Speaker 1: Pushkin.
Speaker 2: Hey, it's Jacob. I recently was a guest co host
Speaker 2: on another Pushkin podcast shows called Cautionary Tales. The host
Speaker 2: is Tim Harford, and it was a lot of fun
Speaker 2: and I thought you might enjoy hearing it while What's
Speaker 2: Your Problem is on a break, so we'll be back
Speaker 2: with What's Your Problem in a few weeks. In the meantime,
Speaker 2: I hope you like this episode of Cautionary Tales.
Speaker 1: Let's play around Warders Studios. It sounds very elvin.
Speaker 3: I always think of David Bowie when I think of Wardog.
Speaker 3: In one of his early songs talks about bright light,
Speaker 3: soho wardour Street.
Speaker 1: Bowie himself has an elfin aspect.
Speaker 3: He said he does is breakthrough gig at Aylesbury, my hometown,
Speaker 3: which basically is about the only thing remarkable about Aylesbury
Speaker 3: is well and also.
Speaker 1: Home of Tim Harford. As the plaque.
Speaker 3: Says, yeah, they've got a statue for Bowie, not yet
Speaker 3: for me. I don't why shore we go Okay, let's go, okay,
Speaker 3: I'm ready. Hello and welcome back to another episode of
Speaker 3: Cautionary Questions, our first of twenty twenty four. I am,
Speaker 3: of course Tim Harford. You are our loyal listeners. You've
Speaker 3: been sending in your burning questions on money, technology, economics,
Speaker 3: and problem solving, and thank you so much to everyone
Speaker 3: who's done so. And today is the day I do
Speaker 3: my best to answer them. And thankfully I won't be
Speaker 3: alone in this endeavor. Here to help me out both
Speaker 3: of the questions and I think with some of the
Speaker 3: answers is the brilliant, brilliant Jacob Goldstein, the host of
Speaker 3: Pushkin podcast What's Your Problem, author of the book Money,
Speaker 3: The True Story of a Made Up Thing. Jacob was
Speaker 3: my inaugural Cautionary Questions co host. Jacob's wonderful to.
Speaker 1: Have you back, Tim. It's an honor. Hi.
Speaker 3: So we should just get home with the questions because
Speaker 3: we always have so many and so much to say. So,
Speaker 3: what have you got in real big bag of listener
Speaker 3: questions for me?
Speaker 1: Let's start with a question from Alex in Melbourne, Australia.
Speaker 1: Alex writes, I work with artificial intelligence image generation software
Speaker 1: almost daily now, and I'm quickly seeing how so much
Speaker 1: of my workforce and processes can either be sped up
Speaker 1: or entirely replaced by AI, and this makes me nervous.
Speaker 1: And then he asks about universal basic income, right, this
Speaker 1: idea of a government giving all its citizens' money, and
Speaker 1: he says it seems for the first time that computers
Speaker 1: and software will actually replace jobs in a deeply concerned way,
Speaker 1: which is both exciting and terrifying. What are your thoughts
Speaker 1: on UBI universal basic income as a solution to an
Speaker 1: AI crisis and the widespread philosophical and economic implications of this.
Speaker 3: I love this question. I mean, it's so big, and
Speaker 3: I think the first thing to say is we don't
Speaker 3: really have any idea. If what Alex is thinking about
Speaker 3: comes true, and if most people just have no economic value,
Speaker 3: they have value as human beings, have value as members
Speaker 3: of society, but there's nothing that they could actually sell
Speaker 3: their labor to do, then that's completely uncharted territory. We've
Speaker 3: never been anywhere like that before, so everything we do
Speaker 3: is kind of speculative.
Speaker 1: We've feared it for a long time, right, We've have
Speaker 1: two hundred years of being afraid of technological unemployment. And
Speaker 1: my prior on this is to be somewhat skeptical. Right, Like,
Speaker 1: clearly there can be some large number of people who
Speaker 1: lose their jobs. We should be concerned about that, and
Speaker 1: we should think about how to mitigate that. But the
Speaker 1: idea of more or less everybody losing their jobs I'm
Speaker 1: skeptical of for the simple reason that it hasn't happened
Speaker 1: in two hundred years of incredible technological progress. And right now,
Speaker 1: after decades of extreme technological progress, in the US, unemployment
Speaker 1: is below four percent, the share of working age people
Speaker 1: who are working is near all time highs, And so
Speaker 1: somehow we keep coming up with new things to do
Speaker 1: for money, no matter how many things computers can do.
Speaker 1: And so my first thought is, I don't think we're
Speaker 1: going to have everybody losing their jobs to AI. I
Speaker 1: definitely could be wrong, but that's what I think.
Speaker 3: No, I think that's a good working assumption. If you
Speaker 3: think back a few centuries, basically, almost all the labor
Speaker 3: that people did, they might wash their clothes occasionally, Well,
Speaker 3: that's been outsourced to the washing machines that spend a
Speaker 3: lot of time moving water around, just drinking water, cooking water,
Speaker 3: throwing out human excrement. That's all now handled by automated systems.
Speaker 1: Digging people did a lot of digging, right, pulling a plow.
Speaker 3: Almost everything we used to do is now done by machines,
Speaker 3: but somehow we still all have jobs. Let's at least
Speaker 3: accept the premise that maybe this time it might be
Speaker 3: different because the robots are doing everything. There's still material prosperity.
Speaker 3: There's food out there, in all the services we could
Speaker 3: possibly want. We just have to find some system whereby
Speaker 3: the humans who have no economic value get to enjoy
Speaker 3: all this cool stuff that's being produced by the machines.
Speaker 1: Yeah, and you know, technological prosperity has given us in
Speaker 1: the developed world ubi for old people, right in the US,
Speaker 1: as in every developed country as far as I know,
Speaker 1: once you get to some age, if you are a
Speaker 1: citizen and you have worked, yeah, the government gives you
Speaker 1: money yea every month until you die, right, and so
Speaker 1: you could imagine a kind of creeping extension of that. Certainly,
Speaker 1: right now they're not talking about lowering the retirement age
Speaker 1: in the US. They're about raising it as in many countries.
Speaker 3: Yeah, raising it in the UK as well, But it's
Speaker 3: still a long way away from life expectancies. My recollection
Speaker 3: is that when Bismarck introduced the first pension, which was
Speaker 3: in Germany in the late nineteenth century, I think the
Speaker 3: pension started to be paid at the age sixty seven
Speaker 3: and the life expectancy was sixty three, you.
Speaker 1: Get negative four years in expectation.
Speaker 3: People who survive long enough to claim any pension at
Speaker 3: all are already exceptional. So that would be like having
Speaker 3: a pension today that started at age ninety. Like some
Speaker 3: people will get it by most bad road. But actually
Speaker 3: a lot of people could easily collect thirty years of pension,
Speaker 3: certainly twenty years. So they're living a large proportion of
Speaker 3: their adult life receiving money from the state, and they're
Speaker 3: also receiving money from their own savings, their own investments,
Speaker 3: which might be a replacement for UBI. Maybe we all
Speaker 3: just have shares in the robots instead, we have shares
Speaker 3: in Google or whatever, and that's how we get paid.
Speaker 1: Yes, whether that is mediated by the government or not
Speaker 1: looks somewhat different. Right, Either the government is taxing the
Speaker 1: owners of in Nvidia and Google stock and distributing the money,
Speaker 1: or everybody owns Google and Nvidia stock. There is the
Speaker 1: piece of this which is about the non financial parts
Speaker 1: of work, right, I mean, there's a political economy piece,
Speaker 1: the sort of bridge. How do we get from here
Speaker 1: to there? If that happens and that's complicated and maybe ugly.
Speaker 3: If the robots can do all of the stuff the
Speaker 3: computers can do it, there's no economic reason why humans
Speaker 3: couldn't just receive whatever an allowance they're given ten robots,
Speaker 3: or they're given ten thousand dollars a month to spend
Speaker 3: or whatever they like. There's no economic reason why that
Speaker 3: couldn't happen. But I think what you're getting at is
Speaker 3: what does it do to us if we're in that situation?
Speaker 1: Yeah? Yeah, Like I don't want to not have a job.
Speaker 1: I recognize that I am fortunate to have a job
Speaker 1: that I enjoy, that I derive a part of my
Speaker 1: identity from. I recognize that for many, in fact, probably
Speaker 1: most people, a job is not that it's some unpleasant
Speaker 1: thing they do because they need the money, and if
Speaker 1: they got more money, they would quit their job. Well,
Speaker 1: you probably know the kind of empirical evidence on this
Speaker 1: better than I do. Like, people have looked at lottery winners, right,
Speaker 1: and my sense is it's not great for you to
Speaker 1: win the lottery and quit your job. It doesn't actually
Speaker 1: make you happier.
Speaker 3: Actually, the evidence on lottery winners is a bit mixed,
Speaker 3: and I think slightly we hear all the disaster stories
Speaker 3: of lottery winners.
Speaker 1: Actually, it's great to win the lottery. That's amazing. Is
Speaker 1: that true.
Speaker 3: I think it's fine. Yes, it's just fine to win
Speaker 3: the lottery. Is not really a problem to win the lottery.
Speaker 3: In my vague recollection I wrote about this a couple
Speaker 3: of years ago. But we may not all want a job,
Speaker 3: but we all want something to do. We all want
Speaker 3: to feel useful, we all want a sense of some
Speaker 3: kind of purpose. We all want, I think, that experience
Speaker 3: of mastery, that experience of knowing that you can do
Speaker 3: something that not everybody can do. Those things don't have
Speaker 3: to come from a job, but for a lot of
Speaker 3: people they do come from a job.
Speaker 1: Yeah. For me, in my narrow provincial experience of life,
Speaker 1: it's frankly hard to imagine and getting those things without
Speaker 1: a job. Yeah.
Speaker 3: It comes back to my initial reaction to Alex's terrific question,
Speaker 3: which is this is such unknown territory that we can
Speaker 3: only really speculate. But I think you and I jcub
Speaker 3: are in agreement that the fundamental issue here is not economic.
Speaker 3: It's really to do with our souls. How would we
Speaker 3: react if our desire for master. We our desire for meaning,
Speaker 3: our desire to feel useful if that had to be
Speaker 3: satisfied without having a job, and what would we do
Speaker 3: and could we cope? And I don't know, I.
Speaker 1: Mean, Harford, if the robots come and take our jobs,
Speaker 1: let's just you and me make a podcast for free.
Speaker 1: I'm in. I'll commit right now in the robot Utopia
Speaker 1: apocalypse to making a weekly podcast with you for free.
Speaker 3: Deal.
Speaker 1: Sorry, we have no more time. You might give in
Speaker 1: your robot overlord. Give us another question, Hello, Race Ubinov,
Speaker 1: I would like to ask, with the onset of AI,
Speaker 1: what is the next cautionary tale you anticipate talking about
Speaker 1: in the years to come?
Speaker 3: Hello Ivanough, I have just finished the first draft of
Speaker 3: a script about the coming of AI, and without giving
Speaker 3: too much away, the cautionary note is about what happens
Speaker 3: when automation gets so good that we lose our own skills.
Speaker 3: We hand over controlled the machine, and then how do
Speaker 3: we respond when the machine says, actually, this one's too hard?
Speaker 3: Could you take over again? Suddenly we're back at the
Speaker 3: wheel and we're out of practice.
Speaker 1: Harford, it's not another plane crash, is it. Don't you
Speaker 1: have a moratory. I'm undering plane crashes at this point.
Speaker 1: Because it sounds like that.
Speaker 3: I'm going to say nothing more fair enough. Let's go
Speaker 3: for a break.
Speaker 1: All right, Yeah, we're back.
Speaker 3: I'm talking to Jacob Goldstein, the host of What's Your Problem,
Speaker 3: and we are doing a Cautionary Questions Q and A episode.
Speaker 3: Jacob has the questions. Jacob's also helping with the answers.
Speaker 3: I'm really sepless to requirements here, but I'm doing my best, Jacob.
Speaker 3: What have you got for me?
Speaker 1: Tim? Our next question comes from Adam, who writes, Hi,
Speaker 1: I have a question about investing in cryptocurrency. Oh dear,
Speaker 1: oh dear, come on give it to them. Okay. It's
Speaker 1: an interesting one. Traditionally, when buying shares in a company,
Speaker 1: you would be supporting that company to grow, create a
Speaker 1: new product, or enter a new retail space. This would
Speaker 1: hopefully create jobs and new products. When people invest money
Speaker 1: into cryptocurrency or any currency for that matter, isn't that
Speaker 1: money just sitting around not doing anything until you withdraw it.
Speaker 1: Would investing in crypto be bad for the economy compared
Speaker 1: with investing in businesses?
Speaker 3: This is a deep question. I really like it. It is
Speaker 3: as the author of the wonderful book Money, The True
Speaker 3: Story of a Maid Art Thing. I am sure you
Speaker 3: have thoughts, Jacob. They may have a first crack and
Speaker 3: you can tell me everything I've made.
Speaker 1: Yeah. Yeah.
Speaker 3: So let's say you buy bitcoin or whatever, and then
Speaker 3: the money's just sitting there because bitcoin is not building anything.
Speaker 3: You're not buying investment in, say a road building company,
Speaker 3: or you're not buying an investment in Google, which is
Speaker 3: developing new technology. There's one of two possible things that happens.
Speaker 3: So most likely is whoever you bought the bitcoin from
Speaker 3: now has your money. Well, now it's their money, and
Speaker 3: then they're going to do something with that money. So
Speaker 3: maybe they then buy shares in Google, or they then
Speaker 3: set up a business, or they will then go on
Speaker 3: to do something with that money, or they'll lend it
Speaker 3: to somebody else and that person will do something with it.
Speaker 3: Eventually the money will find its way into some productive investment.
Speaker 3: The fact that you bought bitcoin off somebody does not
Speaker 3: mean that they won't then do something useful with the money.
Speaker 3: But then let's say for some reason they just go,
Speaker 3: you know what, I'm just going to sit on this money.
Speaker 3: It's just dollars. I'm going to stick them under the mattress.
Speaker 3: I guess a bitcoin guy might do that. That would
Speaker 3: reduce inflationary pressures on the economy, which is something we
Speaker 3: want anyway. And if inflationary pressures are reduced too much,
Speaker 3: the Federal Reserve could then go, you know what, guys,
Speaker 3: we should probably print some money or otherwise stimulate the economy. Actually,
Speaker 3: the worst thing that could possibly happen is that the
Speaker 3: money gets invested in buying more computers that could be
Speaker 3: put to better use, but in fact just end up
Speaker 3: doing bitcoin mining. I guess what I'm saying is, as
Speaker 3: long as they don't spend it on bitcoin mining computers,
Speaker 3: it's totally fine. Well what am I missing?
Speaker 1: I went around the same track as you went around.
Speaker 1: And you know, different cryptocurrencies have different methods of regulation, right,
Speaker 1: So Bitcoin by design is this very energy intensive computing
Speaker 1: process in order to mine bitcoin, and that is, in
Speaker 1: my opinion, a bad outcome. Socially, I agree, because you
Speaker 1: could imagine a world where maintaining the bitcoin network was
Speaker 1: socially desirable. In the world as it has evolved, I
Speaker 1: don't find it particularly socially desirable, but at this point,
Speaker 1: I don't think most of the money going into bitcoin
Speaker 1: is going to miners, right, there's a large stock of
Speaker 1: coin that exists in the world. I mean, an interesting
Speaker 1: thing about money is it almost never sleeps. It keeps going,
Speaker 1: and so you can always ask what happens next, you know,
Speaker 1: with the stock market, sometimes people talk about money on
Speaker 1: the sidelines when they're like, well, the stock market can
Speaker 1: go up somewhere because there's a lot of cash on
Speaker 1: the sidelines. And there's this famous billionaire investor, Cliff Asnes.
Speaker 1: He's an interesting guy. You got a PhD from the
Speaker 1: University of Chicago, studied with Gene Fama, famous economist, and
Speaker 1: Cliff Asnes gets driven up the wall when people say
Speaker 1: cash on the sidelines for the same reason you just said, Right,
Speaker 1: Like every time somebody buys a share of stock, someone
Speaker 1: else is selling it, right, So like the money is
Speaker 1: changing hands, the stock is changing hands. But like there
Speaker 1: are no sidelines with money.
Speaker 3: Yeah, and even if someone puts just cash in a
Speaker 3: checking account, well then now the bank has money, and
Speaker 3: you can bet the bank is going to want to
Speaker 3: do something with that money, something productive. And even if
Speaker 3: they doesn't put it in the bank, as I say,
Speaker 3: it's a dramatris. Well, even then, the Federals could always
Speaker 3: put money.
Speaker 1: Yeah, the stock of money is not fixed, right. I
Speaker 1: think there's an assumption in the question I think goes
Speaker 1: back to the pre modern era, the era before the
Speaker 1: nineteen thirties when money was based on gold or silver
Speaker 1: and it was finite. Right, there was a fixed amount
Speaker 1: of gold and silver in the world in those days. Indeed,
Speaker 1: if you sat on money, you were effectively reducing the
Speaker 1: supply of money in the world. But to your point,
Speaker 1: the supply of money in the world is as big
Speaker 1: as the Central Bank wants it to be, and so
Speaker 1: it's not a meaningful constraint on economic growth. So the
Speaker 1: ultimate answer to the question is if you are just
Speaker 1: sitting on money, it's not really going to have an
Speaker 1: effect on the broader economy.
Speaker 3: Well, I think we've come to agreement. Hopefully that makes
Speaker 3: sense to Adam. Next question.
Speaker 1: Our next question comes from doctor Yvonne Couch, who is
Speaker 1: Associate Professor of Neuroimmunology Alzheimer's Research UK Fellow, Associate Research
Speaker 1: Fellow at Saint Hilda's College, Stipendary Lecturer at Somerville College,
Speaker 1: University of Oxford.
Speaker 3: Yeah, University of Oxford. I know, well, one of my
Speaker 3: sisters went to St. Hilda's College and one of my
Speaker 3: sisters went to Somerville College, so this feels very much
Speaker 3: in the family. So what does Dr Couch got to say?
Speaker 1: She writes, my question was vaguely economics based, although probably
Speaker 1: not very is the way we currently fund science feasible
Speaker 1: going forward? Do we just have too many scientists and
Speaker 1: not enough resources? All the best, Yvonne, oh love it.
Speaker 3: Let me throw out a few thoughts. Then I think
Speaker 3: that probably there is a problem with the way we
Speaker 3: fund science, But there's no one way that we fund science.
Speaker 3: You have university research, you have various grands, various sources
Speaker 3: of funding, philanthropy and so on. You also have private
Speaker 3: sector research, which is often incentivized by the patent system.
Speaker 3: And then you have big block grants that are handed
Speaker 3: out by agencies such as the National Institutes for Health.
Speaker 3: So there are lots of different ways that science gets funded.
Speaker 3: A couple of things that worry me is that, first
Speaker 3: of all, there's a big incentive to make really incremental
Speaker 3: improvements rather than to take risks. There's a great economics
Speaker 3: paper studying scientists who are funded by the National Institutes
Speaker 3: for Health, which is a wonderful institution, very important, and
Speaker 3: scientists who on paper seem to be the same that're
Speaker 3: on the same career track, got very similar publication records,
Speaker 3: and they are instead funded by a private foundation called
Speaker 3: the Howard Hughes Medical Institute. Listeners who want to hear
Speaker 3: more about Howard Hughes and the Howard Hughes biography can
Speaker 3: go to the back catalog of caution details. So the
Speaker 3: Howard Hughes Medical Institute basically takes risks. It wants people
Speaker 3: to do something new. It's happy with a high risk
Speaker 3: of failure as long as there's some chance of a
Speaker 3: real breakthrough success. And this particular paper studying the results
Speaker 3: that come from these two funding systems basically finds that
Speaker 3: the grant funders get what they pay for. So the
Speaker 3: National Institutes for Health get a high success rate, but
Speaker 3: it's often quite incremental progress. And the Howard Hughes Medical
Speaker 3: Institute has lots and lots of failures, but when it succeeds,
Speaker 3: it really succeeds. And they these are hugely important papers,
Speaker 3: and I just feel that we're not deliberate enough about saying, well,
Speaker 3: how much of our funding ecosystem should be aiming at
Speaker 3: kind of venture capital style for really big wins, and
Speaker 3: how much should be incremental. I think those are not
Speaker 3: the sorts of questions that get asked, So that's one
Speaker 3: of the things that worries me. What's your take, Jacob.
Speaker 1: One of the things that I have read is that
Speaker 1: over time the average age of grant recipients from the
Speaker 1: NIH has gone up and up and up. So kind
Speaker 1: of you just think of this whole universe as getting
Speaker 1: all and more risk averse and more kind of bureaucratic.
Speaker 1: There is an interesting set of counter pressures I think
Speaker 1: rising up partly out of Silicon Valley. I don't know
Speaker 1: if you've come across the work of Patrick Hollison and
Speaker 1: his brother. They're from Ireland. They found it Striped. They're
Speaker 1: very rich. Stripe is a big company that does basically
Speaker 1: payment stuff online. They have a really interesting set of
Speaker 1: kind of philanthropic endeavors around the idea of progress. You know,
Speaker 1: they're trying to create a kind of field of progress
Speaker 1: studies that is, it's very meta. What are the conditions
Speaker 1: that best foster technological and scientific progress?
Speaker 3: But this question from doctor Couch, he is very massive. Yes,
Speaker 3: it's very much progress studies, isn't it.
Speaker 2: Yes.
Speaker 1: There is this institute in the Bay Area called the
Speaker 1: ARC Institute that hires leading scientists. The basic idea is
Speaker 1: give talented people freedom and money, right and encourage them
Speaker 1: to take big swings. And they are interested, you know,
Speaker 1: not just in outcomes, but in new tools. Right. Again,
Speaker 1: continuing on the nerdy thing, like if you take a
Speaker 1: tool like Crisper. Crisper is an intermediate tool that allows
Speaker 1: people to cut up a genome. Basically, we just had
Speaker 1: the first transplant from an animal into a human a
Speaker 1: few weeks ago because of Crisper. We have the first
Speaker 1: treatments for sickle cell disease because of Crisper. So I
Speaker 1: do think there is a wave of people trying to
Speaker 1: rethink scientific funding. There is a bottom line aspect to
Speaker 1: this question from doctor Couch that I don't feel like
Speaker 1: I know enough to answer, and I'm curious if you do.
Speaker 1: I mean, the question, is the way we currently fund
Speaker 1: science feasible going forward? There is a yes no version
Speaker 1: of the answer. Do you think you know? Is it?
Speaker 3: I don't know the answer, but I guess I don't
Speaker 3: know either. Another thing that concerns me on this, which
Speaker 3: is potentially really existential is the question of how we
Speaker 3: fund new antibiotics. I think this points to a real
Speaker 3: weakness in the ecosystem of research funding. So if you
Speaker 3: think about the basic way we develop drugs, the fundamental
Speaker 3: incentive is the patent. So a drug company spends a
Speaker 3: lot of money, tries to develop drugs. Some of them work,
Speaker 3: some of them fail, a lot of them fail, but
Speaker 3: in the end you have a drug and the deal
Speaker 3: is we give you this artificial monopoly called a patent,
Speaker 3: and it will only last for a certain amount of time,
Speaker 3: which is kind of a problem because it takes so
Speaker 3: long to develop the drugs. Maybe the patent's nearly expired.
Speaker 3: You can charge an incredible amount for these drugs for
Speaker 3: a while, and then your patents will run out, and
Speaker 3: then loads of as people will make the same drug
Speaker 3: and it'll come down in value. For example, Viagra, you
Speaker 3: know you could sell this for a huge amount of money,
Speaker 3: and now Viagra is off patent and anyone can make
Speaker 3: a generic Viagra. So that's the incentive that we're given
Speaker 3: to private companies, that you will have this temporary monopoly.
Speaker 3: So now think about antibiotics. The problem with antibiotics. We
Speaker 3: have lots of antibiotics work really well, except the bacteria
Speaker 3: have figured them out. And why have they figured them out?
Speaker 3: Because we've used them. The bacteria developed resistance. So what
Speaker 3: we really need is new antibiotics that we don't use.
Speaker 3: And now think about how the pattern system deals with that.
Speaker 3: So you basically say, if you develop a new antibiotic,
Speaker 3: we'll give you a tempery monopoly, but we really need
Speaker 3: you to just not sell any don't sell any of.
Speaker 1: This thing except in cases of dire emergency. It's like
Speaker 1: a break glass in case of emergency. I mean, I
Speaker 1: feel like a bounty. Like every econ nerd storyteller loves
Speaker 1: a good bounty. Right, wasn't this done with a malaria vaccine,
Speaker 1: which is actually coming along quite well. You have some
Speaker 1: universe of people say we will pay a billion dollars
Speaker 1: to anyone who comes up with a new antibiotic that
Speaker 1: meets this set of criteria, that treats this set of
Speaker 1: bugs that are resistant to these existing antibiotics, and we'll
Speaker 1: give you the money, and you give it to us,
Speaker 1: and we'll put it on the break glass in case
Speaker 1: of emergency. Shelf.
Speaker 3: You've used the word bounty, but what the term that
Speaker 3: is normally used is an advanced market commitment. These were
Speaker 3: proposed most famously by Michael Kramer, who's a Nobel Prize
Speaker 3: winner in economics. And basically, the way this price, this
Speaker 3: bounty tends to get paid is as a kind of
Speaker 3: extra payment on top of each dose you sell. Ah,
Speaker 3: so we'll give you extra for every kid that gets vaccinated.
Speaker 1: So or back to the same problem in that universe.
Speaker 3: Back to the same problem. But the reason you go, well,
Speaker 3: why does it have to be like that? It doesn't
Speaker 3: have to be like that. But the reason that they
Speaker 3: tend to be structured like that is because you need
Speaker 3: to demonstrate some kind of market demand. Somebody needs to
Speaker 3: be willing to buy your product. If they are, we'll
Speaker 3: give you an extra payment for every product you sell.
Speaker 3: But that wouldn't work for antibiotics. There's so many different
Speaker 3: ways in which science funding could be said to be broken.
Speaker 3: But I think doctor Couch is right to raise the issue.
Speaker 3: We need to do a lot more of this kind
Speaker 3: of meta thinking about progress studies.
Speaker 1: Tim that was a lot of answer. Let's take a break.
Speaker 1: Cautionary to e will be back in a moment Edward Back.
Speaker 1: I'm Jacob Goldstein here with Tim Harford on cautionary tales.
Speaker 3: Hello, Jacob, more questions? What have you got for me?
Speaker 1: All right, Tim, I got another one for you. Comes
Speaker 1: from Graham in Florida. Graham Rights. I'm fascinated by errors
Speaker 1: made by falsely identifying correlation as causation. What examples of
Speaker 1: this error stand out to you?
Speaker 3: I love the question, but I'm going to slightly sidestep
Speaker 3: it because I'm worried by this question. But I think
Speaker 3: that it's generally more complicated than simply some fool sora
Speaker 3: correlation and thought it was causation.
Speaker 1: You don't want to talk about sun spots and crap yields.
Speaker 3: Well, let's talk about stocks and babies briefly, Okay.
Speaker 1: A classic, A classic of the genre.
Speaker 3: Yeah, the most successful book have a public statistics. How
Speaker 3: to Lie with Statistics by Daryl Huff includes this example
Speaker 3: of stalks and babies and shows that there's a correlation
Speaker 3: between the number of storks and the number of babies.
Speaker 3: And there are various ways to demonstrate this correlation. One
Speaker 3: way to do it is you just look at national populations.
Speaker 3: You go, hey, countries with lots of storks also have
Speaker 3: lots of babies, and there's a very very strong correlation.
Speaker 3: But of course the reason is big places like the
Speaker 3: United States have a lot of room for storks and
Speaker 3: a lot of room for babies, and small places like
Speaker 3: in a Luxembourg or the Vatican City don't have a
Speaker 3: lot of room for babies and don't have a lot
Speaker 3: of room for storks. So then you go, oh, that's
Speaker 3: a great example of this mistake. The sting in the
Speaker 3: tale of that story, as I describe in my book
Speaker 3: The Data Detective, is that Daryl Huff, the guy who
Speaker 3: created that story, then went on to tell the same
Speaker 3: story in congressional testimony, saying that there was no compelling
Speaker 3: evidence that smoking cigarettes would give you lung cancer, and
Speaker 3: it was just like stalks and babies, and he was
Speaker 3: actually high by the tobacco lobby. It was just correlation.
Speaker 3: It was just correlational. They seemed about the same. Sure, yeah,
Speaker 3: there are people who smoke, and that people who get cancer,
Speaker 3: but there's no cause of evidence. One theory was cigarettes
Speaker 3: are so soothing, and if you have some early symptoms
Speaker 3: of lung cancer, maybe you soothe that with the soothing
Speaker 3: vapors of cigarettes. I mean, it's completely ridiculous, but this
Speaker 3: sort of rhetoric was deployed. And so one of the
Speaker 3: things I'm very concerned about in my work on statistics
Speaker 3: is that it's great to be skeptical about statistics and
Speaker 3: to point out lots of examples of statistics being misused.
Speaker 3: But if that's all you do, you just get to
Speaker 3: a canihilistic situation where you're just constantly rejecting statistical evidence
Speaker 3: because it's just another of those damn lines and statistics.
Speaker 3: When you look at the real world, I think this
Speaker 3: gets to be incredibly interesting. So a real hot topic
Speaker 3: at the moment is our smartphones destroying a generation. Basically,
Speaker 3: are our kids having their mental health wrecked.
Speaker 1: There's a new book that basically makes that up.
Speaker 3: Yeah Yeah, by a prominent ecademic yea by Jonathan Hyde,
Speaker 3: and there have been others by Gene Twegian. Lots of
Speaker 3: people have said this, and the evidence for it is
Speaker 3: mostly correlational, not completely. There are some experiments, but they're
Speaker 3: not that convincing. None of them are perfect, but there
Speaker 3: are lots of different ways of measuring it. And the
Speaker 3: really interesting evidence basically says look, there appears to be
Speaker 3: a mental health crisis. The kids seem to get really distressed,
Speaker 3: particularly the girls, when children have access to social media
Speaker 3: on their phones, and that happens around sometime between twenty
Speaker 3: ten and twenty fourteen. And at the same time, suddenly
Speaker 3: you've got this outbreak of suicidal ideation and self harm,
Speaker 3: poor mental health and so on. And that's correlational evidence.
Speaker 3: I don't completely believe it, but I don't completely not
Speaker 3: believe it either. I think that's what makes it interesting
Speaker 3: and makes it important to engage with. You have to
Speaker 3: start going, well, what's the alternative explanation? Is there something
Speaker 3: else that has happened sometime about sort of ten, twelve,
Speaker 3: fourteen years ago that might explain this mental health distress?
Speaker 3: So the timing of the Great Financial Crisis probably not
Speaker 3: quite right. Donald Trump, maybe Donald Trump is upsetting the kids.
Speaker 3: Timing doesn't work, so partly it does. The pattern of
Speaker 3: the correlation make enough sense to explain this causal story, which,
Speaker 3: funny enough, is basically exactly what the scientists finding a
Speaker 3: connection between cigarettes and lung cancer were doing. They only
Speaker 3: had correlational evidence for a long time. They weren't running
Speaker 3: randomized trials saying you know, half of you smoke and
Speaker 3: half of you don't smoke. I mean, they couldn't do that.
Speaker 3: They had to look at correlational evidence, and sometimes that's
Speaker 3: what we've got.
Speaker 1: This question got me thinking about the rise in social
Speaker 1: science of what they call natural experiments, right, trying to
Speaker 1: find instances in the real world where you have something
Speaker 1: that obviously is not as good as a randomized trial,
Speaker 1: because you just can't get that with large numbers of
Speaker 1: people in the world, but that gives you some element
Speaker 1: of randomization or pseudorandomization, something that allows you to try
Speaker 1: and make the leap from correlation to causation. And you know,
Speaker 1: this as far as I know, goes back to the
Speaker 1: Vietnam War, right, where in the US there was a
Speaker 1: draft lottery, and there were social scientists after the war
Speaker 1: who looked and said, oh, look, here are people who
Speaker 1: are at an aggregate level very similar on many dimensions
Speaker 1: socioeconomic dimensions. We can look at people who randomly got
Speaker 1: drafted versus those who randomly didn't, and who appear quite
Speaker 1: similar in the aggregate, and see how their outcomes differ.
Speaker 3: And that's a really good example of a natural experiment.
Speaker 3: Because it's actually very close to a really.
Speaker 1: Yeah, when you get a lottery in the real world. Now,
Speaker 1: social scientists flocked to it.
Speaker 3: Right.
Speaker 1: Similarly, there was one in Oregon some years ago with Medicaid,
Speaker 1: which is the healthcare program for low income people in
Speaker 1: the US, and Oregon got some new Medicaid funds and
Speaker 1: they randomly allocated them to a group of people over time, right,
Speaker 1: so that social scientists could say, oh, look, here are
Speaker 1: people all who are basically identical. Some of them got
Speaker 1: this health insurance and some of them didn't. And in
Speaker 1: that case the findings were quite interesting. Medicaid didn't appear
Speaker 1: to be as helpful as I would have thought, as
Speaker 1: the researchers themselves would have thought. According to the one
Speaker 1: I interviewed, lowered mental health problems. People worried less about money,
Speaker 1: but like their basic health outcomes didn't improve, which nobody
Speaker 1: would have guessed. Right. And the evidence is quite robust.
Speaker 1: When you don't have those lotteries. As you say, the
Speaker 1: world is just hard to understand. I mean, even in
Speaker 1: some instances where you do have randomized trials. People are complicated.
Speaker 1: The body is complicated, society is complicated, and so you know,
Speaker 1: correlation in a certain way I think is underrated, Like, yes,
Speaker 1: obviously it doesn't equal causation, but it's a place to
Speaker 1: start looking, right, it's a place to start asking questions.
Speaker 3: I think that's absolutely right, and we need more randomized experiments.
Speaker 3: There are more opportunities to run them than people seem
Speaker 3: to think. For example, one of the things that John
Speaker 3: Hyde in his book is arguing for is, you know,
Speaker 3: shouldn't have smart funds in school Schools should be phone
Speaker 3: free zones. I could completely imagine a state saying we're
Speaker 3: going to introduce a rule whereby in all of the
Speaker 3: schools in the state, no smartphones strictly forbidden. You have
Speaker 3: to put them in a locker when you show up
Speaker 3: and then unlock them at the end of the day.
Speaker 3: You could introduce that rule and just go, well, we
Speaker 3: introduce it for a semester at random in fifty percent
Speaker 3: of the schools, and then we'll introduce it in the
Speaker 3: other fifty percent of the schools in the next semester,
Speaker 3: and we'll just randomize that because we want to know
Speaker 3: whether there's any point in this experiment or not. That's
Speaker 3: not very difficult to do. It would create so much
Speaker 3: information about children's performance in the classroom, their mental health,
Speaker 3: that could inform policy across the world.
Speaker 1: That would be the dream. You know, there is now
Speaker 1: a robust set of methods essentially where social scientists could
Speaker 1: look at that state and compare it to neighboring states
Speaker 1: and see the difference in differences, as they say, see
Speaker 1: the change over time. And that's an instance where it
Speaker 1: wouldn't as elegant as randomizing within a state. But I
Speaker 1: feel like you could start to get pretty good data
Speaker 1: even if you did one state compared to other states.
Speaker 3: Yeah, if you've got no experiments, we should run them.
Speaker 3: If we don't run them, there are still ways of
Speaker 3: making correlation talk. Should we have another question?
Speaker 1: Okay, Tim, we got one more. We had to have
Speaker 1: one game related question for right, Yes, you're welcome. This
Speaker 1: one comes from Yost, who writes, Hi, Tim, diving into
Speaker 1: the board game shaped flank you've now exposed for discussion.
Speaker 1: That is a very gamersh way in what board games
Speaker 1: or board game mechanisms that you enjoy are particularly insightful
Speaker 1: on some aspect of real world economics offer a unique
Speaker 1: angle to look at a maybe niche problem and what
Speaker 1: non D and D games are you particularly enjoying right now?
Speaker 1: Love the show? However, many episodes you produce that is
Speaker 1: a listener? We all yeah, yeah, so kind your.
Speaker 3: There are a couple of mechanisms that I do see
Speaker 3: used quite often that shared important light on economics. So
Speaker 3: one is trading. A lot of games involved trading. Now Monopoly,
Speaker 3: that classic of sadly not a very good game. Oh
Speaker 3: there's a cautionary tell about the history of Monopoly if
Speaker 3: people want to listen. Monopoly in theory involves trading, but
Speaker 3: in practice, not a lot of trading happens. It turns
Speaker 3: out that you need to give people a reason to trade.
Speaker 3: The great modern game Settlers now about thirty years old.
Speaker 1: By the way, Settlers, I assume that Settlers of Catan
Speaker 1: as an outsider, not on a first name basis, with the.
Speaker 3: Game, Settlers of Katan is the game. It's super It's
Speaker 3: the game that Monopoly wishes it was. It's like if
Speaker 3: Monopoly had been designed with a modern eye to be
Speaker 3: super exciting. The people need different resources, and the supply
Speaker 3: of resources fluctuates, so sometimes you've got loads of wood,
Speaker 3: sometimes there's no wood. So there's an active incentive to
Speaker 3: trade all the time. By the way, if you don't trade,
Speaker 3: every now and then the robber Barron comes and take stuff.
Speaker 3: So it's an interesting insight that trading doesn't just happen
Speaker 3: because it's allowed. There needs to be some difference in
Speaker 3: value and perhaps some incentive to get on with it.
Speaker 3: So my personal favorite game is a gricler, a wonderful
Speaker 3: game about developing a farm, which doesn't sound promising, but
Speaker 3: it's really really good. But one of the clever things
Speaker 3: about a grickler is it uses an auction in an
Speaker 3: interesting way. But it's sometimes called a descending clock auction
Speaker 3: or a Dutch auction. The prize gets more and more tempting,
Speaker 3: so in a grickller there's just more and more good
Speaker 3: stuff on the board. In a traditional descending clock auction,
Speaker 3: basically the price is going down and down and down
Speaker 3: and down, and everyone is just sitting there and then
Speaker 3: it's a question of who grabs it first. The longer
Speaker 3: you leave it, the better it gets, but then only
Speaker 3: one person can have it. It's very very elegant. They
Speaker 3: sell flowers at Alsmere in the Netherlands and it's just
Speaker 3: incredibly quick, much much quicker than selling say art. You
Speaker 3: know you're selling a van god price rises and rises
Speaker 3: and rises.
Speaker 1: So auction design is a whole thing, right, Yeah, When
Speaker 1: would you choose the traditional prices going up eBay art
Speaker 1: style auction in the real world, and when would you
Speaker 1: choose a Dutch prices going down auction? What do you
Speaker 1: get in a relative sense out of each one of those.
Speaker 3: There's a couple of differences. One is that in certain
Speaker 3: types of ascending auction you get to see people dropping
Speaker 3: out as the price rises. It depends on the way
Speaker 3: the auction is designed. But you could imagine an ascending
Speaker 3: auction where you just see people going no, I'm out,
Speaker 3: I'm out, I'm out.
Speaker 1: Sort of the classic kind of art auction in a movie.
Speaker 3: Yeah, and so you're learning information as the price rises.
Speaker 3: How many people are still interested? Are there's still ten
Speaker 3: people interested? Is it just two people? So that generates information.
Speaker 3: By generating information, it might raise the final price. Overall.
Speaker 3: The advantage of the descending auction is it's just so quick.
Speaker 3: You can run an auction in ten seconds. It's one
Speaker 3: hundred thousand tulips. Here are the tulips. We're going to
Speaker 3: sell them for whatever, ten thousand years, nine hundred and
Speaker 3: thin thousand, and it's literally a clock. The clock just
Speaker 3: runs around showing what the price is and then someone
Speaker 3: presses the button. Sold, okay, now bringing the roses. So
Speaker 3: it's very fast.
Speaker 1: You would want to have a good idea of the
Speaker 1: market clearing price if you were going to run that
Speaker 1: kind of auction, so that you didn't sell it for
Speaker 1: too cheap. Right, it's fast, but you run the risk
Speaker 1: of selling it for too cheap. But if it's just
Speaker 1: commodity toolips, then you basically know the market clearing price. Anyways.
Speaker 3: Yeah, it's almost like a stock market for tulips. That
Speaker 3: I think is why it works so well. Whereas if
Speaker 3: it's a unique work of art, you need to give
Speaker 3: maximum information, maximum comfort to people, maybe a little bit
Speaker 3: of theater as well. We're not in a hurry to
Speaker 3: run this auction. The cost of the auction itself is
Speaker 3: trivial compared to the value of what's being sold.
Speaker 1: Now we go over to Agricola and have a descending action.
Speaker 1: It feels exciting, and it also feels like you're trying
Speaker 1: to guess what is in your opponent's head, right, because
Speaker 1: they're not revealing it as they would in ascending price auction,
Speaker 1: you have to think, oh, what are they willing.
Speaker 3: To pay for? Absolutely, and it works slightly differently, but
Speaker 3: the functionally what's going on is that every turn you
Speaker 3: take you get to grab some resource on the board,
Speaker 3: and then once you've grabbed the resource on the board,
Speaker 3: no one else is allowed to grab it until the
Speaker 3: next round. And there are several moves you can make
Speaker 3: in each turn, so you might be able to get
Speaker 3: two or three things each turn. And so you go
Speaker 3: backwards and forwards. It's your move and it's my move.
Speaker 3: And each time we want to grab something, and you
Speaker 3: might go, well do I want to grab it now?
Speaker 3: What do I want to wait until next turn where
Speaker 3: it might be better? And you're trying to figure out, like,
Speaker 3: what is the thing that the other person is desperate
Speaker 3: to have? Can I just let this pile get bigger
Speaker 3: because they can't afford to take it because they've got
Speaker 3: to use their move on something else. It's a very
Speaker 3: very clever game. I do enjoy it. You just also
Speaker 3: ask what non D and D games I am enjoying.
Speaker 3: I am enjoying a modified version of Blades in the Dark,
Speaker 3: Whi's a classic role playing game, very fast moving, you
Speaker 3: get to do Ocean's eleven or other kind of heists,
Speaker 3: and it's very modifiable. We're speaking on Monday. Just yesterday
Speaker 3: on Sunday, had a whole bunch of old friends around
Speaker 3: to my house and we just played this game all
Speaker 3: day and we had an absolutely terrific time.
Speaker 1: I feel like you're living the dream, Harfred makes me happy,
Speaker 1: living my best life.
Speaker 3: Jacob, this has been such fun. Thank you so much
Speaker 3: for doing this.
Speaker 1: Ah, it was a delight. I'll come back anytime.
Speaker 3: We would love to have you back. Thank you everybody
Speaker 3: who sent in a question. Sorry, we weren't able to
Speaker 3: answer all the questions, but we are going to be
Speaker 3: back with another Cautionary Questions episode later this year. Please
Speaker 3: do keep your queries coming, send them into tales at
Speaker 3: pushkin dot fm. That's t a l e s at
Speaker 3: Pushkin dot fm and I'll be back with another Cautionary
Speaker 3: Tale in two weeks time. Jacob Goldstein has a wonderful
Speaker 3: podcast called What's Your Problem? Thank You, Jacob, Thanks Jim
Speaker 3: Caul is written by me, Tim Harford with Andrew Wright.
Speaker 3: It's produced by Alice Fines with support from Marilyn Rust.
Speaker 3: The sound design and original music is the work of
Speaker 3: Pascal Wise. Sarah Nix edited the scripts. It features the
Speaker 3: voice talents of Ben Crowe, Melanie Guttridge, Stella Harford, Jemma
Speaker 3: Saunders and rufus Wright. The show also wouldn't have been
Speaker 3: possible without the work of Jacob Weisberg, Ryan Dilly, Gretta Cohne,
Speaker 3: Vital Millard, John Schnaz, Eric's handler, Carrie Brody, and Christina Sullivan.
Speaker 3: Cautionary Tales is a production of Pushkin Industries. It's recorded
Speaker 3: at Wardoor Studios in London by Tom Berry. If you
Speaker 3: like the show, please remember to share, rate and review,
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