The Pomp Podcast - 296: Robin Hanson On The Argument For Variolation

Episode Date: May 17, 2020

Robin Hanson is an associate professor of economics at George Mason University and a research associate at the Future of Humanity Institute of Oxford University. In this conversation, we discuss the current COVID-19 response, why variolation is a viable option to develop a solution, what futarchy is, why the stock market is a prediction market, and whether aliens are real or not. ===============================  Blockset by BRD is your hosted blockchain infrastructure. Blockset enables enterprises and developers around the globe to deliver high-quality blockchain-based applications in a fraction of the time, at a fraction of the cost. Using the services provided by Blockset, businesses can build professional custody solutions, accurate and near real-time portfolio management solutions, auditing platforms, commercial block explorers, and much more: blockset.com =============================== Crypto.com is the only all-in-one platform that allows you to BUY / SELL / STORE / EARN / LOAN / INVEST crypto all from one place. Join over 1 million users currently using the Crypto.com app. Download and earn $50 USD using my code ‘pomp2020’, or use the link http://platinum.crypto.com/r/pomp2020 when you sign up for one of their metal cards today.  ===============================  Pomp writes a daily letter to over 50,000 investors about business, technology, and finance. He breaks down complex topics into easy to understand language, while sharing opinions on various aspects of each industry. You can subscribe at www.pompletter.com

This is Anthony Pompliano. Most of you know me as Pomp. You're listening to the Pomp Podcast, simply the best podcast out there. Let's kick this thing off. Robin Hanson is an Associate Professor of Economics at George Mason University and a Research Associate at the Future of Humanity Institute of Oxford University. In this conversation, we discuss the current COVID-19 response, why variolation is a viable option to develop a solution, what futarshi is why the stock market is a prediction market and whether aliens are real or not i really enjoyed this conversation with robin and i hope you do as well before we get

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store, earn, loan, and invest crypto all from one place. They've got over a million users currently using the crypto.com app. You can download and earn 50 US dollars using my code POMP2020 or use the link in the description when you sign up for one of their metal cards today. Crypto.com's not only got a cool URL, they also got a whole bunch of new products coming online all the time. Go check them out at crypto.com. Lastly, don't forget that I write a daily letter to over 50,000 investors about business technology and finance. I break down complex topics into easy to understand language while sharing opinions on various aspects of each industry. You can subscribe at pompletter.com, pompletter.com, or go click the link in the description. All right, let's get

into this episode with Robin. I hope you guys enjoyed this one. Anthony Pompliano is a partner at Morgan Creek Digital. All opinions expressed by Pomp or his guests on this podcast are solely their opinions and do not reflect the opinions of Morton Creek Digital or Morton Creek Capital Management. You should not treat any opinion expressed by Pomp as a specific inducement to make a particular investment or follow a particular strategy, but only as an expression of his opinion. This podcast is for informational purposes only. All right, guys. Bang, bang. Super excited to have Robin here. We got a whole bunch of stuff to get through, so thanks for doing this. great to see you absolutely and i don't have a cap on so the only reason i have one on is because

i haven't gotten a a haircut in a while well i haven't either i maybe i should i should put the cap on thing i'll get a haircut next week i'm scheduled finally to get another one so perfect let's um let's start with just your background so those that don't know you you've done a ton of different things um maybe kind of give us because i'm old i'm old let's make sure they know that too. I like to say it's not old, it's experienced, right? Well, it's both. Old comes with a bunch of things, including experience and wisdom, but some other negatives too, sure. So I started out long, long ago as an undergraduate in engineering. And then I thought where I was, it was two cookbooks, so I switched to physics. And then I got a physics undergrad,

but then I decided to go off and do philosophy of science for grad school. But then after two years I decided, oh, I'd learned what I needed to know about philosophy of science. The deep questions I answered enough. And I switched back to physics to get a master's in physics and a master's philosophy of science. Then I read some stuff about cool stuff happening in Silicon Valley about artificial intelligence and hypertext publishing, they called it, the web. That was before there was a web. And so I went out to Silicon Valley. I worked at Lockheed because it's the first job I could find for a couple of years. And then I switched to NASA. And so for nine years I did computer research in Silicon Valley and then I've been doing

on the institution design as a hobby on the side I finally decided to try to make a career out of that so I went to Caltech where initially I plan to do experiments because we've businesses respect experiments but then I learned that you really can't do experiments there unless you have a theory they don't just test institutions they test a theory of an institution so I learned to do more theory I learned lots of things that I didn't realize social scientists because physicists don't believe social scientists know anything, and even computer scientists, I guess, don't believe that so much. And I spent, you

know, four years getting a PhD at Caltech in social science. I did a two-year health policy postdoc at UC Berkeley, and then I got my job here in 1999 where I've been, you know, for 21 years here, and along the way, I, on the side, did some things in The Great Filter, sort of, you know, aliens and extraterrestrial life, and dabbled in a, I have a book called The Elephant in the Brain with a co-author that's classified as psychology. I have a book, The Age of M, that's seen as futurism, and so I've really done a wide range of things, more so than academic academic rewards academia mostly rewards you for being very the best person in the world in a very narrow specialty and I didn't do

that and I got away with it luckily and the thing I'm most known for is prediction markets betting markets on things but I'm known for a lot of things so one of my questions is like you went down so many different paths right and you've got a greater level of expertise or experience on those different paths than most but you kept seeking out other paths to go down or other disciplines and so what was really the driving force behind building that expertise and experience across so many disciplines well I have excuses and I have perhaps real reasons so if I stand away from myself and don't look inside myself and

just say you know why might your person do that I observed that most intellectuals when they fail they fail for failing to sufficiently focus these most ordinary people when they indulge themselves in intellectual things they spread themselves out broadly and even people who are trying to get PhDs they still are tempted to spread themselves out pretty broad because it's just really interesting and so you know they people like to be broad intellectually and they have to learn to be narrow if they want to succeed. So that's the most obvious plausible explanation for me,

is that I'm like everybody else and I didn't do what was good for me and I sort of skirted by. Now, I can justify it in the sense of giving some benefits from it. So certainly one thing I did was to keep asking myself, how important is this thing I'm working on and can I see something else more important?

and to keep switching when I thought something else was more interesting or important, you know, bigger. And most intellectuals, they sort of grab the first thing they seem to have some success at, and they don't ask that question, how important is this compared to other things? And so the work that intellectuals do varies enormously in its value because people are not sort of surveying widely and choosing the most important, interesting things. They are doing whatever they can grab. and the world itself isn't doing that survey it's basically opportunistically you know funding people who seem impressive uh i can also say that i think uh the strategy of looking for

combinations of things and and intersections that are interesting is a useful intellectual strategy that requires that you look at a lot of things so the only people who can really play that game are people who do look at a lot of things and interestingly it has a scale economy of the more things you know the more intersections you can find and so compared to some other strategies it peaks later in life yeah strategy of looking for lots of things and intersecting them i'm still think i'm rising on that trajectory even though my many of my abilities have declined my overall productivity at finding interesting intersections is still going up yeah and i forget the name of the book, I think it might have been range where it basically talks about this idea of like being

a generalist is actually an advantage rather than early in life, getting a very specific focus and becoming a deep expert on one thing, having that kind of more rounded type approach can serve as a significant advantage later in life. That is a good book. And, you know, it's, it's giving a middle ground. It's saying people often over-specialize that they believe they should so humans are relatively general creatures you know compared to most other animals like us we took this generalist niche and it's worked very well for us uh it works better when the environments are changing more so in some sense generalists should work better and more in the modern world than in ancient worlds that were more stable the slower things are changing then the more

by specializing you could win by you know picking something out but um and that's a big issue in our world today a lot of things change a lot but I think actually many of our institutions are not flexible enough because they have got stuck in a stable world I think we're seeing that in the pandemic response and in many other ways the longer your world is stable then the more your institutions and habits are tempted to sort of assume the recent pattern and specialize for that recent pattern and then when you have a shock and a change it's much harder to adapt So, for example, in the pandemic, the nations that have been changing the most recently and that have dealt with problems like this more recently have just done a lot better because they're more flexible.

So you've been all over the virus, right, in terms of very early on calling, hey, this is going to be bigger than we think. This is going to get out of China. You know, a bunch of things that now we know as fact. But at the time, you were early to see that. maybe just give us at a 10,000 foot view, like what has transpired since the end of last year to today with the virus, both good and bad and kind of not only the events that have occurred, but also the responses from various governments. Well, so it showed up initially in China. Initially, Chinese repressed the news and let it get farther than it should have,

but then they switched around and did a strong heroic suppression and managed to keep it suppressed not only in Wuhan where it stopped, but prevented it from spreading to the rest of China substantially. A heroic and strong and expensive effort. And the rest of the world didn't sufficiently keep it from leaving China, unfortunately. And so the ideal thing would have have been if the rest of the world had just locked down, you know, traveling from China and, you know, testing and things like that, then it would have stopped then. And a great many other pandemics have been stopped at that very early stage, and that's overwhelmingly the most cost-effective point at which you want to deal with it, is just to make it stop at the beginning. But

many governments failed to stop it from spreading to the other places. Now, some of the initial places that failed and then you know like South Korea for example they had an you know the initial problem outside of China but then they did a heroic strong effort and managed to suppress it there and some other places in the area did you know pretty strong efforts of grabbing it initially and stopping it like Hong Kong Taiwan but it's a big world and a key thing to know about a pandemic is when you have any sort of growth process, when you average a bunch of different growth processes, the total really is dominated by the fastest growth process of the set. So that it doesn't that much matter what the median place does. It matters what the worst

place does. And when you add up the total, the worst place dominates. At least unless you can sort of isolate them from each other and you know mean that when one hits the maximum the other places don't get affected so but so it's a big world that spread around the world and some places did better than others but of course the basic problem is wherever it does worse that makes a lot of cases those people go elsewhere and that spreads and so that's what we've seen so far is that even though many places have done very well the worst places have dominated and And now the U.S. is kind of one of the worst places.

We're the guilty party. And not overall in the U.S., say New York and a few places, they dominated the total effect. Because, again, it's not about the middle place and how well it does. It's about the worst place and how badly it does. And so, you know, initially, public health officials, when they saw it, it escaped China. They said to themselves, reasonably, I guess that's it. This is going to go most everywhere. And that's what I said.

I said, shit. I even said it, I thought, as it seemed to be escaping from Wuhan. So I guess I was a little early. I said, look, it's going outside of Wuhan. That's it. And the rest of China did manage, surprising to me, to keep it down. But then it went to the rest of the world. And so public health people said, that's it.

I guess we'll have to deal with this going most everywhere. Public health people have a lot of experience with diseases and basically nothing has ever spread that far and then been contained. And so they were perfectly reasonable to expect that that would happen here. But when they've said things like we need to flatten the curve, spread it out so that there's not too much impact at any one moment for the medical system and the rest of our systems, then the elites in the world said, no, they said, no,

no, no, this has to be contained. So they had suddenly woken up and decided that even though initially they screwed up. And so in the United States, the health officials really badly screwed up CDC in terms of preventing testing, preventing masks, a whole bunch of things that you can read about how badly we screwed up for a month there. But then once everybody was, once the elites in the world were concerned about this and talked about the concern, everybody said, no, no, no, we have, we can't give up on this, we must contain. And so ever since then, you know, that was, you know, three months ago, the elites in the world said, we must contain, and they started writing white papers and doing analysis and saying, well, look, some places have

contained, you know, South Korea, Taiwan, Hong Kong, and many places have contained. And here, we're not doing a good job, but we ought to be able to do a better job because how could they be better than us? And they listed out, well, we need a lot more testing and we need a lot more ways to do tests. We need a lot more tracing and maybe apps and different, we need to hire more people and we need more rules about isolation and we need more masks. And, you know, people went wild talking about all the things they thought we should do and all the different big things. If we did them, then that should be enough because, hey, there's other places that are succeeding. But the fact is, we haven't actually gone very far in those directions.

For whatever reasons, we haven't. Now, you know, one way to think about this is to say, look, policy is complicated. And it's less about each little piece than having good packages. So different countries in the world just have whole different governance systems and whole different strategies and all different resources. And I would think if you saw some places are working and other places aren't, and you wanted to win, your best strategy would be to pick the package that works somewhere and just slavishly copy that whole package. I mean, that is how innovation tends to work in the world. If you think, you know, some company like GM is successful and you don't know what about them is successful, you just try to copy the whole cultural package, all the little

pieces, and you think you're going to try to be like them. Unfortunately, that's not what people did they didn't say let's copy south korea or let's copy taiwan they said we here in our different place we're going to do our our package that makes sense to us and they all different different packages and now they're all in different places and even today when we see our package isn't working so well we aren't tempted to do a radical let's now go to south korea package or something even and then even that it might not be feasible anymore in the sense that

that we might be too past an early stage where certain things work at the early stage but don't work later. And so we still got all these people saying, if only you would follow my profit, we would all succeed. But they're not all behind something. So initially, back in, you know, every March, the elites all got behind this story. We're all going to lock down and we're all going to beat this thing. But they let everybody say, well, you choose your own lockdown. You choose your own style and your own everything. And now if they would all say, no, we need the South Korea package or whatever it is um and all get behind that and say and and here's the budget and we're going to spend a lot and you know we're just going to do it we would all probably go along with it

and that might work but we're not the elites are not like behind one common package they're spread across a dozen different like priorities and what things we should be focused on and there doesn't seeming much of a movement to change the overall policy. And after this initial peak, we're going down a bit, but of course, the problem is we're not going down very fast. So, I mean, the two key outcomes for a pandemic are it spreads and everybody gets it, everybody gets exposed, or it's contained and squashed down to a low enough level that then the traditional methods of test and trace can keep it down. That still can be expensive, but those are the options. But hanging out in the middle doesn't get you anywhere. And in fact, if you spend a lot to hang

out in the middle, you're doing worse than going in either direction. For sure. And so I guess that brings two questions, right? One is, do you think what South Korea, Taiwan, and other countries who have done, quote unquote, a good job, is it sustainable? Can they continue to do that? Or do they kind of expend all their resources and can't continue that's still an open question that is you know if the whole world contained it then we could all rest and have it be contained and then open our borders to each other and trade and travel because all the other places would also have contained it the problem is again when we have variety and it's dominated by the worst then even if most

places have contained it then if the place if places haven't and then it you know goes wild there and they get a lot of people affected then you have to close your borders to them and all the people that they were be open to until some strong treatment is so obviously many people are hoping for a strong treatment like a vaccine but that probably many years away and may never come and so you have to be prepared to do whatever you're doing for a long time So we're facing this prospect that, say, there'll be two kinds of nations in the world, the ones that have contained it and the ones that haven't, and they can't be opened up to

each other, right? And we'll have two groups of trading and traveling partners. And these ones who are locked down, they're the ones afraid of the other side. And the question is, how long can they maintain those borders especially say in the United States I mean between countries it's easier to imagine maintaining borders like Australia or New Zealand your islands far away you can manage those borders because we have traditionally managed national borders but within the United States say it's really hard to imagine California putting up the borders so those people from New York don't come etc I mean so then what can California do if

California manages to keep cases down, and New York doesn't, unless they can find a way to put up strong borders, then they're going to be vulnerable to the others. And that's the same as true through the rest of the world. I mean, we've shut down trade a lot, and we've shut down a lot of travel, but how long can we do that? We are really doing a lot of damage to society and the economy with the shutdown. Yeah, and I guess that then brings the question of, you know, we now know, to some degree, what's worked and what hasn't up until this point. There's definitely open questions about moving forward but if we had the benefit of 2020 kind of hindsight what should the U.S. have done differently to prevent getting in the situation that we're in? Well so

that's just you know standard thing obviously if we had taken it seriously early on we would have just shut down travel from the you know infected areas and of course built up resources including testing and not over-regulated these things, which is what hurt us right at the beginning. So, I mean, I think the consensus is pretty clear on what we did wrong and what we could have done with hindsight, but maybe it's not so helpful now. And then you've been a big proponent of kind of this plan B in the finance or Bitcoin world, that plan b is considered bitcoin but in the uh the pandemic world uh this plan b and i may pronounce this incorrectly but it's variolation variolation variolation so tell explain what that

is and kind of why um you've been talking about so we've been talking so far about these two scenarios one you you keep it locked down until you squash it enough that you can manage that or it goes to most everyone so it's been looking bad for a while about the first option the ability to keep a squash down at least certainly it's everywhere so what happens under plan b where it goes most everywhere the question is how can we minimize the damage there what can we do sorry i'm just gonna some reason that thing in my throat you're fine we've got all day you can drink as much water as you need anyway so um if it goes most everywhere how can we minimize the damage so there's a number of considerations there the first standard

one is don't overload the medical system spread it out over time and that means some degree of lockdown but it's not nearly as much as if you're trying to squash and contain this thing but people do overestimate the value of medicine so that's a bit much what else can we do we could make sure that the young were the ones initially exposed more than the old, because they have much lower death rate from this. So we need to get some level of herd immunity, which might be, you know, some roughly half the population, but why not have it be the young half, the healthy half, rather than the old and sick half, and that that's also capable of dramatically reducing the death rate. And then we could try to

make sure that people were deliberately infected, just so we could control when and where it happened. So most of the lockdown is to prevent a tiny fraction of us from infecting others, the tiny fraction who are at the moment infected. But since we don't know who's who, we're locking down everybody. If you deliberately infected some people at a controlled location and time, then you could isolate them there and use your isolation resources far more effectively. And it also allows you to spread out the medical resources over time. You can choose to, say, do it earlier than the peak or later than peak right so just the idea of deliberate infection if we're going to mostly all get an exposed has those

substantial advantages you know get the young and healthy and get you know the control of the isolation resource but in addition to these advantages there's apparently a prospect a very likely prospect that there are big advantages in how someone's infected so for most viruses we know there are a dose effect That is, the initial dose that you get of the virus matters a lot. So for example, if there's a droplet in the air, how many viruses are in that droplet? Or how many droplets do you breathe in the first few minutes where you're getting infected? If it's a tiny droplet with very few viruses, that's a low dose. You know, you

touch a door hot knob an hour after somebody else touched it, then that might also be a low dose. But if you get infected, say at home, by kissing your infected spouse, you're going to get a big dose. And we have a lot of data on other diseases that show low doses can have much lower morbidity and mortality, i.e. you get hurt a lot less. And in fact, before we had vaccines, we were using variolation in particular for smallpox. So, for example, in the United States during the Revolutionary War, U.S. troops in Canada were hit by smallpox and devastated, and that's why basically Canada is a separate country because those troops couldn't fight the war there. George Washington was worried about this,

and even though Continental Congress had outlawed variolation, intentional infection with low doses, he ordered it for the U.S. troops anyway, in secret so that the enemy wouldn't attack while they were sick, and basically this reduced the death rate from smallpox from 20 to 30 percent down to one to two percent and that allowed us to win the revolutionary war is the worry that if we did this there's too much uh societal pressure or like the headlines of uh hey the way to solve this is to actually uh intentionally infect people with low dosage and and we just can't as a society uh even if the science shows that it's effective we can't get there because there's so much fear and uncertainty in kind of the press or do you feel like it's actually viable that we

could do this? So there's a difference between we all deciding to do it together as a joint policy enforced and some of us deciding to do it because we want to so we don't there are many problems with the pandemic that we need to do everything together there are collective problems but this isn't one of them. If we have a low dose way to get infected and we allow some people to get infected that way, that helps. And we don't have to require them or even agree together that we should, we just have to allow it. And in fact, people are in a sense allowed to get infected, but the problem is the people who would supply the infection aren't allowed to supply it because of regulations of drugs and medical ethics experiments. So actually the current limitation

is that we would just need a hundred or so people to just do a small trial and we can't get medical ethics approval to do those small experiments because the people who run ethics experiments say this is unethical because in their calculation, the benefit to society of finding a way to lower our death rate by a factor of 10, it doesn't count. The only thing that counts is these people might by getting infected get sick and get hurt and that's just the rule but in that trial those people would be opting into this right this would not get to your point this but that's still not allowed so a medical ethics calculation say we're not allowed to let people volunteer now of course that's against our practice in the military and for firefighters and police there's lots of people

in our society who we allow to take risks for us and we pay them but the medical ethics interpretation is that's not to be allowed to people who take medical experiments. That's just their decision of what ethics is and they are not budging in this crisis. I mean, it sounds pretty ridiculous, right? I'm immediately thinking of, I saw a video online in a prison where prisoners were basically gathered in a circle and what was being described, and of course we don't know with 100% certainty, but what's being described in the video is that they were, one of them was positive for coronavirus, and they were actually trying to infect each other so that they could get out, right? Which sounds pretty ridiculous, but basically what you're talking about is a much

more medically driven or scientific driven version of that in a low dose manner. Right. So the key problem with people just getting infected in that way, first is they're not getting a low dose or trying to make sure that they're getting a low effect, but also they're not being isolated and preventing it from spreading. So what I recommend is something that I called a hero hotel. You go there, you pay to go there, and then they immediately infect you and keep you there until you're recovered. And so you're not inflaming the whole pandemic.

You are just getting this treatment and getting past it. Now, you know, people may well want to do that for many reasons. So not just wanting to help society to get us all past this, but they themselves could get back to work afterwards and get back to socializing and get back to their lives. And, you know, many people are really quite frustrated at being locked down. So I've heard many people say informally that they sure wish they could find a way to just get past this and they'd be willing to take some risks. But what we'd like to do is to have them have a much lower risk by doing it deliberately. And all we need is some

small trials. And see, unfortunately, the problem is, if people can sit in a circle with an affected person and try to get them, that's legally allowed. But we are not legally allowing doctors, say, to do something like this, because the treatment hasn't been medically approved. And as a company, you couldn't sell people something that let them be affected with a low dose, because that hasn't been approved by regulators. And so we're in this sad situation where you'd legally be allowed to do the worst thing, but not the better things because, you know, we're holding basically these companies and professionals to much higher standards than we hold individuals. Yeah. And this, I think, goes to some of the opening the economy conversation, right? Of like,

I've for a while now, I've been saying, look, if you're sick, old, or have pre-existing conditions, stay inside, open up the economy, allow people to go back on a optional basis, protect the people who aren't comfortable doing that, right? So don't let them get fired. Don't let them get kind of docked pay or anything like that. But ultimately use like influential leadership to get people to go back to work by opting in to doing that, understanding the risks that they're taking. Now you can understand how people who think we're going to contain this are terrified by that. They say, no, no, no, no. You're accepting the idea that this is going to go most everywhere. And of course, they may well notice that we don't very well isolate the old. So, you know,

with a strategy like that there's this key choice how much to isolate the old I mean if you're an old person living with the young do we make you move out move somewhere else with only old people those are completely reasonable questions but nevertheless I think the key point is that that even saying that suggests to them that you have given up on the the strategy of containing this which they are very emotionally committed committed to so I like this analogy of the monkey trap. So there are places in the world where people try to catch monkeys and probably eat them. And to catch a monkey, one way to do it is you take a gourd, which is an empty shelf of a vegetable, and you put a nut inside it, which is the thing monkeys really like, and it rattles around

and the monkey sees that there's a nut in there. And the monkey puts the hand in the gourd, puts the hand around the nut, and tries to pull the hand back out, but now can't get it out the neck because their hand is bigger with the nut and apparently they won't let go of this nut and you can catch them and eat them now so that's this metaphor for things that are so attractive that by trying to grab onto it and not letting go you can suffer a lot more damage than you would if you just let go of the nut and say i'm not going to get it and so i fear that's what's happening and going to happen here with containing covid you know this hope of containing it is so attractive and so emotionally compelling and you feel moral right about that and those people who

are doing it seem like evil capitalists who only care about money or whatever that people will not let go and of course that's going to cost the most in the places where we aren't doing very well at containing it but are doing well enough still to give you hope yeah it's super interesting um how does this affect institutions like you you spend a bunch of time thinking about institutions in our society uh how does the virus um you know my inclination this entire time has been the virus kind of exposed a lot of shams in society but how do you see institutions uh one weathering this storm and then two coming out of it on the other end well so institutions are really pretty stable most of the time and it requires either a big crisis and where people lose faith or some big

opportunity and an entrepreneur like pushes for that opportunity in order to change institutions right so I mean our taxi institutions weren't in a crisis but uber still decided to do a revolution and that was more opportunistic but other times like World War one or two after a big crisis we say what did we do wrong and we try to reform some institutions so this crisis will certainly be available as a resource for people who are going to advocate for changes. But of course, they're not going to just universally look for the best institutional changes. They will advocate for whatever changes they already wanted

and look for some sort of a story to make that connection. So that's what you should watch out for is people trying. So that typically always has an acrypsis. People fight enormously over the story of what went wrong and therefore the story of who should be rewarded and what changes should be made for the better. Those stories aren't always correct. You can look at a lot of historical big changes that were made and the stories that were told at the time, and you go back and you find out those stories were pretty distorted picture of what was going on. But they were a compelling enough story that got a lot of people to back a change. So, you know, we should watch out for people telling sloppy stories about what went wrong

here and therefore what what fixes should be granted right like I mean some people even say well if we had single-payer health care then all these people out there losing their jobs to still have health care that's why we need some single-payer health care code which shows you know that's kind of a weak connection right but people will be eager for these stories and and really brings us to what I think is one of the biggest problems here is those stories are being based on data that are questionable at best right so you know I continue to ask people how what percentage of the American population is

infected we don't really know right we've got guesses we've got estimations but we don't know even the death rate there's people who are arguing it's under accounting there's people who are arguing it's over accounting right and So how do we make good decisions with maybe inaccurate data or questionable data? And then at the institution level, when you layer in all of the agendas that these institutions have,

how do you kind of think through that decision making process? Well, so those of us who specialize in designing institutions try to come up with institutional variations that are robust to these details. If you need to know these level of details, this fast and this precisely, you're kind of lost

and needing to do institutional changes because you rarely know that much, that detail. You're looking for robustness in your institutions. And that's exactly what we should be doing here. We should be not trying to make these institutional choices depend so much on these details, we want to say. So for example, early on the CDC really screwed up the tests. You might say, well, what's the robust solution to that?

The robust solution is to not have them so much control over the tests, to let a lot of different people do different tests and, you know, some of them go wrong, fine, but that's, you know, a robust solution relative to saying, well, who should run the CDC next time to make sure, and what methods should they use and what procedures should they have

in order to decide this better? Well, that's not a robust solution. That's saying, that's trying to make a choice that depends on a lot of parameters. Who should be put in charge? Well, that depends on a lot of different things about who they are and what the problem is, right? I don't wanna solve our problems in the world

by agreeing on who we should put on charge, right? Well, for example, a lot of people want to blame this all on Trump. And there's no doubt Trump has a lot of things to blame for. But if you're going to solve the problems we've had with COVID by replacing Trump, I think you're missing the larger, more institutional problems. You know, replacing any one person just can't do that much of the fixing. Yeah, it's super interesting. One of the other ideas that you've had that you've gotten a lot of notoriety for is you work on prediction markets.

And I think you've actually said that prediction markets is, out of all of the ideas that you've brought kind of forward, is your best or your favorite. Maybe talk just a little bit about the work that you've done there, and then we can talk through various aspects of prediction markets kind of in practice. Sure. So the key idea here is that when we make bad choices, it's mostly because we don't know they're bad choices. or more fundamentally, we don't all together know they're bad choices. So sometimes we make a choice that of us making these bad choices. So the fundamental policy problem is how can we collect the information we all have about the consequences of our choices so that we can all pull it together

into a form. that we can share and use and if you look at the various kinds of institutions we've ever used in the world to collect information and share it together into a consistent form that we can use together the institution that seems to consistently work the best is speculative markets betting markets stock markets currency markets commodity markets these markets have consistently given people the incentive to find things out, bring the information they have to bear to this center, which is the market, include their information in the current market price, and then allow that current market price to be information spread everywhere that tells us all

what we all know. So we've had many tests where we have had a betting market or speculative market price compared at the same time to other institutions that we often use, like committees or expert surveys or all sorts of other mechanisms. And basically, we have many dozens of these comparisons. And consistently, what we find is that either they're both about the same in terms of the accuracy of their forecasts, or the betting market is substantially better, more accurate. That's the consistent data we have. Now, we have some good theoretical reasons for understanding why, but I don't want to make the pitch here to be based on that theory. It seems safer to make the pitch based on the empirics. Consistently, these betting market

prices beat. Now, you can understand in the sense that what they do is they offer a challenge to anybody. They say, look at my price. If you think this is wrong, come fix it, and you will make money. And that's not only true with respect to sort of base things you might know about a factory burning down or something else. It's about the patterns, like do prices go up on Mondays too much do they go down when it rains too much etc and any pattern you can find where you can see a mistake in the market you can make money by betting on that pattern and making it go away and that's the powerful incentive that speculative markets offer and in general we've had speculative markets just on the random topics that have arisen like the price of gold or ibm but we can make a

spending market on purpose on a topic you care about, say even COVID infections, and then get the information on the question you care about. So, for example, if you have a project with a deadline, you want to know, will I make the deadline? Typically, if you ask people on the project, will we make the deadline, what you get back is a politically correct response of whatever the leader wants you to think, which is typically, yes, we'll make the deadline. And if you say something else, you might get punished for, you know, by the person running it for violating their dogma, but if you have betting markets where people can bet

anonymously, then you tend to get the accurate forecast. So we consistently see that people get accurate forecasts and more accurate forecasts when we have betting markets on things, and there's an enormous potential for this to be applied across society and institutions, especially through what I call conditional betting markets or decision markets, and I've given the name future key to sort of governance that way. And the key idea is that you can bet on the outcome of a decision conditional on which decision is made and betting markets on that can basically tell you which decision to make. So my favorite example is firing the CEO. So you have a company, you have a CEO, should you keep the CEO or should you fire them? Well usually a board makes that

decision but that's relatively political and it seems like we make a lot of mistakes there. so the idea is you have a stock market where people trade on stock and then you have a stock market where you let them trade on the stock conditional on whether or not we keep the CEO we have two prices the price of the stock if we keep the CEO the price of the stock if we don't and the difference of those prices tells us should we keep the CEO and that would be a straightforward way to give us advice on a key decision and we could do that everywhere and so the bottom line is we have a lot of data on prediction markets in many different

context, showing that they basically work. We have a lot of innovations of better ways to make them work better in new contexts. We have a lot of tests of those, but what we don't have is a lot of adoption. And the key problem is that they are very politically disruptive. So for example, if you think about this person with a deadline and wanting to know if he'll make the deadline, he can make a prediction marker on the project, and that will tell him whether he'll make the deadline but the person running the project cares more about having a good excuse if he fails than lowering the chance of failure and so typically a person with a project deadline their best excuse if they fail will be to say

well things were going along fine and then at the last minute something came out of left field no one could see him coming not just flat it's so rare and strange it'll never happen again so there's no need to hold anyone responsible here let's just continue on and the person running the project wants that to be the excuse, and their boss and even boss's boss wants that to be the excuse, because they all would look bad if they were in charge of a project that failed for, you know, a reason that could have been prevented. So if you make a prediction market on this project, you could even do conditional versions, which will tell you how to make the project more likely to make the

deadline. But the key problem is, if the market says you won't make the deadline, it'll tell you long in advance consistently, and then you can't have this excuse that at the last minute we were knocked by something out of left field. Everybody can say, look, the market told you you were going to fail. You didn't prevent the failure. You're at fault. And that's an example of how, in our world, political disruption of prediction markets tends to make people not want to adopt them. That is, most people running projects and running organizations care more about defending themselves from blame than they do about making the overall organization work well. Yeah, this reminds me a lot of the book, Super Forecasters. And so would it be fair to say that

you think the stock market is a prediction market as it exists in today's form, or does it not fit that definition? It does, but the thing it's predicting is not very easy to interpret. You know, it's like if aliens had a betting market and you could see the price in the betting market, but you didn't understand what the words were on the bets, then you wouldn't be able to make much use of it, right? So the stock market is a bet on the value of that company, but that's a complicated thing. And so it's hard to apply that insight and information to other things you care about. So the more that we can make betting and speculative markets more directly on the things we care about, including especially the decisions we make, the more useful we can make

them. And how does this get applied to government? Obviously, that is like the ultimate decision making machine that probably has the widest impact on a citizen's life. How do we incorporate the ideas of a prediction market into that bureaucratic process? Well, mechanically, it wouldn't be that hard to do. The harder problem is, do people want to? So what I recommend is that we start with small scale experiments and work our way up. So instead of trying initially to apply prediction markets to government. We apply them to small clubs, small companies, small organizations, and slowly show through a long, detailed track record that this works. And in each case, try to entice neighboring organizations and slightly bigger versions to

copy what it seems to have worked at a smaller scale. And then eventually we could get government. So as you may know, government isn't usually the initiator of a lot of innovations in society, but it tends to belatedly copy them when something works well enough elsewhere. And so that's probably the best route to produce innovation as government is to produce similar innovation in the private sector and then shame the government into copying. But in order to inspire people about what should be eventually possible, I do sometimes describe government applications to give you a sense of just how far this can go. So for example, the simplest thing

might be just there are many government projects with budgets that lie. That is there's an official budget but then later on they're going to come back and ask for some more money and they didn't admit ahead of time they wanted that extra money but they kind of knew. So you can have a betting market on the budget for a project that says well eventually how much will this cost and you can even have that conditional if we adopt this project how much will it cost eventually and now we can get a more honest budget on how much things will cost and of Of course, people who are pushing these projects

now don't want that to happen because they tend to want to convince us to adopt their project by believing it won't cost as much as it really will. Freeways cost more and all sorts of NASA projects cost more than they all initially announced. So that's just one simple example of how you can use it. But these conditional versions of the market

would let us make big key decisions. Like you might justify building a stadium by saying, oh look at all the revenue we'll have if we have a stadium but we might say well if we build the city how much revenue will we really have over these coming years and then that could be more discipline our choice of do we build the stadium we could even do this at the you know presidential election level we could have betting markets and say there's the two you know Republican and Democrat you know what are the outcomes you care about pandemic deaths war

deaths, GDP, stock market, whatever it is, even international respect, we can have betting markets in each of these things conditional on which candidate is elected. Actually today there are betting markets for which nominee should each party produce if they want to win the election. So there are betting markets on who will win the election and also on who will be nominated and you just have to divide those two numbers to get the probability of being elected if nominated. So those betting markets could be much thicker and much more accurate, and then they would give a much stronger message to each party of who to nominate. Of course, the parties are pretending that they

really want to win, but often the insiders care more about who's nominated than who wins, so they may not welcome such things. Yeah, it feels like there's this very direct conflict between what the math and the scientific approach of prediction markets would tell us works. And then the elite powerful people who have realized that if they can actually prevent the efficiency and things like prediction markets from taking hold,

there's an opportunity for arbitrage, which allows them to hold on to power and to hold on to decision-making. So this is, yes, but it's far worse than you say. This is true in almost all the organizations we've participated, from your homeowners association, to your firm, to your church, to schools,

and all the way up to states and nations. In all of these contexts, leaders present themselves and justify their actions in terms of information and analysis of the consequences of actions. So in all of these contexts, the perceptions of which actions have which consequences is always very political, and it's always manipulated in order to help powers that be win over their rivals. And that's just the nature of all the organizations we're part of. So say most CEOs even might present themselves or managers as a scientific analyst. They've got a spreadsheet and they're calculating the costs of this and the benefits

of that. And they're talking to people that get more numbers to put in their spreadsheet. And that's their job is to make the spreadsheet and figure out what to do. That's the presentation for most managers in terms of what their job is. And so that means they're committed to this idea that I want information. And so if you ask them, hey, do you want more information? They got to say yes, but they don't mean it. What they want is information they can massage and control to create the impression they want. And they are very attentive and careful to support information that will support their narrative and to resist information that won't. In all organizations, all people anywhere, if you don't do that, you don't last very long at these levels.

Basically, everybody has to be doing that. They all have to be giving lip service to information. But in fact, in most organizations, they don't try very hard to collect information, and they don't very much want objective information. They want information that they can control. So many organizations, for example, hire consultants to give them advice, but they don't just ask, hey, answer this question. They typically give them strong hints about what answers they want to hear so that they can use that as a supporting, you know, some argument they're trying to make. And that's just the nature of all our organizations. So it means that if we could force our organizations to pay more attention to objective sources of information, then, of course, they could make better decisions. And they all give lip service to that, but they all know that in their struggle with their rival, if they can just allow some out-of-control source of information, then they might well lose to the rival.

So if they have the upper hand on the sources of information, they very much want to control it. I mean, it's, you know, most dictators say want to control the news media and they want to control the schools as major sources of information in the population that could threaten them if they were in someone else's control. It's fascinating to me that you get this balance between science and math with power and control, right? And it just feels like, um, we take a approach where, uh, those in power benefit from most of the society, not understanding the power of a prediction market, not understanding kind of the math. Um, but again, this is far more general, like pretty much all societies in history, you know, powerful people have wanted to control and manage information processes, news processes,

credentialing processes authority processes if the religion is is a source of of authority that people rely on for information about what's good then they want to control religion all the way down the line science today also you know is that science wants to present itself as neutral and independent from all these authorities just telling you the truth and sometimes they do that but less often than they claim and so the key you know question is how can we create a neutral informative source of information. That's been a long, difficult problem, but prediction markets in some sense solve that problem. But if they don't solve the more meta problem, how can you make everybody want them or care? Once you know that you do have this independent objective source

of information, who will want it or allow it? Yeah. One of the things, so Laurent obviously was kind enough to uh to introduce us and uh and he said to me that you would have fantastic ideas around uh extraterrestrial life and alien and one of the questions that i asked is uh if they believe uh aliens exist or not so maybe let's start there just on how you think about uh any sort of intelligent life form uh outside of uh of earth okay so if you just go right to basics the universe is enormous and it's been around for a very long time and we're just on one tiny little quarter so if you just went to basics and said what's the plausibility there there might be life intelligent life even somewhere else you gotta get you gotta put it high i mean there's

just no way you can't say that's got to be hot but then you have to confront that initial plausibility with some data and then ask what do we conclude after we've considered some data so the one in your face biggest piece of data is the fact the universe looks empty and dead everywhere everywhere we've seen i mean there's a lot of activity out there but none of it looks organized intelligent purposeful it's just dead on vast enormous scales i mean there is vast energy wasted even quasars are sending out piles and piles of energy that just gets thrown away. And so that is the spectacular fact about the universe, which says that all these intelligent lives that might be out there, they haven't reached that level of impact. They haven't

reached the scale of doing big things that we would even notice from here. They may be out there and doing big things on their local scale, but they, and it's not allowed. And that's puzzling because there's been billions of years here it's not like there's been a time shortage they've had plenty of time i mean most likely there were aliens many billions of years before us right you know we it's now 13 billion years since the beginning 14 and so you know they were just 4 billion years ago and that's lots of time so what the hell why is it also dead and empty so we struggle to come up with some stories there but that's gotta constrain what whatever they are whatever they're doing apparently they have not reached this massive scale and and it's a core

you know you might think well they have this rule that they don't mess with things or they don't want to be they're hiding but it's really hard to enforce rules on really large scales right you're talking about like way out there say a whole galaxy that would be filled with aliens and they've got this rule that none of them get to ever leave the galaxy to go somewhere else and mess with things like how how could they enforce like a border on a galaxy and make sure nobody ever leaves i mean it's just mind-boggling the sort of coordination and control that would be required to prevent spread and becoming visible on black on cosmic scales so um but that doesn't mean they aren't there somewhere. And it doesn't mean they couldn't come here either. But now if

you think, okay, could they be here? Could they be around here? And you say, well, we have to confront again the data point that they're not obvious around here, right? They don't have shining cities in the sky floating over us, right? They haven't remade the rings of Saturn, whatever I mean they're not visible and we are right I mean we are pretty visible we aren't visible maybe for a thousand light years but we're visible around here so if they're around here they are surprisingly invisible that's also kind of puzzling I mean you know the things that might lead you to prevent you from becoming cosmically visible don't necessarily prevent you

from being locally visible if you're around. I mean, you could certainly have a little city, a little facility, some mines, some production, some whatever, right? Maybe you do fight a war every once in a while and you make a big splash where you slap each other. I mean, you know, these things would be visible. So the question is like, well, how do we understand that hypothesis? I mean, how much do we need to degrade the scenario by saying well that just can't happen then we have to start to think of what scenarios could there be possibly that would be consistent with not only they're not visible in the cosmic table they're also around here and not visible on the smaller scale

and then the third data point that you might try to take into account is to say well they're not entirely invisible locally because there's all these reports of people who say they see them and now you think well you know they've been around for billions of years they're not they've got to be enormously capable technologically because that's the only thing consistent with this age and distance they could have traveled and they could just I guess if they wanted to just completely hide and they could make themselves really visible but no they're right on this edge of visibility and apparently they're smart enough to know that's where they are and so on

purpose somehow they are just being kind of barely visible like what's with that Now, what possible purpose or plan or set of constraints could lead to this combination of these three facts? Again, they didn't give rise to vast visible stuff in the universe. They don't even give rise to much erratically visible around here, but they're giving rise to a small amount of barely visibility, like what the hell? I guess part of this is like, should we be more concerned of them finding us than them finding them who gets discovered or infiltrated they end up being the loser in the engagement

and so should we be worried about that well again the key thing we have to be very confident about aliens is that they are vastly more capable than us on pretty much any margin so if they weren't they wouldn't really be aliens. So you could imagine like, say there was a dinosaur civilization deep under the earth. I mean, it's a crazy scenario, right? But at least they would have shared a history with us, right? They would have come from a similar origin and have similar back and forth interaction. And then you expect a correlation in their capabilities and ours and their interests and ours and even the conflicts. But aliens sort of by definition, they don't share this recent origin and interaction. They just have a very distant origin. And so by definition,

They just came from far away from long ago. And that right there tells you their capabilities have to be vastly larger than ours. So if there's, you know, they're vastly more likely to learn about us than we, before we learn about them. There's just very little chance that could be otherwise. If there's any degree of them looking around and us looking around, they're going to see us before we see them. Full stop.

End of story. There's just, you know, in this contest, there is no contest. I mean, they are just vastly beyond us. the only advantage we could possibly have is this apparent advantage that they must think is not an advantage of being noisy and doing stuff and visibly active when they're apparently really hiding. It is wild to think through what is out there and kind of what that impact on us could be. Before we finish up, I always ask everybody, what's the most important book that you've ever read? well, that's tough. Because I think for most people, there are times when they read a book

and it's really insightful for them. But that was a coincidence about where they were and what they knew. And if somebody else had read a different book at a different time, you know, it would be less insightful. So for example, at one point, I read the book by Hugh Everett about the many worlds interpretation when I was sitting in a library in University of California, Irvine. And that was very influential for me because I had never seen a point of view like that, and that was very dramatic, and that really influenced me at the time. Later in my life, I remember reading Herbert Simon's Sciences of the Artificial, which explained a whole bunch of views, but of course, you could by now get those views from somewhere else. um 20 years ago geoffrey millers um the mating mind was influential for me i had a bunch of concepts about evolutionary psychology uh but of course you could also probably get those ideas

elsewhere depending on you know what you read uh so i i really i think what you read when uh depends a lot on what you already know so i recommend that say most people just read a lot of textbooks. If you're young and you want to learn a lot about the world, textbooks are our standard way to summarize a lot of things and put it all together. If there's not textbooks on your subject, find a review article that summarizes a bunch of things. And that'll depend on what you already know, of course. So obviously, you know, what books, I mean, the Bible, of course, is very influential for our culture. So I read the Bible when I was a kid, and no doubt that influenced me a lot. How could it not? Spending that much time involved in this one book over and

framing it. But I don't know if I can point to that many things now, but no doubt it's influential. So I guess I'm not that big a fan of the influential book question. Yeah, well, I couldn't agree with you more in terms of when you read a book is almost as important as what the book actually is. Like, I couldn't agree with that more. Your idea about reading textbooks is really interesting in that uh i think the more we go into this digital world the more people want uh kind of the information delivered digitally but we forget that the whole point of the textbook is to teach people about a subject right and that's going to be digital textbooks right but it's more about a systematic thing right pick a subject and let somebody walk

you through it systematically rather than just grabbing a blog post here and a tweet there and you know a news article there and just piling these things up randomly i definitely think people are way too into the news so the time to pay attention to the news is where it's affecting your life and maybe where your expertise is now at the moment where you can say something to the world but mostly you want to learn about stuff not because it's in the news at the moment you just want to learn about the fundamental important stuff in the world what what's going on what are the key

issues and at any one moment you could decide which subject you're interested in and maybe something will spark an interest but you know use even a news article as a question ask the question do i want to spend a month now diving into this subject and really learning a lot about it is this news article so intriguing that that's what i want to do that's that's a pretty high standard you can't do that for most news articles of course but maybe that's the best question to ask about a news article is this a hint that this subject is worth just diving way into yeah I think that's really really good advice where can we send people to to get in contact with you learn more about

your work find your books and everything else well I have webpages Hansen gmu.edu and I'm on Twitter at Robin Hansen blog overcoming bias and so you know you'll you'll get more than enough at those places? We could use many, many more people like you, because I think that there's a lot of bias. There's a lot of paying attention to the news right now. And frankly, I think the world would be a better place if we could get people to kind of go back to first principles thinking and sound decision-making. One last recommendation that people liked when I did the Sam Harris interview, which is to say, try not to have as many opinions. People feel this need to have an opinion on every

subject that comes up, people talk about, and most of those opinions aren't very well thought out, and so not helping very much. Pick your area of specialty, what you're going to really learn about and know well. Tell us your opinions in that area, and then I want to listen and defer to you when it's not my area. I want to defer to other people who specialize in most of the topics, and I want to pick a small set of topics, which are the ones that I think I've specialized in enough to be worth have in my own opinions. I think that is a very intelligent and prescient way to look at the world. So listen, Robin, I really appreciate you doing this. This is fantastic. I think people will learn a lot from this and hopefully we can drive some people to check out more of your work

because I think that we could just benefit from more people thinking like you and kind of consuming the content that you're putting out there. So from everyone else, just thank you. been fun chatting and enjoy the rest of your day. Absolutely. And thank you to Leron, obviously, for making the introduction as well. All right, guys, thanks for listening to that episode. I hope you enjoyed it just as much as I did. My goal is to educate as many people with these conversations as possible. So please go subscribe on your favorite podcast channel, leave a five-star rating and a review. These things really help the podcast get higher up on the popularity charts, which ultimately brings more people to learn. Also, don't forget you can

go to YouTube to watch each conversation in video format as well. Just search my name, Anthony Pompliano, on YouTube, and you'll find our channel with hundreds of awesome and informative videos. Thanks again for listening to this one, and I'll see you for the next one.