals are working on sensitive government projects or receiving you know government funds or for research or whatnot.
I think there's a number of, you know, more carefully targeted, or we can run counter espionage networks. Or additionally, sometimes it's the uncertainty about Chinese students' ability to stay in the United States that ends up giving the CCP leverage.
And so if you give them a clear path to, you know, say permanent worker status in the United States upon completion of their degree, I think that reduces a lot of the leverage that the CCP has. So broad story, I would say, yeah,

we could certainly take many more targeted actions than we should to reduce, you know,

the threat of espionage, but to take overly broad actions that end up, you know, playing into the

CCP's hands would actually be a mistake. Yeah, the fact that their top talent wants to come here

and stay here is such a good car to be have. And it's amazing that people just want to burn it down.

Absolutely.

Yeah.

Okay, so here's another argument. Eric,

Thank you. Yeah, the fact that their top talent wants to come here and stay here is such a good car to be happy.
And it's amazing that people just want to burn it down.

Absolutely.

Yeah. Okay, so here's another argument.
Eric Weinstein argues that in the long term, in a free market, wages and demand equilibrate. So there's no such thing as labor market shortage.
So that this entire business about having shortages and STEM fields is a conspiracy from the NSF to reduce wages for STEM field graduates to help employers? Yeah, I think, again, that's pretty silly. I think it really misses the positive sum nature of especially fields in technology.
The fact is we don't have some set number of top end machine learning jobs that are just waiting to be filled by American nationals. And if you keep foreign nationals out, then that means more jobs and higher wages for Americans.

like that may be true in individual cases but I think in a dynamic equilibrium it's totally not

true you see that you know foreign immigrants that come here have much higher rates of patenting

and that they actually they're sort of again going back to the agglomeration effects they

make their American counterparts more productive and they patent at higher rates when they've had

exposure that come here have much higher rates of patenting and that they actually, they're sort of, again, going back to the agglomeration effects, they make their American counterparts more productive and they patent at higher rates when they've had exposure to these international entrepreneurs. They also start businesses at higher rates, which again, if you're like explicitly starting a business, it's kind of by definition net positive in terms of the number of jobs.
Yeah. So, so I think, yeah, he's completely missing the, the, the positive some element of this.
And I think in some ways, like the, there's sort of a word game about, oh, is there a STEM shortage or not? But I think is, again, like not particularly relevant. Because it is true that to make progress on the cutting edge of emerging technologies, you just need more really smart people working in a conducive environment.
And the more really smart conducive people you have working in a conducive environment, the faster your progress will go. And so again, I would prefer the United States to have that progress inside.
I want all of the best and brightest world talent to be coalesced in the United States. And I'd say as one additional point, there's also some interesting, I mean, there's a long line of academic research, I think, backing up.
There's a very strong case for high-skill immigration. But there's a new paper recently that came out in VR that specifically showed when you cut down programs like the H-1B program, it actually increases offshoring.
Because when companies don't have the option of bringing their talented people that they would like to hire here in the United States, it's sometimes easier to just move your headquarters somewhere else where you can hire them. So I think that's a whole nother dynamic that he's not considering.
Oh, that's a very interesting piece of evidence. And it's probably going to be exasperated by remote work.
So it's going to be much easier to just offer labor. And yeah, it seems our intuition works here when we're just talking about native born talent.
It's like, there's more CS graduates now than there were 20 years ago, but there's more IT jobs because every new CS grad is a probability that the new business is going to be created and more jobs will be created. I would say though that I think there's a lot of complaints against the H-1B program that are completely valid and I have a long list of reforms that I would like to see the H-1B undertake, but just taking it as it is and sort of like cutting in half or slashing it, I think would be very kind of productive.
Yeah, I know those pains personally. My dad is a doctor.
And so when I was eight, we moved to the US and I'm 20 now. But we're still waiting in the queue to get, you know, get the because there's per country caps to get green cards.
So we'll start getting green cards. And I'll probably get kicked off unless Congress passes a bill to let kids stay on.
I'll probably get kicked off and I'll have to start the process again to get my own H-1B off my CS degree. And at that point, it might be easier to like leave the country and go to another where there's more lax immigration laws.
Yeah, that's such a mess. Okay.
So how would you go about reforming the H-1B visa?

Yeah, so I would say I have a number of specific reforms for the H-1B, but then almost as a meta thing, I think in some sense the H-1B is like an overrated visa program, and I would like us to almost move our focus more broadly, but I'll start with the specific reforms to H-1B. So there's a couple problems here you could try to address.
address. One is the fact that the current lottery system that's used is it adds a lot of unnecessary uncertainty and also doesn't prioritize the most highly skilled candidates that we care about.
You know, because it's just a lottery, if you've met certain qualifications, it gives kind of equal weight to the, you know, top end machine learning engineer who has a salary offer of $400,000 from, you firm with the IT specialist that is still important, but would be making $60,000 or $70,000. And I just think if this is a high skill immigration program, we should be giving priority to those that have the higher salary offers.
And so some suggestions have said, oh, maybe we should do a salary ranking where basically like the higher up you have as a salary offer, then, you know, the higher priority you should have in the queue. I would be open to something like that, but I would also want to modify it to include equity because there's a lot of times small startups can't compete on, you know, just a salary wage, but they can offer pretty, you know, lucrative equity packages.
And so I think so long as you have some sort of equity adjusted salary ranking, I think that would be, you know, one easy way of making the H-1B much better targeted. Another issue with the H-1B is that it's tied categorically to like a very specific employer, and then it's kind of hard to transfer.
And this is, you know, leads to some of the complaints people have that, oh, well, maybe you can be underpaying workers because they really have no other option. But again, that's not like a problem with the workers or them being in the United States and bringing their talents here.
It's a problem with the structure of the visa that doesn't let them switch, you know, and so you could either try to make it easier for, you know, H1B workers to switch between employers or to even start their own business. Because oftentimes you have people that, you know, come here, want to live and work in the United States, and maybe they even have an interesting startup idea, but they end up having to work at a big company, you know, for six years while they're in line for a green card.
And then finally, once they get permanent residence, then they can start. Six would be great.
Yeah, that would be ideal. Which kind of gets to, I think, the larger meta problem that the H-1B is just pretty poorly structured to actually like both attract and integrate the kind of talent that we want.
And so I've been looking at alternative programs. One that I'm particularly excited about is the O-1 visa for immigrants of extraordinary ability.
It's a pretty under leveraged visa right now, but in principle, it's very flexible because congressionally it has no cap. It's just supposed to be, you know, for immigrants of extraordinary ability.
And then USCIS has like sort of an eight factor test evidentiary criteria for choosing who then fits into that. And so you could conceivably have a new USCIS director come in and either issue new regulations to change those eight criteria, or even just rewrite the internal guidance documents that they use to, you know, make these decisions, and end up letting in dramatically, you know, more really talented, really exceptionally, you know, individuals through that program.
And the nice thing is, unlike the H-1B, that's not categorically tied with one employer. So you could use an O-1 to then start a business or work for a startup or, you know, any number of things.
So that's just, you know, a few examples. Yeah, isn't that called like the Einstein visa because of how hard it is to get it and how rare it is? It is.
Yeah. Yeah.
So it's very hard right now, you know, you really have to be like a top, top, top end. And, you know, even then it's like a 500 length, you know, or 500 page length petition process, which is awful.
But again, because it's so subjective, and because the congressional mandate is so broad, I think that means that the scope for possible reform without even necessarily needing to go through Congress is also very broad. Okay.
Has Joe Biden spelled out how he would, if he would liberalize high school immigration and how he would do it if he became president? He has not given a lot of details. He's certainly spoken very positively about trying to undo some of the damage of the last four years and make it clear that the United States wants to be, you know, the destination for a lot of these high-skill immigrants.
But I think, understandably, voters have not shown a strong preference for really detailed policy plans. And so I don't think that's his highest priority right now.
But I think in the months after the election, if he wins, then there will be a lot of attention to actually getting the details on board. I hope so.
Oh, speaking of what's going on at this time, so another argument that I forgot to bounce off of you is, well, listen, high-scale immigration is usually good, and we should usually have more of it. But right now, given the high unemployment rate, given the economic catastrophe, we need to be emphasizing our own laborers.
And so for a little while, let's just pause the H-1B while our economy adjusts. Yeah, I mean, again, I think you can see that we have lots of economic evidence about, you know, the regions that have higher rates of H-1B historically have higher rates of job growth.
You know, for native workers, they have higher wages. So again, I think if you're looking at in a positive some sense, even like a pause doesn't necessarily make sense.
One, because also the kinds of, you know, job categories that have been the hardest hit by the pandemic are not the ones where H1B employers are typically going to be hiring from. And so I think it's mostly service sector jobs or jobs that require a lot of in-person interaction with customers and whatnot.
So I think it's pretty unconnected from the specific job market issues of this pandemic. To the extent it is connected, it's through medicine, which is an increased demand now, if anything.
Exactly. Yeah.
Yeah. Yeah.
Okay. So I think you said somewhere or wrote somewhere that immigration is the one lever you change first to increase levels of innovation.
Why is it so much more important than other factors? Yeah, I mean, it's, I would consider it my number one lever right now, simply because I guess it's so far away from optimal. So if we look at maybe, say, trade policy as an analog, right, you could talk about the free flows of people and the free foods of good.
Right now, the free flow of goods is like pretty close to optimal, right? We still have tariffs and we still have dumb regulations and inversing that prevent us from getting to some hypothetical free trade optimal. But moving another five percentage points in favor of free trade the margin, just matters not that much.
But we're so far away from the global optimum on immigration policy that, you know, a 5% change in how many really smart, skilled, talented people can come to the United States could make a very large difference. And I think also, if you kind of follow the idea that people are, in some sense, the ultimate resource, right, you know, they are sources of creativity, of innovation.
Then, of course, if you're trying to affect innovation, you want the thing that, you know, can most directly come up with new ideas, which are people. Yeah, yeah.
That's definitely all very persuasive. Okay, so let's talk about big tech.
We were talking, I think, a month after Congress held hearings considering antitrust association against big tech companies. And here are the concerns.
And I want to bounce these off of you as well. Okay.
They're too big. Small startups can't compete with them.
And they limit innovation. They buy up new startups.
These are a lot of concerns. So there's a lot to unpack here.
And then you've also written a paper about decreasing the barriers to entering the AI market. And the concern is they have too much data.
And how are you supposed to compete with the petabytes of user data that Google has? And they need to be broken up so there could be more competition and innovation. Will breaking up these big tech companies increase innovation? Yeah, so there's a lot there.
Obviously, we can try to break down into chunks. I think in broad strokes, I would say that, again, if we're looking at this in expected value terms, there is some probability that if you broke up these big tech companies, maybe you get lots of innovation.
Personally, I would assign a pretty small value there. I just think it's unlikely given many arguments that we can talk about in just a little bit.
But in broad strokes, I think it's pretty unlikely. And the other factor is that it's a very high risk strategy.
So if you break them up and you're wrong about the effect of innovation, then you've just destroyed like, you know, the few golden geese actually producing productivity gains in our economy. And that's extremely bad.
And you've given an edge up to China and blah, blah, blah. So I think a much lower risk strategy that maybe gets at some of these same concerns would be sort of like a big national push to tear down entry barriers, make it much easier to compete against these companies in a variety of ways and sort of, you know, reduce the maybe moats they have around them in some sense, increase, you know, the gale of creative destruction to use a Trumpeterian term.
And then if they can survive that, you know, a level of increased competition, then that further increases the evidence we have that maybe they are efficient, they are competitive. And if they end up falling because now some new startup has outcompeted them, then congrats, you've gotten the outcome that you wanted.
So I think as a meta strategy, I would prefer to at least at first try the strategy of really increasing the level of competition they're faced with, not by artificially tearing them down, but by making it much easier to compete with them. And so that's sort of the broad strategy I was trying to lay out in that AI paper.
One thing, kind of briefly connecting this to the immigration discussion, is the fact that I think a lot of these big tech companies have a huge advantage in the immigration market, because they actually have, you know, large HR departments that are capable of braving the immigration bureaucracy. If you look at the career preferences of a lot of these, you know, top end talented immigrants, a lot of them say they would prefer to work at startups or start their own company at a much higher rate than American native foreign workers in these same, you know, graduate programs.
But then in actuality, the immigrants are way more likely to work at the big firms, because that's the only place that they can actually end up getting, you know, an immigration visa. And so if you could find ways to make it, you know, just as easy for startups to have access to this, you know, high skill talent, I think you would sort of unlock a whole pool of entrepreneurial talent that right now is currently stuck at big tech firms.
So that's just one example of a policy lever I think you could pull that wouldn't be artificially tearing down, you know, these big tech companies, but would be making it easier to compete against them. And I think you could try to do similar things for, you know, data.
I think on the data side, we sometimes get confused if we think of data as this like homogenous thing. But like, oh, just the more data you have, always the better it is.
Data is not context dependent. It's just, you know, reams and reasons of data.
And the more you have, the better it is. In reality, data is very context dependent.
It almost has no value outside of, you know, almost the original circumstances that created it. And trying to almost utilize data is itself, it requires like a massive infrastructure, internal operation to be able to utilize the data.
You know, if someone gave you all of the, you know, the data from Amazon Web Services or from Google search results, it's pretty unclear how you could use that, even if you're trying to build a competition or competitor. And even then, even if you have this one-time static flow of data, that totally misses the dynamic flow of data that actually matters.
Because it's what happens when you make a change in your platform, and then you can see the results are. And so I think, yeah, there might be like one-off isolated cases where I'd be in favor of like interoperability.

But I think we want to be pretty careful about that because also trying to make data useful

in the first place is a very expensive operation.

You know, it requires building a massive internal infrastructure where you have, you know, data

engineers that can collect the data in the first place or think carefully about what kind of data you're trying to collect, how can you process it, actually turn it into useful insights, and then how can you apply it? And so you actually need lots of talent, again, at each step of that phase to be able to turn raw data into something useful, which is, I think, actually, in some sense, where the barrier is. And I think there might also be some interesting things you could do with government sector data.

You know, the government like has lots of data about, you know, the business sector and, you know, geographical regions. And there's been plenty of examples of times in which the government has made, you know, information that they only have and then made it public.
And then that's ended up, you know, leading to pretty large gains. Probably one of the best examples is a lot of geolocation data from GPS satellites and how that's created an entire industry.
So I would be interested in also looking at maybe various open source data sets or data sets you could make open source. Yeah, you've been writing about how this attention the news media gives to, glowing attention news media gives to EU's regulation of tech companies is so misplaced.
Because if the claim is that they're really going after the big guys, you have to explain why only one of the top 30 big tech startups came from Europe. And these new startups are the ones that would be competing against Google and Facebook and Amazon.
They're the ones that these companies are afraid of. And they put up such barriers against starting such things that it benefits the very big companies that they're presumably trying to target.
That's exactly right. If you look at something like the GDPR, which Europe was touting, and still you see tons of conversations in the United States about, oh, well, really, we should just adopt the EU approach and have our own version of GDPR.
But after the GDPR has gone into effect, it's only increased the market share of Facebook and Google. Because, again, sort of similar to the immigration discussion, the more you have these large bureaucratic burdens that you need to meet, the easier it is for large companies to be able to handle that because they actually have the staffing resources to be able to have these huge teams of lawyers to make sure that they're compatible.
And so, yeah, the United States is the one that's actually producing a lot of these top end companies that are competing internationally. They're by far, you know, the most innovative in terms of like patents and where interesting startups are coming from.
And then the EU, you know, talks a big game, but their regulations and practice just make it even easier for the big companies to succeed there. Yeah, I like a thing Jonah Goldberg says, which is that complexity is a subsidy, that if you have more cognitive or legal or whatever other resource or labor resources, the more resources you have, the easier you can navigate the complexity.
That's a great framing, yeah. Yeah.
Okay, so let's get a little bit into the politics here. This might be a meaningless question, but given that there's an election coming up, which party cares more about innovation or would have a better pro-innovation strategy? Because you can look at Trump and say, he might be good on regulation taxes, he's bad on immigration, and the Connors or the Democrats on balance, which one is better for innovation? Yeah, I mean, I think almost talking about parties in some sense, I don't know if it's the best framing, partially because the parties are so broad.
I mean, if on the one hand, you have one party that incorporates everyone from AOC to Joe Biden, on the other hand, you have everyone that incorporates someone from Donald Trump to Jeb Bush, you know, really, I think a better way of almost thinking about it is that there's sub parties within the existing national parties, and they're, you know, competing, and then whoever, you know, went the primary ends up getting sort of the national thing. But I would say certainly, I think a Joe Biden agenda would be better for innovation in the United States, I think, than a Donald Trump agenda, especially when you consider what I would see as the biggest driver's innovation right now that we're missing, which are things like high-skill immigration reform, I think federal R&D reform, a lot more housing in these big agglomerations and these industrial clusters.
Those would probably be my top three. And on each of those, I think, you know, Joe Biden has expressed more interest in those than Donald Trump has.
Oh, I didn't know that he was proposing zoning reforms in the big cities. Well, again, he's not really talking about many of these things.
But in terms of like, where's the energy within the people that would likely be in, you know, put into the various cabinet positions? Good, good. Okay, I'm happy to hear that.
But what about the fact that he wants to raise the corporate income tax rate or probably increase the regulations that Trump cut down? Yeah, I mean, that would be, you know, bad in some ways. Everything is like a series of trade offs.
I would say at this point, like I would take a trade off where we get more high school immigration and more say, you know, federal R&D or experimentation there in exchange for, you know, slightly higher taxes or slightly higher regulations in some ways. But again, I think the better way to try to look at these things is on a case-by-case basis.
Of course, at some level, practically, you have to choose which of those packages do you prefer. And yeah, that's kind of what I would prefer at this point.
But that doesn't mean you have to... Strategically, I'm going to be also trying to push the Biden administration in a better direction in some of these things.
I'm happy to hear that. Okay.
All right. So I want to ask you, with these three areas, what is the most undervalued phenomenon relative to its impact? Okay.
So relative to its impact, what is the most understudied public policy issue? Stuff like immigration, taxes, regulation, health care? Oh, that's a good question. I think we still have a pretty poor understanding of why some of these industrial clusters form in the first place.
It seems like sometimes it's like accidents of history, you know, that it just so happened that such and such a company was here. And then, you know, there was a number of competitors that kind of formed around them.
But then how you get from sort of like a fledgling industrial cluster to something that becomes, you know, full scale, like Silicon Valley, I think it's pretty mysterious. And certainly we've had lots of artificial experiments to try to, you know, seed new industrial clusters and other places that have failed pretty miserably.
But, you know, sometimes they work. So I think a much better understanding of how and why these agglomerations form is one of the things that I would love to see.
I think also the structure of federal R&D support is pretty understudied. You know, it seems like both as like a percentage of GDP, we've seen, you know, basic R&D support from the federal government just keeps on declining as a percentage of GDP.
But then also we're just not seeing like a lot of experimentation in the structure of these grants. And so I'd love to see almost like a science of science, like, how do we know that actually that, you know, these structures where we're using are the best versions of them, because I think we're probably pretty far away from the optimal.
But given the huge public spillovers of, you know, really well structured, well targeted, you know, public subsidies for R&D, it matters a lot. So I would love to see a lot more attention on that too.
Okay. So I have it like a sort of like naive, I know that like, I know like the first few arguments against more government spending in R&D, and I want you to just see what you respond with here.
So Matt Ridley's new book on innovation talked about this. The problem with government spending more on innovation is that they don't know where the next big areas of innovation are.
And so they might be misspending their money. And worse yet, they might be crowding out the priorities of the actual businesses that have a hands-on practical understanding of what the interesting problem areas are.
And so the researchers are working on the problems the government wants them to work on instead of the problems that businesses would have a better understanding of. Yeah, I mean, I, again, a lot of these arguments could be true, like in the abstract, but not necessarily true on current margins.
I mean, I think that's probably an example. So if you look at something like the R&D tax credit, which is probably like the biggest in terms of spending that the federal government does, but I think about that is that it's not directed towards a particular thing.
It's basically saying, hey, you know, companies, you invest in the R&D that you think is most

valuable and it will reduce the amount of taxes you need to pay on that, basically.

And you've seen that a lot of, you know, the biggest tech companies today are by far the

biggest R&D spenders.

You know, if you look at like the top five, it's like Amazon, Google, Apple, Qualcomm,

you know, in some order, I can't remember exactly.

But it certainly, it seems to be successful in prompting our big tech companies to be able to spend on R&D, which is good. I think the other thing is, we maybe need a better structure or a better theory of what are the kinds of science that we want the federal government to be investing in.
So, so for, for, from my perspective, I think private companies will invest in R&D so long as it is sufficiently predictable in sort of what kind of outcomes you're going to get, sufficiently timely in terms of like, is it going to be, you know, on a profitable timeline in the next, you know, five to 10 years? And I guess sufficiently, you know, cost effective, you know, has to be like profitable in some sense. But there's a lot of ways in which valuable questions don't fall into one of those three categories and in which previous scientific advancements have not met one of those criterias.
I mean, especially in terms of the predictiveness, we're constantly getting scientific advancements in fields completely unconnected from what we think we're going to be studying, partially because scientific advancements, especially breakthroughs, kind of in some sense has to be unpredictable, otherwise it would have already been, you know, discovered. That means that there's not really an incentive for, you know, Google's driverless car division to be pouring a lot of money into something that, you know, might suddenly have an advancement for molecular biology, you know, because why would they do that? So the more unpredictable in terms of what, how is this going to pay off, the less likely companies are to do it.
And so I think when you start focusing on what are the kinds of scientific questions that fall into those three buckets, the less relevant the crowd out question is. Because again, if private companies are not going to be spending on these areas anyways, because it's sufficiently untimely, sufficiently unconnected and not sufficiently profitable, then yeah, you have way less concern about credit.
Yeah. And there's also the question of, there's a lot of science that's inexcludable and inexhaustible.
And maybe it's not worth it for companies individually to invest in that R&D, but for the economy as a whole, the tech is more than worth it. For sure.
Yeah. Yeah.
Okay. So the next question is, what is, relative to its impact, what is the most undervalued future technology? This is like stuff like crypto or AGI, biotech, VR.
Yeah, I mean, that's a hard question. I mean, I would say, sort of it depends on, if AGI does end up being feasible, then probably it's AGI, just given how know, given how wide-ranging its effects would be across the economy.
But of course, you know, that's in some sense begging the question. We don't know if AGI is going to be, you know, completely possible to create.
There might be, you know, difficulties that we're not running into yet that we don't know about. So I think one thing I would like to see a lot more emphasis and research on is, um, sort of big climate mega projects, um, that I think are being very under hyped.
Um, we're getting to a point where to really avoid, um, some of the, you know, worst outcomes of climate change, we're going to start needing pretty dramatic action now. Um, but I think any sort of political approach that basically just asks consumers to take massive welfare hits themselves is going to be completely untenable.

It's not going to get anywhere.

But there's lots of, you know, big environmental mega projects that we could do.

Eli Dorado has been paying a lot of attention to this.

He's talked about olivine is this kind of mineral that I think you can put on a lot of beaches that ends up absorbing a lot more carbon than traditional sand does, but it has a very similar texture. The main difference from sand is that it's green.
So it kind of even looks cooler. Or, you know, you could do something like Yellowstone produces just an absolutely massive amount of geothermal energy, partially because there's a massive super volcano underneath it.
And so you could tap Yellowstone for geothermal energy supply a very high percentage of U.S US national energy needs just via that. And you would also be reducing the risk of that super volcano erupting.
So it seems like a win win. So those are, I think, just a few examples.
But I think as an area, it's really under leveraged. Oh, yeah, it's super fascinating.
I actually had no idea about the specific things you talked about. And also, if you think climate change is a serious threat to human civilization, it makes perfect sense to take a few risks, just see what happens if you throw some stuff in the oceans, if it's going to save you.
For sure, yeah, yeah. Okay, so relative to its impact, what is the most undervalued social or geopolitical threat? This is stuff like falling fertility rates, the rise of Asia, stuff like that.
Yeah, I mean, I think earlier I would have said maybe falling fertility rates, just because, you know, it's only really in the last couple of years, especially in the U.S., but I feel like that's become like a major political phenomenon. But you are starting to see a couple of books now that are starting to discuss that more explicitly.
Ross Douthat's Decadent Society makes that a big central focus. Matt Iglesias's upcoming One Billion Americans talks about that.
So I'm glad to see that, you know, start becoming a major focus. But it does seem like demographics are just so connected with a wide range of outcomes.
You know, culturally, I think it makes like a society more conservative and less risk-taking, you know, when you have an older demographic, you know, Megan McArdle had an interesting example, I think a couple of years ago, when she was writing about this, where she talks about, you know, think about an average town that has, you know, median age of 27 versus a town that has like an average age of 57. And just, you know, when you're that much older, like, yeah, you are more experienced, and maybe you have more, you know, human capital or technical skills, but partially because you have less time, and you're, you know, more embedded in like a family, you're less willing to work the 18 hour days and to, you know, leave your job to go, you know, create the new startup.
And so that ends up having sort of cultural effects, both in terms of company formation and idea generation, innovation, that I think end up resounding. And of course, even young people that are traditionally surrounded by an older society, I think will themselves be less risk taking too.
So yeah, maybe I would still say, you know, demographic aging, just given the fact that it's starting to get a bit more attention now, but it has such wide ranging consequences that, and it's not really talked about in the, you know the national discourse in a major way yet.

Oh, yeah. That was the scariest chapter in the Decadent Society for me.
And there was a chapter on authoritarianism coming to liberal democracies and the one on falling for terror. Yeah.
OK. So, by the way, does that mean that you expect Sub-Saharan Africa and parts of Asia to be a much bigger deal, given that they have rising populations? Oh, totally.
Yeah, I totally know, I think at the end of the decadent society, Ross says, you know, one of the, the more optimistic, um, versions is some sort of like, uh, Afro, uh, Eurasian, um, futurism, you know, where sort of, if you imagine, um, you know, classically, uh, European, uh, cathedrals being filled, um, you know, by sub-Saharan Africa, like that, that's a great vision and something that could end up, you know, providing both sort of like multicultural society that we want to see, while also trying to help solve some of these, you know, birth rate problems. Wakanda forever.
Yeah, that's the future. Okay.
All right, to close it out, what kind of advice would you give to a 20 year old, maybe when you were 20, or just to a generic 20 year old? Yeah, I think I would say, think hard about like the kinds of questions that you think matter for society, and where you might be most effective. So one of the things that I was trying to think about in my own career is, I think problems that like the profit motive can kind of be brought to bear on, I just have a higher certainty in my own hand that those will eventually get solved.
Like if there's money out there, someone's going to solve it. But where there's not, that's maybe where there's more attention worth throwing at it.
Because in some sense, it runs like counter to self-interest. So I think something like policy analysis, like the reason I'm in there is because it does kind of seem like the missing element in like the American growth engine.
If you think about like an O-ring theory of growth where you need all of the components to really be working well for like the rocket ship to take off, it seems like bad policy is really the thing that's like strangling, you know, the American growth engine. And so trying to fix that bad policy is not something that right now is going to be economically, you know, profitable, but could end up having like a really big impact.
And it just so happened that I think, you know, my comparative advantage was in writing and communicating and whatnot. So that's why I went into that.
But yeah, if you think about, yeah, sort of you can use a traditional, you know, effective altruism framework, you know, what's the highest impact combined by, you know, what are your efforts on the margin going to have the highest impact on? And I think that'll get you pretty close to what you should do. Yeah, I'm glad you're doing the work you're doing, because innovation is like the most salient fact about our civilization.
If we just look at what makes our life better over time, it's clearly innovation. But our incapacity to see future innovation and how much better our lives could be, it just makes us undervalued so much.
I'm glad you're doing the work you're doing. Thanks.

Yeah, no, I'm hoping to, yeah,

get other people excited about this too.

Okay.

Well, thank you so much for talking to me.

This is a lot of fun.

I learned a lot.

Definitely.

Yeah. Great conversation.
Thank you.