Conversations with Tyler - Mark Zuckerberg Interviews Patrick Collison and Tyler Cowen on the Nature and Causes of Progress (Bonus)

Episode Date: November 27, 2019

Over the past year Mark Zuckerberg has held a series of interviews themed around technology and society. This conversation with Tyler and Patrick is the last in that series, and covers why they think the study of progress is so important, including how it could affect biomedical research, the founding of new universities and foundations, building things fast, housing and healthcare affordability, the next four years of the Chan Zuckerberg Initiative, and more. Read a full transcript enhanced with helpful links, or watch the full video. Recorded November 22nd, 2019 Other ways to connect Follow us on Twitter and Instagram Follow Tyler on Twitter  Follow Patrick on Twitter Follow Mark on Facebook Email us: [e-mail] Subscribe at our newsletter page to have the latest Conversations with Tyler news sent straight to your inbox. 

Hi, it's Jeff, producer of conversations with Tyler. In the spirit of Thanksgiving, we're bringing you another bonus episode. This time, it's Mark Zuckerberg interviewing Tyler Cowen and Stripe's CEO Patrick Collison about the need to better understand the nature and causes of progress. Now, this was the final interview in Mark's year-long series on technology and society, and you can also find it on Mark's Facebook page. So as you're sitting around the Thanksgiving table this week, take a tip from Tyler and Patrick. Instead of politics, talk about the paper from Duflo and Banergy.

found coaching improved the effectiveness of foreign aid, or marvel at how we built the Golden Gate and Bay Bridge simultaneously in four years. How fast did you get your Thanksgiving feast ready? Enjoy. Conversations with Tyler is produced by the Mercatus Center at George Mason University, bridging the gap between academic ideas and real-world problems. Learn more at Mercadis.org. And for more conversations, including videos, transcripts, and upcoming dates,

visit Conversations with Tyler.com. Hey, everyone, and welcome to the next in our series of discussions on the internet and technology and progress and some of the social issues that we face. We've done a number of these this year, focused on topics ranging from regulation to journalism to biomedical research. And today, we're going to focus on a discussion around what progress is itself and how we might study it and what academic work is already going on in this space and what we might think about to look at examples from the past to determine how we can make more progress for humanity going forward.

So today joining me is Tyler Cowen, who is Studies Economics at George Mason University and is also the co-author of the popular blog, Marginal Revolution, and Patrick Collison, who's the co-founder and CEO of Stripe, which is a pretty amazing company that basically does payments and economic infrastructure for the internet. So, you know, we've been talking about these topics for a while now. I mean, this is something that you guys have both studied in a lot of depth. And you know, you recently wrote an op-ed together, I think it was in the Atlantic, about how we might have a new or different approach for studying the nature of progress. And, you know, in order to kind of mine historical examples to figure out how we can make more progress in the

future. So I think it would probably be interesting just to start off by, you know, hearing how you're thinking about that and the basic summary and what feedback you've gotten on the piece that you wrote. Sure. So I think one of the most important sort of facts in the world and sort of of the history of civilization to date is that the rate of progress has not been constant, right? if you look at sort of what happened in the world, say, between zero and 1700, 1800, 1800 thereabouts, the rate of progress by so any major metric in terms of, you know, average income or average life expectancy or infant mortality, any of these measures, it was either sort of constant or only very, improving at a very slow rate, right?

And then something happened, something changed around sort of 1700, 1750, you know, the industrial revolution, the enlightenment, some sort of, you know, the advent of something approximating modern science. And once that happened, so many things started to get better together, right? Again, incomes improved, life expectancy is increased. We started to discover really fundamental knowledge about the world. We started to invent really important new technologies, and these things over the last couple of centuries really diffused around the world.

So that's very interesting and important. And the intuition, I think, and the thing that sort of really struck, or has been sort of a focus of both of ours for the past couple of years is thinking about, well, we sort of transitioned from this regime where we weren't making much progress to one where we have been making much more.

Is this the best we can do, right? Or is there something that looks, you know, compared to the status quo today, you know, so much better again that it's sort of like the status quo ex ante, before the Industrial Revolution. And, you know, as you look around the world today, you know, on the one hand,

we see the tremendous importance of the progress that we are generating, right? And that, you know, for example, the number of people in extreme poverty is declined by, you know, more than a billion people since I was born. But on the other hand, there's a lot of suggestive evidence that maybe we aren't as effective at generating progress today as we have been in the past.

And so, you know, for example, if you look at the U.S., sort of productivity growth mid-century, or so between, you know, 1920, 1970 was maybe about sort of 1.9% a year. Now most economists think it's much lower, you know, maybe around sort of, you know, 0.4% year or something like that. So we're, we're, at least by economic measures, generating progress more slowly than we used to be. Now, whatever the rate at which we're kind of making progress or sort of, you know, figuring out ways to do things better today, whatever that absolute level is, it would be much better if we were, you know, doing it more

effectively, if we were able to solve the most important problems that face us today in, you know, 50 years and 100 years rather than 500 years or 1,000 years, right? And so the meta question that, you know, we're really interested in is how does progress happen? How do we disqualify? How do we discover useful knowledge, how is that diffused, and how can we do it better? It's important to understand, I think, how much this is an invisible crisis. So if you have a growth rate that is one percentage point lower, over the course of a bit more than a century, you could have been three times richer with the higher growth rate. That would be something like the difference between the United States today and Mexico. So by having a lower rate of productivity growth, in no given

year does it feel that bad, but two, three generations later, you're much worse off. It's harder to pay off your debts, harder to solve climate change, harder to address a whole host of problems. Yeah. So before we kind of dive into, you know, how we could improve this, you know, what do you say to the people who question whether all this progress is positive? I mean, certainly as we make progress in one area, it creates issues in other areas. I mean, that's been a big topic that, you know, I focused on in my work at Facebook over the last few years and a lot of these challenge discussions. But how does that fit into the overall framework of, of, uh, you know, what you're studying in this discipline here.

I don't think economic growth is always a positive, but the world in America has serious problems. I would rather address those problems with more resources rather than fewer, whether it is paying off our debts, addressing climate change, fixing global poverty. And knowledge matters too. So there's a recent paper by Esther Dufloh and Abhijit Banerjee, and they find if you give foreign aid combined with coaching,

the rate of return to that intervention is maybe 100, to 400%. Now, that may or may not be true, but what I would like to see is a world where everyone is obsessing over that claim, over that debate, working very hard to figure out that it's true. That should be on the front page. People should be talking about it. You know, calling up their siblings, my goodness, I just read this. What are we going to do? Do you agree or not? Yeah. And look, well, again, I think it's sort of unequivocally the case that sort of certain kind of progress in certain places or, you know, to a certain extent, you know, can't have harms and externalities and all the rest. And, you know, a really important part of progress is

figuring out how do we mitigate those, how do we solve them and so on? And, you know, I think climate change is probably the kind of the foremost global example today. But I think it's really important. It is easy for sort of us sitting here in the Bay Area in California, I think, to undervalue the prosperity and the kind of wealth we've been able to generate over the past couple, you know, again, a hundred years. And so, you know, since I was born, for example, global life expectancy has increased by about six years. And infant mortality has fallen by more than 50 percent. Again, I mentioned the statistic about the number of people who have left extreme poverty. This is incredibly important, right?

And so I think we're not the first people to say it, but there is a moral imperative to this kind of progress, and we shouldn't lose sight of that fact. Yeah, I agree. I just, I think it's important. You know, a lot of these things are not uniform. And, I mean, you know, from running a company that, you know, when you look at averages and anything, it hides a lot of issues. I mean, your example on the rates of poverty going down, I think, is an important. interesting one in this because, you know, what a lot of people don't particularly want to talk about these days is that most of the benefit of people coming out of poverty has happened in China,

and a lot of other places around the world, in some places, poverty is actually increased. So I generally agree with the premise, and I think studying this stuff will generally help us to make more progress in those places. I mean, that may be a good example, because perhaps looking at some of the examples of what has done well in China could be applied. to other places where there have been issues. But before we dive into the discussion on this, I just wanted to make sure that we didn't cover this in a way that comes across as if like every step forward it comes without a cost. And I'm sure as we talk through the different examples, I mean, that'll come up as well. Yeah, well, and we should emphasize that, you know,

when we sort of talk about the phenomenon of progress, I think GDP or GDP per capita is a sort of pretty good first approximation measure of it, and it correlates strongly with many of the things I think we care about. But they're definitely not the same thing. I think an important question for anybody kind of interested in this area to think about is, well, how should we define progress, right? And what are the better and worse kinds of it? And again, in GDP, we kind of have a relatively effective metric we can use across countries. But there already is interesting work on what might better measures be, and I think that's really important to study. Let's say you want to improve a lot of people in West Virginia. One growth-enhancing way of doing that is to make it easier to build,

say, in Washington, D.C., in the Bay Area. Right now, to move from West Virginia, say, to Menlo Park, it's extraordinarily expensive. You can't just pick up and show up here and hope to get a job washing dishes the way one might have done in America 50 years ago. So by having more building, more economic growth, also more GDP, it would increase more opportunity. So, economic growth and opportunity, they do tend to be correlated. And sometimes the problem is we don't have enough growth, not that we have too much. And look, not to hammer this point too strongly, but you know, you did invite the two people who wrote the piece about progress here. Yeah, and I want to see most of the time actually talking about that. I just wanted to make sure

that we hit that up front. So what are you, when you're talking about, you know, there are a lot of people who already are studying this in different ways, right? There are historians, economists. When you're thinking about what the field is, when you're talking about trying to create a new science of studying progress, what more do you think needs to get done? Or what do you envision on that? I mean, I know you have a fund that you've put together, emerging ventures. Emerging ventures, yes. And where you're basically finding academics who are studying examples of where there's progress in the past to start this field. But I mean, but what does this kind of add up?

How do you think, what form does this take over time? One view of mine is that not enough philanthropy is long-term oriented. In this regard, I've been influenced by your Chan Zuckerberg initiative. And also in philanthropy, there are too many choke points that can say no. So foundations become their own bureaucracies. They become very risk-averse. So Emergent Ventures is a new kind of philanthropy. There's one layer of yes or no. People are encouraged to apply. If the payoff is 30, 40 years down the road, the attitude is great. take a lot of chances, worry about getting some winners and some risk,

and not expecting the median project to be something that necessarily looks good when taken to a board. So that's one way that thinking in terms of progress helps us restructure at the micro level, particular decisions we're making. Yeah. I strongly agree that there's a lot of really, you know, important work already happening across, you know,

multiple disciplines that is relevant to these questions. And, you know, part of what, like, the idea of there being a new science of progress, that's not sort of quite, you know, that was the headline, you know, placed on the article, but sort of not exactly what we are saying. What we were arguing is that the work that's already happening should be receiving more attention and there should be much more of it. And just to give us a couple of quick examples.

So, you know, there's strongly suggestive evidence that we can teach management, you know, practices such that people can, you know, run firms more effectively, right? And so there's, you know, a couple of studies on this. There's a good one from some folks at Stanford. They did sort of a randomized trial in India. and there's a really neat one that came out, I think, last year from Michaela Giorelli, looking at firms in Italy and showing that like over 15 years after, again, a management training program with sort of a natural, some natural randomization, that again, those firms were employing more people,

paying more wages, being more successful. And another randomized trial in Mexico conducted over the past couple of years, again, 600 firms ensuring that just teaching better management practices actually makes those companies much better off. that's true. That's amazing low-hanging fruit, right? We should be investing much more in this area. We should be figuring out which kinds of management training work better and worse than others. Does this generalize to all countries? How can we actually implement and execute this in the world more broadly? So that's kind of one. Second is, you know, if you take, you know, Tyler mentioned this point about sort of, you know, geographic mobility, right? When you think about sort of how do we grow GDP or how do we generate progress, you know,

maybe kind of housing policy is not kind of the first thing we're naturally drawn to thinking about. However, if you look at the world in, say, the U.S., say, in 1980, about 40% of people when they took a new job moved somewhere else, right? So those things went together much more. If you look last year, about one in ten people moved when they took a new job, right? And so within the U.S., geographic mobility has really declined. That is in large part because the costs of movement have enormously increased as housing costs have increased, especially in our most productive regions over the past couple of decades. If you look into that sort of more closely, again, there were sort of economists who've been studying these questions, you know, quite closely for the past couple of years. These two guys, Shea and Moretti published a paper, an updated version of a previous paper, this summer, claiming or kind of putting forward a model showing that if you, if you look at the zoning restrictions that existed in the Bay Area and New York between 1964 and 2009, and you kind of imagine a counterfactual world where there was sort of much more supply.

elasticity in these places. We build way more homes here in the Bay Area and in New York. In that counterfactual world, average U.S. income would be in their model $3,700 per person higher. Again, not just for people in those places, but across the country, right? That's a huge effect size. And so again, we should be studying these questions much more closely and we should be figuring out, okay, well, you know, if that's true, what are the policy prescriptions? You know, how do we actually go act upon that? It's amazing low-hanging fruit. And then just to give a third one, you know, I mean, as those two examples show, funding science is incredibly important, but there's surprisingly little work about how we should be funding

science and how could we do that most effectively. And actually, sort of beneath the surface, it's been changing a tremendous amount, you know, here in the U.S. over the past couple of decades. And, you know, there are important, you know, policy questions, is that a good thing? And so, for example, in 1980, 12x more dollars, or the NIH spent 12x more dollars on researchers under 40 than researchers over 50. So, you know, they predominantly funded younger people. Today, they spend 5x more dollars on people over 50 than under 40. And so it's really inverted. It's kind of gone from, you know, primarily funding these young investigators to this kind of gerontocracy where they're funding older scientists. Maybe that's good, maybe that's bad,

you know, I don't know, but that seems like a very important question to answer. And so, you know, part of our point in arguing for progress studies is when you really look at the kind of the expansive version of this, of all the different things that can sort of, you know, influence our to discover new useful knowledge to generate economic growth, the set of questions is super broad, and we should be trying to kind of synthesize this effectively. Yeah. So let's go deep on medical research here for a second,

because this is an area that you wrote this paper about before, about how the progress in the field might be slowing. And like you mentioned, I mean, the Chan Zuckerberg Initiative, the philanthropy that I run with my wife, I mean, a big focus of it is on medical research. And trying to, you know, we have this aspirational goal that we want to help build tools that can help scientists cure, prevent, or manage all diseases by the end of this century. And basically the math of how you get there is, you know, starting about 100 years ago, call it, you know, there was really this uptick in medical research where, you know, we started doing randomized control experiments, treating it more like an experimental science.

since around that time the average life expectancy is increased by a quarter of a year every year relatively linearly. There's no guarantee, of course, that that continues. But if we were able to have that continue, then that would imply that by the end of the century, we will generally have had to have either cure or prevent or be able to manage most, if not all of the diseases that we're aware of now. So there's some trend that suggests that this should be reasonable. and the approach that we're taking in the work at CZI

is largely about building tools to help compound the rate of science. So, you know, what we see is that, you know, like you mentioned, the government is the largest and most important funder of science, and, you know, it basically funds the whole establishment of scientists across the country. But the grants tend to be very spread out across a lot of people. they're not typically put into kind of big infrastructure projects. And that's the niche that we felt through CZI that we can maybe help to fill is, you know, investing instead of, you know, a million dollars in a lab, put $100 million or a couple hundred million dollars over time into building up really important scientific assets for the community, like helping to fund scientists to put together this human cell atlas, almost like the, you can kind of think about it as only, it's a little. It's almost like the periodic table of elements, but for biology, of all the different kinds of cells in the human body.

And the goal is just, you know, if you look throughout the history of science, at least, you know, most major scientific breakthroughs have been preceded by the invention of new tools that help people look at things in different ways. And so the theory is kind of similar to what you're going at of how do you increase the compounding rate of progress. But there are a couple of different directions that I think we could go in here. I mean, one is I'm curious what you've seen in your studies in the space that suggests to you that the rate of progress is actually. slowing. And I'm also curious, what are the examples that you've seen overall of how the science around studying progress would potentially lead to a different approach or a different portfolio of how this kind of work gets done? So I don't know where you want to start with that, but there's a lot here to do. Here's what worries me, and it should worry you too. So as you mentioned, U.S. life expectancy

is basically going up in linear fashion. But if you look at expenditures, we used to spend a few percentage points of GDP on health care, and now it's about 18%. So we've gone up to 18% and we're not even boosting the rate. I'm not saying it's the fault of any one group of people, but something has gone wrong. There's some kind of last mile problem. You can turn into the newspapers and read all kinds of fantastic stories, new research, new ideas, new tools. But when the rubber hits the road, people living longer, we're spending more and more and more for exactly the same returns. So if that trend continues, and you see a similar trend in many areas, also crop yields, feeding the world, other areas, the question becomes, you know, where does all the progress go? So the idea that you need to look at each structure and encourage more risk-taking, better decisions with the money, less bureaucratization, maybe in some cases more centralization, whatever it takes, but that there is this invisible crisis and people are distracted by the headlines about CRISPR, whatever, but actually what you get for the money, performances, so-so, I think.

Yeah, and so what we wrote in this article a year ago about sort of what's going on in science, you know, if you look at it, by sort of the most kind of macroscopic measures, right? Like the number of PhDs in the US, like active PhDs has grown by, you know, well, actually, you take all the macroscopic measures, they've all grown by a factor between a 50 and 100, right? Number of PhDs, number of papers published every year, just like actual dollars instead of science funding and so on. So if, you know, in some very stylized way,

if we look at sort of the first half of the 20th century, as compared to the second half, just like way more kind of input in the second half of the century. And again, not. by kind of 50%, but by kind of orders of magnitude. And so then I think the question for all of us would be, well, you know, in which half of the century did we get, you know, more out in terms of kind of useful scientific knowledge, you know, and whichever we think kind of did better, you know, to what degree, right? And, you know, again, this is a very difficult question to answer, you know,

how do you weigh kind of scientific knowledge? And so you have to kind of look at it, I think, in sort of various applied contexts like life expectancy or semiconductors or, as Tyler mentioned, crop yields or, you know, whatever. And I think what's interesting and it should be concerning is that for almost every conceivable, it's of applied measure, we seem to be getting, you know, at best, constant returns. But that's really bad because, you know, we've exponentially increasing inputs and we've, you know, constant return outputs. Like that that is kind of almost by definitions of not a process that we can sustain. Now, you know, there's two, I think, broad possibilities there. One is it's just getting intrinsically harder to generate progress and to kind of discover these things.

And, you know, who knows, maybe some significant amount of that is true. but the other possibility is it's somehow more institutional, right? It's more kind of contingent. It's more sociological. And again, we do have suggestive evidence that, you know, our institutions, well, they're certainly kind of older than they used to be. And they're also kind of, as in the kind of NIH funding example, there are, you know, changes happening beneath the surface and so on that, you know, may or may not be good.

So I don't think we should write off the possibility that it's actually, you know, it's not inevitable and that there is, or that there do exist alternate forms of organization where things would work better. And again, if we sort of, you know, dig a little bit. into the evidence there, you know, you see things like, there's a science funding program that obviously you're familiar with called H.GMI, the Howard Hughes Medical Institute. They give grants sort of along the lines of how CCI does,

where, you know, their longer term, they're kind of more open-ended and so on. Pierre-eslaid at MIT wrote a paper a couple years ago and trying to look at, well, if you take, you know, ostensibly identical scientists who, you know, some of whom receive HMI grants, some of whom don't, you know, how much more successful are the H.HMI recipients? And he concluded they're about twice as likely to produce a kind of top 1% paper by citation count. Again, that's really suggestive. They're top 1% if they do what? They're about twice as likely to produce a top 1% paper by citation count. If they receive an HHMI grant. Well, that might be correlation, not causation.

Yeah, so he tries to control. They do get a lot of the best people. Yeah, yeah. So he tries to control for that. And, you know, he's a reasonable methodology for it. But, but, some, Some of it could totally be sort of that just selection effect. But again, I think it's very suggestive that, hmm, maybe there are things we could do that would, you know, better enable this kind of discovery. And, you know, this might seem like a bit of a red herring, but I think it is kind of, you know, again, suggestive. That in many other domains where we can objectively assess progress, it's very clear that our productivity has fallen off a cliff and for reasons that we can be pretty sure are not that it's getting intrinsically hard. And so, you know, for example, when New York decided to build a subway in 1900, right, you know, they decided to build it. Four point seven years later, they opened 23 subway stations, and in 2019, they spent just over a billion dollars doing so, right?

So, 23 stations just over a billion dollars. When New York decided to build a Second Avenue subway in, you know, 2000, 17 years later, they opened three stations, and they spent four and a half billion dollars doing so, right? And so kind of our productivity in, in subway construction, has, you know, at least in New York, decreased by a factor of 40. Here in the Bay Area, we decided to build the Golden Gate Bridge and the Bay Bridge, starting in 1933. Both projects finished within four years. And then to celebrate it, we decided to build a man-made island.

And we built that island in 18 months. And I haven't tried, but I would wager that if one tried to build a new island in San Francisco, it would be difficult to do so today in 18 months. And so, I mean, California, you know, you have high-speed rail. where when France decided to build, you know, the TGV, it's high-speed rail. It opened the first line after five years. California started pursuing high-speed rail 11 years ago. They forecast, we forecast being finished in 233.

So we project a 25-year project, but of course that's a projection. It'll probably end up being much longer still. Right. So, you know, this is a domain where it's hard to imagine that getting, or excuse me, the building infrastructure has gotten intrinsically harder, right? Like the atoms aren't physically heavier than they used to be, right? And so clearly there's something institutional, sociological going on with infrastructure. You know, Larry Summers talks about the idea of the sort of promiscuous distribution of the veto power

and just, you know, how much harder it is to sort of get things done. In as much as that's true, then there's the question of, well, you know, have other institutions, have other sort of progress generating mechanisms in our society, have they also got less efficient? And if so, you know, what can we do about it? So as an aside, if you're watching this, Patrick collects these agreements. examples of historical projects that went fast and that you can't imagine how they went that fast.

So if you Google his website, he has like a whole list of these that I think is pretty interesting and compelling when you go through all of them. Yeah, I think it's just important to understand how effectively we as a species, how effectively we can do things when we're organized the right way. humanity is pretty amazing. And when possibilities are unlocked, when efficacy is enabled, we can do great things.

Sometimes it is a matter of actual will. So for the last 40 years, getting around for almost all Americans, it is slower. And before that, we had a period from 1800, say to 1970, when it got quicker and quicker and quicker. And now even flying in airplanes for most people is slower. Traffic is worse. Those are solvable problems. Manhattan should have congestion. pricing and a stiffer form of it than they're likely to opt for. So the notion that people have

lost the ability to imagine a future much different and much better than what they know, to me, is one of the most worrying aspects of where we are now. Yeah, and this shows up quantitatively. I mean, if you look at sort of the percentage of Americans who think that their kids' lives will be, you know, better than theirs, that has been in sort of monotonic decline, well, not strictly monotide, but generally declining since World War II. And so on an empirical basis, Americans are getting less hopeful about their futures, their kids' futures. And that's a really bad thing because it can be kind of an auto-catalyzing process in a self-fulfilling prophecy. And we're supposed to be the most optimistic forward-looking country.

The data on France, how many people think their kids will be worse off. That's much more worrying yet. And there may be a self-fulfilling prophecy to this. If you think the future won't be so great, you'll invest less, you won't work as hard, you'll contract your risk-taking. And you end up with a kind of social and economic malaise. And indeed, you see falling rates of economic growth in most of the Western world. So I'm curious how you would think about going about and studying these kind of organizational changes. So going back to biomedical science, for example, just because this is an area that we do a lot of work in,

you know, the woman who runs CZI's science initiative, Corey Barkman, she's a very renowned scientist. And she has this theory about that a lot of the granting process that NIH does, but also HHMI. It basically encourages very individualistic work, right? You give people grants, they work on their own, you're not incentivizing people to work together. People actually want to work together. They want to coordinate. And when I was talking about the human cell atlas, you know, a lot of the issue there that needed to get dealt with was, you know, a lot of people were working on cell atlases for different parts of the body.

Okay, the liver cell atlas, you know, whatever. And but they were all in different data types and format. so that way you couldn't compile a holistic thing. So a lot of what she did in the work of CZI was basically helping to coordinate. That way, when these grants were given, everything, like the teams work together, the data types were similar. So that way it all added up to a bigger thing. And that certainly seems like one of many theories that one could have for how you could organize this stuff better. But there's this question of how much of progress, whether that's something that one could have determined just through historical data versus this is the type of thing

that you need people or the government or foundations to go out and just run different experiments and see how this works. And I'm curious how you think about in terms of studying this, how much of this is history and kind of history of science based on data that's already out there versus we should just try different models of things and encourage more creativity and more competition and try different things. It's striking to me if you look at American universities. The list of the top place is in 1920 and the list today. It's completely the same, except we've added on California. Otherwise, no change. Top 50 universities, if you look at... It's very different companies. Of course, even from 1980. It's... Decade over decade. Yes. List of the top 10 companies by market cap almost completely turns over. Procedures for tenure in the top 50 research universities, almost exactly the same. Whatever you think of those, there's some. something gone wrong in the sector. There's not enough experimentation with how you reward people.

More schools should experiment with a different kind of tenure or reward people more on the basis of practical impact. And again, you might object to any particular solution. But the extent to which experimentation has died at the institutional level, to me, is striking. And to underscore that point, if you look at the top 25 universities in the world today, or the Times is ranking. There's lots of them. Seven of the top 25 are American universities that were started in a single 30-year period

between 1861 and 1891. And if you look at, well, where did those universities come from? And, you know, what were the people behind them thinking? They were very deliberately, sort of specifically reform-minded. And progress-minded. Absolutely. They thought, well, you know, obviously academic institutions exist. You know, Harvard, Yale, and so on,

were, you know, already around. But they saw the success. of the German sort of research university model. They saw kind of the possibilities of the US and they saw at least what they thought was kind of required for the future. And they very deliberately decided we will try something different.

And again, that yielded now seven of the top 25 universities today. And so I think it's kind of strongly, you know, empirically underscores the value of the kind of experimentation you're talking about. And, you know, fully agree. I think we should be historically informed

but ultimately, you know, a certain amount of sort of commitment, decision and just willingness to experiment is going to be required. The other thing I think your point about the teams gets at is there are these really thought-provoking examples of just like productive cultures through history, right? If you look at Vienna, 1880 to 1940 or something, you know, you have in so many different fields, you have, you know, people who did this sort of incredibly formative work. You'd Klimt and you'd Mahler and you'd mock in physics and you had, of course, you know, Austrian

in economics and, you know, Fund Mises and Hayek and all the rest, and you'd Freud and you'd Wittgenstein, you know, like Vienna was sort of amazing in this period. And, you know, when you kind of dig into the specific stories, you realize a lot of these people knew each other and they were sort of inspired by each other. They kind of give credit to each other for, you know, again, across multiple disciplines, sort of, you know, different parts of their thinking. Or if you look at Edinburgh, so during, you know, the Scottish Enlightenment, you know, again, sort of a tiny place. I mean, Edinburgh at the time, say, in 1780

was like the size of Santa Cruz, right? And yet you get, you know, sort of modern economics from Smith, you know, you've hume, you have, you know, the birth of modern geology, you know, amazing literature, poetry and so on. And so clearly there was something,

you know, extant in Edinburgh in 1780. There was, you know, not there in Dublin in 1780. And I think, you know, Obviously, it's hard to pin down, like, what was that? But at the same time, you know, the difficulty in defining it doesn't mean it wasn't there or it's not important. I would say this.

I'm sitting here with two university dropouts. That's notable to me. The Bay Area is our modern Vienna, you know, Bravo to the Bay Area. But we're not working nearly hard enough to build other new Viennas and other places. And I don't really think it's quite Manhattan anymore. It's a wonderful city, amazing place to go. But it is not a world leader for ideas in the way it was, say, the 1920s. through the 1980s. People study this, right? I mean, so what, I mean, what have been the main

things that people have learned so far from studying Vienna or Edinburgh? I don't think there's a rich literature of lessons from those places. Obviously, lots has been written about them. They're great historical accounts. I've enjoyed reading them. But I mean, well, it's an intrinsically very difficult thing to do to figure out, well, you know, which things causally mattered. And these things, you know, there's a certain degree to which they might be kind of, you know, overdetermined. And so I think it's very hard to, you know, you don't have counterfactuals. Obviously, you can't run trials. And so I think it is a very difficult question to answer. And I think, you know, for understandable reasons, people studying these questions are reluctant to, you know, take definitive stances that, you know, this is what mattered in 1900 Vienna. But one lesson I would say, the Scottish islands, people move to Edinburgh, right? Vienna, you have Jews coming in from the Pal of Settlement, the Bay Area, people coming from all over the world.

And indeed, you're from Ireland. So immigration, immigration is not a guarantee of things going well, but the bringing together of different ideas and cultures and the new clash of opposing perspectives has been correlated with a lot of these Viennes in the world history. Very true, although I'm pretty sure that in 1900, Paris had more foreigners than Vienna. I think it was like 2% in Vienna. So anyway, I very much a point. If you go from the Scottish islands to Edinburgh in 1740, that's a huge difference.

It's a bigger difference maybe than, you know, Mexico to Los Angeles today. If you're thinking about what kind of work to fund in terms of studying historical progress, what's your framework for figuring out where to even begin studying? Because, I mean, what you're talking about here is basically studying the economic and scientific result of immigration, which is obviously a massively socially important debate that's the center of a lot of political debates and has been for a long time. So from one perspective, it would be very, it's sort of surprising that it wouldn't have been studied in more detail to understand the impact of it. But that's very different from kind of the biomedical science

type stuff that we were talking about a second ago. Do you have a framework in your head for how you would think about or prioritizing, studying in different areas? Or is it mostly just about finding really sharp people who have new ideas and funding them to do different kinds of work? Or how do you think about that overall? People who are curious, people who have bold ambitions, people who have what I call stamina, they just don't ever stop. People who are working in productive small groups that may be through WhatsApp, in fact, or it could be their next door neighbors, their colleagues at a university. when those, say, four items come together, then I think you have possibly what is a very good funding decision,

and I would take a lot of chances on those people, not worry too much about the micromanaging and let talent rip and let groups form and see what happens. Got it. So it's very much like entrepreneurship in that way. You're betting on the person more than the idea. But also the vision, right? There has to be a vision.

And there are plenty of successful entrepreneurs who are not curious. So for intellectual progress, to really put curiosity very highly as part of my philosophy. Yeah, and I want to be kind of carefully here. On the one hand, not only do we acknowledge that an immense amount of very important, insightful work has already been created, and it's that work

that to a large degree has, I think, inspired both of our viewpoints. For example, the paper, sort of Tyler mentioned about declining research productivity in semiconductors, opioles and a couple of other fields that was done fairly close to here. And, you know, that is work squarely relevant to these questions that I think is really important and we may not be here in the same way without it. On the other hand, it is simultaneously true that major

sways of these questions really are surprisingly underinvestigated. And so, again, just to return to biomedical funding and the NIH, as far as I can tell, there are no books assessing how well is the NIH working? And I don't have a strong view on the answer to that question, but I do have a strong view on the importance of knowing and which parts of the NIH are working better and worse. And in as much as the NIH has changed over the last couple of decades, was the old NH better or the new one? Like, this stuff is so important. And so while it's the case that there's a huge amount of good research happening today with fantastic researchers, in a sense there aren't enough of them. And a lot of the central questions are still

answered. Yeah, interesting. Do you think, so you were talking a minute ago about the explosion and costs in healthcare. And right now, I think one of the defining aspects of the moment that we're in is a lot of the basic costs of living for a lot of people have just increased a lot. Right, where, you know, the story that we tell about our society is that, okay, you have technology and you have competition and it drives down prices. So, you know, if you bought a TV today, if you, if if you bought a TV from, you know, a 10-year-old TV today, it would cost, you know, a 5% of what it cost 10 years ago. So clearly the value and efficiency has increased a lot there.

But then in things that matter so much, like healthcare, education, rent, those things have generally just increased, right? And in like the normal dynamics that you would be hoping would play out, aren't. And to some degree, for the quality of life for a lot of people, the increases in those costs may even be dwarfing all the other advances and everything else. So do you think that that is, that those things are all related? Or do you think, I mean, I think you use the phrase cost disease, right? When referring to, you know, the cost explosion of things like health care and education, student debt, and rent.

Do you think that that's a different type of problem, or do you think that that is fundamentally related to the rate of progress in biomedicine, as an example? I think there are common features to these problems, though each one is different. Restrictions on entry is one. Highly bureaucratized institutions. Sometimes a lot of third-party payment, which may be required in the case of catastrophic health care, but it nonetheless has distorting effects. areas where people have very strong moral feelings. I think we often make worse decisions about. We're not analytical enough.

And you put all of those together, but I would stress, say, health care, if you go to Singapore, health care there, I think it's about 4% of GDP. They have slightly higher life expectancy than we do. Their system is by no means perfect. But we can see through comparative analysis, there are ways of doing this better.

The NIMBY problem, cost of living, getting an apartment, in Japan. It is mostly solved. because building in Japan tends to be regulated at higher levels than the city or the county. So more gets built. Living in Japan is cheaper, the cost of renting an apartment. So often we kind of know the answers. We shy away from really focusing on a concerted effort to get to doing them in this country.

I agree with all of that. And I would just underscore the entry costs aspect. And the entry costs aren't always, or they, I think, take different forms, right? that sort of impurity the entry costs of forming a new university are really high, but that's not because there's a kind of formal toll you have to pay. It's not like zoning where there are kind of deliberate specific kind of legal restrictions that prohibit you from doing so. But just as a practical matter, sociologically, institutionally, accreditation dynamics, who knows, it's apparently almost impossibly difficult to create a successful new university today.

And so I think answering the cost disease question is one of the most important sort of subcomponents in this broader question of, you know, what is it that enables our progress? And at an overarching level, it's just surprising to me that we don't have sort of more definitive and clear answers there. Alex Tabrock, a colleague of Tyler. Wrote a long paper on the cost of ease. Exactly. Last summer. And, you know, there are other papers, you know, analyzing the, you know, analyzing the. also analyzing the question, but it's a surprisingly sparse literature. You know, Alex's list of

citations was not that long. And, you know, he had some suggestions as to, you know, what the underlying etiology might be. Maybe he's right, maybe he's wrong. But again, that that's, it's, to your point, it's one of the most pressing questions, you know, for American society, for global society in 2019. We really have to know what's happening. And, you know, to return to something Tyler said earlier, part of our hope, you know, it's not to kind of promote any specific solution, any specific, I don't know, aspect of it, but rather that, you know, even though this is not what's kind of vocally central in the headlines today, it should be. And as we think of what the world is going to look like in 50 years or in 100 years, it plausibly more than anything else

is going to determine the shape of that. As an entrepreneur, what is it you find most striking about America's dysfunctional economic sectors. Because you intersect with them all the time, right? Yeah, I mean, I would want to see this get studied more. But so there were just so many different factors. And I think part of what is a little bit confusing is that the things that are making healthcare so expensive, they may have some fundamental link to the things that make college tuition so expensive. But on its surface, it seems like there are also.

more proximate causes that are quite different. You know what I mean? So with with college tuition, the fact that, okay, it's really expensive, so then we do more to subsidize the cost of it. And then by doing so, we're not providing any pressure on colleges to make it more efficient. And then the cost just goes up further is a pretty different dynamic than what's going on with health care, where we're basically Americans want to know that if someone in their family gets sick, going to be able to get every treatment possible, which ends up, I mean, I'm sure you've seen all the stats on this, that half of the health care costs that someone incurs are in the last six months of their life. And that's, I guess, part of what you're saying is an American moral value,

which is that, you know, we believe that you should do everything you can to help so new sick, whereas in a lot of other countries, I don't know what Singapore's situation is, but a lot of the ones that are often cited as more efficient health care systems, don't have that approach. They say, okay, if someone in your family has this form of cancer, we'll do these two treatments, and then we're done. And part of that is because they may not be able to incur the level of debt as a country that the U.S. can. So they may just have to make that trade off. But it creates all these downstream dynamics where, okay, now if you as a society are willing to say, okay, we're going to have two treatments for this kind of cancer, not do, not try all seven things,

then now, you know, France can go, for example, negotiate with the drug companies and say, all right, I'm only going to support the two that are the most cost effective and the other ones are out to dry, whereas in the American system, you don't have that kind of negotiating leverage. So it seems like they're very different things. But I kind of, intuitively, it seems like at their root, there should be some commonalities. and I would be very interested to kind of understand that in more detail. I'm curious why, you know, from what you're saying about, so that the literature is sparse. On Kotzzi's in particular.

Yeah. Why do you think more people aren't studying this? I mean, given that this is just such a central thing in the lives of most people, right? It's, I mean, the cost of living in cities has gone up so much. We have a whole generation of students. I think the total student debt is now almost $2 trillion, right? It was 1.7, the last stat that I saw. And of course, health care is, you know, the number of people in the country who are within one issue of being bankrupt is just kind of staggering.

So what's preventing people from studying this? I wouldn't say anything's preventing them. The incentive is to build a brick and to build a brick that can survive scrutiny by referees. The incentive is not to build a building in most cases. Biomedicine actually is often different. But in the social sciences. So there's so many bricks out there. And so people want to say, oh, we're already studying this.

It's correct. The bricks are there and the millions. But the bricks and the buildings are a different thing. But I have a question for you, if I may be allowed. Go for it. What is it you would most like to see from academics? And I don't mean research on social media. I mean America, the world.

What do you want? Although I would like more research on social media. Absolutely. That's fun. No, look, I think that these issues on exploding costs and why these systems aren't aren't working the way that they're supposed to for people is probably one of the most pressing questions. And when I think about our work over the next decade, and it's like, what are we going to do that's going to fundamentally make people's lives better? There's a lot that we can do. But if these problems continue at the rate that they're going at, it's actually quite hard for me

to imagine how we could do enough good to overcome the increase in costs that people are incurring at things that are so fundamental. So, you know, we're working on them in somewhat different ways. Where I think healthcare is difficult because it is so inherently political for the, because it touches on moral values. Where if you want to have a difference in approach of how we treat the last six months of people's lives, that's something that's more of a democratic question than a technocratic one, I think. People need to be able to support that. So I don't personally feel like that's an area that I'm going to have a huge impact.

A lot of people are focused on that. But the area that I do think we can make a big impact is on long-term science research. So if you can just make it more efficient to cure, prevent, or manage diseases, then that over the long term should really be the answer for bringing health care costs in line. Not in the next 10 years, but maybe over the next 50 years, I'd like to see a solution before that. so I'd love to see more studying of the healthcare part of this, but on the science side, I'm quite optimistic about that.

On housing, I don't know, I mean, it's, you know, there's always the question of what, which forces in technology end up being stronger than, like, which trends end up being stronger. So, you know, on the one hand, you have this giant mismatch of opportunity where people feel compelled to move to cities because that's kind of where a lot of the jobs are. But then there's not enough building of supply of health. housing, so rent just increases. And then that means that even though people are going and doing higher value things, their lives actually aren't benefiting as much from that because so much of their costs are just of the value that they're generating is just going to housing because rent

is getting so high. So, I mean, historically, what have people done? I mean, we invented cars, right, and freeways. That way people could live further out. You know, I mean, maybe, you know, maybe something like the hyperloop could extend suburbs like five times as far. So, you know, that could make it so someone could live quite further away. And that would be good, right? If you can increase the effective radius of a city, that's one way to alleviate constraints, political constraints, or concerns about people building things. So that way you can get more supply, bring the cost down. But, you know, I happen to have a more, I happen to think a different thing is probably the right solution. In 2019, it's a lot easier to move bits around than it is atoms.

So rather than people moving, inventing a new hyperloop or cars, I tend to think that the set of technologies around whether it's augmented reality or virtual reality or video presence that just let people be where they want to be physically and feel present with other people wherever they need to be to do their job, to connect with the people they care about. That feels to me like the better long-term solution. Don't make everyone move to cities. Make it so people, can choose where they want to be and can get access to all the opportunities they want everyone. So those are kind of, it's hard for me to imagine more important problems, at least over the next, pressing problems for the next decade. I think over the longer term, you know, potentially climate change is more of an existential issue. But in terms of people's lives today, I think the exploding costs from these areas is such a profound issue. And the trend is so an adequate world. Well, just three quick points on that.

One is, I think these questions are often a little bit, like the cost of these question, I think one of the reasons it's kind of difficult to study is because you sort of have to take this very macroscopic and potentially this very microscopic view. And so, say, for example, in science, if it were the case that the administrative burden on scientists had increased by, say, two-thirds over the last 40 years, not saying it has and not saying that even if it has, that that is, in fact, the cause of any kind of slowdown. But if it had, that might be quite difficult to observe because it could come in the form of, well, it takes twice as long on average for things to be approved and the forms are kind of longer and you're interrupted more. And so actually specifically diagnosing the kind of causal pathways, I think can really be quite tricky.

And I think that generalizes the latter of the fields. Secondly, to your point about sort of technology potentially solving the adlamoration kind of imperative of cities, I think that could be true, although here we are. person, you know, is... Others are watching. Yeah, but the people are watching wherever else. Fair. In the past that. Very fair.

But, you know, even if technology solves that, I guess my worry would be that the sort of the socio-institutional dynamics that have kind of ruined cities or made them less effective or whatever, probably also generalize and apply to other domains. And so we're going to suffer the costs of those same phenomena elsewhere. Oh, yeah. Yeah. And what do you want to ask, Mark? Hmm.

Well, I guess what have you learned from doing CCI in that, I mean, you launched it five years ago? Four years ago. Okay. Yeah. How will the next four years be different to the first four? Well, so one of the things that we struggle with here is these are such long-term projects, right? So we talked a lot about the scientific research. We're also doing a bunch of work with education to build tools for teachers to do more project-based learning,

personalized learning for kids, but basically make it so that teachers have tools to do the work that they want to do, mentor students, and not just have to have to lecture and have everyone learn at the same pace. So this stuff, we're making progress in all of these areas. And I think one of the meta questions in running the CCI is at what point to check in and consider evolving the direction. I mean, obviously there's minor execution things that you try to improve along the way. But I want to make sure that we have an awareness that these are fundamentally problems that we're going to be working on for 10 or 20 years. I think a lot of these things just kind of a consistency of approach and in building trust is kind of more important than

constantly evaluating or potentially thrashing. In science, we've had the benefit of taking on a number of different projects. So the human cell Atlas was one of the original ones. Now, one of the next areas that we're really excited to work on is imaging. There's a lot of advances in microscopy, but there are a lot of things that we still can't see. And as engineers, I think one of the things that you can probably appreciate is, you know, just when you're trying to debug a system, you really want to like get into the code and see, step through it and see where the thing is breaking down. But, you know, we don't really have a way today to see a white blood cell eat a virus, right? It's like to see, like in vivo, right, like in the body, to see proteins folding

live. And I think that, you know, there's certain optical levels, optical thresholds on the physics that you might not be able to get beyond. But between that and the advances in AI, I do think that it's possible to give scientists new imaging capacity that hasn't been possible before. So a lot of what we're trying to do is, all right, so the human cell Atlas, we took an approach. It was kind of very broad and collaborative and somewhat chaotic even in a way. And I think we're able to learn some of the lessons from that as we're now thinking about how we organize the imaging project about, okay, maybe it would be helpful to have more clearly established leadership around it up front. You know, maybe there are things that, you know, that rather

than having just one big project, there are going to be areas where we can just build tools that go into every lab. There's one software package called Napari that a lot of scientists, it's like, like right now there's, the actual technology of microscopes is kind of ahead of scientists' ability to process the data. So there's this weird mismatch because that kind of makes sense. If you're, you know, the NIH funding supports people to basically have a lab. Yeah, tool building is not really, you know, subsidized or supported that well.

Yeah, but I mean, if you want to have a team of ongoing software engineers, that's like, okay, you're going to want an effort that's going on for a while. That's more than a couple of people. So that kind of thing, I think, there's a real niche that no one is doing that stuff at the scale that it needs to get done. So just pushing on both of the... Yeah, and then there's uniform agreement on that particular point from almost every biomedical scientist that I speak. with, like tool buildings under-supported. Yeah, so, so I don't know. From a meta point, I'm a little wary of concluding whether that things have like, which

things have worked and not worked well yet. I mean, certainly not everything we're going to do is going to work. I mean, that's like... It's four years. It's too ready to say. Yeah, but like, but it's certainly interesting. And I mean, what I try to push the teams to do is make sure that the work that we're doing are things that clearly would not have happened otherwise.

Right. I think, especially in a lot of these fields, and in philanthropy, I think that there are a lot of potential issues with this where it's easy to give money to something and feel like you're doing good because you probably are doing some good, but then lack the discipline to say, okay, am I doing the most good that I can, right? And I think we kind of have a responsibility to do that. So that's the thing that I push our team to do is develop really different theories. I'm quite confident that in education, the work that we're doing is just stuff that if we weren't trying it, it's not clear that like anyone else would be doing an effort like this at scale. I feel really good about that.

I think in imaging, something like that is going to be similar. Even in social advocacy, we're doing a lot of work in criminal justice reform. That's a combination of advocacy and building tools for accountability and working with reform-minded prosecutors that they can be. more data-driven about who they try to bring charges against because, I mean, they want to be fair, you know, or at least a lot of folks want to be fair, and they don't have the data to either optimize how they run their office or to hold the people in their accountable. So building those kind of tools can be super helpful. And I'm quite confident that if we weren't pushing on that, I'm not, and I feel good that that's like a good theory to at least

try to push on. So that's what we try to do in the work. Say like the criminal justice work, education, biomedical, what's the underlying view or insight or experience of yours that's the common element behind those areas? Like how do we boil down

Mark Zuckerberg philanthropy to a smaller number of dimensions? Well, first of all, it's not just me. I do it with my wife. I'm sorry. She actually is an important element to this because she was a teacher.

Actually, she is a teacher. She's building a school. I mean, she spends a lot of time over there. She is a doctor. So if you're looking at the education, and health aspects, the domain expertise is more hers than mine. And she is quite, I think, compelling and insightful on some of the things that need to get done there.

In terms of the approach, that may be more inspired by me in some ways where it's the very long-term focus, which I think it comes from a lot of the lessons I've learned from Facebook. It's the tool building, which comes from having the experience. building engineering teams. And it's some of what we've learned just in kind of managing and partnering with folks through building the company is that it's a lot of what you said. It's like you want to bet on the best individuals in different spaces and give them room to run. In managing complex projects, you need to know when something needs to be a little more directive versus when you want it to just be an open thing that can make progress in a more chaotic way. And that might be more

art than science, or at least until your field gets, fully solves all these questions. But it's a, but yeah, it's, I don't know, it's an interesting set of questions. And, you know, certainly the, you know, I guess one animating theme certainly is, you know, as our kids grow up, we want to make sure that they live better lives. So it's, so these aren't things that are primarily going to benefit us. If you're trying to benefit us, we wouldn't be working on education. I think The health work is very long-term oriented. If we were focused on kind of our own health, you'd probably be doing more disease-specific work

rather than fundamental science to try to, or tool-building for fundamental science, which might even be a level more abstract than fundamental science to try to compound the rate of progress in science. And then a lot of work on equality in making sure, you know, the criminal justice work, I think, is, I mean, a lot of, you know, the way that our country-hand the stuff is just such an unfortunate outlier compared to other countries and the amount of

human capital that is locked away is, you know, is its own thing that I think deserves, I mean, a lot more than studying. But I mean, certainly I think just improving that would be a big advance. But I don't know, it's interesting. I mean, this conversation is interesting because it's, I think it highlights somewhat of a distinction in, I guess my approach to learning or studying these things is more the try different things and experiment and kind of, and then play it forward, generate new data that doesn't exist and see how that goes. And, you know, talking to you and seeing the work that you do, and I guess this is probably intrinsic to being an academic too, where more of the work is about, you know, looking at

at data sets that can exist and studying what is already there rather than trying to kind of create the new data sets or approaches. It's, I mean, there are two approaches that I think complement each other, but are actually quite different in terms of how you kind of approach learning about how to do the best work going forward. Well, I think there is a very important to emphasize sort of complementarity where, you know, for any of these kind of really important questions about sort of, you know, how should science be organized or which kinds of policies generate the most economic growth or how one should

support the diffusion of innovation or whatever. I don't think there exists kind of definitive data on that question. I don't think by sort of just going deep in the literature you're going to come up with clear answers that one can feel confident in going and executing or implementing. I think of the data such as it exists and the existing findings as kind of food for hypothesis generation. and, for example, you know, to kind of return to the management training one, like, I would probably not have guessed the effect sizes would be that large, right? And so if those studies hadn't been conducted, I don't think, you know, I would have, you know, ascribe sort of particular, you know, sufficient expectation value to the effort of maybe, you know, Stripe going and doing something there. But now because of those studies, I think, well, perhaps there are on the margins. things we could do. Maybe there are things that end up being quite materially valuable over time. I think being able to sort of marshal those, you know, potentially being able to sort of encourage people to dig more sort of in sort of particular directions and then to, you know, combine that with a willingness

to experiment and a willingness to, you know, frankly just be wrong. I think kind of the synthesis of that is really powerful. And again, if you go back and you look at the, um, the, um, the foundations that I think have really had significant impact over the past 100, 200 years, I think it's that kind of combination in that, you know, if you look at Warren Weaver, who is the guy who is at Rockefeller, who funded Norman Borlaug, right, he'd worked with Vannevar Bush at OSRD during World War II. He, I think he'd, he was familiar with a lot of the data and just kind of empirical realities of, you know, how different kinds of scientific and, you know, technological ventures were likely to work. But he was also willing to just place a bold bet and that, you know, pursue the hypothesis that agronomy could be radically improved.

But, you know, there was no particularly strong basis, you know, ex ante to really have conviction in that. And so I think it's all in the combination. Yeah, interesting. So, I mean, I'm curious to push further on one question that was, I mean, you asked me what I would want people to be studying. why don't you think people are studying the cost questions as much as it seems like they should be? Or it seems like if these are as big of questions for society and it certainly seems like there are issues that most people have, what are the structural barriers that are preventing the top people in these fields from deciding to go study it? Is it that the fields don't line up with it?

Is that there's not funding for it? Is it too hard in certain ways? Like, what are the dynamics that are going on here? There are many big questions. It's hard to study them. So at the end, you have quite a speculative answer or set of hypotheses. So the world as a whole isn't sure what to make of that. Is it a real contribution?

So the private return to you as a researcher, maybe is unclear. So you tend to get very famous people who are quite well established, looking at really big ideas, maybe a bit later in their career. And I'm not saying that's bad work, but it's not necessarily cutting edge either. And they've spent their whole lives being famous, and they're not necessarily in a position to actually make the breakthrough. And then younger people, their incentive is to first get established and do something that is quite defensible. So I think in general, big questions are understudied. The tenure system, I think, increasingly is broken.

A lot of academics do work pretty hard, but that so much of your audience is a narrowly defined set of peers who write, you reference in tenure letters. I think we need to change. And the incentive for academics to integrate with practitioners and learn from them and actually try doing things, we need more of that. I've often suggested for graduate school instead of taking a class, everyone should be sent to a not-so-high-income village for two weeks. They can do whatever they want. Just go for two weeks, think about things. No one wants to do this. No one wants to experiment with it. People who do development often do it on their own, but the notion that every economist should have studied the East Asian economic miracle, the industrial revolution, and spent two weeks or more in a poor village, it's just not how

things are, and I'd like to change that. So how does one go about changing that? So if you're trying to create a network of people who feel like they have an incentive to study this, because it's going to be good for their career, right? And it's not, and they're going to, they have a network of supportive people who might be reviewing the grants or the work that they're doing and also think that this is important work to be done. How do you go about establishing that? I can selfishly cite that at George Mason, virtually all of our students have very directly studied these questions, and we funded a lot of them to go live other distant, strange, possibly poor places. Other departments may have more money than we do. It can be done because

we've done it at George Mason. So I think, again, it's a question of the will. And just the ability and desire to imagine that things could be quite different in a sense that I think was more common in the America, say, of 1958 or JFK's decision to put a man on the moon than you see actually in 2019. All right. Is that a good place to wrap? Fine by me. All right. Well, thank you guys. This has been a great conversation.

Thank you. Thank you, Mark. Patrick. All right. Thanks for listening to Conversations with Tyler. You can subscribe to the podcast in iTunes, Stitcher, or your favorite podcast. app. And if you like this podcast, please consider rating it on iTunes and leaving a review. This helps other people find the show.