Speaker 1: Pushkin Wonderful News Cautionary Tales has been nominated for a
Speaker 1: Webby Award. The category is Best Original Music Score and
Speaker 1: Sound Design. Where you know who deserves the credit for that,
Speaker 1: It is the wonderful Pascal Wise. Pascal has been with
Speaker 1: Cautionary Tales right from the start. I remember sitting with
Speaker 1: him plotting how to make the sound of rats scurrying
Speaker 1: in a deserted warehouse for our airship episode. If you
Speaker 1: would like to show us some love, and show more
Speaker 1: importantly Pascal wyse some love, go along to Webby Awards
Speaker 1: dot com and give us a vote. We will put
Speaker 1: a link in the show notes. Twenty years ago, I
Speaker 1: was working on the final draft of my first book,
Speaker 1: The Undercover Economist, when my publisher sent me a worried email.
Speaker 1: There's this new book about to come out. He said,
Speaker 1: it's also about economics, and it looks like it's going
Speaker 1: to scoop you, and that might be a problem. But
Speaker 1: I wasn't worried. If the book was a success, it
Speaker 1: would just make economics seem cool. And anyway, how big
Speaker 1: a success could an economics book be. At the time,
Speaker 1: I lived in the US, and I've been doing some
Speaker 1: writing for the Financial Times, so I pitched the idea
Speaker 1: a flying to Chicago to interview the economist whose work
Speaker 1: was at the heart of this book. It was my
Speaker 1: first ever interview, and little did either of us know
Speaker 1: that his work was about to become one of the
Speaker 1: biggest books of the decade. I walked away from the
Speaker 1: interview with a copy to Tim the first book I've
Speaker 1: ever signed. You can probably get at least nine dollars
Speaker 1: fifty on eBay. Steve Levitt. The book, co authored with
Speaker 1: Stephen J. Dubner, was called Free Economics and a Combined
Speaker 1: Pop Culture with Economics. It was a global smash hit.
Speaker 1: It spawned several sequels, a documentary, film, and a podcast,
Speaker 1: and twenty years after our first meeting, I am reunited
Speaker 1: with Steve Levitt. Steve, welcome to caution me sales.
Speaker 2: Ah, great to talk to you, Tim. We both had
Speaker 2: a pretty good run for the last twenty years.
Speaker 1: Well you about an even better run than me, but yeah,
Speaker 1: good enough. I can't believe it's been twenty years. It
Speaker 1: was my first interview, so I was just terrified that
Speaker 1: the digital recorder wouldn't work. You kept picking it up
Speaker 1: and going, you sure, this is working. I was like, please,
Speaker 1: please don't mess with my take recorder. Did you really
Speaker 1: not know the book was going to be so big?
Speaker 2: I mean, nobody thought the book would be successful. After
Speaker 2: we signed the contract, I called my dad to celebrate,
Speaker 2: and his only response was, this is completely immoral. I said,
Speaker 2: what are you talking about? He said, it's a moral
Speaker 2: to take the money from the publishers when you and
Speaker 2: I both know no one wants to read the junk
Speaker 2: that you write about. And I think that everyone kind
Speaker 2: of had that view. I mean, Stephen Denner and I
Speaker 2: we both agreed that we could use a little extra cash.
Speaker 2: So when they were willing to overpay us for the book,
Speaker 2: we agreed to write it. But honestly, it was just luck. Really.
Speaker 2: The biggest thing that happened was they got me on
Speaker 2: The Daily Show with Chance Story. And honestly, the way
Speaker 2: they got me on I know, I'm not sure to
Speaker 2: say this, but somebody traded a rent controled apartment to
Speaker 2: someone who worked that Chance so in return for getting
Speaker 2: me on to the show, and that changed everything. It
Speaker 2: was pure graft, you know that made this thing take up.
Speaker 1: Well, I mean, graft is cool these days, So you
Speaker 1: were as so often you were ahead of the curve.
Speaker 1: Although I have to say I was on I was
Speaker 1: on John Stewart's show, but I was on the Colbert
Speaker 1: Report with my second book, and I can assure you myself,
Speaker 1: and I don't think anybody traded in any rent control departments.
Speaker 1: But I assure you my second book did not do
Speaker 1: nearly as well as Freakonomics, So I think there was
Speaker 1: more going on than just corruption. But first I need
Speaker 1: to say, I'm Tim Harford, and you're listening to cautionary tales, Steve,
Speaker 1: if you can recall the elevateor pitch from twenty years ago,
Speaker 1: what wasmics all about?
Speaker 2: Yeah, So Freakonomics was really my research. Up to that time,
Speaker 2: I'd written dozens and dozens of of really oddball economics papers,
Speaker 2: so about how real estate agents rip you off because
Speaker 2: they have bad incentives in the contract, How getting the
Speaker 2: financial records of a crack selling gang and looking at
Speaker 2: the economics of selling drugs and the names you give
Speaker 2: to your kids doesn't expect the life. So that's the
Speaker 2: kind of research I did. Now, of course it was
Speaker 2: very dry and academic, but it was on topics that
Speaker 2: lent themsel self to storytelling, and so when I got
Speaker 2: together with Stephen Dumner, we turned all of these academic
Speaker 2: papers I had written into a series of interwoven stories
Speaker 2: that were fun and exciting and really touching on pop culture.
Speaker 2: So in many ways it was a rigorous economics book
Speaker 2: because the ideas and the studies that we're writing about
Speaker 2: were really serious and had the validation of having been
Speaker 2: published in Top Economics turnnes, but done with a tone
Speaker 2: that nobody had ever really done before. The heart and
Speaker 2: soul for economics is how can you talk about economics
Speaker 2: but as if you were kind of what we call
Speaker 2: like a rogue. So it's a rogue way of having
Speaker 2: fun and making fun of a lot of things and
Speaker 2: a lot of people while you're dabbling in big economic ideas.
Speaker 1: You may remember, you probably don't. I did actually auction
Speaker 1: that book you signed for me on eBay quite a
Speaker 1: lot more than nine dollars fifty for it.
Speaker 2: Do you remember that?
Speaker 1: No?
Speaker 2: I don't. I don't remember that at all.
Speaker 1: I said, look, I'm going to auction this and give
Speaker 1: the money to charity, and you very nobly said, well,
Speaker 1: whatever they pay, I'll match it, so or'll double the money.
Speaker 2: You know, it's coming back to me. Yeah, yeah, it
Speaker 2: wasn't it a few hundred dollars?
Speaker 1: It was a few hundred I think it was about
Speaker 1: six hundred dollars. I can't remember exactly. Wow, So it
Speaker 1: was not nothing slightly self interestedly. I sold it about
Speaker 1: the time my book was coming out, which was about
Speaker 1: six months after Freakonomics, obviously, just you know, anything to
Speaker 1: get a little bit of attention.
Speaker 2: And I remember a six poker game too.
Speaker 1: Ah yeah, you So this is a separate interview. The
Speaker 1: ft the Financial Times made me go and lose a
Speaker 1: poker to you while trying to interview you. It was
Speaker 1: really really difficult multitask.
Speaker 2: It was good though. I thought that turned out really well.
Speaker 2: It was.
Speaker 1: It was a fun interview, but you took all my money,
Speaker 1: and by the way, the expense claim on that was
Speaker 1: quite difficult.
Speaker 2: That's like when I invited a call girl, a prostitute
Speaker 2: to come in and get lecture to my class at
Speaker 2: the Universe of Chicago on the economics of crime, and
Speaker 2: to get her to come, I had to agree to
Speaker 2: pay her hourly wage. And I will say I did
Speaker 2: not have success billing either the National Science Foundation or
Speaker 2: the Universit of Chicago six hundred dollars to cover the
Speaker 2: cost of hiring a prostitute to come to teach my classroom.
Speaker 1: Because of the amount, or because of who it was
Speaker 1: being paid too.
Speaker 2: It was because I didn't even try. Could you imagine that,
Speaker 2: I can imagine. I can imagine the National Science Foundation
Speaker 2: pays a freaking author six hundred dollars.
Speaker 1: For prostitute with the benefit of twenty years of hindsight,
Speaker 1: any sense of why the book was such a phenomenon.
Speaker 2: It really was a case of being in the right
Speaker 2: place at the right time. A combination of that and
Speaker 2: the fact that Dubnr and I didn't expect anyone to
Speaker 2: ever read the book, so we wrote it in a
Speaker 2: way that was very, very freeing, because we started we
Speaker 2: started out trying to write a regular book, and it
Speaker 2: was terrible, and we knew it was terrible, and we
Speaker 2: were almost going to write it anyway, because well, that's
Speaker 2: the way you write books. And then we had the
Speaker 2: good sense to sit back and look, since no one's
Speaker 2: going to read it, why don't we try to write
Speaker 2: a book that's fun for us. Dubnor is an amazing writer,
Speaker 2: and I think he and I had the right tone.
Speaker 2: But Dubnor had written this piece about me in the
Speaker 2: New York Times, and he had cast me as this
Speaker 2: genius Sherlock Homes of economics. You give him a pile
Speaker 2: of data and he'll go bang away in his computer
Speaker 2: for two hours and solve any problem. I mean, it
Speaker 2: was completely and totally artificial. But people loved it. It
Speaker 2: was a great piece. It was a reading that was
Speaker 2: a great piece of writing. So we just basically have
Speaker 2: been milking that completely fake image he built about me
Speaker 2: for the last twenty years, and it was a really
Speaker 2: easy voice for both of us to fit into. And
Speaker 2: I think that's part of it. I don't know why
Speaker 2: people were so eager to read it. Now. What was
Speaker 2: really funny for me is we wrote that book, and then,
Speaker 2: of course, if you have that kind of success, you think, well,
Speaker 2: let's write a second book. And what we thought is, oh,
Speaker 2: people loved our stories, and so if we can come
Speaker 2: up with a whole bunch of good stories, people will
Speaker 2: love the next book. But people didn't really like it,
Speaker 2: and people didn't really buy it nearly as much. And
Speaker 2: I came to realize it wasn't actually the stories that
Speaker 2: people wanted. It was more the attitude, and it was
Speaker 2: an attitude that people weren't used to, a sassy kind
Speaker 2: of exploration of possibilities people hadn't thought about, and getting
Speaker 2: that once was plenty, people didn't really need any more
Speaker 2: of it, And so we had the good sense eventually
Speaker 2: to stop writing books because I think, if anything, maybe
Speaker 2: reading Freakonomics it made people feel smart because it was
Speaker 2: really easy to read. It was written at the seventh
Speaker 2: grade level, but it kind of invited you inside of
Speaker 2: academia in a way that was more fun and unusual
Speaker 2: compared to other books. Look, nobody really knows why it worked.
Speaker 2: I'm sure if we did it again it wouldn't work,
Speaker 2: but we were super lucky.
Speaker 1: You said it invited people into academia in a way
Speaker 1: that made it seem really fun. Is academia really fun?
Speaker 1: I mean, you recently announced that you're leaving academia and
Speaker 1: listening to conversations you've had about that, not only are
Speaker 1: you leaving academia, but you kind of wish you'd left
Speaker 1: academia a long time ago. So what is it about
Speaker 1: academia that, if anything, that ever was fun and why
Speaker 1: did it stop being fun?
Speaker 2: The fun part about Academia for me is the freedom
Speaker 2: to pursue ideas and the ability to tackle things you
Speaker 2: don't know anything about, and then to take the time
Speaker 2: to learn about them, and to have the freedom to fail,
Speaker 2: to not have a boss. Sometimes it's an incredible gift.
Speaker 2: In another sense, it's complete travesty because it leads many
Speaker 2: people to be very unproductive and get paid very well
Speaker 2: for many, many years. Now, that is all really fun.
Speaker 2: I think what's not fun for me about academia is
Speaker 2: that the standard of evidence is sky high. So when
Speaker 2: you try to publish your work, you've got referees whose
Speaker 2: job is to find every possible hole in the paper,
Speaker 2: and there's an incredible bias there for in academics the
Speaker 2: answering very small questions very very convincingly, and ultimately I
Speaker 2: didn't find that so exciting because anytime there was a
Speaker 2: little bit of uncertainty, not that you thought it was wrong,
Speaker 2: you're ninety seven percent sure that you're right, And even
Speaker 2: the referees are ninety seven percent sure they're right. Their
Speaker 2: whole job, all of their incentives, is to poke holes,
Speaker 2: and the editor's job is not to get called out
Speaker 2: later for having published a paper that's wrong. All of
Speaker 2: the work goes into trying to polish off that last
Speaker 2: one or two percent of certainty. It's really not fun
Speaker 2: and it drives you away from tackling big problems. And
Speaker 2: so for me, ultimately, I found it really fun to
Speaker 2: be in the real world after fre economics. So many
Speaker 2: doors opened up. I got to talk to people like you,
Speaker 2: and it just showed me how big the world was
Speaker 2: and how many exciting things there were to do. And personally,
Speaker 2: the part I like best about ideas is coming up
Speaker 2: with them and testing them until I'm eighty five percent
Speaker 2: sure they're right. That's good enough for me, and then
Speaker 2: I like to move on to the next thing. And
Speaker 2: so the real world is a much better lab for
Speaker 2: doing that than academics.
Speaker 1: You were talking about in another interview about your experiences
Speaker 1: at the University of Chicago. The Economic department at the
Speaker 1: University of Chicago was very famous, lots of Nobel Prize winners.
Speaker 1: But some of the stories you were telling about what
Speaker 1: sounded like a really toxic culture, a lot of bullying.
Speaker 1: It sounded really really bad.
Speaker 2: Actually, most of my colleagues were wonderful, but the monster
Speaker 2: in my case is this guy Jim Heckman, who's a
Speaker 2: brilliant economist, a Nobel Prize winner. But just to give
Speaker 2: you an example, at some point he just started to
Speaker 2: hate me. But the most extreme thing you ever did
Speaker 2: was to start a seminar series. And typically the seminar
Speaker 2: series and academics are like macreeconomics, macreconomics, law and economics, trade,
Speaker 2: things like that, and we only invite academics and usually
Speaker 2: pretty esteemed academics to come and visit and talk. The
Speaker 2: seminar that he put into place, the only requirement to
Speaker 2: speak in that is that you had to hate me
Speaker 2: and have written something critical about me. And it was
Speaker 2: completely absurd, and eventually the powers that be made him
Speaker 2: stop doing it. But there's a core exam that every
Speaker 2: first year student has to pass in order to stay
Speaker 2: into the program, and it would be completely standard that
Speaker 2: the question he would put on would be discuss what's
Speaker 2: wrong with Steve Levitt's work, which, of course what's the
Speaker 2: GRATTU students in a terrible position because they have no
Speaker 2: choice except to say everything that is supposedly wrong with
Speaker 2: my work, when maybe they want to actually be my student.
Speaker 2: But it was an extremely rambunctious and difficult environment. The
Speaker 2: idea at some level was that that kind of roughness
Speaker 2: would lead to big breakthroughs in scholarship.
Speaker 1: Do you think it does?
Speaker 2: You know, I don't think so. I think what is
Speaker 2: good for a scholarship is that people will tell you
Speaker 2: the truth about what they think about your work. But
Speaker 2: I think it also helps if you do it nicely.
Speaker 2: And there are amazing scholars at the UFC Economics devironment.
Speaker 2: But when we were completely dysfunctional, you know, a lot
Speaker 2: of people were winning Nobel prizes, and in part it
Speaker 2: was because Chicago was willing to take folks who were
Speaker 2: thinking about things differently and to invite them in and
Speaker 2: it didn't have to come at such a high cost
Speaker 2: personality wise.
Speaker 1: Obviously, Jim Hackwin's not on the podcast to give his
Speaker 1: side of the story, No doubt he would describe everything
Speaker 1: in his own way, but just to leave academia behind
Speaker 1: on a high before we move on, what's the academic
Speaker 1: paper you've written that you're most proud of?
Speaker 2: So I wrote this paper and abortion in Crime got
Speaker 2: enormous amounts of attention. And the idea is that unwanted
Speaker 2: children are at risk for crime. Okay, and that's I
Speaker 2: think very well documented from decades of social science research
Speaker 2: that if your mother doesn't love you, your life is
Speaker 2: going to be difficult on many dimensions. And so we
Speaker 2: applied that very simple logic to the changes in abortion
Speaker 2: laws in the US, the legalization abortion, and we showed
Speaker 2: that pretty credibly a huge share of the declining crime
Speaker 2: that happened in the nineteen nineties was due to the
Speaker 2: legalization of abortion. Okay, At the end of that first paper,
Speaker 2: we in our conclusion said, well, because abortion only affects
Speaker 2: crime with a twenty year lag, we can see as
Speaker 2: we write this paper the predictions we can make about
Speaker 2: what will happen to crime over the next twenty years,
Speaker 2: and we predict that crime will continue to fall in
Speaker 2: the US about one percent a year for the next
Speaker 2: twenty years. So the paper I'm most proud of it
Speaker 2: is that twenty years later, John Donnie, who was my call,
Speaker 2: and I said, Hey, we made that prediction twenty years ago,
Speaker 2: why don't we go test it. Let's see if it
Speaker 2: really worked. And it was different from a typical academic
Speaker 2: paper because number one, we had exactly the hypothesis we've made.
Speaker 2: We knew exactly what we were testing, and number two.
Speaker 2: We had a set of tables we had used in
Speaker 2: the initial paper that we said, look, well, exactly replicate
Speaker 2: that methodology. So we'll get twenty years of data that
Speaker 2: is completely out of sample, and we'll just see what
Speaker 2: happens in the data. And what was so interesting is
Speaker 2: that the data over those next twenty years were completely
Speaker 2: consistent with our hypbotsis, I think, better even than we
Speaker 2: had expected. And I do not know any economist who
Speaker 2: has made a prediction and waited twenty years and then
Speaker 2: seen whether that prediction came true and done it with
Speaker 2: a real scientific rigor. And it was so confirming to
Speaker 2: me of what we had done. And in some sense though,
Speaker 2: my deep pride about that paper also led to my
Speaker 2: exit from the profession because nobody cared. We couldn't get
Speaker 2: academics to care. We couldn't get it published easily. I mean,
Speaker 2: I sent it back to the original journal that our
Speaker 2: first paper had been polished in, and the responsors, well,
Speaker 2: we don't really publish simple papers like that anymore. And
Speaker 2: so it really pointed to me that what was important
Speaker 2: to me and what I thought was exciting about academics,
Speaker 2: there was no market for that anymore. And when there's
Speaker 2: no market for what you're making. It's a really good
Speaker 2: idea to exit, and that's what I did.
Speaker 1: You're listening to Cautionary Tales with me, Tim Harford and
Speaker 1: my special guest, Steve Levitt. When we come back, we'll
Speaker 1: be talking about how to teach maths in a way
Speaker 1: that makes it exciting. We're back, and I'm here with
Speaker 1: Steve Levitt. Steve, when you were at Chicago University, you
Speaker 1: founded the Center for Radical Innovation for Social Change. It's
Speaker 1: quite a grand sounding title.
Speaker 2: I just call it RISK. I barely remember what it
Speaker 2: says for anymore.
Speaker 1: Okay, Oh yeah, Radical Innovations has changed RISK. Yeah, I
Speaker 1: got it. Okay, So you were just aiming for the backronym.
Speaker 1: Now I understand what were you trying to do with
Speaker 1: that center.
Speaker 2: I had gotten tired, as we've talked about already about
Speaker 2: what was going on in academics. But I wanted to
Speaker 2: try to do something that put together the best of academics,
Speaker 2: so real rigor based on innovative ideas and unpopular ideas.
Speaker 2: I didn't want to shy away from things that were unpopular,
Speaker 2: as academics don't have to shy away from unpopular things.
Speaker 2: Mixed that with a kind of startup feel and with
Speaker 2: a philanthropic feel to try to go out and solve
Speaker 2: really big, important problems, often problems that regular nonprofits couldn't
Speaker 2: tackle because the ideas might be repugnant or unpopular. I
Speaker 2: guess it's been six or seven years now we've been
Speaker 2: at it, and like it's hard, it's hard to make
Speaker 2: real world change, but I think we finally got two
Speaker 2: or three successes on the book that we can feel
Speaker 2: pretty good about. For example, for a long time we've
Speaker 2: been working on the issue of kidney donations, and so
Speaker 2: in the US, in particularly, there's this huge waiting list
Speaker 2: of people who are on dialysis who need a kidney,
Speaker 2: and there's a tremendous shortage of donors for kidneys. In
Speaker 2: large part that is because it is against the law
Speaker 2: to compensate financially people for giving their kidneys. It all
Speaker 2: depends on altruism. So economists disagree with most people in
Speaker 2: the sense that we think that doesn't make sense. That
Speaker 2: done well, we could give financial incentives for kidneys and
Speaker 2: it would make the world a much better place. And
Speaker 2: the value of a kidney to the recipient and to
Speaker 2: the government who's paying for the dialysis is huge, hundreds
Speaker 2: and hundreds of thousands of dollars. So we could offer
Speaker 2: donors hundreds of thousands of dollars and still it would
Speaker 2: be worth doing the transplant operation. And so the ethical
Speaker 2: issues around kidney donation are such that people say, well,
Speaker 2: we can't really have a mare market for kidneys because
Speaker 2: the market price is ten thousand dollars, and that'll be
Speaker 2: expectation of the poor, but it's not exploitation. If you
Speaker 2: actually pay people two hundred thousand dollars for kidneys, then
Speaker 2: what you have is you have a list of seven
Speaker 2: million people all signed up begging to give their kidney.
Speaker 2: I tried to do that for years and I failed.
Speaker 2: But as part of risk, as we were trying to
Speaker 2: push that adenda, we were just learning a lot about kidneys.
Speaker 2: And one of my young people we really hire, really
Speaker 2: twenty really talented twenty two year olds to come and
Speaker 2: work with. He was talking with some doctors and actually
Speaker 2: maybe watching an intake of a potential dollar. What he
Speaker 2: realized was that it turns out that of every one
Speaker 2: hundred people who show up and say I would like
Speaker 2: to donate a kidney, in the end, only about three
Speaker 2: of them make the donation, and fully forty percent of
Speaker 2: those are kicked out of the process because they're either
Speaker 2: too heavy or they smoke, and those are two things
Speaker 2: that will make doctors unwilling to do the transplant. And
Speaker 2: he had this incredibly simple idea. He said, hey, why
Speaker 2: don't we work with the transplant centers and when someone
Speaker 2: comes in and the weight is too high, instead of saying, hey,
Speaker 2: you can't donate, we'll just have the transplant center say hey,
Speaker 2: you can't donate yet, but if you lose weight, you could.
Speaker 2: And there's this group called Risk that will for free
Speaker 2: help you lose weight. So all we did was just
Speaker 2: work with transplant centers, give them flyers and say send
Speaker 2: people our way. And all we would do was just
Speaker 2: give them free access to weight watchers, and we would
Speaker 2: have a young person who would text them and try
Speaker 2: to give them moral support and be a cheerleader to
Speaker 2: help them lose weight. And it seems really silly and
Speaker 2: really simple and so obvious that how could it make
Speaker 2: any difference. But on a shoestring budget, our little group
Speaker 2: has led to sixty extra kidney donations over the last
Speaker 2: year and a half. And that's sixty lives changed or saved,
Speaker 2: and the cost per life saved is something like five
Speaker 2: thousand dollars. It is about the best intervention that anyone
Speaker 2: has ever seen from a simple cost benefit and it's
Speaker 2: totally obvious. Why was no one else doing it? We're
Speaker 2: not sure, but it's a really simple insight that led
Speaker 2: to a big impact, and at scale, we could be
Speaker 2: doing thousands of these per year. We really did it
Speaker 2: almost as a pilot, and now we're trying to figure
Speaker 2: out how we can make it really transformational in the
Speaker 2: kidney space. So that's one example of a success. I'd
Speaker 2: say another one that is really interesting to a sale.
Speaker 2: Con of the con Academy and with Arizona State University,
Speaker 2: we helped start in online school, and you know, we
Speaker 2: had various ideas about what we thought was wrong with
Speaker 2: the way current high schools are run in the US,
Speaker 2: and it turned out that the online school was incredibly
Speaker 2: successful in terms of test scores. And what we've learned
Speaker 2: is that the idea that there'd be a teacher standing
Speaker 2: in front of twenty five or thirty students lecturing them
Speaker 2: about things, that turns out to be roughly the least
Speaker 2: efficient way to learn that you can come up with,
Speaker 2: and the only reason we do it is because it's
Speaker 2: the technology. We had to do it in the eighteen
Speaker 2: fifties when public education got going. And so now we're
Speaker 2: launching an in person school at brick and mortar School.
Speaker 2: So I can't say it's going to be success that
Speaker 2: because it has happened, but I have every reason to
Speaker 2: believe that we are going to be able to deliver
Speaker 2: a high school experience that is staggeringly better than what
Speaker 2: is being done right now in terms of what kids learn,
Speaker 2: how enjoyable it is to them. That we will build
Speaker 2: in creativity rather than drive creativity out. And so for me,
Speaker 2: that is the single most important and interesting and inspiring
Speaker 2: thing I'm working on right now. Is I just believe
Speaker 2: that we are at the right moment post COVID to
Speaker 2: create a completely different model for how we teach and
Speaker 2: how we learn. And I hope that this is something
Speaker 2: I'll do till the day I die, and that more
Speaker 2: than freakonomics, that this will be my legacy.
Speaker 1: You and I both have an interest in maths or
Speaker 1: math as I guess you would say, what do you
Speaker 1: think that we get wrong in the way the young
Speaker 1: people are taught to engage with numbers.
Speaker 2: So I think what we do up through about the
Speaker 2: age of twelve or thirteen is not that bad. I
Speaker 2: think knowing how to add and subtract and divide and
Speaker 2: do fractions and things like that is just the basic
Speaker 2: skill in life that you need and everyone should have that.
Speaker 2: And like I don't think we do in the most
Speaker 2: efficient way, but at least we have our eye and
Speaker 2: the prize up through about the age of thirteen. High
Speaker 2: school math, on the other hand, I think is a
Speaker 2: complete horror show because we ask children to do a
Speaker 2: whole bunch of math, which is complicated based on doing
Speaker 2: computations that nobody does anymore. So one of the things
Speaker 2: that I watch all of my high school kids do
Speaker 2: is try to learn how to compute the minimums and
Speaker 2: maximums or the zeros of polynomials. And that is something
Speaker 2: that they did in Hidden Figures, that movie about getting
Speaker 2: but to the Moon, because we didn't have good computers
Speaker 2: and so people had to do that. But since computers
Speaker 2: came in, there's not a person on the planet who's
Speaker 2: had to do that manually other than a high school student.
Speaker 2: And we try to teach kids how to do proofs.
Speaker 2: Again great, I think knowing how to prove things is wonderful,
Speaker 2: But we make them prove all sort of things about
Speaker 2: triangles that who cares about. Back in ancient Greece, it
Speaker 2: was important to know things about triangles. Now it really isn't.
Speaker 2: What do people actually use in their daily life. They
Speaker 2: add and subtract, They do simple arithmetic, and that's good
Speaker 2: because they've usually learned that, and then they analyze data.
Speaker 2: They use spreadsheets, They have to make sense of complicated relationships,
Speaker 2: and we do almost none of the teaching of that
Speaker 2: in high school. And so data science might call it
Speaker 2: data analytics. That those are the skills that people need,
Speaker 2: and I believe we should teach people the things that
Speaker 2: they will use. Many of the hardcore mathematicians get upset.
Speaker 2: They say, oh, we're not teaching deep math. But I
Speaker 2: would tell you there's very deep math in data science
Speaker 2: and a lot of artistry and a lot of judgment.
Speaker 2: And another thing that we've been doing at my Risk
Speaker 2: Center is we ended up launching something called Data Science
Speaker 2: for Everyone, which has become the leading think tank everything
Speaker 2: group that's trying to change the way we teach math
Speaker 2: to incorporate data science in the United States, and it's
Speaker 2: been really, really quite successful.
Speaker 1: I'm sure you know. Steve Strogatz has this idea that
Speaker 1: colleges should teach math appreciation. We have art classes where
Speaker 1: you teach people to draw. You have art appreciation where
Speaker 1: you teach people the history and you know, you get
Speaker 1: people to look at pretty pictures and discuss like why
Speaker 1: they're such studying works of art. And he suggested for
Speaker 1: some students, Okay, fine, they're not going to calculate a
Speaker 1: lot of stuff. They're not going to be high powered
Speaker 1: mathematicians or statisticians, but they could still have an appreciation
Speaker 1: of how math works, how data works. I guess fre
Speaker 1: economics should be on the course, right. It's an example
Speaker 1: of data appreciation. It doesn't really tell you the details
Speaker 1: of how your detective work was done, but it gives
Speaker 1: you a sense of the kind of things you were
Speaker 1: doing and the kind of things that you could do
Speaker 1: if you had control of the data.
Speaker 2: Steeve Shortts and I have talked a lot about that.
Speaker 2: Actually worked with the State of Utah in the United
Speaker 2: States to try to implement some of those ideas, and
Speaker 2: we're just getting gone. We'll see how that works. The discoveries.
Speaker 2: The process of the history of math, I think is
Speaker 2: actually fascinating once you get into it.
Speaker 1: Yeah.
Speaker 2: But the real power of this idea of appreciation is
Speaker 2: with young people, because so many twelve and thirteen year
Speaker 2: olds are right at the point where they're deciding, oh, oh,
Speaker 2: I'm not a mass person. That's not for me, and
Speaker 2: then they check out. And that's because they don't understand
Speaker 2: why they're doing this complex math, and which makes sense
Speaker 2: because I don't really understand why they're doing their complex math.
Speaker 2: But on the other hand, if you instead focused with
Speaker 2: young people and saying, hey, here's what's amazing about math.
Speaker 2: Here's how math is useful, here's how math is a
Speaker 2: form of storytelling, or here's how math is the language
Speaker 2: of the universe. I mean my own high school kids.
Speaker 2: They just thought, well, the teacher told me I do
Speaker 2: this this and this the answer, and so I do that.
Speaker 2: But they didn't really understand it is true that if
Speaker 2: you would do a different galaxy, it would also be true.
Speaker 2: And so I think the idea, the most powerful part
Speaker 2: of the appreciation idea is to take people who are
Speaker 2: still trying to figure out who they are. They don't
Speaker 2: know who they are, and they're making these choices, and
Speaker 2: if they say, WHOA, maybe math is fun, then they
Speaker 2: won't close off the path to eventually maybe saying that
Speaker 2: math could be a part of your career from they
Speaker 2: don't have to be afraid of science, and so that's
Speaker 2: where I think the idea has its real leg.
Speaker 1: You're listening to Cautionary Tales with me, Tim Harford and
Speaker 1: my guest Steve Levitt. After the break, we'll be talking
Speaker 1: about Steve's very own podcast. People I mostly admire to
Speaker 1: ask you about podcasting. When you and Dubna launched the
Speaker 1: Freakonomics radio podcast, I remember thinking, what are they doing.
Speaker 1: They've created this unbelievably successful brand. People love the books,
Speaker 1: they got a New York Times column, But podcasting, you're
Speaker 1: going to spend your time podcasting. Obviously that worked out
Speaker 1: pretty well. So you guys were really ahead of the
Speaker 1: curve there.
Speaker 2: I was in the exact same boat as you were
Speaker 2: when when Duminy said I'm gonna start a podcast. I
Speaker 2: think I said, what's a podcast? This wants what? Fifteen
Speaker 2: years ago He's one of the really early podcasters, and
Speaker 2: I thought it was the silliest idea. He would say Hey,
Speaker 2: can you come on my show? Could I interview you?
Speaker 2: And I'd always do it, It's really out of sympathy
Speaker 2: for him. And then I remember if we were on
Speaker 2: a book tour, and I suppose it must have been
Speaker 2: for our third book, Thinks Like a Freak And Dumna
Speaker 2: said to me, Hey, how many downloads do you think
Speaker 2: I get a month for Freakonomics? And I didn't want
Speaker 2: to hurt his feelings, so I said, I don't know,
Speaker 2: maybe ten thousand and fifteen thousand. I really thought it
Speaker 2: was probably five hundred, but I didn't want to say
Speaker 2: that and make him think I had a low opinion
Speaker 2: and said, oh no, it's actually over a million. I
Speaker 2: said over a million a month, and he said yeah,
Speaker 2: and I couldn't believe it. And that was one of
Speaker 2: those epiphanies, those moments of truth where you say, wait
Speaker 2: a second, So in a year, you have twice as
Speaker 2: many downloads of the podcast we've ever sold the books,
Speaker 2: even though we had a really excis book, and it
Speaker 2: really opened my eyes that as a vehicle for talking
Speaker 2: about ideas, it is amazing. And so I never could
Speaker 2: have imagined that I would end up doing my own
Speaker 2: podcast But when I decided that I wanted to leave academia,
Speaker 2: I thought, well, you know, for twenty five for thirty years,
Speaker 2: I've been so hell bent on being a producer of ideas.
Speaker 2: I literally spent all my time trying to come up
Speaker 2: with grade economic ideas that I had closed myself off
Speaker 2: completely to learning or knowing about any anything else. And
Speaker 2: I said, I just want to relax for a while
Speaker 2: and be a consumer. And a podcast was a way
Speaker 2: that I could convince all sorts of amazing people to
Speaker 2: come and talk to me, Nobel Prize winning chemists and things,
Speaker 2: that I could just have the joy of having really
Speaker 2: amazing conversations with incredible people and completely switch my own
Speaker 2: role from being the person who's supposed to be the
Speaker 2: genius to being the person who doesn't know anything. And
Speaker 2: this is asking the questions and got I've I found
Speaker 2: him very comfortable with that second role. I love being
Speaker 2: the person who doesn't know anything. And then he's trying
Speaker 2: to extract information from experts. And one of the things
Speaker 2: I've learned is that many experts are incredibly bad at
Speaker 2: explaining what they do and making it approachable. And I
Speaker 2: think one of my real talents is that I'm pretty
Speaker 2: good at hearing something complex, grasping on to the end
Speaker 2: of a string and on it until I can get
Speaker 2: people to explain things in ways that I and other
Speaker 2: regular people can understand.
Speaker 1: The podcast is called People I mostly admire, and it's
Speaker 1: a really wonderful podcast. I love listening to it. I'm
Speaker 1: sure you'll take this as a compliment. You are quite
Speaker 1: a weird interviewer in a way that it's hard to
Speaker 1: put my finger on exactly what it is. But I
Speaker 1: think it is partly this. You don't mind appearing like
Speaker 1: you don't know what you're talking about. You don't mind
Speaker 1: seeming a little bit stupid, and I think it's because
Speaker 1: actually everybody knows you're not stupid. You're a professor at Chicago.
Speaker 1: You want all these prizes, so you don't mind asking
Speaker 1: the dumb questions. There's an artlessness about it, which I
Speaker 1: really like.
Speaker 2: I'm very antisocial in general, and I have very little
Speaker 2: human interaction. But for these podcasts, I come prepared and
Speaker 2: I think I ask them different questions and they're used
Speaker 2: to being asked sometimes, and sometimes because of that, it
Speaker 2: gets very personal and we end up talking about things
Speaker 2: that might be seen as out of bounds, but build
Speaker 2: this strange bond. And for me, that's what is completely unexpected.
Speaker 2: But there's something about the artificiality of a podcast interview
Speaker 2: that allows this emotional connection. You wouldn't expect it, but
Speaker 2: that's how I judge whether a podcast episode is successful.
Speaker 2: And it happens often in the most unexpected, strange ways,
Speaker 2: and that's but so fun about it for me.
Speaker 1: Yeah, there's definitely some podcasts you listen to that you're
Speaker 1: clearly just like having the best time. I mean, there's
Speaker 1: an incredible podcast where you interviewed your daughters, which is
Speaker 1: not a normal podcast behavior for a podcast like people,
Speaker 1: I mostly admire you interviewing all these academics, and there's
Speaker 1: one point where you're in tears. She's in tears. I'm listening.
Speaker 1: I'm in tears. I mean that, you know, it's it's
Speaker 1: heavy stuff. It was an incredible interview.
Speaker 2: So yeah, I did interview my two oldest daughters, and
Speaker 2: one of my daughters was anorexic, seriously inerrexic in hospitalized
Speaker 2: in your death. And we never really talk about the
Speaker 2: deepest issues in regular life because there's always some excuse
Speaker 2: not to. But the idea that we would sit down
Speaker 2: in a recording studio and for you know, an hour,
Speaker 2: she and I would talk and it was a conversation
Speaker 2: that for me is so special, and honestly, we hadn't
Speaker 2: had a conversation ever before that, and we really haven't
Speaker 2: had a conversation ever that special since. Again, it was
Speaker 2: this weird thing about it being an interview being a
Speaker 2: podcast that somehow got us to open up. And I
Speaker 2: have to say, I'm so glad that I did that.
Speaker 2: Everyone else thought it was a terrible idea. My producer
Speaker 2: thought it was a terrible idea. I wasn't sure if
Speaker 2: it work or not, but it was really magical and
Speaker 2: I think it it's pulled my daughter, Lily and I
Speaker 2: closer together than we ever would have been otherwise. But again,
Speaker 2: it's almost like that initial freakonomics somehow captured light thing
Speaker 2: in a bottle. It's the right thing at the right time,
Speaker 2: and that conversation with Lily was just I'm so glad
Speaker 2: that I had that, and I think I don't really
Speaker 2: have it enemy to have those kind of conversations with
Speaker 2: her outside of that setting. It was the artificiality that
Speaker 2: somehow allowed both of us to open up in a
Speaker 2: way we don't.
Speaker 1: Usually you're kind of trapped. You might make an excuse
Speaker 1: and walk away from the conversation. But yeah, I wanted
Speaker 1: to ask you, Steve, about your perspective on parenting. And
Speaker 1: when I first met you, I was about to become
Speaker 1: a dad for the first time. That my oldest daughter
Speaker 1: is is slightly younger than freakonomics. You have been through
Speaker 1: some very difficult experiences as a parent. You lost your
Speaker 1: youngest son when he was very young, this experience with
Speaker 1: your daughter Lily, who was so ill. But you know,
Speaker 1: you're still going. You've got a young family, you've got
Speaker 1: more children under the age of five. You've got a
Speaker 1: chance to do it all again. And I just think
Speaker 1: people who have had to deal with these really difficult
Speaker 1: challenges learn something that those of us who get a
Speaker 1: bit more lucky and don't have to deal with so much,
Speaker 1: maybe we don't learn. So I just wanted to get
Speaker 1: your thoughts on what you've learned from everything.
Speaker 2: Well, I really thought after I went through my older
Speaker 2: children and then I did it, she said, I started
Speaker 2: a new family. Oh my god, all the lessons I learned,
Speaker 2: I'm going to be such a better parent. The second around,
Speaker 2: and two things happened. Number One, I realized I was
Speaker 2: so tired as first kids, I can barely remember what
Speaker 2: I did. And number two, in the actual practice of it,
Speaker 2: I literally made all the same mistakes, and it was
Speaker 2: really disappointing to me. I have two simple pieces of
Speaker 2: ice about parenting, one of which I take and the
Speaker 2: other which I don't take, even though it's my own advice.
Speaker 2: The first simple one is that I believe that if
Speaker 2: your kids feel loved, most other things will take care
Speaker 2: of themselves. I don't do a lot of helicoptering of
Speaker 2: my kids. I don't care whether they are good at school,
Speaker 2: and I don't push them or pressure them anyway. I
Speaker 2: think that's so much less important than just having kids
Speaker 2: who can see and know that you love them deeply
Speaker 2: and that no matter what happens, you're going to be
Speaker 2: behind them. So that's the piece of advice that I
Speaker 2: actually do a good job of parenting. The thing I
Speaker 2: don't do whish I wish I would do is not
Speaker 2: trying to do other things while you parent. What I
Speaker 2: do all day long is I have take care of
Speaker 2: my kids, and I have work on my podcast or
Speaker 2: my new school, and it's frustrating to everyone, and it's
Speaker 2: no fun at all. And whenever I have the discipline,
Speaker 2: which isn't very often, to say, hey, for the next
Speaker 2: four hours, I'm going to sit with my and I'm
Speaker 2: not even gonna think about anything else. I'm just gonna
Speaker 2: be with them and let them dictate what happens. I'm
Speaker 2: always happier, it's always more rewarding. The kids love it.
Speaker 2: It's good for me. I have such a lack of
Speaker 2: discipline that I cannot do that on a regular basis.
Speaker 2: There is just this outside pulls, I mean, are so strong.
Speaker 2: But if I were to give advice to others, if
Speaker 2: you're gonna work work, if you're gonna be with the kids,
Speaker 2: to be with the kids, try not to do both
Speaker 2: at once.
Speaker 1: Steve, thank you so much for joining us on caution retales.
Speaker 2: Oh, thank you, Jim. It's all so good. We got
Speaker 2: to do this more often.
Speaker 1: Yeah, I'll take you up on that. I'm sure this
Speaker 1: conversation would have whetted your appetites to hear Steve interview
Speaker 1: a huge variety of guests on his podcast, people I
Speaker 1: mostly admire. You can of course find that anywhere you
Speaker 1: get your podcasts. As for caution Retaales. We will be
Speaker 1: back very soon in your feed with another of our episodes.
Speaker 1: For a full of our sources, see the show notes
Speaker 1: at Timharford dot com. Cautionary Tales as written by me
Speaker 1: Tim Harford with Andrew Wright, Alice Fines and Ryan Dilly.
Speaker 1: It's produced by Georgia Mills and Marilyn Rust. The sound
Speaker 1: design and original music are the work of Pascal Wise.
Speaker 1: Additional sound design is by Carlos san Juan at Brain Audio.
Speaker 1: Bend ad af Haaffrey edited the scripts. The show features
Speaker 1: the voice talents of Melanie Guttridge, Stella Harford, Oliver Hembrough,
Speaker 1: Sarah Jupp, massaam Unroe, Jamal Westman, and Rufus Wright. The
Speaker 1: show also wouldn't have been possible without the work of
Speaker 1: Jacob Weisberg, Greta Cohne, Sarah Nix, Eric Sandler, Carrie Brody,
Speaker 1: Christina Sullivan, Kira Posey, and Owen Miller. Cautionary Tales is
Speaker 1: a production of Pushkin Industries. It's recorded at Wardore Studios
Speaker 1: in London by Tom Bearry. If you like the show,
Speaker 1: please remember to share, rate and review. It really makes
Speaker 1: a difference to us and if you want to hear
Speaker 1: the show, add free sign up to Pushkin Plus on
Speaker 1: the show page on Apple Podcasts, or at pushkin dot fm,
Speaker 1: slash plus