Maintenance Phase - Bonus： Mike's New Podcast!

00:00:00.000 wait our cameras are still on i've never seen you do this in person before it's weird

00:00:15.580 you're like i don't like it i was like why does this feel weird

00:00:18.260 uh hi everybody and welcome to maintenance phase or as we call it if diet books could kill

00:00:25.380 oh that's good right thank you that's actually a better name than we have

00:00:29.320 actually we should have done that why didn't we think of this before uh i'm aubrey gordon i'm

00:00:34.120 michael hobbs and today we are bringing you a fun little treat fun little treat michael hobbs has a

00:00:40.480 new show if you have not already heard it mike's side chick yeah i don't know if they still say 0.88

00:00:46.820 that probably not i say if you haven't heard it yet because so many fucking people have heard it 0.75

00:00:54.680 michael it's been a really weird week so starting like i told you about this project i don't know 0.77

00:01:01.580 nine months ago or something yeah it's been almost all year a very long time so people who know me

00:01:07.880 and know the show and know my like weird little personality know that i'm like fascinated by bad

00:01:13.120 ideas and earlier this year i started thinking about how to do a podcast about the most wrong

00:01:20.600 and harmful ideas of the last 50 years, because I feel like we're just awash in like bad ideas.

00:01:26.620 And so I started talking to my friend Peter Shamsheri, who co-hosts the 5 to 4 podcast

00:01:31.200 about why the Supreme Court sucks, which is an excellent podcast if you're not already

00:01:34.900 listening to it. And we decided that the best way to dissect the worst ideas is to go through like

00:01:40.820 airport books one by one. These have become one of the main vectors for bad history and bad

00:01:48.120 statistics and misinformation. And we have for the last couple months been recording episodes

00:01:54.240 about the most harmful airport books of all time. And now we have a podcast about it called

00:01:59.580 If Books Could Kill. It's my favorite podcast title that I've heard in like a while. It is not

00:02:05.440 mine. It came from the same friend who told me to start a podcast about the history of fishing

00:02:11.120 called cod past this person is a fount of ideas if you need a title for your podcast let me know

00:02:18.880 and i'll get you in touch and yeah we launched this week and like whatever i put it on twitter

00:02:24.220 peter put on twitter you tweeted about it we put on instagram whatever and within 24 hours it was

00:02:29.600 the number one podcast on apple podcasts number one michael hobbs number two rachel maddow i know

00:02:37.580 me and uh me and rachel if you could introduce me that would be great and you know that my

00:02:42.520 immediate reaction to like any form of attention is just pure panic of course like losing my mind

00:02:50.040 all week i'm like oh fuck people are listening no i have been with you at a point when we got 0.99

00:02:56.560 recognized and i have watched you try to recede into your own body like a turtle 0.99

00:03:01.960 that is what i have been doing the last three days conceptually yeah i think you and i have

00:03:12.560 this in common which is like a deep desire to correct the narrative and like zero desire for

00:03:16.920 the attention that comes with correcting the narrative i feel very weird about being a person

00:03:20.460 on the internet as you as you know very well yes uh so our first episode is about freakonomics

00:03:27.480 It's such a joy. So you and I talked about this when you started working on it. We talked about like a couple of episode concepts. And I think it was last week before the show came out. You sent me the Freakonomics episode and just like it has just been like hockey stick growth for my enthusiasm for this show getting out into the world.

00:03:48.160 you mentioned that you have a fascination and sort of a fixation on bad ideas i would say

00:03:53.880 my observation of you is it's not just bad ideas it's bad ideas that take off and people get

00:04:00.360 attached to yes and i struggle to think of a wilder more entrenched uh sort of airport book

00:04:10.520 set of bad ideas than the ones in freakonomics it's incredible i'm so fucking happy for you

00:04:16.220 buddy and i'm so excited for this show to be out into the world and i'm so excited for our listeners

00:04:21.480 to have like our number one request is can you get us more shows and our number one response to that

00:04:26.840 is no yeah yeah but like now there's another outpost for more content and i'm very excited

00:04:33.640 about that so the podcast is available wherever you get your podcasts and we'll leave links in

00:04:40.020 the description and we'll also link aubrey's book in the description delightful and we'll see you

00:04:44.680 next week. We'll see you next week. Peter. Michael. What do you remember about a book

00:04:51.160 called Afrikonomics? If I recall correctly, the thesis of the book is had my mother aborted me,

00:04:57.600 I would not have committed so many crimes.

00:05:14.680 All right. Welcome to If Books Could Kill.

00:05:18.460 Premier episode.

00:05:19.200 Are we taglining this, Mike?

00:05:20.420 I don't think so. I think that was the tagline. I don't know.

00:05:22.680 Yeah.

00:05:22.980 I've done that for two shows already.

00:05:24.440 Need a new thing.

00:05:25.580 Yeah. The dumb books that captured our collective imagination. 0.99

00:05:30.940 Yes. The books that did to our brains what Jigsaw did to Robin Hood. 1.00

00:05:35.940 I'm Michael Hobbs. I'm a journalist and the co-host of Maintenance Phase.

00:05:39.300 I am Peter Shamsheree. I am a lawyer and the co-host of the 5 to 4 podcast.

00:05:47.060 Both of us are fascinated by dumb ideas and how they spread through the population. And so a 0.92

00:05:52.420 couple months ago, we started talking about how to do a podcast about the dumbest ideas of the 0.98

00:05:57.040 last 50 years. And the more we thought about it, the more we realized that like a good way to do

00:06:01.980 it would be by going through airport books, which are kind of like the super spreader events at this 0.96

00:06:08.980 point of american stupidity yeah they're they're the natural vessel for pseudoscience and fake 0.91

00:06:15.580 history uh and just sort of quintessentially american you know all of this complex knowledge 1.00

00:06:22.300 and information boiled down into a mush and packaged and sold for 24.95 to people who forgot

00:06:30.340 to charge their kindle for the flight this is the seventh episode that we've recorded but the first

00:06:35.660 episode that we're releasing because i started reading freakonomics and then i realized that

00:06:41.380 this book is the perfect overture the quintessential airport book the quintessential

00:06:46.520 like wrong and bad airport book it's like really shocking how bad this book is and it's also like

00:06:54.280 the badness of the book is also matched by like how influential it was right what do you actually

00:06:59.700 remember about the book itself and like the era it comes out in 2005 is that right 2005 yeah okay

00:07:04.880 So in the 80s, you have sort of like the Chicago school economists who start to like posit all of these theories that are that basically boil down to like we can solve most social problems with like economics principles.

00:07:19.520 And then you get something like Freakonomics, which feels like the mainstreamification of that concept, right?

00:07:26.580 Just taking that sort of nihilistic, neoliberal sort of viewpoint and bringing it to the masses.

00:07:35.180 Exactly. I mean, you cannot underestimate how popular this book was.

00:07:39.120 So it sold 4 million copies. It was on the bestseller list for 39 weeks.

00:07:44.420 I think an underrated aspect of this book's influence is the fact that they had a New York

00:07:50.040 Times blog and a podcast like five years before Serial. I mean, I listened to that podcast for

00:07:56.080 years. Like there wasn't that much else to listen to. It was like this or fucking Ricky Gervais.

00:08:02.460 And it's like, that's what you listened to when you were washing dishes. I also think the subtitle 0.99

00:08:06.920 of the book is important because it's a rogue economist explores the hidden side of everything.

00:08:12.820 like this guy's outside the mainstream and he's saying things they don't want you to hear

00:08:17.620 is also like one of the dominant paradigms of the ways that americans are liable to believe 0.85

00:08:23.320 bullshit we're coming off a decade of disaster movies each of which has one scientist that 1.00

00:08:28.980 nobody believes that's trying to get the truth to the president yeah people love this shit they're 1.00

00:08:33.980 primed for it everybody reading this thinks that they're pierce brosnan and dante's peak but 0.98

00:08:37.800 they're actually randy quaid and independence day so i'm going to send you some paragraphs the

00:08:43.300 book began with a new york times magazine article okay stephen dubner who's one of the co-authors

00:08:49.980 of economics was at the time a story editor at the new york times and he was working on a story

00:08:56.060 about the psychology of money and that's how he met stephen levitt who's his co-author and this

00:09:01.100 university of chicago economist so the book is co-written by both of them but it's not kind of

00:09:05.620 clear who wrote what. And there's lots of stuff in the book that is based on Levitt studies,

00:09:10.060 but there's also lots in the book that isn't based on Levitt studies. It's just kind of random.

00:09:13.320 Got it. Got it.

00:09:14.160 So I'm sending you the first five paragraphs of the New York Times story.

00:09:19.340 Oh boy.

00:09:19.700 This is America's first introduction to the Freakonomics guys and like the Freakonomics

00:09:25.120 way of thinking.

00:09:26.080 The most brilliant young economist in America, the one so deemed at least by a jury of his elders,

00:09:32.240 Breaks to a stop at a traffic light on Chicago's south side.

00:09:35.940 It is a sunny day in mid-June.

00:09:37.880 An elderly homeless man approaches.

00:09:39.760 He wears a torn jacket, too heavy for the warm day, and a grimy red baseball cap.

00:09:45.020 The economist doesn't lock his doors or inch the car forward, nor does he go scrounging

00:09:49.620 for spare change.

00:09:50.760 He just watches, as if through one-way glass.

00:09:53.880 After a while, the homeless man moves along.

00:09:56.080 He had nice headphones, says the economist, still watching in the rearview mirror.

00:10:03.040 Well, nicer than the ones I have.

00:10:05.360 Otherwise, it doesn't look like he has many assets.

00:10:08.960 Stephen Levitt tends to see things differently than the average person.

00:10:12.900 Differently, too, than the average economist.

00:10:15.700 What do you think?

00:10:16.440 Is that seeing things differently?

00:10:18.440 I'm pretty sure that staring down a homeless person asking for money

00:10:22.360 and then making a snarky comment about the quality of their accoutrement is a classic

00:10:29.820 American tradition. Is that is it not? If he's so poor, why does he have stuff?

00:10:34.380 If he had taken that headphone money, Michael, and invested it in an ETF starting in 2002,

00:10:41.460 he could have eight pairs of headphones by now. I also love it because we're seeing this like

00:10:48.200 he's different from the other economists in a story that's not remotely different from other

00:10:52.720 like pretty well-off people seeing a homeless man in public. And also it's basically trying

00:10:57.400 to establish him as like a rogue economist and outside of the strictures of the field

00:11:03.300 while acknowledging the fact that he's a tenured professor at the University of Chicago.

00:11:08.820 He has degrees from Harvard and MIT and he won the John Bates Clark medal. So the article wants

00:11:15.560 to use that as like this isn't just some crank saying stuff right like look look how awarded he

00:11:20.500 is within economics but then also we'll switch and be like oh she's different i almost feel like

00:11:25.500 like remember when like the trump campaign had like establishment washington folks talking about

00:11:31.440 like the swamp and you're and you're just like you feel like you're through the looking glass a

00:11:34.940 little bit you're like what are you that's you exactly not just an establishment economist but

00:11:39.580 like the most establishment economist being like, I'm a sort of a bad boy in the economics

00:11:45.560 industry.

00:11:46.460 Who everybody really likes.

00:11:47.860 Yes.

00:11:48.440 He also, there's another piece of foreshadowing that says one paper he wrote as a graduate

00:11:53.340 student is still regularly cited.

00:11:55.280 His question was disarmingly simple.

00:11:57.140 Do more police translate into less crime?

00:11:59.780 The answer would seem obvious.

00:12:01.200 Yes, but had never been proved.

00:12:03.040 Since the number of police officers tends to rise along with the number of crimes, the

00:12:06.920 effectiveness of the police was tricky to measure.

00:12:09.240 Leavitt needed a mechanism that would unlink the crime rate from police hiring.

00:12:12.900 He found it within politics.

00:12:14.700 He noticed that mayors and governors running for re-election often hire more police officers.

00:12:18.900 By measuring those police increases against crime rates,

00:12:21.600 he was able to determine that additional officers do indeed bring down violent crime.

00:12:26.800 That paper was later disputed.

00:12:28.500 Another graduate student found a serious mathematical mistake in it.

00:12:31.280 But Leavitt's ingenuity was obvious.

00:12:33.520 so uh it's not real it's he found something that was fake and but let's all just be in awe of his 0.98

00:12:44.740 creativity this runner tripped and absolutely ate shit on his first lap but his speed was obvious 0.76

00:12:51.100 it's like what are we doing here and so the article ends with tax evasion money laundering 0.96

00:12:59.200 I'd like to put together a set of tools that lets us catch terrorists.

00:13:02.960 I don't necessarily know yet how I'd go about it, but given the right data,

00:13:06.460 I have little doubt that I could figure out the answer.

00:13:10.960 Small problems, just ending terrorism.

00:13:13.300 Yeah, what am I working on now?

00:13:14.640 Look, I've been thinking about stopping terrorism, you know, if someone can get me some numbers.

00:13:18.860 Stephen Levitt may not fully believe in himself, but he does believe in this.

00:13:22.900 Teachers and criminals and real estate agents may lie and politicians and even CIA analysts, but numbers don't.

00:13:31.880 I don't think that Stephen Levitt seems like he lacks confidence in himself, but perhaps I'm misreading. 0.97

00:13:38.800 But then one thing I genuinely really appreciate about Freakonomics is that everything that people will later accuse Freakonomics of, they just fucking say.

00:13:48.240 So, like, in this passage, he's saying, like, everybody else lies, but the numbers don't lie.

00:13:54.000 And it's like, right, the whole problem with this is this overconfidence in quantitative data that is completely stripped of all of its societal context.

00:14:02.640 That's why we object to this.

00:14:04.420 This is a classic economics guy thing where they act like the narratives that they map onto the data are themselves just as infallible as the data.

00:14:15.520 Exactly. That's a good way to put it.

00:14:16.720 The idea that there's like always something hidden, right, seems to be lurking here where there must be an explanation that is counterintuitive and fascinating and people are trying to hide it from you, right? 0.96

00:14:30.600 God, this is so fucking annoying.

00:14:34.120 You're having the same experience that I had in like slightly distilled because like you can't believe they're just saying it. 0.98

00:14:39.440 That's what I cannot get over.

00:14:40.760 God.

00:14:40.980 So after the article got published, it was a huge sensation because of all these like bold ideas.

00:14:45.800 then like book publishers got in touch and then they're like quite open about the fact that this

00:14:51.020 was a rush job oh my god they just like grabbed a bunch of random anecdotes i have a lot of respect

00:14:57.080 for being like look we're cashing in yeah exactly and they're like other people have said there's

00:15:01.940 no overarching theme to this book that's correct what we're doing is we're talking about numbers

00:15:06.620 and it's like okay you just have a bunch of cute anecdotes and you're gonna string together the

00:15:10.700 cute anecdotes with like the most fucking try hard transitions I've ever seen. So I've, I've

00:15:15.980 kind of broken apart this book and put it back together because even though the book is only

00:15:21.660 207 pages, they only spend a paragraph or two on each one of these anecdotes. It's like a collection

00:15:28.260 of basically like a hundred cute little stories. I'm trying to take a representative sample of the

00:15:34.240 way that they present information, but it's like, we're only going to touch on like 10% of the book

00:15:39.140 Right. Because to debunk these like ridiculous paragraphs takes you four times longer than it took to write them. Right. So we're not going to go through the book chapter by chapter, basically because like it's too much of a mess to do that. But I do want to talk about the core ideology of this book and like why it exerted such a negative influence on the culture.

00:15:59.180 The reason I wanted to read that concluding paragraph from the original New York Times story is that the entire Freakonomics approach is setting up this binary between intuitive thinking and data-driven thinking, right?

00:16:15.460 So economics is uniquely positioned to allow us to see the world without all the human nonsense that comes along with asking people about it.

00:16:25.360 Right. You're cutting through the bullshit. 1.00

00:16:26.660 Right. And they're extremely explicit about this in the book. So in the introduction, they say morality, it could be argued, represents the way that people would like the world to work, whereas economics represents how it does work. 0.99

00:16:40.580 No, no, no, no.

00:16:44.080 So, like, this is just a totally false binary. And the best evidence that this is a false binary is their own book.

00:16:52.160 So in this episode, we are going to talk about all of the ways that they misuse data.

00:16:57.480 The first thing we're going to talk about is the way they use true data to reach false conclusions.

00:17:04.560 So let me send you one more paragraph.

00:17:08.220 All right.

00:17:08.660 What about the election truism that the amount of money spent on campaign finance is obscenely huge?

00:17:14.840 In a typical election year, campaigns for the presidency, the Senate, and the House of Representatives spend about $1 billion.

00:17:21.220 dollars. That sounds like a lot of money, unless you care to measure it against something seemingly

00:17:26.220 less important than democratic elections. It is the same amount, for instance, that Americans

00:17:31.040 spend every year on chewing gum. This is like classic Freakonomics, where it's like phrased

00:17:36.140 as some sort of debunking. You thought political spending was bad, but wait till you hear about

00:17:42.580 chewing gum. But like those things have nothing to do with each other. You're just juxtaposing

00:17:47.120 an important thing with a frivolous thing to make them both seem frivolous right and also like i

00:17:52.600 mean the the objection to money in politics is a moral one right it's not like we're spending

00:17:59.700 too much money in a vacuum and that's it it's it's because it's like the literal manipulation of

00:18:05.920 society like that's the point of campaign finance so yes people have objections to that in and of

00:18:12.400 itself, whatever. And they also another example is they have this whole thing. They have a section

00:18:17.200 about cheating and how there's this infamous thing in 1987 where the IRS started asking people to

00:18:23.840 list the social security numbers of their children if they wanted the child tax deduction. So you get

00:18:29.480 like it was like 2000 bucks at the time. And you could just say, OK, I have little Timmy. And then

00:18:34.100 all of a sudden your tax bill would go down by $2,000. And then all of a sudden you had to start

00:18:38.420 providing the social security number for timmy and seven million children disappeared from the

00:18:44.500 tax rolls they explicitly link this to cheating that all these people were lying about their kids

00:18:49.980 and then they had to prove that they had kids and all of a sudden all these kids disappeared right

00:18:54.160 what they leave out is the fact that before 1989 children were not assigned social security numbers

00:19:00.180 automatically so when the irs announced this thing you're gonna have to start putting social

00:19:04.600 security numbers every single parent in america had to fill out a form send it to the irs wait

00:19:09.800 two weeks and get their kids social security number back so of those seven million people

00:19:14.880 that didn't include their kids on their taxes that year a huge percentage of them were people

00:19:19.860 who were like oh shit i forgot to do this i just can't include my kids this year right most of the

00:19:24.300 kids that disappeared were divorced parents and both parents were putting the kid for the deduction 0.50

00:19:29.220 on their taxes and so some of that's cheating but also it could also just be something of like they

00:19:34.760 had never really talked about it before or thought about it and didn't know that they couldn't both

00:19:38.340 claim the kid right again the number seven million appears to be true although i've seen somebody say

00:19:42.400 that it was actually more like two million but the interpretation of it like what they are using that

00:19:47.480 number to say is mostly wrong like we don't we don't know how much of that was cheating yeah as

00:19:54.240 look as someone who used to do his own taxes and then gave it to an accountant this year

00:19:57.940 I understand fucking it up completely. 0.65

00:19:59.840 My accountant was like, what are you? 0.55

00:20:01.120 What have you been doing?

00:20:01.980 I'm like, I don't know.

00:20:03.180 I just I kind of wing it and then I submit it and I haven't been arrested.

00:20:07.100 That's I thought I was doing it right.

00:20:08.940 But then, God, this is not the worst one in the whole book, but this is like peak smug.

00:20:14.800 This this will give you flashbacks to the kind of dude who read this book.

00:20:18.040 So this is in a section about parenting.

00:20:20.140 It's talking about risks and how people can be irrational when they consider risks.

00:20:24.120 It says, consider the parents of an eight year old girl named Molly.

00:20:27.740 Her two best friends, Amy and Imani, each live nearby.

00:20:31.100 Molly's parents know that Amy's parents keep a gun in their house,

00:20:33.920 so they've forbidden Molly to play there.

00:20:36.000 Instead, Molly spends a lot of time at Imani's house,

00:20:38.900 which has a swimming pool in the backyard.

00:20:41.500 Molly's parents feel good about having made such a smart choice to protect their daughter.

00:20:45.700 But according to the data, their choice isn't smart at all.

00:20:49.200 In a given year, there's one drowning of a child

00:20:51.880 for every 11,000 residential pools in the United States.

00:20:55.140 In a country with 6 million pools, that means that roughly 550 children under the age of 10 drown each year.

00:21:01.920 Meanwhile, there's one child killed by a gun for every 1 million plus guns.

00:21:06.900 That means that roughly 175 children under 10 die each year from guns. 0.63

00:21:12.020 Molly is roughly 100 times more likely to die in a swimming accident at Imani's house than in gunplay at Amy's.

00:21:19.480 Okay.

00:21:19.700 they're making a mistake here that i can't quite articulate but it might have to do

00:21:25.100 with um the amount of guns per household yeah um but i i want to take a step back and say

00:21:31.120 one of the least interesting things on earth is when people do this sort of like people are

00:21:37.340 assessing risks incorrectly oh my fucking god kind of analysis and it's like are people supposed

00:21:42.700 to know statistics like this before they like make everyday decisions no this is again weirdly 0.97

00:21:48.880 conservative where they're sort of being like guns aren't as dangerous as people think exactly i

00:21:52.720 would love for them to be like actually uh undocumented immigrants aren't as dangerous 0.52

00:21:58.320 you know things like crime for example street crime are areas where people are way out of whack

00:22:06.240 and yet these books don't seem to focus on it so the obvious statistical thing to say here is that

00:22:12.480 it's absurd to say deaths per gun versus deaths per swimming pool. Most people who own guns own

00:22:19.340 more than one gun. And most people who have swimming pools have exactly one swimming pool.

00:22:24.320 So what you'd want to do is households with guns versus households with pools. Right. But that's

00:22:29.760 not that's like the sort of 101 bullshit thing. The much bigger thing is you should not be using 0.97

00:22:35.980 average mortality statistics to lecture other people on how to parent their kids. Right. Most

00:22:41.820 of the kids under 10 who drowned this is like really awful is like it's mostly very young kids

00:22:46.920 in bathtubs uh-huh another very large portion is in like lakes and rivers it's mostly poor kids

00:22:54.200 a lot of it is like kids with disabilities like physical disabilities who can't swim

00:22:58.100 backyard pools actually are really dangerous compared to like municipal pools yeah but the

00:23:02.660 reason is not that kids drown when like they're playing at a friend's house and like you know

00:23:07.600 usually mom is watching when kids are playing in the pool because they know it's dangerous, right?

00:23:12.460 Usually how kids die in backyard pools is the back door is unlocked and they wander outside

00:23:17.460 and they fall into the pool like at night when nobody's around and they can't get out of the

00:23:21.120 pool. If your kid can swim, they're probably fine. Like the dynamics of drownings, you shouldn't just

00:23:27.220 be looking at the average number of drownings across the entire country. Like there are specific

00:23:32.920 dynamics to this. And of course there's specific dynamics to firearm deaths too.

00:23:36.740 But this whole thing is just like, you might think that you have a good intuition about this. 0.98

00:23:43.060 But what if I presented you with the worst oversimplification of the data that you've ever heard in your fucking life? 0.96

00:23:49.360 What do you think now, Molly's parents? 0.95

00:23:52.140 It's also seemed totally rational for me to be just kind of in general worried and uncomfortable around an object that essentially only exists to cause harm.

00:24:02.160 Like there's no reason for my child to be anywhere near a gun.

00:24:05.480 whereas swimming pools like swimming is good for kids it's social it's exercise you as a parent

00:24:13.060 might say like oh that's actually really worth the risk for me what they seem to be driving at

00:24:17.580 in part is that maybe we're a little too uptight about gun restrictions and gun safety right what

00:24:23.940 they're missing is that maybe part of the reason that children are getting killed by guns at

00:24:28.860 relatively low rates is because people are cautious around them. Right. And trying to like

00:24:35.200 drop that social stigma is just going to drive those numbers up. Right. Oh, no, I'm I'm about

00:24:41.580 to quote Ruth Bader Ginsburg and I don't want to do that. Do it. Notorious RBG. I know you love it.

00:24:46.440 You have the mug next to you. It's throwing away the umbrella in a rainstorm because you're not

00:24:51.340 getting wet. Right. That's what they seem to be advocating for here. What drives me nuts about

00:24:55.280 this section and like this kind of way of doing statistics is like it doesn't give you any

00:25:00.660 understanding of drownings of firearm deaths yeah all you have is like a little factoid that you can

00:25:07.760 drop at like a barbecue with the other dads and be obnoxious you know molly's parents don't let

00:25:12.580 her go over to emily's house because emily's parents own a bear and they let it roam free

00:25:17.920 but did you know that bear attacks kill under 10 children per year so that's the misuse of data

00:25:27.000 part one part two is most of the content of the book it's the over generalization from extremely

00:25:36.600 specific data so there's some dude who's like an office drone in dc and he starts selling bagels

00:25:44.340 at work. He brings in bagels and he puts like 20 bagels in the kitchen and a bowl. And it's like

00:25:51.300 a trust system. People are supposed to take a bagel, leave a book. And so he starts making so

00:25:55.180 much money from the bagels that he decides to do this full time. So now he delivers like, I don't

00:25:59.440 know, 10,000 bagels a day to various offices around DC. And he does the same thing. He leaves

00:26:03.740 a big bowl of bagels and he leaves a bowl for money. And allegedly this guy has kept meticulous

00:26:08.920 records for years and so he has basically the the honesty of various customers right because they

00:26:15.180 don't have to put in a dollar they can just take a bagel so according to this guy's data it's like

00:26:19.260 90 percent of people pay for the bagel and there's some like borderline interesting stuff around like

00:26:24.300 around the holidays people are less likely to pay for the bagels certain kinds of companies like

00:26:30.020 people in big companies are more likely to pay for the bagels than at small companies and people in

00:26:35.340 the executive suite like on those floors are less likely to pay for the bagel so like rich people

00:26:40.100 are stingy or whatever i believe that it's kind of interesting like it's a cute story this guy

00:26:45.320 but like is this generalizable i don't really know freakonomics

00:26:49.700 thinking like a freak will this guy give me a dollar for the bagel uh on the honor system

00:26:58.180 maybe not freakonomics it's very funny to me that like the only good parts of this book are just the

00:27:04.800 descriptive parts yeah where it's like they just like these are the phenomenon you're like oh

00:27:08.300 interesting but then as soon as they try to turn them into like pat little lessons they're like

00:27:12.720 and that's why you're like i don't know that we can really learn anything from this right they

00:27:18.920 have a whole thing with like incentives and like it turns out people cheat way less than you think

00:27:23.220 they do right well maybe but it's like these are bagels at work and they cost a dollar yeah they're

00:27:28.720 cheap yeah it just seems like a very unique situation that i'm not sure you can really say

00:27:33.320 anything about like humans propensity to cheat based on this they then have a whole section

00:27:39.520 about sumo wrestlers this is another study of levitt's there's a weird thing in sumo wrestling

00:27:44.960 tournaments where you do the best of 15 so you have to win eight matches out of 15 right okay

00:27:51.940 but the problem with sumo tournaments is that oftentimes people reach their eight wins and

00:27:57.620 then they're still they still have like three more matches to go so basically you have all these

00:28:01.700 matches between like people who it just doesn't matter if they win or not because they've already

00:28:05.940 gotten their eight matches and sometimes they are matched with people who are like seven and seven

00:28:10.220 and like really need to win really need to so sure levitt runs the numbers and he finds it like you

00:28:15.440 would expect a sort of 50 50 split you know winning and losing percentage on these matches

00:28:19.580 but it turns out it's 80 20 for people who need to win end up winning these things and the the

00:28:26.720 only explanation for this is like widespread criminal conspiracy it must be fixed but then

00:28:32.380 what's wild so i i had the same reaction as you i was like this seems like a really big leap but

00:28:37.480 then in 2011 there was an actual like huge scandal in sumo wrestling that confirmed that like was a

00:28:43.700 massive criminal conspiracy among these dudes oh hell yeah and like wow it's interesting in that

00:28:48.860 there wasn't actually that much selling of matches but like these guys would just kind of meet in the

00:28:54.180 dressing rooms and be like dude you don't need to win this i need to win this do you mind just

00:28:57.400 letting me win and they'd be like yeah yeah you're fine uh-huh this is one of the only examples in 0.57

00:29:01.580 freakonomics where like he was fucking right like good for him kudos i will give you this one steve

00:29:06.500 economics could have never predicted this only freakonomics could have predicted this exactly 0.75

00:29:10.580 well this is this is the other thing that i learned when i was researching the match fixing

00:29:14.120 scandal is it like sumo fans have been complaining about this for literally decades like they they

00:29:19.620 changed the rules in the 1970s to try to prevent this obviously not effectively enough but like

00:29:25.400 everyone knows that like these matches are kind of fake right i do think that like providing

00:29:30.360 numbers to these things and giving evidence to something that feels true is like a very important

00:29:35.040 role for academia yeah but i don't know that there's like human human behavior there other

00:29:39.300 than the super banal finding that like yeah when it matters to one person and not the other they're

00:29:45.240 probably going to trade right you know this reminds me of like you know in like econ 101

00:29:51.300 when you learn about moral hazard yeah yeah and you feel like really smart for a day yeah this

00:29:57.680 this is like some of the most basic human behavior stuff um that you could ever conceive of but they

00:30:03.260 present it like they're blowing your mind well this is something i learned from reading a bunch

00:30:06.880 of extremely scathing reviews of this book by economists one thing this book does that i think

00:30:12.080 became very prominent in the early 2000s was this idea that like incentives explain everything right

00:30:17.540 and if you want to understand a situation you sort of look at the incentives of all the actors

00:30:21.080 involved right and of course this book does that right it like presents the bagel anecdote and like

00:30:25.520 50 other anecdotes and it's like all the incentives economists can understand things better than other

00:30:30.680 types of scientists because they look at the incentives but then when you look at the bagel

00:30:35.880 example, it's like, well, everybody has the incentive to steal a bagel, but only 10% of

00:30:42.080 people do. And they spend almost an entire chapter on this example of Chicago school teachers and how

00:30:48.160 Stephen Levitt designed an algorithm to detect teachers who were like erasing bubbles on

00:30:53.920 standardized tests and filling in their own answers to make sure that they didn't get fired.

00:30:58.720 And it's like, oh, the incentives of the teachers. But then they mentioned sort of offhand that it's

00:31:04.500 only 5% of the teachers who cheat. So it's like 100% of the teachers have the incentive,

00:31:11.140 like very strong incentives to cheat, but very few of them do. So like, what does it actually

00:31:16.520 mean to say incentives matter? Right, right, right.

00:31:20.580 You could just as easily say that people pay for a bagel because of their upbringing. You could say

00:31:25.200 it's because their psychology. You could say it's because they want to be moral people and they

00:31:28.900 don't want to be the kind of person who steals a bagel. Like those are incomplete explanations

00:31:32.640 too but it's not clear to me that those are less scientific than just saying like incentives over

00:31:37.620 and over again right i don't i just this book has a very complicated relationship with like morality

00:31:43.220 and it sort of sees morality as like this weird irrational thing that people do that's a classic

00:31:48.620 um conservative economist tick right where the goal of a lot of the work is to critique

00:31:56.200 liberal sentimentality right right in their view so the third way that this book misuses data

00:32:02.920 is leaping to conclusions on some things while refusing to reach conclusions on others

00:32:10.240 this is where we get into the black names stuff throughout the book there's like various

00:32:18.540 examples of kind of weird race stuff steven levitt did a study on do you remember the

00:32:24.520 weakest link the game show yeah it's like a cross between who wants to be a millionaire and survivor

00:32:30.040 you like vote people off for getting questions wrong yeah it's uh with the mean british lady

00:32:35.000 yes the mean british lady was the host yeah so he did a study of everyone who's ever been kicked 0.98

00:32:40.760 off of that show and it's like you'd expect the black contestants to be kicked off right but

00:32:45.120 actually it wasn't and the female contestants weren't kicked off either it turns out the

00:32:49.920 hispanic and the elderly contestants were the ones who faced discrimination okay other people

00:32:55.360 have questioned this because there were only 22 hispanic contestants on the show out of a thousand

00:33:00.120 contestants so like you can't you can't really like make claims about that but anyway it's like

00:33:04.020 okay whatever then we get to the final two chapters of the book which are all about like

00:33:10.040 cultural explanations for poverty yep here we go so here's a couple of paragraphs that

00:33:16.380 I don't want to read it, but I'm going to make you read.

00:33:19.740 They're talking about a researcher named Roland Fryer.

00:33:22.220 In addition to economic and social disparity between blacks and whites,

00:33:26.320 Fryer had become intrigued by the virtual segregation of culture.

00:33:29.680 Blacks and whites watch different television shows.

00:33:32.260 Monday Night Football is the only show that typically appears on each group's top 10 list.

00:33:37.200 Seinfeld, one of the most popular sitcoms in history, never ranked in the top 50 among blacks. 1.00

00:33:42.380 they smoke different cigarettes and black parents give their fucking shit it's happening and black 1.00

00:33:49.500 parents give their children names that are starkly different from white children's 1.00

00:33:53.140 friar came to wonder is distinctive black culture a cause of the economic disparity between blacks 0.93

00:34:00.320 and whites or merely a reflection of it time to ask are poor people poor because it's their fault 1.00

00:34:05.900 Yeah. I mean, are you poor because of socioeconomic structures or are you not watching Seinfeld?

00:34:14.520 Is that the problem? The black names thing like this is a tale as old as time, right? 0.94

00:34:20.860 People being like, well, if you have a black name, you're less likely to get job offers. 0.99

00:34:26.660 And then like their conclusion is it's stupid to give your kid a black name instead of like, wow, must be some serious racism at play, 0.99

00:34:34.340 which is the obvious conclusion it's it's worse peter it's okay okay this is in a chapter called 0.99

00:34:40.960 would a roshanda by any other name smell as sweet oh shit long silence long silence

00:34:49.780 freakonomics we meet this roland fryer guy who has a database of every single person born in 0.93

00:34:57.020 california since 1961 and he starts combing through like the demographic data and like

00:35:01.680 cross-checking it with like the names so it says the data show that the black white gap is a recent

00:35:07.620 phenomenon until the early 1970s there was a great overlap between black and white names the typical

00:35:13.100 baby girl born in a black neighborhood in 1970 was given a name that was twice as common among

00:35:17.980 blacks than whites by 1980 she received a name that was 20 times more common among blacks boys

00:35:23.960 names moved in the same direction but less aggressively probably because parents of all

00:35:27.920 races are less adventurous with boys' names than girls. A great many black names today are unique

00:35:33.160 to blacks. More than 40% of the black girls born in California in a given year receive a name that

00:35:38.300 not one of the roughly 100,000 baby white girls received that year. The California study also

00:35:44.000 shows that white parents send a strong signal in the opposite direction. More than 40% of white

00:35:48.900 babies are given names that are at least four times more common among whites. Consider Connor

00:35:53.900 and cody emily and abigail this is interesting yeah that is interesting descriptive statistics

00:35:59.240 it's like wow social trends yeah although this is also like a few years before the great i don't

00:36:05.120 know how to what to call it uh dipshitification of white names the gwyneth effect yeah yeah we're at

00:36:12.260 a time where um the desire among white parents to throw a why where an eye used to be is that

00:36:20.940 just it's at peak we then get a long section that's basically just like riffing on black names

00:36:28.000 so they talk to a judge in family court in new york who is like presumably a friend of one of

00:36:34.900 theirs who just like tells them the funniest black names that he's ever seen they start out with the

00:36:41.160 story of a girl named temptress who's arrested for prostitution at age 15 you're literally make

00:36:48.260 You're making cracks about a 15-year-old who's probably being sexually trafficked.

00:36:53.060 Yeah.

00:36:53.240 Just that's the joke.

00:36:54.580 Good stuff. 0.91

00:36:55.000 And then we get the story of someone named Amcher who had been named for the first thing

00:37:01.840 his parents saw upon reaching the hospital, the sign for Albany Medical Center Hospital

00:37:07.220 Emergency Room.

00:37:09.120 And then we have this paragraph.

00:37:11.960 Roland Fryer, while discussing his name's research on a radio show, took a call from

00:37:16.680 a black woman who was upset with the name just given to her baby niece it was pronounced shiteed 0.96

00:37:22.680 but was in fact spelled shithead or consider the twin boys orange jello and lemon jello 0.97

00:37:29.280 also black whose parents further dignified their choice by instituting the pronunciations 0.56

00:37:34.680 orangelo and limongelo now that first one was like 80 a prank call but yeah go on this thing 0.58

00:37:42.720 of like black people giving their kids weird names is like a very well-known urban legend

00:37:47.520 there are numerous snopes articles about this this is something that was like huge in email

00:37:53.460 forwards in the 1990s there are stories of this going back to 1917 these were like vaudeville

00:38:00.380 jokes this thing of naming your kid after like the emergency room where you were born this is a 1.00

00:38:05.840 really old joke it's like black people are so stupid that they name their kids like no smoking 1.00

00:38:10.360 right because that's like the sign above the you know place where they're filling out the birth 1.00

00:38:14.800 certificate right there's another one where they they name their kid female because that's like

00:38:19.080 the word in the box and like they don't understand how to fill out the form but it's pronounced

00:38:23.640 famale do you have you heard this there's like this urban legend that there's someone named 0.75

00:38:29.400 ladasha yeah how's it spelled l-a-dash-a right like just obvious bullshit i was amazed that

00:38:36.940 this wasn't in the Freakonomics book because like every other urban legend about this is in the 0.60

00:38:41.860 Freakonomics book. And then the Shateed thing, I've seen this in a Kevin Hart routine. I think 0.80

00:38:47.840 that he did years ago was the first place I came across it. I like the idea that Kevin Hart is

00:38:52.480 pulling jokes from Freakonomics. He's like, good one, guys. But so this like in a book that is

00:39:00.900 meant to be like data driven, you know, and like exploring the world through quantitative data to

00:39:06.220 fall for this just rank bullshit that i don't know what the google situation was in 2005 but 0.98

00:39:11.760 like two minutes on google yeah it's like do black people name their kids shithead ah yeah this has 0.99

00:39:16.140 been bouncing around for decades right we then get into you know these studies about they send 0.98

00:39:20.180 in resumes and if you have like a black name you're less likely to get a call back than if

00:39:23.860 you have a white name right this says according to one such study if deshaun williams and jake

00:39:29.080 williams sent identical resumes to the same employer jake williams would be more likely to

00:39:33.460 get a call back. The implication is that black sounding names carry an economic penalty. Such

00:39:38.700 studies are tantalizing, but severely limited for they can't explain why Deshawn didn't get the

00:39:44.320 call. Was he rejected because the employer is a racist and is convinced that Deshawn Williams is

00:39:49.520 black? Or did he reject him because Deshawn sounds like someone from a low income, low education

00:39:55.520 family? A resume is a fairly undependable set of clues. A recent study found that more than 50%

00:40:01.520 of them contain lies. So Deshawn may simply signal a disadvantaged background to an employer

00:40:07.800 who believes that workers from such backgrounds are undependable.

00:40:13.800 You might think this is racism, but what if I told you that they're simply associating the name

00:40:20.380 with a set of undesirable qualities that they attach to black people? Are you fucking kidding 0.99

00:40:26.920 me did they not hire somebody named muhammad due to islamophobia or did they simply believe that 0.99

00:40:32.900 he was going to strap a bomb to himself and blow up that's a longer way of saying islamophobia

00:40:39.360 also how come this is the one time in the book that they're like demanding more data yeah no 0.99

00:40:43.780 shit everything else they'll hang on to two data points and be like we've proven that uh people

00:40:49.720 are irrational about guns vis-a-vis swimming pool yeah but with this one they're like let's not get 0.99

00:40:55.340 crazy before we start calling people racist also dude this is why i mentioned the fucking weakest 0.93

00:40:59.860 link study because like three chapters ago you're like whoops turns out racism doesn't exist we 0.91

00:41:04.300 looked at evidence from a game show and now they're looking at like real world examples these

00:41:10.220 studies are extremely consistent there's been like a million of these by now this is like some of the

00:41:15.700 strongest data for racism and hiring because exactly you can eliminate so many variables

00:41:23.280 that otherwise might complicate the process, right?

00:41:25.600 It's just resumes and they're identical.

00:41:29.020 And also, how is this Freakonomics?

00:41:30.900 Where's the Freakonomics here?

00:41:32.980 Well, I mean, Stephen Levitt did a study on this

00:41:35.860 where he's basically asking the question of like,

00:41:39.560 should Deshaun change his name?

00:41:41.500 Yeah.

00:41:42.020 And so he concludes, so does a name matter?

00:41:45.660 The data show that on average,

00:41:47.220 a person with a distinctively black name,

00:41:49.200 whether it's a woman named Imani or a man named Deshaun,

00:41:51.820 does have a worse life outcome than a woman named Molly or a man named Jake.

00:41:55.780 But it isn't the fault of their names.

00:41:58.700 If two black boys, Jake Williams and Deshawn Williams,

00:42:01.240 are born in the same neighborhood, into the same family and economic circumstances,

00:42:05.660 they would likely have similar life outcomes.

00:42:08.380 The kind of parents who name their son Jake don't tend to live in the neighborhoods

00:42:11.800 or share economic circumstances with the kind of parents who name their kid Deshawn.

00:42:16.340 A Deshawn is more likely to have been handicapped by a low-income, low-education, single-parent background

00:42:21.360 his name is an indicator, not a cause, of his outcome. 0.98

00:42:25.440 Good Lord.

00:42:26.600 I mean, first, he's just making that up, right?

00:42:28.640 The whole point of the resume studies is that they show that that's not true.

00:42:32.580 Exactly.

00:42:32.960 That actually there are disadvantages to the name in and of itself because people are racist.

00:42:38.760 So he's just saying, no, let's ignore those studies and just get the causation exactly

00:42:43.420 backwards or at least eliminate some complexity.

00:42:47.140 But I feel like this is another feature of these books is that oftentimes they'll set up this like straw man to debunk.

00:42:55.220 So in this, he's like, you thought the only reason Deshaun can't get a job is his name. 0.95

00:43:00.920 But it turns out most poor black people can't get jobs. 1.00

00:43:05.360 It's like, right. 1.00

00:43:06.700 That's what I thought in the first place.

00:43:08.440 I didn't think it was only the name.

00:43:11.120 This is this is like a little darker than like what Gladwell does, which is always like

00:43:17.020 often a little cuter, like Gladwell would be like how one soccer team used jelly donuts

00:43:22.460 to win a championship.

00:43:23.520 And you're like, hmm, what's going on there?

00:43:25.620 And Levitz is like it feels just a little more racist every single time. 0.98

00:43:29.940 Yeah, there's a huge amount of conservative Ayn Rand bullshit presented in this book as 0.99

00:43:36.780 like harsh truths. 0.98

00:43:38.320 Yeah, yeah, yeah. 0.60

00:43:39.400 And again, I would like to circle back to whoever thought of Freakonomics as a title because Black People, a Critique is a much worse title.

00:43:51.400 God, I didn't realize he was a Chicago guy, but it's starting to all click together in my brain.

00:43:57.380 Chicago and bio.

00:43:58.560 We could have stopped at that.

00:43:59.860 So, speaking of which, the final way that this book misuses data is waltzing into huge pre-existing debates and pretending to solve them.

00:44:13.860 Chapter 5 of Freakonomics is dedicated to the question, what explains the crime drop of the 1990s?

00:44:21.160 Oh, yeah.

00:44:21.740 We both know where this one is going, but we're going to let them work up to it.

00:44:24.400 So first of all, the massive crime drop of the 1990s is probably one of the biggest social shifts to happen in our lifetimes.

00:44:32.400 Yes.

00:44:32.740 The murder – the national murder rate went down by 50 percent.

00:44:35.960 Murders in New York City went from 2,300 a year to 600 a year.

00:44:40.600 Yeah.

00:44:40.760 This is like an actual huge deal and there's a whole field of criminology dedicated to explaining this.

00:44:47.660 I interviewed three different criminologists for this.

00:44:49.760 So Stephen Lovett says there's actually three things that explain the massive crime drop in the 1990s, right?

00:44:58.320 So the first is imprisonment, mass incarceration.

00:45:02.420 You will love this because this is Supreme Court.

00:45:04.800 First of all, to explain the crime drop, we have to explain why crime rose so much in the 1960s, like massive increase in crime.

00:45:11.740 He says, in retrospect, it is clear that one of the major factors pushing this trend was a more lenient justice system.

00:45:18.320 conviction rates declined during the 1960s and criminals who were convicted served shorter

00:45:23.120 sentences this trend was driven in part by an expansion in the rights of people accused of

00:45:28.220 crimes a long overdue expansion some would argue others would argue that the expansion went too

00:45:33.180 far at the same time politicians were growing increasingly softer on crime for fear of sounding

00:45:39.880 racist the economist gary becker has written since african americans and hispanics commit a

00:45:45.540 disproportionate share of felonies. So the reason we got more crime is because America was famously 0.87

00:45:51.840 not racist in the 1960s. Yeah, we hadn't hit that Goldilocks just right amount of racism that we

00:45:59.140 need to drive crime down to historic lows. So the only citations in like this section of like

00:46:06.820 mass incarceration, reduced crime are three articles that Gary Becker wrote in Business

00:46:11.840 Last week, all three criminologists told me that like this is not remotely an accepted explanation.

00:46:17.860 Like we gave too many rights to people and then we got more crime. 0.86

00:46:21.440 I want to point out some big picture social science shit before we advance just to get it off my chest. 0.91

00:46:26.740 First of all, taking away the like inherent moral concerns with mass incarceration. 0.97

00:46:33.340 A lot of what it's actually doing is just containing crime, right?

00:46:37.660 Placing crime into prisons where it's generally not recorded and doesn't add to the crime rate.

00:46:43.420 Another thing is that when we talk about the decrease in crime, what we're talking about is something very specific, and it's really the decrease in certain crimes, generally violent crimes, right?

00:46:54.640 We're talking about murders, assaults, et cetera.

00:46:57.560 This sort of phenomenon of corporate-level crime and government-level crime, right?

00:47:04.020 Crime by massive institutions is completely excluded from these calculations.

00:47:09.780 And so I'm not saying that crime didn't go down, but our understanding of crime is tunneled through street-level violent crime.

00:47:18.720 But this is one of the reasons why I think this book has been such a negative force in American life is that a lot of policymakers read this and I think adopted the conflation that the book is making where it's toggling back and forth between what is the most effective policy for reducing crime and what is the right policy.

00:47:40.020 I remember when I was in grad school, I took a class on crime and punishment. And on the first day, the professor told us that like if you imprisoned every teenage boy on their 16th birthday and released them on their 25th birthday, you would prevent 80 percent of crime. Right. That's a horrifying policy for many reasons, but it would be very effective to deter crime. Right. If every speeding ticket came with the death penalty, just immediate shot to the back of the head, we would have no speeding in America. Right.

00:48:06.840 Many, many, many policies would be effective at reducing crime, but that does not mean that they are the right policy.

00:48:14.800 You know, other countries which did not have mass incarceration also had huge crime drops in the 1990s.

00:48:21.380 This is a worldwide phenomenon. 0.99

00:48:23.160 So I actually think that it's probably the case that mass incarceration reduced a lot of crimes, mostly because you're just imprisoning a bunch of fucking teenagers. 0.96

00:48:32.100 But that doesn't mean that it was the right policy. 0.93

00:48:34.440 And that also doesn't mean that there weren't other policies that would have had the same outcome with a lot less like human misery.

00:48:41.080 And also it's not an assurance of long term declines in the crime rate.

00:48:47.000 Right. Right. The benefit, quote unquote, is extremely immediate.

00:48:50.340 Right. This person is off the streets, you know, so to speak, and not committing crimes.

00:48:55.560 What happens in 10 years when they're out and unemployable?

00:48:59.080 Yeah. I don't know what else to say about these sorts of analyses.

00:49:00.960 But the idea that someone is saying, like, mass incarceration is uniquely effective, it's like, what fucking country are you looking at? 0.98

00:49:07.280 That's why America has so few murders. 0.98

00:49:09.020 Yeah, right.

00:49:11.120 Right.

00:49:11.700 So that was reason one for the crime drop.

00:49:14.140 He says that explains 40 percent of the reduction in crime, mass incarceration.

00:49:18.560 Reason number two is that we had more cops on the street.

00:49:22.420 Of course.

00:49:22.920 This is the one time in the book they talk about, like, actual methodologies and how difficult it is to measure many things.

00:49:28.720 So they basically say you can't just do a correlation between like this city has more

00:49:33.280 cops and less crime and divine any kind of causal analysis.

00:49:37.400 But then Stephen Levitt comes up with this unique model that does allow you to do causation

00:49:43.160 where he says after mayoral and gubernatorial campaigns, they often hire more cops.

00:49:50.940 It's like a campaign promise.

00:49:52.060 Like I'm going to hire 50 more cops, put them on the street, whatever.

00:49:55.460 And then you get less crime.

00:49:57.020 The main thing to know about Levitt's work on this is that it's it doesn't hold up. People have found coding errors in it. There's like mistakes in the data shocker. Other people have pointed out that like mayors and governors don't hire enough cops after elections to make much of a difference. Like you can only really get to this through like weird statistical mumbo jumbo. And also there's other reasons why crime might go down after a giant election that don't have to do with cops.

00:50:22.600 And then the number one problem with this, which I feel like should be much more front and center in like every debate about crime and policing, is that crime statistics are not statistics about crime.

00:50:35.720 They are statistics about reports of crime.

00:50:38.620 Right. Which which run through police departments.

00:50:41.480 Exactly. And there are many, many things that would increase reports of crime, but not increase crime.

00:50:49.380 A lot of countries that have done like large scale public information campaigns on like sexual assault have like sky high rates of rape and sexual assault, not because they have more of those crimes, but because people are willing to come forward about them.

00:51:02.480 You also find after like large corruption scandals or police brutality incidents, people become more reluctant to report crimes to the police.

00:51:11.160 And that results in what appears to be a drop in crime because you have fewer reports of crime and the police list that as a triumph.

00:51:18.300 Like, look, the police are working.

00:51:19.580 We're reducing crime.

00:51:20.600 But it actually means they're not working because people don't trust them.

00:51:23.240 Right. 0.96

00:51:23.320 So every single like study of crime and like discussion of crime has to start with the fact that like for most crime statistics, we don't know what the fuck we're talking about.

00:51:33.140 Most crimes are not reported to the police.

00:51:35.700 And there's all kinds of weird stuff about like what counts as an aggravated assault versus not an aggravated assault.

00:51:41.240 Even violent crime statistics include robbery, which is stealing from somebody through violence or the threat of violence.

00:51:49.460 That's also something that depends on a judgment call.

00:51:51.840 Right.

00:51:52.320 So with the exceptions of homicides where, like, basically a body is a body and, like, those tend to get counted.

00:51:59.480 And one of the criminologists I talked to said that, like, motor vehicle theft is also weirdly reliable because people have to report it to their insurance.

00:52:04.980 Yeah.

00:52:05.360 I also want to point out this is 2005.

00:52:09.000 Another big cultural phenomenon, 2005, The Wire.

00:52:12.720 Oh, yeah.

00:52:13.020 And if you watch The Wire, you would know that when there's a new mayor, they put pressure on the police departments to keep the crime stats down, artificially deflated, OK?

00:52:23.540 And I want to be a guy that learns lessons about city government from The Wire, but I do trust it more than Stephen Levitt at this point.

00:52:30.840 There are two separate teams of researchers that tried rerunning his data and weren't able to replicate it.

00:52:36.240 So the first one just found this coding error.

00:52:38.040 And then the second team of researchers said that when you run it, you actually find more

00:52:42.920 reports of crime.

00:52:44.400 But that's probably because when there's more cops on the street, they just see more

00:52:48.180 stuff.

00:52:48.500 Yeah, right.

00:52:49.040 And like it, it gets included.

00:52:50.580 But it's this weird thing where a reduction in crime reports means the cops are working

00:52:55.140 and an increase in crime reports also means the cops are working.

00:52:58.400 Yeah, yeah.

00:52:58.900 So we just really don't like know very much about what's going on.

00:53:02.480 And so, again, do cops reduce crime is like a huge debate in like three different fields.

00:53:10.660 And they're just like waltzing into this and being like, obviously, police reduce crime because like I did a single study.

00:53:16.740 Freakonomics.

00:53:20.440 So that explains.

00:53:22.320 So mass incarceration and policing explain 50 percent of the crime reduction, according to this argument. 0.95

00:53:27.740 And the third reason is shmushmortion. 0.94

00:53:30.400 Hmm. Do you remember like this theory? Yeah. I mean, in broad strokes, the theory is that I'm going to try to be somewhat polite about it. That crime disproportionately emanates from poor communities and is within poor communities. Abortion is something that is utilized disproportionately by poor communities. 0.99

00:53:55.640 Therefore, the decline in crime can be explained by Roe v. Wade and the spread of abortion.

00:54:04.040 Yes.

00:54:04.720 So this is from the chapter of the book.

00:54:06.040 It says,

00:54:07.200 Leavitt and his co-author, John Donahue of Stanford Law School,

00:54:10.160 argued that as much as 50% of the huge drop in crime since the early 1990s can be traced to Roe v. Wade.

00:54:17.420 Their thinking goes like this.

00:54:19.100 The women most likely to seek an abortion, poor, single, black, or teenage mothers,

00:54:23.120 were the very women whose children, if born, would have been most likely to become criminals. 0.91

00:54:28.680 But since those children weren't born, crime began to decrease during the years they would 1.00

00:54:33.480 have entered their criminal prime. In conversation, Levitt reduces the theory to a tiny syllogism.

00:54:39.880 Unwantedness leads to high crime. Abortion leads to less unwantedness. Abortion leads to less crime.

00:54:45.540 Look, I don't even want to say that this is like, that there is like no causal connection here. I

00:54:51.520 I have no idea, but the amount of information you would need to draw that conclusion is enormous, right? 0.83

00:54:59.800 The fact that this comes after them casting doubt on a much clearer correlation with the resume, like the black names and resumes, it's fucking hilarious.

00:55:10.020 But why, Peter? But why? 0.94

00:55:11.980 Yeah, it's a real mystery.

00:55:12.920 they begin with a cute anecdote about romania where abortion was a really common form of birth

00:55:22.260 control for every four live births there was one abortion okay and then in 1966 ceausescu was doing

00:55:29.740 some like national romanian greatness thing and he banned abortion so like overnight abortion went

00:55:34.380 from like extremely common to non-existent essentially and so they say compared to romanian

00:55:41.840 children born just a year earlier, the cohort of children born after the abortion ban would do

00:55:46.980 worse in every measurable way. They would test lower in schools, they would have less success 0.74

00:55:51.720 in the labor market, and they would prove much more likely to become criminals. And then they

00:55:56.200 sort of lay out the argument for the way that abortion reduces crime, which basically it reduces

00:56:01.300 the percentage of unwanted kids in the population. And so when you have abortion being legalized,

00:56:07.240 so the opposite of what Romania did, it's like clockwork. 18 years later, you start to see these 0.73

00:56:12.980 really significant reductions in crime. To make this argument, they have four pieces of evidence.

00:56:20.080 The first is that five states legalized abortion two years before Roe, and all five of those states

00:56:28.360 had earlier crime drops. The second piece of evidence is states with higher abortion rates

00:56:35.460 at that time also had bigger crime drops. The third piece of evidence is people born after

00:56:42.820 Roe v. Wade have lower crime rates. If you look at people born after 1973, it's like, oh, they

00:56:47.420 commit less crime. And number four is data from other countries confirms the result. So they say

00:56:53.400 studies of Australia and Canada have since established a similar link between legalized

00:56:57.920 abortion and crime. Of these four pieces of evidence, two are dubious and two are straight

00:57:05.640 up lies. So the main thing to know about all this stuff about like states that are legalizing

00:57:11.280 abortions had less crime and states with more abortions had the biggest crime drops is like 0.92

00:57:17.100 mostly the data is just garbage. So all of the states that legalized abortion earlier had like

00:57:23.900 huge rates of abortion because people were traveling to those states to get abortions.

00:57:27.920 There's no guarantee that those people are living in those states 18 years later.

00:57:31.700 Right, right.

00:57:32.140 And I really couldn't believe this.

00:57:34.880 They don't actually track like a rise in abortion.

00:57:39.440 Oh.

00:57:39.760 For this, I interviewed a guy named Ted Joyce who's written a bunch of articles about this

00:57:43.680 because he's an economist who specializes in abortion policy.

00:57:48.200 He points out that Stephen Leavitt is just assuming that there were zero abortions in

00:57:53.600 all of these states before Roe v. Wade. 0.88

00:57:56.120 Right.

00:57:56.500 You're proposing that abortion explains 50% of the crime drop.

00:58:01.900 This is a huge effect, right?

00:58:04.260 To demonstrate that you would have to have like doubling, tripling, quadrupling of abortions,

00:58:10.060 right?

00:58:10.600 But a lot of the states that legalized abortion early were fairly liberal states that had

00:58:16.800 a lot of abortions going on, even when it was technically illegal.

00:58:19.780 It's not big enough to explain this huge effect.

00:58:24.460 And then Ted Joyce also points out that like abortion didn't actually change the birth

00:58:28.160 rates all that much.

00:58:29.380 Like it was like the same number of people being born.

00:58:32.260 One of the weird things about this is that abortion in and of itself is just another

00:58:37.780 way of talking about birth rates, right?

00:58:40.680 You're saying there's this thing that decreased birth rates among poor people.

00:58:44.660 Then why not just look at birth rates among poor people, right?

00:58:47.940 Why do this whole rigmarole?

00:58:49.340 And also, the biggest thing to me, if it was Roe v. Wade, right, you have this cohort of kids that are born after Roe v. Wade is legalized, right?

00:58:58.760 So if there were 20% unwanted kids in the population, now there's like 10% because there's higher access to abortion, right?

00:59:06.060 But then when you look at the specifics of how crime dropped, it wasn't young people who drove the reduction. 0.96

00:59:12.480 It was old people. 0.79

00:59:13.600 I read this fascinating article on the reduction in adult homicides. 0.60

00:59:18.260 This was also a time when the demographics were shifting, where there were, you know, the baby boomers were aging into later adulthood.

00:59:24.880 So basically, you just had the entire population getting older.

00:59:27.820 There's just fewer teenagers in the population.

00:59:29.540 So like that drove a lot of reduction in crime rates to begin with.

00:59:33.360 And at the same time, you had reductions like fewer adults killing each other.

00:59:38.200 And like the biggest decrease was among wives killing their husbands. 0.99

00:59:43.060 Dudes rock. Let's go, boys. 0.86

00:59:44.500 that's also something that draws upon all these other social shifts at the time right there's like

00:59:49.860 there's no fault divorce people waiting longer to get married people moving in together before

00:59:57.300 they get married it's easier to leave somebody rather than have this sense of desperation guys

01:00:01.060 just getting nicer you know give us some credit michael no it's it's definitely the decreasing

01:00:06.420 murderability of straight men they stopped wearing such provocative clothing i i don't want to swap 0.97

01:00:13.040 like one cute counterintuitive explanation for another one yeah there's not that many wives

01:00:18.840 killing their husbands in the country it's just this is insanely noisy exactly it's just so noisy

01:00:23.860 the amount of variables we have going on here is just crazy and so you would expect for something

01:00:29.240 like this for like way fewer teenagers to be killing each other the the cascade through the

01:00:35.120 population is exactly the opposite it starts with like 40 year olds and teenagers were actually

01:00:39.400 killing each other more because this was right during the crack epidemic right so it's this

01:00:43.700 extremely weird thing where stephen levitt says oh abortion explains the crime drop among teenagers

01:00:49.500 and then people are like oh well teenagers were actually killing each other more oops but then

01:00:54.600 he says like if you control for the crack epidemic then we have the effect well then what's this based

01:01:01.120 on sorry but control for the crack epidemic is killing me this is too good control for the causes

01:01:08.720 of crime please but then to me this is where it gets really cynical so in the book they say

01:01:14.780 studies of australia and canada have established a similar link between legalized abortion and crime 0.97

01:01:20.120 this is a lie this is just a straightforward fucking lie in canada abortion was legalized 0.80

01:01:24.960 in two waves one in 1969 and one in 1988 and the crime drops don't line up with either one of them 0.99

01:01:30.740 and then the paper that they're citing about australia finds mixed results it's like in

01:01:37.680 australia it's also some states did it before other states the researchers who clearly agree

01:01:42.060 with levitt and are like trying to make the data show that they're like uh we found it earlier in

01:01:47.540 some states but not in others and also we don't have data on like the age of perpetrators of

01:01:54.260 homicide so we can't actually say whether it was teenagers so it's like oh so you just can't say

01:01:58.940 anything right there's other studies where they found that in the uk the crime rate fell almost

01:02:04.940 equally in england and northern ireland even though northern ireland didn't legalize abortion

01:02:09.020 there's a review of 20 countries which found no link between abortion and crime yeah this also

01:02:17.100 brings us back to the romania stuff so in the book the way that they describe this is like this

01:02:24.220 perfect mirror image of what happened in america so in america we legalized abortion and then we

01:02:30.800 got less crime and in romania they banned abortion and then they got more crime right so again the

01:02:39.000 way that freakonomics frames this is these children would turn out to have miserable lives compared to 0.73

01:02:45.160 romanian children born just a year earlier the cohort of children born after the abortion ban

01:02:50.160 would do worse in every measurable way they would test lower in school they would have less success 0.54

01:02:55.080 in the labor market and they would also prove much more likely to become criminals. So like

01:03:00.160 slam dunk, right? One of the first things you find when you start Googling around for this is you

01:03:04.780 find a series of studies by an actual Romanian who looked into the data on the abortion ban and then

01:03:12.260 this huge explosion of birth rates right after the abortion ban. And what he finds is exactly

01:03:18.520 the opposite. The kids born in the wake of the abortion ban committed less crime. So the reason

01:03:26.540 for this is all about who was getting abortions in Romania. So the people who were getting abortions

01:03:33.020 were mostly middle class, more educated women, partly because you would get abortions from like 0.99

01:03:39.740 the official medical system. And you had to be able to afford to go see a doctor. You had to 1.00

01:03:45.560 be educated enough to know that abortions were available to you, right? And like living in a 0.99

01:03:49.360 city where you could access them. And so when they banned abortion, the birth rate spiked.

01:03:54.820 But the women who were having babies were mostly educated, middle class, relatively well off women

01:04:02.220 who could afford to give their kids the resources to make sure they sort of ended up okay in life.

01:04:08.080 And then when you look at America, it turns out to kind of be the same thing. One of the things

01:04:13.920 they mention in the Freakonomics book is that after abortion is legalized in the United States,

01:04:17.820 the cost of an abortion goes from roughly $500 to around $100, which is like a huge difference,

01:04:25.180 right? But also $100 in the early 1970s is still a decent amount of money. And a lot of people do

01:04:31.420 not have access to abortion clinics, right? If you live in a rural area, if you're not educated

01:04:36.620 enough to know like what the signs of pregnancy are, you don't realize what's happening. You might

01:04:41.640 have super religious parents that don't allow you to go get an abortion, it would be very

01:04:46.880 odd to act like Roe v. Wade didn't increase abortion access for poor women because like

01:04:51.640 obviously it did, right?

01:04:53.440 But there's not enough of a shift in who was getting abortions to explain all that much.

01:05:00.100 Right.

01:05:00.280 Right. 1.00

01:05:00.560 The poorest women, the most marginalized women in America were having babies when abortion 0.86

01:05:06.560 was illegal and they're having babies when abortion is legal. 1.00

01:05:09.900 Right. 0.93

01:05:10.080 he's he's implying that legality was the real barrier to abortion access but it's only one

01:05:16.360 barrier right and i i really could not believe this so when when i read the freakonomics book

01:05:21.400 googled around found this romanian study and i was thinking of like how to explain this to you i was

01:05:26.380 like okay so they wrote freakonomics and then later this romanian guy looks into the data

01:05:31.000 and he finds that it doesn't hold up and like fair enough we've all written stuff in popular

01:05:35.700 media that like eventually it turns out not to be true when we get better data whatever right

01:05:39.720 Yeah. So I went back and double check this Romanian study. The study came out in 2002, three years before Freakonomics.

01:05:47.800 Oh, my God. So this is not a debunking of Freakonomics. This is this is their source. This is the source they're using in the footnotes.

01:05:56.220 Oh, my God. So it's like this to me is like a new level of cynicism for this fucking book. 0.99

01:06:03.180 There's something so wild about this because what you expect from these like little pop science books is oversimplification. And what you so often get is just incorrect information, right? 0.97

01:06:19.280 Well, this is what is so fascinating about this book and like the discourse around this book is that whenever you see criticism of these dumb airport bestsellers, the defense of them is usually like, well, you got to sand down some rough edges, right?

01:06:32.660 You're trying to convey complicated issues to the lay public and like, you know what?

01:06:37.640 Fine.

01:06:38.180 I have spent a lot of my career doing this.

01:06:40.500 It is hard to simplify complex ideas and like entire fields of academic studies.

01:06:46.300 I get that, right?

01:06:47.260 But it's very odd to use that defense when what we're talking about is a study says crime went down and you are saying crime went up.

01:06:57.740 No one would understand that as like simplification of a complex idea. 0.99

01:07:02.480 That is a fucking lie. 0.99

01:07:04.120 There's something completely insane about it was 40 percent this, 10 percent this, 50 percent this. 1.00

01:07:10.020 And it's like, what the fuck? 0.99

01:07:10.940 Yeah, yeah, yeah. 1.00

01:07:11.500 Let's just take a big step back.

01:07:13.160 And this is speculative, but also almost certainly true.

01:07:15.780 part of the crime drop i don't know how much maybe even a very tiny amount part of it is probably

01:07:20.680 just cultural norms shifting part of it is probably education going up you know like all

01:07:26.260 these like little things and when you're saying three things account for 100 of it you're allowing

01:07:33.320 for no flexibility but like i i looked into this i there's a really good post by john roman

01:07:39.140 where he goes through like 25 explanations for the crime drop all of which are backed up by like

01:07:45.660 pretty good data right but like you can't combine all of them right like everybody has their kind

01:07:50.960 of pet theory and you can use statistics however you want to like bolster your pet theory yeah as

01:07:56.520 far as i could tell the consensus seems to be that it's like some combination of various like

01:08:03.700 justice system things so like incarceration policing i mean this is also a period where

01:08:08.800 there's like huge technological changes you know people are less likely to carry around cash now

01:08:14.760 There's one theory that it's air conditioning where people were just indoors more in comfort

01:08:19.580 and not like outside hanging out where they're like interacting with people.

01:08:23.380 People talk about the VCR.

01:08:25.220 Yeah, because crime goes up in the summer, right?

01:08:27.100 That's like a classic sort of social psych 101 thing.

01:08:30.860 Yeah.

01:08:31.160 And the reason for that, of course, that people tend to be outside more.

01:08:34.100 And the idea that things are keeping people indoors more seems to make some sense, right?

01:08:39.200 There's also a lot more people are on medications for various mental health things.

01:08:43.620 There's also I think a really underrated factor is better medical procedures.

01:08:47.960 So if somebody gets shot, they're much more likely to live now than they were 40 years ago.

01:08:51.520 So a lot of those murders just became assaults.

01:08:54.080 There's all kinds of other social changes which like you can't really disentangle from the crime stuff.

01:08:58.700 So like teen pregnancy, teen fertility is way down.

01:09:02.500 That's another like long, slow shift that has happened in our lifetimes.

01:09:06.540 Teens are less likely to use drugs and alcohol now.

01:09:08.740 Adults drink less alcohol.

01:09:10.260 There's less, you know, whatever.

01:09:11.780 Inflation and unemployment is higher.

01:09:13.620 And just like living standards are higher.

01:09:15.640 One theory is that it's immigration, you know, because immigrants commit less crime.

01:09:19.420 Oh, Michael, I think you have that backwards.

01:09:21.540 Surely we are under siege, sir.

01:09:24.780 There's the lead stuff.

01:09:26.360 People are kind of like very attached to this one.

01:09:29.000 And like, I think it's in there.

01:09:30.800 I think it might explain why crime went up so much in the 1960s, basically because baby 0.92

01:09:35.240 boomers were becoming teenagers. 0.88

01:09:36.700 And then crime didn't go up as much when like Gen X and millennials became teenagers. 0.65

01:09:41.340 Like maybe the lead thing is in there. 0.54

01:09:43.620 although it totally breaks down internationally and doesn't really work.

01:09:46.300 I'm not invested in like it's fake, but I'm also not accepting that like that's what really

01:09:51.400 explains it.

01:09:52.080 I don't think there's any like quote unquote real explanation.

01:09:54.440 But what they're doing is the equivalent of just being like, you're just looking at one

01:09:58.860 trend and being like, wow, it looks like ice cream sales went up and crime went down.

01:10:05.680 There it is.

01:10:06.360 Ice cream and crime. 0.99

01:10:08.420 That's all they're fucking doing here, right? 0.99

01:10:10.140 Just like throw a dart at a board, hit a data point, throw another at another board, hit another. 0.99

01:10:15.480 And you're like, those two, bang.

01:10:17.040 Ultimately, you're looking at correlations.

01:10:19.820 You're looking at very noisy data on crime, very noisy data on abortions.

01:10:25.900 And like, I'm not even covering all of the statistical debate that has gone on around this.

01:10:31.700 Like there's been a huge number of papers about like there are basic coding errors in Levitt's study.

01:10:38.120 he uses arrests as a proxy for crime oh he uses the raw number of arrests rather than the arrest

01:10:45.720 rates so it's like new york has more crime than wyoming it's like well yeah because it has more

01:10:49.960 people one of the criminologists i interviewed said that like no responsible sociologist would

01:10:56.440 ever say that it's one thing or even like three things it's going to be like 12 and they're all

01:11:01.640 going to be interlinked right we may just never be able to untangle this that's a sound right but

01:11:07.220 But then what's so weird to me is like, you know, the international comparisons don't hold up.

01:11:11.500 The timeline doesn't hold up.

01:11:13.520 The statistics don't hold up.

01:11:15.460 And yet Levitt continues to double down.

01:11:19.460 Yeah.

01:11:20.020 I remember a couple of years ago, right?

01:11:22.680 Yeah.

01:11:22.840 They're still publishing papers on this.

01:11:24.380 Yeah. 1.00

01:11:24.800 I mean, what the fuck, man? 0.99

01:11:25.980 So he just released an updated version of this. 0.99

01:11:28.760 I think it was 2018.

01:11:29.880 Maybe it was 2019.

01:11:30.580 And they did an updated Freakonomics episode about this, which I listened to.

01:11:35.660 and again they find oh it explains 50 of the crime drop but then in the freakonomics episode

01:11:41.520 levitt just sort of drops in he's like well it might even explain as much as 80 or 90 percent

01:11:45.920 hell yeah it's like well that's not in your paper but okay i love the idea of like a serious

01:11:51.520 academic and this actually happens i think to some like more than you might expect but an academic

01:11:57.040 puts a thesis out there and they're just in need of therapy and so when people attack the thesis

01:12:03.720 Rather than being like, hmm, you know, that's interesting.

01:12:07.120 Maybe if we reconceptualize it like this or maybe I'm wrong, they just get defensive for 20 years.

01:12:13.120 And by the end of it, they're just a complete crank.

01:12:16.160 What's so weird to me is like, I don't even feel all that strongly that like this effect doesn't exist.

01:12:22.520 Yeah.

01:12:22.880 If it's really important to you to say that like abortion is one of the things that's in there.

01:12:27.760 Yeah.

01:12:27.940 I can't really disprove that given the data that we have.

01:12:31.060 but to me it's it's on the level of like vhs or air conditioning you know it's vaguely plausible

01:12:37.280 you can kind of use statistics to say almost anything you want if you're trying to explain

01:12:42.440 10 of this massive social shift you can say like the decline of vinyl records explains 10 of the

01:12:48.840 crime drop if you want to using like modern statistical techniques so i'm not i'm not going 0.94

01:12:53.060 to say that like he's full of shit the data does not allow me to say that i mean look yeah i mean 0.94

01:12:58.300 this is an incredibly complex set of phenomena and if you wanted to say that abortion is like 0.99

01:13:05.280 part of this tapestry sure when you're once you're saying it's 50 right then you need to 0.96

01:13:12.020 show an unbelievable amount of data yeah and instead he gives you fucking nothing right 0.73

01:13:18.760 some incorrect data from romania and uh some hypothesizing to wrap up i mean i i read a bunch 0.80

01:13:24.560 of reviews of this book and there was only one that pointed out what an ideological project this

01:13:31.500 is right once you get to the actual things that you learn from reading this book it's like okay

01:13:36.060 campaign finance doesn't matter that much and like discrimination isn't that big of a deal

01:13:41.740 they have a whole section that i fucking skipped about how like protecting the forests to save the 0.77

01:13:47.280 spotted owl is like not worth the money and like throughout the book they're setting up this binary 0.95

01:13:53.340 between acting on intuition and acting on data. Right. But what we see throughout this book is

01:14:00.420 that all of their quote unquote data driven presentation is riddled with ideology. Right.

01:14:07.780 Yeah. They're leaving out important information. They're using data that doesn't indicate

01:14:12.600 what they say it indicates. They're miss citing existing research. Right. I don't want to set up

01:14:19.460 like a weird QAnon thing where it's like it's bullshit to look at the data or like we shouldn't

01:14:23.920 look at research. Like that's obviously just as shallow as saying that like research will solve

01:14:28.420 everything. But I just want to stress that this is a false binary. There is no such thing as using

01:14:35.500 data to remove all human judgment value ideology from the way that we make decisions. We should

01:14:43.560 make decisions based on values, right? The book has a confidence to it that carries forward into

01:14:51.820 its readers almost, right? Where people had like this belief that this was sort of groundbreaking

01:14:58.080 in a sense. And, you know, I have to say as much as they present that dichotomy between like

01:15:03.620 intuition and science, the appeal of most of their ideas is really intuitive, right? You know,

01:15:09.840 They're making these claims that might not be the consensus but are not really counterintuitive, right?

01:15:17.160 Oh, well, swimming pools are dangerous, too.

01:15:18.860 I mean, that's something we all sort of know, right, that kids around swimming pools is a dangerous combination.

01:15:24.660 I actually think what they're presenting is basically something that is designed to appeal to your intuition, and that's why it's effective.

01:15:33.420 And I think very importantly, they're repackaging it and selling it back to you while telling you that it's science, right?

01:15:39.680 While telling you that it's objective, which I think is like somehow worse because if you know that you're going on your gut, you can compare that to other people's guts and have a little bit of humility about like, oh, I see it this way.

01:15:51.220 Somebody else sees it the other way. 0.99

01:15:52.420 But it's like, no, no, I'm doing science and everyone else is a fucking rube. 0.99

01:15:56.200 That's actually like really dangerous. 0.99

01:15:58.140 Right.

01:15:58.700 And there's an implication that institutions like major academic institutions are either ignoring or covering up this information in some way.

01:16:09.680 Right. And that shit is wildly dangerous. Right. And there's a sense to which sometimes I hear about a book like Freakonomics and it conjures up like very specific discussions like the abortion component. And then you hear all the things that the book contains. And rather than getting clarity, it just ends up being a jumble of bullshit in my mind. 1.00

01:16:33.380 where i'm like damn that book was a lot dumber than i thought it really is shocking how dumb 0.99

01:16:38.380 this book is i was expecting like gladwell where you have to kind of look for it this is also why 0.97

01:16:42.860 i wanted to leapfrog this to the first episode that we release because we've talked about a lot

01:16:48.420 of other books we've already recorded episodes on like one of the gladwell books and the end of

01:16:53.020 history and clash of civilizations but i think freakonomics is really one of the worst entries

01:16:59.380 in this both because of how stupid it is and also how like no one seemed to comment on that at the

01:17:05.880 time right it's kind of incredible and you know michael you once described this phenomenon to me 0.98

01:17:11.360 that the ted talkification of american discourse as a common consumer i think you would assume

01:17:19.200 that to the degree that this sort of like pop science exists above it somewhere is a level

01:17:27.040 of serious science that the serious people are discussing but in reality there are no serious

01:17:32.720 people and they're all reading this bullshit yeah that is like a very true and haunting phenomenon 0.88

01:17:37.980 but we're like you know the most powerful people in the world are absorbing the same 0.99

01:17:42.920 dumb ideas that the rest of us are freakonomics 0.96

01:17:57.040 We'll be right back. 0.99

Maintenance Phase - November 08, 2022

Bonus： Mike's New Podcast!

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