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Speaker 1: Pushkin.

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Speaker 2: Welcome back to Risky Business, a show about making better decisions.

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Speaker 2: I'm Nate Silver. My co host Maria Khannikova is off today,

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Speaker 2: but we do have a special guest. David Swag is

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Speaker 2: a journalist and author, most recently of the book An

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Speaker 2: Abundance of Caution, American Schools, The Virus and the Story

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Speaker 2: of Bad Decisions. He also writes a substack newsletter, Silent Lunch.

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Speaker 2: So welcome David. There are two reasons we're having you

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Speaker 2: on today. Why is I really like your book, In fact,

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Speaker 2: I endorse it. I blurred the back cover. And the

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Speaker 2: other is that it is Risky Business. It is a

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Speaker 2: show about making better decisions. That's our tagline, and this

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Speaker 2: is the case where a lot of really bad, high

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Speaker 2: stakes decisions were made. So welcome, Welcome to the show, David,

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Speaker 2: Thanks Nate, and to help you and the audience navigate,

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Speaker 2: we are covering quite a bit of territory today. I

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Speaker 2: want to kind of situate us at the start of

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Speaker 2: the pandemic, which may be a traumatic time frankly for

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Speaker 2: a lot of people. I want to talk through the

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Speaker 2: notion of cost benefit analysis and go through some terminology there,

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Speaker 2: talk about politics, and psychology talk about the model. So

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Speaker 2: there's a lot to get to. But I want to

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Speaker 2: first just ask, Okay, sometimes you'll hear this more often

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Speaker 2: from liberals who may be at made a Interesteff, we

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Speaker 2: didn't have the best possible COVID response, But why is

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Speaker 2: it important to talk about this? I mean, it's been

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Speaker 2: more than more than five years. What's your response to that.

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Speaker 1: Well, I'd say I have two responses. One is that

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Speaker 1: this was, to my mind, possibly the most important event

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Speaker 1: in some regards, you know, as far as infringing on

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Speaker 1: personal liberties of American citizens that we've seen in a

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Speaker 1: generation or more. And you know, when you compare it

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Speaker 1: to other events like I don't know nine to eleven

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Speaker 1: or the Iraq War, the amount of analysis and books

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Speaker 1: written and scholarly study of those events to me seems

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Speaker 1: like there should be that but times ten for this,

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Speaker 1: I mean, like the actual impact on every single person

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Speaker 1: in the country, and of particular interest to me children,

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Speaker 1: to my mind, has not remotely been adequately studied or

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Speaker 1: reckoned with one of the prime reasons I wrote my book.

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Speaker 1: And the second answer to your question is that, ultimately,

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Speaker 1: you know, I think, like any good books should be

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Speaker 1: my book is not really about the pandemic. That's the backdrop,

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Speaker 1: but hopefully what it's about is indeed to the topic

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Speaker 1: of your podcast. It's really, to use a medical word,

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Speaker 1: it's an anatomy of decision making, and my whole book

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Speaker 1: is interested in how do individuals, how do policymakers, and

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Speaker 1: how do we as a society make decisions, particularly when

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Speaker 1: we have limited information and in a time of crisis.

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Speaker 1: I use the pandemic as a case study or is

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Speaker 1: a back to kind of explore these these dynamics in

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Speaker 1: our country, where the reader hopefully comes away from the

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Speaker 1: book with an understanding about these kind of decision making

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Speaker 1: dynamics that can be applied really to any time that's happening,

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Speaker 1: not just a sort of retrospective.

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Speaker 2: Look, do you think there's some scar tissue where people

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Speaker 2: find it traumatizing it because, like so, we just had

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Speaker 2: two big books come out about Joe Biden, which is

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Speaker 2: a case that in certain ways is parallel where things

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Speaker 2: maybe people on the left kind of got wrong right

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Speaker 2: directionally speaking, do you think people are traumatized by this

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Speaker 2: experience and don't like talking about it?

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Speaker 1: Well, I don't just think and I know it because

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Speaker 1: many people have told me so. But you know, a

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Speaker 1: reaction I've heard many times to the book is someone

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Speaker 1: said they wanted to put their fist through a wall

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Speaker 1: while they were reading it. Someone else said they cried,

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Speaker 1: people are cringing. Someone said they had to read it

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Speaker 1: in stages. But with all that said, to my mind,

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Speaker 1: this is something that is both a difficult but necessary read.

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Speaker 1: So Scar Tiss would be damned.

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Speaker 2: So I do want to take us back now five

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Speaker 2: plus years roughly. You know, for me, it was kind

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Speaker 2: of a crazy time. This is just the climax of

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Speaker 2: the Democratic primary campaign. So I'm like flying around like

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Speaker 2: New Hampshire and South Carolina and various events, big conference

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Speaker 2: in Boston. Increasingly you see every flight, every flight, it's

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Speaker 2: a little bit emptier every time. You get a little

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Speaker 2: bit more worried about, you know, maybe we shouldn't be

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Speaker 2: gathering all these people together. You are in Westchester County, correct,

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Speaker 2: which is if people don't know, it's the immediate northern

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Speaker 2: suburbs of New York City, stereotypically nice, leafy houses, liberal,

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Speaker 2: kind of pro democratic politics, middle class, upper middle class

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Speaker 2: depending on the precise community. Right, And you're a dat

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Speaker 2: of too Yep, everything you said sounds accurate. I live

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Speaker 2: part time in Weschester County two. My mom grew up

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Speaker 2: in a town called Crotons, so I can visualize this

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Speaker 2: and like, so one might say, it's like not the

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Speaker 2: worst place to be in a pandemic, right, It's kind

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Speaker 2: of medium density. There tend to be parks and places

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Speaker 2: to go jogging. So what's your sense at the very

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Speaker 2: start of the pandemic when do you start to worry

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Speaker 2: this is going to be severe? How are you behaving?

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Speaker 1: Like most people in my area when when things kicked off,

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Speaker 1: I listened to the experts. We locked down. I'm a

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Speaker 1: little embarrassed to admit we even wiped our groceries when

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Speaker 1: they came in. So I did not start out as

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Speaker 1: a contrarian on this. I had no political motivations in

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Speaker 1: this at all, and I had no reason to disregard

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Speaker 1: what we were being told simultaneously. However, within like day

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Speaker 1: one of so called remote learning, it was very obvious

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Speaker 1: to me that this was not going to work over

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Speaker 1: a long period of time. It seemed a reasonable trade

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Speaker 1: off initially based on the information we were given, so

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Speaker 1: I wasn't disregarding that, but Nevertheless, this still seemed like, whoa,

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Speaker 1: how is this going to play out? Because this is

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Speaker 1: not working. I had a third grader and a fifth

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Speaker 1: grader at the time, and it was just obvious this

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Speaker 1: was going to be a disaster, and that really led

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Speaker 1: me to start digging into this.

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Speaker 2: So when did you have these moments, David where you

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Speaker 2: felt like, oh my god, there's not a lot of

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Speaker 2: trustworthy information. What were those those inflections?

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Speaker 1: Yeah? So, like I said, I sort of had no

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Speaker 1: reason initially to disregard what we were being told. But

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Speaker 1: my nature, just my disposition is to always be somewhat skeptical,

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Speaker 1: and initially I wasn't pursuing this professionally at all. It

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Speaker 1: was just sort of my own need to feel informed

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Speaker 1: about what was going on. And what changed for me

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Speaker 1: was I started realizing the information was getting I started

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Speaker 1: emailing infectious disease experts and epidemiologists and others, almost all

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Speaker 1: of them in Europe because the ones in the States

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Speaker 1: weren't responding or didn't have the information. But I started

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Speaker 1: reaching out to people in Europe trying to get more information,

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Speaker 1: and I very quickly had this strange feeling. I'm like,

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Speaker 1: holy shit, like none of this stuff is really being

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Speaker 1: printed in the Times or I'm not seeing this elsewhere.

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Speaker 1: And then that's when I was like, all right, maybe

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Speaker 1: I need to do something about this. I'm in the media.

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Speaker 1: You know, it's like the media is disappointing me. Well, okay,

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Speaker 1: then I guess it falls on my shoulders. And I

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Speaker 1: was writing another book at the time, obviously totally unrelated

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Speaker 1: to the topic. I just couldn't concentrate on anything. All

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Speaker 1: I could think about was this insane, you know, circumstance

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Speaker 1: that we were in. And then just more specifically, Nate,

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Speaker 1: toward the end of April, I was walking with a

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Speaker 1: friend of mine on the high school track here in

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Speaker 1: my town and we were dutifully separated on like lanes

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Speaker 1: one and four, wearing masks most likely. And by the

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Speaker 1: end of April, I think it was new cases in

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Speaker 1: New York had dropped by something like fifty percent. And

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Speaker 1: as you'll recall and everyone else will, you know, we

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Speaker 1: were told and the official slogan was fifteen days to

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Speaker 1: slow the spread that began in March, and then they

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Speaker 1: tacked another thirty days onto that, and you know, and

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Speaker 1: there was seemingly, to my mind like there was no

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Speaker 1: real debate or pushbackers, just like, oh yeah, I remember

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Speaker 1: how we told you fifteen days. Now we're adding another thirty.

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Speaker 1: And so the thing is, the reasoning behind the fifteen

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Speaker 1: days to slow the spread was we had to prevent

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Speaker 1: hospitals from being overwhelmed. And you know how, we were

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Speaker 1: shown this this graph of you know, if everyone just

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Speaker 1: follows instructions, you'll have this gentle slope, and if you

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Speaker 1: don't follow instructions, we'll have this spike and the hospitals

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Speaker 1: will be overwhelmed. So by the end of April, cases

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Speaker 1: had fallen, new cases had fallen something like fifty percent.

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Speaker 1: And I said to my friend, I'm like, oh, well,

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Speaker 1: do you think schools are going to open next week?

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Speaker 1: You know, I assume, And he's like, what are you

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Speaker 1: talking about. I'm like, well, we did it. We flattened

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Speaker 1: the curve, man. We we had a very specific goal

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Speaker 1: that we were told we needed to achieve. We achieved it.

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Speaker 1: We flattened like literally, and and then he was like, dude,

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Speaker 1: they're not going back. They're not going back to school,

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Speaker 1: and like, still, even though I've retold this story a

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Speaker 1: million times and talk about in the book The Hairs

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Speaker 1: on the back of my neck still stand up, because that,

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Speaker 1: to me was one of the in was like the

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Speaker 1: initial moment where I'm like, oh, like, so that's really

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Speaker 1: weird that we're in a country where the government told

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Speaker 1: us like, here's the thing you need to do, here's

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Speaker 1: the goal that we're trying to achieve. Then we achieved

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Speaker 1: that goal, but but then they just kept going anyway.

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Speaker 2: Yeah, I know, people forget how much goodwill there was, right, Like,

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Speaker 2: so when shit hit the fan, like kind of Rudy

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Speaker 2: Gobert Tom Hanks day, Right, I was flying to Kansas City,

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Speaker 2: where my partner's father was in hospice cares. So, you know,

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Speaker 2: to be in an environment like that, in a kind

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Speaker 2: of rural Missouri hospital at a time when this disease

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Speaker 2: is getting to spread around the country was I think

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Speaker 2: scary for everybody involved. Right, But we wound up staying

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Speaker 2: in Kansas City for a month because there's a giant

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Speaker 2: red circle around New York City. Of course, there's no

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Speaker 2: way to ascertain cases in Kansas City. I call the

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Speaker 2: Department of Health in Missouri. They're like, have you been

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Speaker 2: to Wuhan, China, Well, then you can't get a COVID

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Speaker 2: test kind of thing, right, But then it was that

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Speaker 2: question of like, what is the endgame here?

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Speaker 1: Right?

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Speaker 2: I remember we had friends over like you. At first

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Speaker 2: I was very cautious, remember, like yelling at a stranger

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Speaker 2: for not wearing a mask on an elevator and some

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Speaker 2: carini ish behavior there, right, But gradually there was kind

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Speaker 2: of this thing where you start to I roll and

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Speaker 2: group chat and you're like, we can't really not do

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Speaker 2: and we don't even have kids, you do, right, we

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Speaker 2: can't really stay cooped up for the definite future, right,

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Speaker 2: because you could project fotward that like there was no

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Speaker 2: there was no plan at all.

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Speaker 1: So one of the things that was really important to me,

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Speaker 1: and you know what I call like a record scratch

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Speaker 1: moment in the book is when at the end of

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Speaker 1: April and beginning of May, twenty two countries in Europe

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Speaker 1: began reopening their lower schools. So this is not like

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Speaker 1: one tiny schoolhouse in the you know, in the countryside

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Speaker 1: of you know, Denmark, twenty two countries and this includes

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Speaker 1: massive cities like Paris and you know and elsewhere. And

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Speaker 1: toward the end of April, the education ministers of the

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Speaker 1: EU met or met you know, at least online and

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Speaker 1: they said, we've observed no negative consequences of this. They

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Speaker 1: met a second time in June and they hade the

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Speaker 1: same reaction and that for me, I remember watching the

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Speaker 1: video of this and like I just it was like

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Speaker 1: a sense of unreality because that is the type of

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Speaker 1: thing that should have been splashed across the front pages

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Speaker 1: of every newspaper. This should have been you know, crawling

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Speaker 1: on the screen on every cable news network. This was

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Speaker 1: the news. Ostensibly we were waiting for Europe looked at

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Speaker 1: all the same information we had and came to a

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Speaker 1: very different conclusion about what was wise, and for them

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Speaker 1: was we should open the schools. And it is not

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Speaker 1: because Europe controlled the virus, which is like one of

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Speaker 1: the false arguments about oh well Europe did that, because

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Speaker 1: they know they didn't. I give an analysis within my book.

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Speaker 1: You know, maybe on a country level when you look

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Speaker 1: at it, but if you look at different you can

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Speaker 1: match up city to city, small town to small town,

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Speaker 1: and go on and on and on and see that

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Speaker 1: in Europe they had cases that were above, that were below,

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Speaker 1: and that were around the same. It was all over

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Speaker 1: the map, you know, literally and figuratively. So they didn't

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Speaker 1: quote control the virus. I think that you know, they

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Speaker 1: weren't doing mass mandates across the board, they weren't doing

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Speaker 1: distancing across the board of six feet. They didn't have

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Speaker 1: have the filters, they didn't have barriers across the board,

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Speaker 1: none of this stuff that we were told, and nevertheless

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Speaker 1: they said we haven't observed any negative impact. That is

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Speaker 1: an extraordinary moment that this was ignored and then if

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Speaker 1: it was ever mentioned, was waved away. I ultimately wrote

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Speaker 1: about it in June I think that meeting, and you know,

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Speaker 1: and I talk about it in my book, but this

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Speaker 1: was not covered. Essentially, this was just memory hold. So

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Speaker 1: that was one key point, key moment. Another one was

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Speaker 1: when the cases had fallen in New York City, as

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Speaker 1: I mentioned, you know, by the end of April dropped

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Speaker 1: something like fifty percent. Another key moment was an article

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Speaker 1: that had come out on NPR. Of all places where

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Speaker 1: they talked about the where they talked about the daycares

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Speaker 1: and the YMCAs, tens of thousands of kids were in

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Speaker 1: these programs early on and they observed no real outbreaks

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Speaker 1: or no kind of like overt negative impacts of this.

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Speaker 1: And then lastly there was the study out of Sweden

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Speaker 1: where they never closed the lower schools. And by the way,

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Speaker 1: Stockholm is, you know, that's a major city. We had

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Speaker 1: like empirical evidence just kind of like screaming at us

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Speaker 1: in the face, and it just kept being waved away.

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Speaker 1: So those were kind of like three or four really

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Speaker 1: important moments quite early in the pandemic when it was

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Speaker 1: clear that schools were not driving the pandemic, and indeed,

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Speaker 1: tons of studies later on showed how schools by and

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Speaker 1: large tended to mirror at most or or be below

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Speaker 1: the community rates of infection.

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Speaker 2: Do you want to talk a little bit, So, first

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Speaker 2: of all, it is an election year. Do you think

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Speaker 2: the polarity of this was inevitable? What if Hillary Clinton

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Speaker 2: had gotten a few more thousand votes in Wisconsin, Michigan,

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Speaker 2: Pennsylvania and Hillary Clinton had been president, do you think

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Speaker 2: this would have polarized in reverse?

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Speaker 1: You know, it's a counterfactual, so who's to say. But

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Speaker 1: I do think, based on all the evidence that I

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Speaker 1: describe in my book, it seems impossible to not see

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Speaker 1: it that way. That and I you know, and I believe,

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Speaker 1: and you can tell me if you disagree, But I

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Speaker 1: think I make a pretty strong, like lawyerly persuasive case

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Speaker 1: that much of the response in America from the public

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Speaker 1: health establishment, from the legacy media, from the broader sort

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Speaker 1: of like left wing you know, elites, so to speak,

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Speaker 1: was reactionary against Trump and against Republicans. And you know

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Speaker 1: that's not just sort of like an opinion. There's all

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Speaker 1: sorts of like interesting data on this, and also you know,

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Speaker 1: my anecdotal experience of this, you know, and we can

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Speaker 1: get into it. You know, there's the countless numbers of

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Speaker 1: doctors and others who reached out to me saying that

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Speaker 1: they agreed with the stuff I was writing, but they

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Speaker 1: were afraid to say so publicly, or they were explicitly

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Speaker 1: told they couldn't say so. I don't make this statement

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Speaker 1: lightly about the left being reactionary. I think a lot

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Speaker 1: of people and left weren't even aware that they were

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Speaker 1: being reactionary. I don't even know how much they were

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Speaker 1: thinking about it. This is what the people from on

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Speaker 1: high were telling them. So, you know, we could get

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Speaker 1: into it. But it's like most these you know, most

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Speaker 1: experts in anyfield have a relatively narrow range of expertise.

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Speaker 1: But yet somehow this is slightly tangential to your question.

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Speaker 1: But somehow anyone who was a quote epidemiologist, anyone who

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Speaker 1: had MD after the name, they all of a sudden

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Speaker 1: became experts in like an entire way of living your life,

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Speaker 1: an entire sort of societal response.

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Speaker 2: I can't I can't resist the bait about the way

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Speaker 2: that experts were thrown around and they I mean, first

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Speaker 2: of all, sometimes it was just like blatantly exclusionary, where

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Speaker 2: if you're you know, like Jay Boicharia who now works

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Speaker 2: to the White House, right perfectly what credential expert, but

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Speaker 2: he was going against the consensus, so therefore was kind

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Speaker 2: of black balls too strong a phrase. He had a

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Speaker 2: strong voice and social media and so forth right, but

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Speaker 2: like who is an expert when it comes to COVID policy?

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Speaker 1: So that's an awesome question, and it's one of the

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Speaker 1: to my mind, I think key threads in my book

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Speaker 1: where I discussed the idea that only certain people were

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Speaker 1: allowed really within the public conversation and within the media

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Speaker 1: to weigh in on what we should be doing. There's

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Speaker 1: sort of two problems with that. One is that someone

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Speaker 1: like Anthony Fauci has a particular at least ostensibly a

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Speaker 1: particular expertise within infectious diseases and perhaps how to manage them.

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Speaker 1: He does not have an expertise in the values of

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Speaker 1: society and in second order effects of non pharmaceutical interventions

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Speaker 1: and mitigations that I know, that's like a mouthful, but

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Speaker 1: in plain English, he's not an expert on what happens

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Speaker 1: to children who when schools are closed and they won't

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Speaker 1: be able to graduate, you have kids stuck at home

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Speaker 1: with an abusive parent. Because child abuse cases had skyrocketed,

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Speaker 1: and by the way, we knew this data as early

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Speaker 1: as April of twenty twenty. They already had indications that

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Speaker 1: very very bad things were happening to a lot of

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Speaker 1: really vulnerable kids. So Anthony Fauci, you know, and others

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Speaker 1: sort of like within that lane, have a very specific

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Speaker 1: range of knowledge and expertise, and yet they were given

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Speaker 1: this mandate really on being the overall sort of director

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Speaker 1: of society. And then to make matters worse, Nate, there

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Speaker 1: were other people who sort of fashioned themselves as these

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Speaker 1: like COVID pundics, who really for much of the population

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Speaker 1: dictated how they were supposed to think about what was

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Speaker 1: prudent and what was critical or not critical about various

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Speaker 1: interventions that we had to be subject to.

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Speaker 2: Yeah, my model of this right, as you have kind

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Speaker 2: of one group of experts that might attempt to predict

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Speaker 2: how bad the disease will be, both in terms of

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Speaker 2: number of cases and mortality under certain scenarios. You might

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Speaker 2: have another group of experts, maybe more economists, who talk

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Speaker 2: about what the what the trade offs are, what are

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Speaker 2: the consequences of closing schools, And then it's a society's

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Speaker 2: job to, in our flawed democratic system way that expert

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Speaker 2: evidence and make what our ultimately political decisions. But I

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Speaker 2: want to set one thing up, and maybe it's kind

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Speaker 2: of an inside baseball question about the reporting of the book,

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Speaker 2: But so, why the decision to focus so much on

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Speaker 2: schools right? Why that focus?

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Speaker 1: I mean, I use schools right as a launch point

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Speaker 1: into this sort of larger Obviously I get into a

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Speaker 1: lot of mask mandate stuff and all these other interventions

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Speaker 1: imposed I would say schools and children in tandem, because

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Speaker 1: I'm really concerned about not just the school closures, but

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Speaker 1: the broader sort of view of children in society during

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Speaker 1: in America and the positioning of them as these sort

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Speaker 1: of like silent super spreaders and the interventions that were

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Speaker 1: imposed on them in our country in a sort of

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Speaker 1: somewhat uniquely aggressive medical culture that we have here, you know,

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Speaker 1: where it's like two year olds had to be masked

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Speaker 1: in America, whereas in Europe, the ECDC, that's their version

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Speaker 1: of the CDC, they didn't even recommend that kids in

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Speaker 1: primary school wear masks at all. And you know, the

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Speaker 1: World Health Organization they had mask mandate. I think it

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Speaker 1: was age six and up. So the fact that just

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Speaker 1: just one of the zillion examples, the fact that it

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Speaker 1: was like required for two year olds in America to

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Speaker 1: wear masks was you know, it was quite unusual and

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Speaker 1: worthy of comment. So the reason I mentioned this is

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Speaker 1: is to me, the kind of like biggest unforced error

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Speaker 1: in America was the long term closure of schools, and

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Speaker 1: then secondarily the impositions imposed on children when schools were open. Finally,

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Speaker 1: that of all the harms that happened, to my mind,

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Speaker 1: this one is, you know, and it's hard to quantify

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Speaker 1: this stuff, mate, but this was perhaps the most consequential,

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Speaker 1: and if not the most consequential, certainly the most unnecessarily

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Speaker 1: harmful of all the interventions that were imposed.

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Speaker 2: Yeah, I want to get one. So I guess I'm

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Speaker 2: going to ask you an epidemiological question, right. So one

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Speaker 2: of the first things that was there very early on

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Speaker 2: that this disease was hitting older people exponentially harder than

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Speaker 2: younger people, which is not true for all pandemics. So

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Speaker 2: can you explain why that was true for this particular coronavirus.

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Speaker 1: One of the things that that I'm really interested in

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Speaker 1: his narrative formation and you know, and I talk about

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Speaker 1: that a lot in the book is like how these

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Speaker 1: certain narratives and ideas were formed and then how they

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Speaker 1: were enforced. And one of them is even when you

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Speaker 1: think about the term novel coronavirus, even the word novel

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Speaker 1: adds on an immediate type of association for people. This

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Speaker 1: is new, and often with a disease, something that's new

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Speaker 1: is going to be particularly scary. Think about the word COVID.

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Speaker 1: It's written in all caps. It's different than just like

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Speaker 1: the flu, you know, in lowercase. These things, these things matter,

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Speaker 1: I think to some extent. And the reality is that

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Speaker 1: coronaviruses have been with us for a zillion years. Much

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Speaker 1: of the common colds that we get are from coronaviruses.

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Speaker 1: There's a lot of literature that shows that SARS Kobe two,

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Speaker 1: which causes COVID, you know, the novel coronavirus, that it

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Speaker 1: behaved very similarly to way other coronaviruses had behaved. And

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Speaker 1: I interviewed this gentleman who's a specialist in actious diseases

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Speaker 1: and looking historically from an ethical perspective about how we

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Speaker 1: respond to these things, and he kind of went into

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Speaker 1: a whole thing with me saying like, look this, He's like,

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Speaker 1: this was positioned from the beginning as something that was

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Speaker 1: quote unprecedented. He's like, if I can tell you one thing,

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Speaker 1: please don't use the word unprecedented. It's not our reaction

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Speaker 1: was unprecedented. But having a highly contagious respiratory virus, that's

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Speaker 1: old news. And we shouldn't have been surprised that this

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Speaker 1: was particularly dangerous to old people. There are old people

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Speaker 1: who die every year from just common cold coronaviruses in

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Speaker 1: you know, long term care homes. It's very typical, and

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Speaker 1: children are largely unscathed. It's like a common cold. So

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Speaker 1: unless we were given evidence or shown a reason why

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Speaker 1: to think that this should be performing or acting differently,

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Speaker 1: we should have gone with what to expect. You know,

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Speaker 1: in medicine, there's that expression, if you hear or hoods,

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Speaker 1: think of a horse, don't think of a zebra. I

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Speaker 1: mean everyone and I talked about this in the book.

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Speaker 1: Everyone thought of the zebra, but we should have thought

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Speaker 1: of the horse. Whether this came from a lab or not,

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Speaker 1: it's still a coronavirus and still largely behaved similarly to

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Speaker 1: other coronaviruses, if perhaps more virulent for older people. Though,

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Speaker 1: of course.

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Speaker 2: We'll be right back after this message. I'm going to

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Speaker 2: give you some phrases and you can kind of use

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Speaker 2: these as jumping off points. I think these are all

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Speaker 2: phrases where there was some degree of ambiguity or maybe

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Speaker 2: strategy and how they were employed. But let me start

429
00:25:05,404 --> 00:25:08,404
Speaker 2: with precautionary principle. It's kind of related to the title

430
00:25:08,444 --> 00:25:12,284
Speaker 2: of your book. What does that mean? What should it mean?

431
00:25:12,804 --> 00:25:15,244
Speaker 1: Yeah, I spend a lot of time talking about the

432
00:25:15,324 --> 00:25:21,444
Speaker 1: precautionary principle. I think it's fascinating. I interviewed this scholar

433
00:25:21,524 --> 00:25:26,644
Speaker 1: named Eric Winsburg, who's a philosopher of medicine and particularly

434
00:25:27,244 --> 00:25:31,284
Speaker 1: of ethics in modeling, and we talked a lot about

435
00:25:31,324 --> 00:25:34,244
Speaker 1: the precautionary principle. And one thing I learned from him,

436
00:25:34,684 --> 00:25:36,204
Speaker 1: and that I talk about in the book, is that

437
00:25:36,284 --> 00:25:39,084
Speaker 1: a lot of philosophers don't even believe there's such a

438
00:25:39,124 --> 00:25:41,924
Speaker 1: thing as the precautionary principle, because it's based on an

439
00:25:41,964 --> 00:25:45,524
Speaker 1: assumption that you know how much harm may come to

440
00:25:45,524 --> 00:25:48,444
Speaker 1: you from doing one thing and how much harm you'll

441
00:25:48,484 --> 00:25:52,404
Speaker 1: avoid by doing this other thing that already within the

442
00:25:52,724 --> 00:25:56,044
Speaker 1: beginning of the precautionary principle. It's based on certain assumptions. Now,

443
00:25:56,164 --> 00:26:00,684
Speaker 1: the precautionary principle, as we conventionally understand it, is a

444
00:26:00,724 --> 00:26:04,684
Speaker 1: prudent and reasonable course of action in certain circumstances. But

445
00:26:06,084 --> 00:26:11,004
Speaker 1: those circumstances require a real kind of specific set of

446
00:26:11,924 --> 00:26:16,084
Speaker 1: data or information that you can be certain about, and

447
00:26:16,804 --> 00:26:20,564
Speaker 1: very very quickly within the pandemic, we no longer met

448
00:26:20,884 --> 00:26:25,324
Speaker 1: that specific criteria for the precautionary principle. Certainly so Nate.

449
00:26:25,564 --> 00:26:29,124
Speaker 1: By the end of April beginning of May, if particular,

450
00:26:29,124 --> 00:26:32,044
Speaker 1: if we're thinking about schools, millions of kids twenty two

451
00:26:32,124 --> 00:26:35,004
Speaker 1: countries reopen their schools. At that point, you can no

452
00:26:35,084 --> 00:26:38,444
Speaker 1: longer say that we are keeping schools closed. Here quote

453
00:26:38,644 --> 00:26:41,804
Speaker 1: out of an abundance of caution, you just can't so.

454
00:26:42,084 --> 00:26:45,324
Speaker 1: But this was the sort of like mic drop, It's like, well,

455
00:26:45,364 --> 00:26:49,084
Speaker 1: I'm just being cautious. It became very hard for most

456
00:26:49,124 --> 00:26:52,444
Speaker 1: regular people to push back against something when they're like,

457
00:26:52,484 --> 00:26:53,964
Speaker 1: who wouldn't want to be cautious?

458
00:26:54,484 --> 00:26:59,564
Speaker 2: Yeah. There's kind of this effective altruist slash rationalist adjacent

459
00:26:59,604 --> 00:27:03,244
Speaker 2: phrase called Chesterton's fence, which is the idea that if

460
00:27:03,244 --> 00:27:05,684
Speaker 2: you see a fence out in the middle of the wilderness,

461
00:27:06,444 --> 00:27:09,684
Speaker 2: then you probably shouldn't remove it, right, Maybe it's preting

462
00:27:09,724 --> 00:27:13,204
Speaker 2: you from bears or snakes or who knows what, right,

463
00:27:13,564 --> 00:27:16,964
Speaker 2: And that's I think a more coherent version of the

464
00:27:16,964 --> 00:27:22,364
Speaker 2: precautionary principle, or like be wary of uprooting society if

465
00:27:22,404 --> 00:27:25,084
Speaker 2: there might be unknown consequences. But it seemed like, if anything,

466
00:27:25,124 --> 00:27:27,324
Speaker 2: that might be the reverse of it, right.

467
00:27:27,724 --> 00:27:31,364
Speaker 1: Just to kind of dontail with your point there. In medicine,

468
00:27:31,364 --> 00:27:34,484
Speaker 1: everyone knows the cliche of first, do no harm, yea,

469
00:27:34,844 --> 00:27:39,924
Speaker 1: and we reversed that in the pandemic that typically what

470
00:27:39,964 --> 00:27:44,884
Speaker 1: you're supposed to do ethically is you don't act first

471
00:27:45,124 --> 00:27:47,564
Speaker 1: and then try to figure out things you first. You

472
00:27:47,564 --> 00:27:49,924
Speaker 1: know there's a reason why the FDA's you know modo,

473
00:27:50,124 --> 00:27:52,724
Speaker 1: you know, or their mandate is first you have to

474
00:27:52,804 --> 00:27:56,724
Speaker 1: find out if something is safe and effective, then it

475
00:27:56,764 --> 00:27:59,924
Speaker 1: gets approved by the FDA. Yet we did the opposite

476
00:28:00,044 --> 00:28:03,884
Speaker 1: in the pandemic. We had all these interventions because the

477
00:28:03,924 --> 00:28:06,924
Speaker 1: school closure is an intervention. That's not the norm. The

478
00:28:06,964 --> 00:28:09,404
Speaker 1: norm is for kids to be in school, that's the default.

479
00:28:09,724 --> 00:28:12,884
Speaker 1: But we flipped the default. And again there could be

480
00:28:12,964 --> 00:28:17,484
Speaker 1: some argument made for that in you know, March tenth

481
00:28:17,924 --> 00:28:21,644
Speaker 1: of April twenty twenty. But once there was an enormous

482
00:28:21,644 --> 00:28:26,644
Speaker 1: amount of empirical evidence that millions of kids in school

483
00:28:27,004 --> 00:28:30,844
Speaker 1: was not having a catamoclysmic effect. The precautionary principle or

484
00:28:30,844 --> 00:28:33,604
Speaker 1: this quote acting out of an abundance of caution, like

485
00:28:33,644 --> 00:28:38,964
Speaker 1: I titled my book, this was just a complete bastardization

486
00:28:39,284 --> 00:28:43,164
Speaker 1: of what that actual sort of principle is about and

487
00:28:43,204 --> 00:28:44,804
Speaker 1: how it can or should be used.

488
00:28:45,364 --> 00:28:49,444
Speaker 2: The two word phrase quote no evidence. I came to

489
00:28:49,444 --> 00:28:52,444
Speaker 2: be very wary of, right, because you'd read things like, oh,

490
00:28:52,484 --> 00:28:56,764
Speaker 2: there's there's no evidence that children transmit the disease less

491
00:28:56,844 --> 00:29:00,404
Speaker 2: effectively than adults, right when like though the way that

492
00:29:00,404 --> 00:29:03,884
Speaker 2: we used to me, there's like there's no absolute proof, right,

493
00:29:03,964 --> 00:29:07,084
Speaker 2: when there's lots of evidence, right, there might be pulminary studies.

494
00:29:07,124 --> 00:29:10,364
Speaker 2: They're also you know, to use term that our listeners

495
00:29:10,404 --> 00:29:13,484
Speaker 2: will know there are Bayesian priors, right, you know, we

496
00:29:13,524 --> 00:29:15,684
Speaker 2: probably had strong priors to believe that, yes, if you

497
00:29:15,764 --> 00:29:18,204
Speaker 2: got this disease, like almost every other disease, you would

498
00:29:18,244 --> 00:29:21,604
Speaker 2: get some degree of immune protection from that. I mean,

499
00:29:21,644 --> 00:29:27,924
Speaker 2: how did a certain faction manage to wrangle the default

500
00:29:28,124 --> 00:29:31,964
Speaker 2: toward being on their side? How did that become the default?

501
00:29:33,204 --> 00:29:36,084
Speaker 1: I think a lot of it has to do with that.

502
00:29:36,124 --> 00:29:43,324
Speaker 1: We have a very very large degree of homogeneity of

503
00:29:43,684 --> 00:29:49,004
Speaker 1: uniformity within certain very influential institutions in our country, and

504
00:29:49,044 --> 00:29:52,004
Speaker 1: in particular to the pandemic. We think about public health

505
00:29:53,204 --> 00:29:58,044
Speaker 1: and within the legacy media. And the uniformity, there's two

506
00:29:58,084 --> 00:30:01,924
Speaker 1: aspects to it. One is sort of political uniformity that

507
00:30:02,044 --> 00:30:05,044
Speaker 1: both of these kind of institutions tend to lean left

508
00:30:05,444 --> 00:30:09,644
Speaker 1: the people within them. And number two, they also to

509
00:30:09,764 --> 00:30:12,524
Speaker 1: self select for a certain type of person. So you

510
00:30:12,684 --> 00:30:16,204
Speaker 1: have this kind of thing where you had almost everyone

511
00:30:16,244 --> 00:30:20,004
Speaker 1: there on the left in these important institutions in our

512
00:30:20,084 --> 00:30:22,644
Speaker 1: country during the pandemic. And not only were they all

513
00:30:22,844 --> 00:30:26,004
Speaker 1: kind of largely of the same political persuasion, but they

514
00:30:26,004 --> 00:30:28,764
Speaker 1: were also most of them, not all, but most of

515
00:30:28,804 --> 00:30:31,804
Speaker 1: them are of the same type of personality type that

516
00:30:33,364 --> 00:30:36,084
Speaker 1: got to the level of success where they are so

517
00:30:36,244 --> 00:30:39,844
Speaker 1: all that merged together, Nate is it leads to a

518
00:30:39,884 --> 00:30:45,004
Speaker 1: situation where when Donald Trump tweeted in July, schools should

519
00:30:45,044 --> 00:30:47,484
Speaker 1: open in the fall or schools must open in all

520
00:30:47,564 --> 00:30:51,364
Speaker 1: caps or a bunch of exclamation points. That was immediately

521
00:30:51,484 --> 00:30:54,964
Speaker 1: radioactive to a lot of these people, and to whomever

522
00:30:55,084 --> 00:30:59,164
Speaker 1: else it wasn't radioactive. They got the message quickly that

523
00:30:59,484 --> 00:31:03,524
Speaker 1: you cannot agree with Donald Trump on anything. And there

524
00:31:03,604 --> 00:31:09,084
Speaker 1: was such a sort of enforced uniformity within these institutions,

525
00:31:09,084 --> 00:31:12,964
Speaker 1: within public health, and within the media that that's how

526
00:31:13,004 --> 00:31:17,444
Speaker 1: you get to a circumstance where something manifestly crazy is

527
00:31:17,524 --> 00:31:21,324
Speaker 1: accepted by a very large portion of society. Yeah.

528
00:31:21,364 --> 00:31:23,924
Speaker 2: The next phrase I wanted to ask you about, which

529
00:31:23,964 --> 00:31:27,204
Speaker 2: I think a quite complicated phrase actually, is scientific consensus.

530
00:31:28,764 --> 00:31:30,564
Speaker 2: What does that mean? What should it mean?

531
00:31:31,884 --> 00:31:35,324
Speaker 1: Yeah, this was bandied about all the time, and this

532
00:31:35,564 --> 00:31:38,084
Speaker 1: you know, what's nice is your questions here. Everything kind

533
00:31:38,124 --> 00:31:44,284
Speaker 1: of threads together because the idea of a scientific consensus

534
00:31:45,004 --> 00:31:47,484
Speaker 1: was to a large extent, or at least to some

535
00:31:47,564 --> 00:31:52,044
Speaker 1: extent manufactured. Once I started writing some articles that were

536
00:31:52,524 --> 00:31:55,444
Speaker 1: challenging to some of the establishment views, but I was

537
00:31:55,444 --> 00:31:59,084
Speaker 1: writing them in largely kind of legacy media outlets, so

538
00:31:59,124 --> 00:32:02,364
Speaker 1: it's kind of had a different type of impromoter, you know,

539
00:32:02,444 --> 00:32:05,884
Speaker 1: attached to it that people could accept it. I started

540
00:32:05,884 --> 00:32:09,004
Speaker 1: getting emails from people around the country, including a lot

541
00:32:09,004 --> 00:32:13,044
Speaker 1: of doc and including some former CDC and former NIH people,

542
00:32:13,124 --> 00:32:15,484
Speaker 1: and they would say most of them would start off

543
00:32:15,524 --> 00:32:17,684
Speaker 1: something like, thank you so much for this, you know,

544
00:32:17,724 --> 00:32:20,164
Speaker 1: for writing this article. I agree with the points you're

545
00:32:20,164 --> 00:32:23,004
Speaker 1: making in here. This just doesn't seem like it's beneficial

546
00:32:23,044 --> 00:32:25,284
Speaker 1: for schools to be closed. I think it's really harmful.

547
00:32:25,404 --> 00:32:27,484
Speaker 1: I don't see the value in mask mandates on these

548
00:32:27,524 --> 00:32:30,324
Speaker 1: little kids, or barriers on their desks, on and on

549
00:32:30,404 --> 00:32:33,644
Speaker 1: whatever it may be. And then they would say, but

550
00:32:34,204 --> 00:32:35,524
Speaker 1: all of this is off the record.

551
00:32:36,964 --> 00:32:37,164
Speaker 2: Yeah.

552
00:32:37,244 --> 00:32:39,244
Speaker 1: And then the second part of that is some of

553
00:32:39,324 --> 00:32:42,964
Speaker 1: these people were told explicitly by their bosses, you know,

554
00:32:43,004 --> 00:32:44,924
Speaker 1: when we're talking like at you know, some of our

555
00:32:44,964 --> 00:32:48,284
Speaker 1: top university hospitals in the country. There was a particular

556
00:32:48,324 --> 00:32:50,804
Speaker 1: physician who I spoke with who worked in the nick you,

557
00:32:50,964 --> 00:32:54,724
Speaker 1: that's like the the pediatric or pick you pediatric intensive

558
00:32:54,764 --> 00:32:57,044
Speaker 1: care unit. And she had said to this was like

559
00:32:57,084 --> 00:33:00,004
Speaker 1: a small kind of like niche media outlet, so it

560
00:33:00,044 --> 00:33:02,284
Speaker 1: didn't have a big readership. But she had done an

561
00:33:02,284 --> 00:33:06,204
Speaker 1: interview after the vaccine had come out and was available

562
00:33:06,324 --> 00:33:10,404
Speaker 1: then for adolescents, and she said, look in our pick

563
00:33:10,484 --> 00:33:16,964
Speaker 1: you we've had more kids, more patients here from Meyer

564
00:33:17,044 --> 00:33:21,204
Speaker 1: Kurt Artists following the vaccine than we had COVID patients

565
00:33:21,244 --> 00:33:24,764
Speaker 1: in an entire year. Now this was someone I just know,

566
00:33:24,844 --> 00:33:27,324
Speaker 1: this shouldn't matter. She was like very much like a

567
00:33:27,404 --> 00:33:31,804
Speaker 1: lefty democrat, like she had no motivation behind this. She

568
00:33:31,884 --> 00:33:34,644
Speaker 1: was just telling the truth. This is just simply what

569
00:33:34,804 --> 00:33:38,604
Speaker 1: happened in the intensive care unit for pediatrics in her hospital.

570
00:33:38,684 --> 00:33:42,804
Speaker 1: This is what happened. Her boss told her, you are

571
00:33:43,284 --> 00:33:47,164
Speaker 1: never to speak to the media again about this. So

572
00:33:47,484 --> 00:33:50,484
Speaker 1: people need to understand when we are told there's a

573
00:33:50,564 --> 00:33:57,124
Speaker 1: scientific consensus on something, that consensus very much maybe manufactured,

574
00:33:57,204 --> 00:34:01,324
Speaker 1: it's an illusion. So I had people, you know, contacting me,

575
00:34:01,764 --> 00:34:04,404
Speaker 1: you know, because they self censored, or you had people

576
00:34:04,444 --> 00:34:06,884
Speaker 1: like this physician who I just talked about, where they

577
00:34:06,884 --> 00:34:09,764
Speaker 1: were explicitly told not to say things. And then the

578
00:34:09,804 --> 00:34:14,524
Speaker 1: third category, mate, aren't all the experts outside the United States.

579
00:34:14,724 --> 00:34:17,564
Speaker 1: It's quite remarkable when you think about in the modern

580
00:34:17,644 --> 00:34:19,884
Speaker 1: era it was. And I had some sort of joke

581
00:34:19,924 --> 00:34:22,004
Speaker 1: about this in the book. It was as if we had,

582
00:34:22,084 --> 00:34:25,244
Speaker 1: you know, rewound the clock like five hundred years and

583
00:34:25,324 --> 00:34:28,124
Speaker 1: the message from the continent hadn't reached us yet, you know,

584
00:34:28,164 --> 00:34:32,284
Speaker 1: across the Atlantic that like, there were plenty of public

585
00:34:32,284 --> 00:34:37,084
Speaker 1: health experts throughout Europe who viewed what was happening very

586
00:34:37,204 --> 00:34:40,844
Speaker 1: very differently from what was happening here, yet that somehow

587
00:34:41,164 --> 00:34:45,044
Speaker 1: was not included in the consensus. So the idea of

588
00:34:45,324 --> 00:34:50,524
Speaker 1: a consensus is almost always BS, or certainly was during

589
00:34:50,564 --> 00:34:51,164
Speaker 1: the pandemic.

590
00:34:51,884 --> 00:34:53,404
Speaker 2: For the next phrase, this would be the last one.

591
00:34:53,404 --> 00:34:57,644
Speaker 2: I'm gonna give your pick between two, either flatten the

592
00:34:57,724 --> 00:34:59,564
Speaker 2: curve or social distancing.

593
00:34:59,644 --> 00:35:06,924
Speaker 1: Oh god, I'll pick social distancing. You know, I discuss

594
00:35:07,004 --> 00:35:08,884
Speaker 1: it at length in the book. I make a really

595
00:35:09,044 --> 00:35:11,364
Speaker 1: to my find valiant effort to try to track down

596
00:35:11,364 --> 00:35:15,124
Speaker 1: the origin of six feet of distancing. You know, as

597
00:35:15,164 --> 00:35:18,404
Speaker 1: everyone now knows, this was made up. And I would

598
00:35:18,444 --> 00:35:21,084
Speaker 1: just say on that point that I actually don't think

599
00:35:21,084 --> 00:35:25,804
Speaker 1: it's unreasonable to have benchmarks for like behavior, because we

600
00:35:25,884 --> 00:35:28,604
Speaker 1: need something to aim for. It's a bit too vague,

601
00:35:28,644 --> 00:35:30,964
Speaker 1: particularly if you're talking about like schools for example, or

602
00:35:31,004 --> 00:35:33,484
Speaker 1: it's like do your best. You know that's going to

603
00:35:33,484 --> 00:35:36,044
Speaker 1: be interpreted differently and it could lead to a contentious

604
00:35:36,084 --> 00:35:41,284
Speaker 1: and chaotic kind of environment. However, the way that these

605
00:35:41,764 --> 00:35:46,404
Speaker 1: interventions were presented to the public, they were presented with

606
00:35:46,644 --> 00:35:50,924
Speaker 1: such a degree of certainty about like their effectiveness and

607
00:35:51,124 --> 00:35:54,684
Speaker 1: a degree of certainty about the evidence behind them, that

608
00:35:54,724 --> 00:35:59,364
Speaker 1: it led to this perverse situation where you had people,

609
00:36:00,084 --> 00:36:02,764
Speaker 1: you know, I likened it to sort of like a

610
00:36:02,804 --> 00:36:05,924
Speaker 1: master carpenter, you know, the precision you had you know,

611
00:36:06,124 --> 00:36:09,524
Speaker 1: teachers and school janitors with with tape measures of r

612
00:36:09,884 --> 00:36:13,524
Speaker 1: up this is five feet and three quarters. Nope, this

613
00:36:13,564 --> 00:36:15,964
Speaker 1: isn't going to work, and they're measuring down to this

614
00:36:16,164 --> 00:36:21,244
Speaker 1: was madness. There was never anything particular about somewhere between

615
00:36:21,284 --> 00:36:24,404
Speaker 1: five feet and seven feet that made something magical. So

616
00:36:24,484 --> 00:36:27,444
Speaker 1: if they want to create a benchmark, that's okay, But

617
00:36:27,484 --> 00:36:30,004
Speaker 1: then you have to say, look, we don't have strong

618
00:36:30,084 --> 00:36:35,124
Speaker 1: evidence for this being a particularly magical distance, but try

619
00:36:35,124 --> 00:36:37,124
Speaker 1: to aim for it if you can. Here's why we

620
00:36:37,164 --> 00:36:40,044
Speaker 1: think it might be helpful. But you know, the American

621
00:36:40,124 --> 00:36:44,524
Speaker 1: Academy of Pediatrics, early on their initial guidance said, and

622
00:36:44,604 --> 00:36:46,204
Speaker 1: you know that one of the people from the AP

623
00:36:46,364 --> 00:36:48,884
Speaker 1: discussed this in an interview. He had said, look, if

624
00:36:48,924 --> 00:36:50,964
Speaker 1: you can do six feet, great, but if you can't,

625
00:36:51,084 --> 00:36:53,564
Speaker 1: don't worry about it. It's far more important to get

626
00:36:53,564 --> 00:36:55,764
Speaker 1: the kids in school. We don't think there's any real

627
00:36:55,804 --> 00:36:58,604
Speaker 1: good evidence that the benefit of an extra couple of

628
00:36:58,604 --> 00:37:00,884
Speaker 1: feet is going to matter in the scheme of things. That,

629
00:37:01,004 --> 00:37:05,324
Speaker 1: of course, was reversed after Donald Trump's tweet. So we

630
00:37:05,484 --> 00:37:10,844
Speaker 1: had inklings of a reasonable sort of idea about social distancing,

631
00:37:11,924 --> 00:37:15,564
Speaker 1: but those sadly kind of evaporated relatively quickly, and then

632
00:37:15,604 --> 00:37:18,244
Speaker 1: it became this very militant type of idea.

633
00:37:18,564 --> 00:37:21,564
Speaker 2: No, well, some of it is kind of is ritualistic, right.

634
00:37:21,604 --> 00:37:24,844
Speaker 2: I think I heard friends in Mexico that like, using

635
00:37:24,924 --> 00:37:27,604
Speaker 2: ultra violet technologies was kind of this ritual they used, right.

636
00:37:27,844 --> 00:37:30,364
Speaker 2: I mean, in New York City, we would put our

637
00:37:30,404 --> 00:37:32,884
Speaker 2: mask on to walk past the hostess sand in a

638
00:37:32,884 --> 00:37:35,604
Speaker 2: crowded restaurant, right, and then go eating a room full

639
00:37:35,644 --> 00:37:38,644
Speaker 2: of people. Everyone's mouths open, right, So you're reducing their

640
00:37:38,684 --> 00:37:41,204
Speaker 2: risk by zero point on one percent, But like I

641
00:37:41,244 --> 00:37:43,484
Speaker 2: do want to you know, I do want to get

642
00:37:43,524 --> 00:37:45,844
Speaker 2: into a little bit more of the evidence. Well, how

643
00:37:45,924 --> 00:37:50,084
Speaker 2: strong is the evidence on the effect of school closures.

644
00:37:50,164 --> 00:37:52,524
Speaker 2: So you'll see some studies saying it's really bad. See

645
00:37:52,564 --> 00:37:55,004
Speaker 2: another city is saying only sort of bad. Right, But

646
00:37:55,044 --> 00:37:57,844
Speaker 2: what's what's your best review of the evidence.

647
00:37:59,044 --> 00:38:04,524
Speaker 1: Our intuitions, and particularly our intuitions with medical matters are

648
00:38:04,684 --> 00:38:09,884
Speaker 1: often wrong. And I'm sympathetic to the idea of anyone

649
00:38:10,084 --> 00:38:13,204
Speaker 1: which included me in early on, who would think, well,

650
00:38:13,244 --> 00:38:15,444
Speaker 1: of course school closers are going to have some sort

651
00:38:15,444 --> 00:38:17,764
Speaker 1: of benefit. It's a bunch of snotty kids running around

652
00:38:17,804 --> 00:38:21,604
Speaker 1: or teenagers gathering. Of course, that you know intuitively makes sense.

653
00:38:22,004 --> 00:38:25,444
Speaker 1: Other people similarly, well, of course, having like a cloth

654
00:38:25,524 --> 00:38:27,844
Speaker 1: in front of your face strapped on, of course that's

655
00:38:27,844 --> 00:38:31,004
Speaker 1: going to have some sort of benefit. There's this intuitive sense.

656
00:38:31,204 --> 00:38:33,684
Speaker 1: But what I show in the book there's a zillion

657
00:38:33,764 --> 00:38:37,844
Speaker 1: examples throughout history, including recent history, where things that seem

658
00:38:38,244 --> 00:38:42,524
Speaker 1: really obvious, where it's like, well, if course, if kids

659
00:38:42,764 --> 00:38:45,604
Speaker 1: are we're seeing a spike in peanut allergies, well, of

660
00:38:45,644 --> 00:38:49,164
Speaker 1: course we should dial back exposure to peanuts in in

661
00:38:49,484 --> 00:38:52,284
Speaker 1: little kids because that's exactly what the American Academy the

662
00:38:52,324 --> 00:38:54,764
Speaker 1: Pediatrics told us to do, and that was the exact

663
00:38:55,244 --> 00:38:58,044
Speaker 1: wrong advice. It was literally the opposite of what they

664
00:38:58,044 --> 00:39:01,604
Speaker 1: should have done. You know, they said, uh, doctor Spaga,

665
00:39:01,604 --> 00:39:03,364
Speaker 1: you said, you know, put a baby on their stomach,

666
00:39:03,404 --> 00:39:06,564
Speaker 1: that'll prevent sids because they could choke. Wrong, bad advice.

667
00:39:06,604 --> 00:39:08,604
Speaker 1: We should actually do the opposite. There's a zillion things,

668
00:39:08,684 --> 00:39:11,284
Speaker 1: I'm sure you know of of many examples where things

669
00:39:11,284 --> 00:39:14,204
Speaker 1: that seem obvious that they will be beneficial once you

670
00:39:14,284 --> 00:39:17,044
Speaker 1: actually use science, once you actually look at the evidence,

671
00:39:17,124 --> 00:39:19,164
Speaker 1: it turns out, oh my god, this thing that seemed

672
00:39:19,204 --> 00:39:21,964
Speaker 1: to be one way is not so. So the reason

673
00:39:21,964 --> 00:39:25,164
Speaker 1: I mentioned all of this is that you or people

674
00:39:25,164 --> 00:39:27,684
Speaker 1: listening might think, well, of course they had some benefit.

675
00:39:28,084 --> 00:39:32,644
Speaker 1: The reality is they had no benefit any intervention. There's

676
00:39:32,644 --> 00:39:35,844
Speaker 1: this phrase called voltage drop within medicine, which is like

677
00:39:36,204 --> 00:39:40,164
Speaker 1: that they expect when you do something that its impact

678
00:39:40,204 --> 00:39:45,044
Speaker 1: is going to wane over time. People don't comply with

679
00:39:45,124 --> 00:39:48,644
Speaker 1: things that are uncomfortable. Wearing a mask, human beings, you

680
00:39:48,684 --> 00:39:51,604
Speaker 1: tug at them, even if even unconsciously you're pulling on it.

681
00:39:51,684 --> 00:39:55,404
Speaker 1: You do things and also people, even the introverts among

682
00:39:55,524 --> 00:39:59,404
Speaker 1: us were social creatures, and there's cellular phone data that

683
00:39:59,444 --> 00:40:01,884
Speaker 1: I talked about in the book. Even well before they

684
00:40:01,924 --> 00:40:07,724
Speaker 1: started easing restrictions, people started moving around that closing schools

685
00:40:08,004 --> 00:40:10,644
Speaker 1: could have a benefit need for a week or a

686
00:40:10,684 --> 00:40:13,924
Speaker 1: couple of weeks, if done in conjunction with everything else

687
00:40:13,964 --> 00:40:17,964
Speaker 1: being closed. But there is zero evidence that over time,

688
00:40:18,124 --> 00:40:19,844
Speaker 1: having them close over a long period of time was

689
00:40:19,884 --> 00:40:22,564
Speaker 1: going to have any benefit at all, because everyone was

690
00:40:22,684 --> 00:40:25,804
Speaker 1: mixing anyway. And that includes, by the way, not just voluntarily.

691
00:40:26,004 --> 00:40:28,604
Speaker 1: As we know, a significant portion of the country were

692
00:40:28,644 --> 00:40:31,404
Speaker 1: never locked down. These were the people you know in

693
00:40:31,524 --> 00:40:34,524
Speaker 1: the in the slaughterhouses, the cashier in a store, the

694
00:40:34,564 --> 00:40:36,924
Speaker 1: people fixing the electrical lines and so on, and the

695
00:40:36,924 --> 00:40:39,604
Speaker 1: healthcare workers. So a significant portion of our country were

696
00:40:39,644 --> 00:40:42,804
Speaker 1: never even allowed to be locked down. So for all

697
00:40:42,844 --> 00:40:45,884
Speaker 1: of those reasons, it should make sense now to anyone

698
00:40:45,924 --> 00:40:50,324
Speaker 1: listening why extended school closures were never going to be beneficial.

699
00:40:50,564 --> 00:40:53,404
Speaker 1: When you had everyone moving about, and you had adults

700
00:40:53,484 --> 00:40:55,964
Speaker 1: going to restaurants and grabbing a drink at a bar,

701
00:40:56,084 --> 00:40:58,284
Speaker 1: while at the same time you have a healthy kid

702
00:40:58,484 --> 00:41:01,804
Speaker 1: locked in their bedroom for six months or for twelve months,

703
00:41:01,844 --> 00:41:06,204
Speaker 1: it made no sense epidemiologically or ethically.

704
00:41:06,844 --> 00:41:09,404
Speaker 2: Yeah, Castinos were open, as I experienced a couple of times.

705
00:41:09,484 --> 00:41:11,124
Speaker 2: I only went after it got vaccinated. I was a

706
00:41:11,164 --> 00:41:13,684
Speaker 2: good boy on that. But I want to kind of

707
00:41:13,684 --> 00:41:16,644
Speaker 2: back up to something we've been kind of dancing around

708
00:41:16,964 --> 00:41:19,364
Speaker 2: a little bit. Why is it so difficult for people

709
00:41:19,364 --> 00:41:21,404
Speaker 2: to accept the notion that we need to do some

710
00:41:21,604 --> 00:41:24,684
Speaker 2: form of cost benefit analysis?

711
00:41:25,964 --> 00:41:28,844
Speaker 1: I mean, this is perhaps, you know, a jaundiced view

712
00:41:28,964 --> 00:41:33,924
Speaker 1: of things, but people like to be told what to do.

713
00:41:34,444 --> 00:41:38,124
Speaker 1: Some portion of people in a certain way, and what

714
00:41:38,164 --> 00:41:40,444
Speaker 1: we saw are at least some people in our country.

715
00:41:40,524 --> 00:41:48,404
Speaker 1: What we saw was this very paternalistic, almost like infantilization

716
00:41:48,764 --> 00:41:51,684
Speaker 1: of the public. You had the equivalent of like a

717
00:41:51,764 --> 00:41:55,084
Speaker 1: mom wagging her finger at a three year old saying

718
00:41:55,324 --> 00:41:58,964
Speaker 1: because I told you so, you know, when they didn't

719
00:41:58,964 --> 00:42:03,244
Speaker 1: provide evidence for something. And that's how much of the

720
00:42:03,324 --> 00:42:07,284
Speaker 1: response was conducted and how people reacted. And most people,

721
00:42:07,804 --> 00:42:11,204
Speaker 1: at least in Blue America went along with this, this

722
00:42:11,324 --> 00:42:14,724
Speaker 1: sort of argument from authority. That they went along And

723
00:42:15,044 --> 00:42:20,124
Speaker 1: I can only surmise that that is because it's just

724
00:42:20,204 --> 00:42:24,564
Speaker 1: a it's just easier, it's less cognitive load on you.

725
00:42:24,884 --> 00:42:31,404
Speaker 1: Then everyone was just kind of externalizing a complex at

726
00:42:31,484 --> 00:42:36,964
Speaker 1: least you know, moral and logistical decision making. They were

727
00:42:37,124 --> 00:42:41,004
Speaker 1: just sort of farming it out to someone else, let

728
00:42:41,044 --> 00:42:44,444
Speaker 1: them decide for me. It's kind of amazing, mate, how

729
00:42:44,524 --> 00:42:48,844
Speaker 1: few people actually dug into the data, actually looked at

730
00:42:48,884 --> 00:42:52,124
Speaker 1: and it didn't even require much digging. This was an

731
00:42:52,164 --> 00:42:56,764
Speaker 1: extraordinary kind of like default to the experts, don't ask

732
00:42:56,804 --> 00:42:57,364
Speaker 1: any questions.

733
00:42:57,404 --> 00:42:59,084
Speaker 2: Yeah. Look, there are a lot of books about kind

734
00:42:59,084 --> 00:43:01,604
Speaker 2: of when. I mean, if you read Daniel Kneman and

735
00:43:01,844 --> 00:43:04,164
Speaker 2: late now Dan Conman is sticking fast and slow. There's

736
00:43:04,284 --> 00:43:08,004
Speaker 2: like so someone fast sticking, which is more kind of

737
00:43:08,564 --> 00:43:13,164
Speaker 2: intuitive in the system too, thinking that requires more deliberation, right,

738
00:43:13,204 --> 00:43:16,564
Speaker 2: And if any problem required more deliberation, I think it

739
00:43:16,604 --> 00:43:19,044
Speaker 2: would be Covid right, that you have to kind of

740
00:43:19,884 --> 00:43:22,604
Speaker 2: go back almost the first principles and thing through things.

741
00:43:22,644 --> 00:43:26,204
Speaker 2: You know, to the extent people's had intuitions, they were

742
00:43:26,284 --> 00:43:28,884
Speaker 2: often very wrong intuitions, right. I remember Mary de Blasio

743
00:43:29,644 --> 00:43:32,004
Speaker 2: in New York told people we're gonna shut the bars

744
00:43:32,044 --> 00:43:34,444
Speaker 2: down for a while, right, so go out and have

745
00:43:34,484 --> 00:43:37,564
Speaker 2: a big night tonight, right, which is an intuition you

746
00:43:37,644 --> 00:43:40,124
Speaker 2: might have in New York if there's a hurricane coming

747
00:43:40,124 --> 00:43:42,404
Speaker 2: which we've had a couple of hurricanes, right, because there's

748
00:43:42,484 --> 00:43:45,364
Speaker 2: zero threat from the hurricane at one point in time,

749
00:43:45,444 --> 00:43:47,524
Speaker 2: then there's a window where it's threatening, and then hopefully

750
00:43:47,564 --> 00:43:50,324
Speaker 2: it's not too bad. Right. But that's probably the most

751
00:43:50,644 --> 00:43:52,844
Speaker 2: time of most transmission in New York, right. Or I

752
00:43:52,884 --> 00:43:55,284
Speaker 2: think you point out like a lot of people's intuitions

753
00:43:55,284 --> 00:43:57,564
Speaker 2: were based on it being an influenza pandemic and not

754
00:43:57,604 --> 00:44:02,524
Speaker 2: a coronavirus pandemic, which is dramatically different. Effects on how

755
00:44:02,564 --> 00:44:11,604
Speaker 2: transmisfold is in children, for example. And we'll be right

756
00:44:11,644 --> 00:44:25,204
Speaker 2: back after this break. Okay. The models. So I've built

757
00:44:25,804 --> 00:44:29,764
Speaker 2: models in the past. Sometimes I think skepticism of models

758
00:44:29,844 --> 00:44:35,804
Speaker 2: is unwarranted. I think people also have very difficult, very

759
00:44:35,804 --> 00:44:39,044
Speaker 2: difficult time telling from the outside what's a good model

760
00:44:39,084 --> 00:44:41,204
Speaker 2: and what's a bad model. When is a model reliable

761
00:44:41,204 --> 00:44:43,804
Speaker 2: and when is it just garbage in? Garbage out? But

762
00:44:43,884 --> 00:44:46,084
Speaker 2: these COVID bells were not very good, David, Can you

763
00:44:46,124 --> 00:44:48,604
Speaker 2: tell me kind of more about what you learned about them?

764
00:44:48,964 --> 00:44:51,004
Speaker 1: Yeah? Well, you know, as you know, one of my

765
00:44:51,084 --> 00:44:54,604
Speaker 1: chapters is titled Geigo for Garbage and Garbage Out. And

766
00:44:55,444 --> 00:44:59,844
Speaker 1: the models were built upon an enormous kind of pile

767
00:44:59,964 --> 00:45:05,444
Speaker 1: of assumptions, and I started digging into them because I'm curious.

768
00:45:05,484 --> 00:45:07,444
Speaker 1: It was like, how did they come up with this model?

769
00:45:07,604 --> 00:45:10,964
Speaker 1: You know, showing that if you you do X, Y

770
00:45:11,084 --> 00:45:15,324
Speaker 1: and z actions, this will lead to such and such results.

771
00:45:15,404 --> 00:45:17,364
Speaker 1: That's what the models were showing. You said, if you

772
00:45:17,564 --> 00:45:21,484
Speaker 1: follow instructions, then we'll have this amount of case rates

773
00:45:21,564 --> 00:45:23,684
Speaker 1: or this amount of you know, transmission, and if you

774
00:45:23,724 --> 00:45:26,724
Speaker 1: are bad and you don't follow instructions, then it's going

775
00:45:26,764 --> 00:45:28,964
Speaker 1: to be this big spike. And they would show these visualizations.

776
00:45:29,084 --> 00:45:31,084
Speaker 1: It's like, well, how did they figure this stuff out?

777
00:45:31,244 --> 00:45:35,244
Speaker 1: And I started reading some of the papers that went

778
00:45:35,284 --> 00:45:38,524
Speaker 1: along with the models and the methodology, and what I

779
00:45:38,564 --> 00:45:41,244
Speaker 1: always do is, because I'm a crazy person, I always

780
00:45:41,244 --> 00:45:43,204
Speaker 1: look at the citations. I'm like, well, where did they

781
00:45:43,244 --> 00:45:45,604
Speaker 1: get that from? So you see there's like a little

782
00:45:45,604 --> 00:45:48,964
Speaker 1: superscript citation. I see it there, you know, in that notes,

783
00:45:49,124 --> 00:45:51,564
Speaker 1: and I click on it. I'm like, okay, where did

784
00:45:51,564 --> 00:45:54,244
Speaker 1: they get this from? And then it leads me to

785
00:45:54,404 --> 00:45:58,084
Speaker 1: another model. I'm like what, so wait, this models based

786
00:45:58,084 --> 00:45:59,804
Speaker 1: another model. Okay, well where did they get that from?

787
00:45:59,844 --> 00:46:02,284
Speaker 1: So then I'm leading the second model, and then I'm

788
00:46:02,284 --> 00:46:05,404
Speaker 1: looking through and there's claims in there, and then I say, oh,

789
00:46:05,604 --> 00:46:08,924
Speaker 1: that's based on yet more models, And then I likened

790
00:46:08,964 --> 00:46:11,564
Speaker 1: it to this of like a never ending Russian Dolls

791
00:46:11,924 --> 00:46:15,124
Speaker 1: type of thing. It was just models upon models upon

792
00:46:15,244 --> 00:46:18,364
Speaker 1: models and one of them. Ultimately I get to like

793
00:46:18,404 --> 00:46:23,124
Speaker 1: the bottom and I'm reading in like the supplement buried

794
00:46:23,124 --> 00:46:25,764
Speaker 1: in the supplement of a paper where they had a

795
00:46:25,844 --> 00:46:29,244
Speaker 1: claim about transmission in schools as a certain portion of

796
00:46:29,284 --> 00:46:33,444
Speaker 1: overall kind of transmission activity and it was something like

797
00:46:33,924 --> 00:46:36,884
Speaker 1: thirty seven percent, and you go deep in, you know,

798
00:46:36,924 --> 00:46:39,204
Speaker 1: in my mind sort of metaphorically, it's in like six

799
00:46:39,244 --> 00:46:44,964
Speaker 1: point five it says this figure was chosen arbitrarily. Now

800
00:46:45,044 --> 00:46:48,564
Speaker 1: that's like you just are peeling back model upon model

801
00:46:48,644 --> 00:46:51,484
Speaker 1: upon model until finally in the supplement you get to

802
00:46:51,644 --> 00:46:54,924
Speaker 1: like actual data and then you find out that it

803
00:46:55,004 --> 00:46:58,284
Speaker 1: was made up. That's kind of wild.

804
00:46:59,004 --> 00:47:01,764
Speaker 2: What's so tricky about building models is like, yeah, they

805
00:47:01,804 --> 00:47:07,124
Speaker 2: are kind of a definition simplifications, right, and sometimes if

806
00:47:07,124 --> 00:47:09,724
Speaker 2: a point in a model, a data point, is non

807
00:47:09,804 --> 00:47:12,284
Speaker 2: central to the thesis of the model, then it's totally

808
00:47:12,324 --> 00:47:15,484
Speaker 2: fine to estimate, right. It's like, Okay, we could do

809
00:47:15,524 --> 00:47:17,044
Speaker 2: a more rigorous job with this, but it's probably not

810
00:47:17,164 --> 00:47:20,884
Speaker 2: very important. The model is like robust to different specifications

811
00:47:20,884 --> 00:47:23,764
Speaker 2: of this parameter. I'm using technical language here, right, there

812
00:47:23,764 --> 00:47:26,684
Speaker 2: are other times when like it just becomes littally garbage

813
00:47:26,684 --> 00:47:29,364
Speaker 2: in garbage out, where you know, you're just taking that

814
00:47:29,444 --> 00:47:32,844
Speaker 2: arbitrary back of the envelope number, feeding it through a

815
00:47:32,844 --> 00:47:35,284
Speaker 2: bunch of loops, right, and then spinning it back out

816
00:47:35,364 --> 00:47:38,324
Speaker 2: and pretending that you've done like real real science there.

817
00:47:38,404 --> 00:47:39,684
Speaker 2: I mean, you know, I mean there's the other big

818
00:47:39,724 --> 00:47:42,284
Speaker 2: problem with these models too, is so I call it

819
00:47:42,284 --> 00:47:45,124
Speaker 2: like the kind of like tyranny of the measurable. So

820
00:47:46,524 --> 00:47:50,764
Speaker 2: cases are easy to measure, actually not as easy as

821
00:47:50,804 --> 00:47:53,924
Speaker 2: they might be, because it was hard to find enough

822
00:47:54,004 --> 00:47:57,604
Speaker 2: tests and a lot of cases are you know, asymptomatic

823
00:47:57,684 --> 00:47:59,604
Speaker 2: and things like that, right, but you know, and you

824
00:47:59,604 --> 00:48:02,204
Speaker 2: can always try to make the red arrow on CNN

825
00:48:02,444 --> 00:48:08,924
Speaker 2: go down. Conversely, things like psychological harms of being isolated

826
00:48:08,964 --> 00:48:11,444
Speaker 2: from other people for months at a time are harder

827
00:48:11,884 --> 00:48:14,444
Speaker 2: to measure, you know, I know in baseball analysis, offense

828
00:48:14,524 --> 00:48:17,324
Speaker 2: is much easier to measure than defense in baseball, Right,

829
00:48:17,364 --> 00:48:19,684
Speaker 2: So some of these teams would build teams that hit

830
00:48:19,724 --> 00:48:21,884
Speaker 2: a lot of home runs but were terrible defensively because

831
00:48:21,924 --> 00:48:23,684
Speaker 2: we couldn't measure it well. It turns out as you

832
00:48:23,724 --> 00:48:26,284
Speaker 2: study it more carefully, it is important. So what are

833
00:48:26,284 --> 00:48:30,404
Speaker 2: the psychological harms to people of social isolation?

834
00:48:31,364 --> 00:48:34,164
Speaker 1: Yeah, just before I get to that, just to your

835
00:48:34,204 --> 00:48:38,884
Speaker 1: point about the models is the modelers decide what goes

836
00:48:38,924 --> 00:48:42,404
Speaker 1: in and they can turn those dials whichever way they

837
00:48:42,484 --> 00:48:44,484
Speaker 1: want if the model doesn't put out what they want

838
00:48:44,524 --> 00:48:47,844
Speaker 1: to put it out. And I interviewed some really interesting philosophers,

839
00:48:47,964 --> 00:48:50,524
Speaker 1: Eric Winsburg, who I mentioned before, and a colleague of his,

840
00:48:51,044 --> 00:48:57,084
Speaker 1: Stephanie Harvard, who they study how models are made, in

841
00:48:57,124 --> 00:49:01,964
Speaker 1: the sort of ethical implications of models, and what does

842
00:49:02,004 --> 00:49:05,684
Speaker 1: it say about a society about what goes into the

843
00:49:05,724 --> 00:49:07,684
Speaker 1: models that they do, and what does it say about

844
00:49:07,684 --> 00:49:11,324
Speaker 1: the people who build the models. And it's quite astonishing

845
00:49:11,604 --> 00:49:14,204
Speaker 1: when you think about it that the people who built

846
00:49:14,244 --> 00:49:17,724
Speaker 1: the models are also the people who tended to fare

847
00:49:18,044 --> 00:49:21,364
Speaker 1: really well in the pandemic relative to the rest of

848
00:49:21,404 --> 00:49:25,844
Speaker 1: the country. That's not an accident. So we had models

849
00:49:26,324 --> 00:49:32,044
Speaker 1: dictating how we responded in America, and the models only

850
00:49:32,124 --> 00:49:36,444
Speaker 1: took into account certain factors that were of the most

851
00:49:36,444 --> 00:49:38,244
Speaker 1: interest to the people who are in this kind of

852
00:49:38,284 --> 00:49:41,484
Speaker 1: white collar profession if they were living If the people

853
00:49:41,484 --> 00:49:45,284
Speaker 1: who designed the models for IHME and Imperial College were

854
00:49:45,324 --> 00:49:49,444
Speaker 1: living in a studio apartment in the Bronx with no

855
00:49:49,604 --> 00:49:53,364
Speaker 1: air conditioning and you know, six children in there, maybe

856
00:49:53,404 --> 00:49:56,644
Speaker 1: they would have had an input on there. For school closures,

857
00:49:57,084 --> 00:49:58,964
Speaker 1: you know, maybe they would if they were running a

858
00:49:58,964 --> 00:50:01,764
Speaker 1: little mom and pop business, et cetera, et cetera. So

859
00:50:01,924 --> 00:50:05,484
Speaker 1: all these things that are really important in society now.

860
00:50:05,524 --> 00:50:07,764
Speaker 1: Of course, if anyone's listening, really well, it's not as

861
00:50:07,804 --> 00:50:11,764
Speaker 1: important as death. But that's a false binary to draw,

862
00:50:12,164 --> 00:50:15,604
Speaker 1: and for a whole variety of reasons. We tolerate death

863
00:50:15,644 --> 00:50:17,564
Speaker 1: in a whole variety of ways in our country. For

864
00:50:17,844 --> 00:50:19,844
Speaker 1: because you know, on the highway we can make the

865
00:50:19,844 --> 00:50:22,924
Speaker 1: speed limits thirty five, but we don't because we want

866
00:50:22,964 --> 00:50:25,164
Speaker 1: to get places faster. There's all sorts of things going

867
00:50:25,164 --> 00:50:27,604
Speaker 1: on that they chose not to put these things in

868
00:50:27,644 --> 00:50:29,884
Speaker 1: the models, and one of them. So just kind of

869
00:50:29,884 --> 00:50:33,044
Speaker 1: getting now to your question, there's all sorts of evidence,

870
00:50:33,204 --> 00:50:35,644
Speaker 1: and this is quite obvious. We know this just as

871
00:50:35,684 --> 00:50:40,084
Speaker 1: people that isolation is incredibly damaging. It's also it's physically

872
00:50:40,164 --> 00:50:43,364
Speaker 1: damaging to people. We had people in hospitals, particularly the

873
00:50:43,364 --> 00:50:46,644
Speaker 1: elderly people who were not allowed to see their family.

874
00:50:48,004 --> 00:50:53,044
Speaker 1: We had children. The rates of depression and anxiety and

875
00:50:53,444 --> 00:50:57,124
Speaker 1: of eating disorders both B and I going up, and

876
00:50:57,324 --> 00:51:01,484
Speaker 1: also anorexia going up and bolimia going up. All these

877
00:51:01,524 --> 00:51:06,564
Speaker 1: things were directly tied to isolation and school closures. There

878
00:51:06,564 --> 00:51:08,804
Speaker 1: were people who've said, no, it's just because of the

879
00:51:08,844 --> 00:51:11,884
Speaker 1: pandemic overall, and they were upset. It's just simply not true.

880
00:51:11,924 --> 00:51:14,604
Speaker 1: There was a lot of evidence and I cited in

881
00:51:14,604 --> 00:51:19,124
Speaker 1: my book that directly ties these effects to isolation to

882
00:51:19,404 --> 00:51:21,884
Speaker 1: school closures. It had nothing to do with the broader

883
00:51:22,044 --> 00:51:24,524
Speaker 1: kind of like experience of the pandemic.

884
00:51:24,924 --> 00:51:27,004
Speaker 2: There's this thing called the value of a cistical life,

885
00:51:27,084 --> 00:51:30,684
Speaker 2: which is like from empirical data on how many trade

886
00:51:30,724 --> 00:51:33,844
Speaker 2: offs people are willing to make, and like people have

887
00:51:33,924 --> 00:51:36,244
Speaker 2: well established trade offs for how much they're willing to

888
00:51:36,284 --> 00:51:40,164
Speaker 2: trade off length of life in essence for quality of life.

889
00:51:40,164 --> 00:51:44,084
Speaker 2: It gets complicated when like when I was, you know,

890
00:51:44,124 --> 00:51:48,084
Speaker 2: a pretty dutiful mascuer and indoor crowd avoid before I

891
00:51:48,124 --> 00:51:50,884
Speaker 2: got vaccinated, and I wasn't doing it for me. I

892
00:51:51,004 --> 00:51:53,324
Speaker 2: was doing it for because I would feel guilty as

893
00:51:53,364 --> 00:51:57,044
Speaker 2: fuck if I transmitted COVID right, but at some point

894
00:51:57,484 --> 00:52:01,804
Speaker 2: people it just people's tolerance for it lags. And anyway,

895
00:52:02,284 --> 00:52:05,644
Speaker 2: do you think the models were trying or the modelers

896
00:52:05,684 --> 00:52:07,044
Speaker 2: were trying to scare people?

897
00:52:07,684 --> 00:52:11,964
Speaker 1: Yes, yeah, I mean it's unequivocal, and we know there's

898
00:52:12,124 --> 00:52:15,324
Speaker 1: more broadly, there are statements, you know, from Fauci saying,

899
00:52:15,524 --> 00:52:18,364
Speaker 1: if you think you're doing too much, that's probably the

900
00:52:18,444 --> 00:52:24,484
Speaker 1: right thing. There's some internal documents in the UK government

901
00:52:24,604 --> 00:52:27,924
Speaker 1: that I cite my book where they talk about specifically

902
00:52:28,244 --> 00:52:31,524
Speaker 1: like exaggerating and scaring people in order to get them

903
00:52:31,564 --> 00:52:34,364
Speaker 1: to comply. There are articles in the New York Times

904
00:52:34,364 --> 00:52:38,004
Speaker 1: that talked about this where they were fairly explicit about

905
00:52:38,244 --> 00:52:41,804
Speaker 1: having people be frightened in order to get them to

906
00:52:41,884 --> 00:52:47,164
Speaker 1: behave in a certain way. Ultimately, people people's experience of

907
00:52:47,244 --> 00:52:52,524
Speaker 1: reality was so divergent from what we were told was

908
00:52:52,604 --> 00:52:55,684
Speaker 1: the risk ratio and what we were told we needed

909
00:52:55,684 --> 00:52:59,564
Speaker 1: to do. At a certain point people just called bullshit.

910
00:53:00,204 --> 00:53:02,604
Speaker 2: I agree. At the same time, I do think COVID

911
00:53:02,724 --> 00:53:06,644
Speaker 2: was in this kind of like messy middle ground, where

912
00:53:06,724 --> 00:53:09,244
Speaker 2: like if it were an order of magnitude more deadly,

913
00:53:10,004 --> 00:53:12,364
Speaker 2: then people would comply on their own and then very

914
00:53:12,404 --> 00:53:16,044
Speaker 2: harsh protocols I think would be rational and justified and

915
00:53:16,084 --> 00:53:18,684
Speaker 2: passed most cost benefit tests. Right. If it were ten

916
00:53:18,684 --> 00:53:21,684
Speaker 2: times less deadly, then it would be you know, the

917
00:53:21,724 --> 00:53:24,244
Speaker 2: seasonal flu basically, and people would just kind of let.

918
00:53:24,204 --> 00:53:24,724
Speaker 1: It pass through.

919
00:53:24,804 --> 00:53:27,844
Speaker 2: We're kind of stuck in the middle, and then there's

920
00:53:27,924 --> 00:53:29,844
Speaker 2: kind of so much data to cherry pick, and you

921
00:53:29,884 --> 00:53:32,724
Speaker 2: kind of are forced to kind of figure things out

922
00:53:33,044 --> 00:53:36,084
Speaker 2: on your own. I think the problem at its core,

923
00:53:36,804 --> 00:53:39,804
Speaker 2: as I describe it in the book, is that it's

924
00:53:39,884 --> 00:53:43,644
Speaker 2: really kind of epistemological, isn't it. And it comes down to, like,

925
00:53:44,124 --> 00:53:45,844
Speaker 2: how do we know it is true? How do we

926
00:53:45,884 --> 00:53:51,604
Speaker 2: think about evidence? And what frustrated me, just endlessly and

927
00:53:51,804 --> 00:53:56,324
Speaker 2: enraged me and fascinated me was and still is the

928
00:53:56,404 --> 00:53:59,364
Speaker 2: fact that the idea of like anyone can cherry pick

929
00:53:59,364 --> 00:54:01,764
Speaker 2: stuff and you can have dueling studies. If I were

930
00:54:01,764 --> 00:54:04,044
Speaker 2: to debate someone tomorrow about school.

931
00:54:03,764 --> 00:54:06,364
Speaker 1: Closures, they could cite twenty studies if they want, then

932
00:54:06,404 --> 00:54:08,564
Speaker 1: I could cite twenty studies that you know, have an

933
00:54:08,564 --> 00:54:11,684
Speaker 1: opposite conclusion. And I spoke to a guy who an

934
00:54:11,764 --> 00:54:15,684
Speaker 1: oncologist who's but he's I don't think he's practicing anymore,

935
00:54:15,684 --> 00:54:18,004
Speaker 1: but he talks to patients about how to think through

936
00:54:18,204 --> 00:54:20,404
Speaker 1: like their treatment and what to do or not and

937
00:54:20,444 --> 00:54:23,524
Speaker 1: how to think about evidence. And I was talking with

938
00:54:23,604 --> 00:54:26,284
Speaker 1: him and I said, you know, I talked about you know,

939
00:54:26,324 --> 00:54:28,804
Speaker 1: the millions of kids in school in Europe and stuff,

940
00:54:28,804 --> 00:54:31,364
Speaker 1: and I'm like, so does that not count though, because

941
00:54:31,364 --> 00:54:33,284
Speaker 1: it's you know, in the hierarchy of evidence, it's not

942
00:54:33,324 --> 00:54:36,564
Speaker 1: a randomized trial. And he was like, David, He's like,

943
00:54:36,884 --> 00:54:41,164
Speaker 1: that's better than a study. He's like, that's just reality.

944
00:54:41,924 --> 00:54:46,364
Speaker 1: Studies always have chosen parameters. And it like was really

945
00:54:46,404 --> 00:54:49,324
Speaker 1: an incredible like moment for me where it was like, right,

946
00:54:49,844 --> 00:54:55,444
Speaker 1: like empirical reality trumps everything. So the idea, like you know,

947
00:54:55,924 --> 00:54:57,564
Speaker 1: you mentioned like, oh, in five years from now, you

948
00:54:57,564 --> 00:54:59,044
Speaker 1: don't want to get into an argument with some and

949
00:54:59,164 --> 00:55:01,724
Speaker 1: again about like what the outcomes are this that or

950
00:55:01,764 --> 00:55:04,404
Speaker 1: the other thing. But it's like, I feel like we

951
00:55:04,444 --> 00:55:06,404
Speaker 1: don't have to. You don't have to look at tons

952
00:55:06,404 --> 00:55:10,324
Speaker 1: of studies. We can, but studies to just by their nature,

953
00:55:10,684 --> 00:55:14,524
Speaker 1: have some degree of subjective parameters, you know, put around them,

954
00:55:14,604 --> 00:55:17,444
Speaker 1: the timing that they run from X day to Y day,

955
00:55:17,924 --> 00:55:20,004
Speaker 1: you know, the inputs, et cetera. But when you just

956
00:55:20,044 --> 00:55:23,364
Speaker 1: look at reality, empirical reality. If millions of kids are

957
00:55:23,364 --> 00:55:27,204
Speaker 1: in school, nothing really happened that, you know. When I

958
00:55:27,204 --> 00:55:29,524
Speaker 1: spoke to this on college is, he's like, that's better.

959
00:55:29,644 --> 00:55:35,844
Speaker 1: That's actually above a randomized trial. We're just observing empirical, empirically,

960
00:55:35,924 --> 00:55:40,404
Speaker 1: something that's true. But instead of looking at that, we

961
00:55:40,684 --> 00:55:43,924
Speaker 1: favored theory, you know, and all of these things well

962
00:55:43,964 --> 00:55:46,444
Speaker 1: we well they didn't say we think, They said we know.

963
00:55:46,964 --> 00:55:50,364
Speaker 1: But implicit in this idea, remember the Swiss cheese model,

964
00:55:50,564 --> 00:55:53,084
Speaker 1: ny where of course, right, So they told us each

965
00:55:53,124 --> 00:55:55,484
Speaker 1: of these interventions was like a slice of Swiss cheese,

966
00:55:55,524 --> 00:55:58,084
Speaker 1: and if you do all of them, hopefully the holes

967
00:55:58,124 --> 00:56:00,604
Speaker 1: won't line up and the little very ons won't get

968
00:56:00,684 --> 00:56:03,124
Speaker 1: you know, won't make it through. But what's the implicit

969
00:56:03,164 --> 00:56:05,644
Speaker 1: message in that? It's that they don't know what works.

970
00:56:05,924 --> 00:56:09,244
Speaker 1: They were already admitting they didn't know which intervention worked.

971
00:56:09,244 --> 00:56:11,844
Speaker 1: Therefore we have to do all of them. But yet

972
00:56:11,924 --> 00:56:15,644
Speaker 1: no evidence was actually accrued to support them, and and

973
00:56:15,764 --> 00:56:20,204
Speaker 1: we had evidence to the opposite that in reality. So

974
00:56:20,324 --> 00:56:22,524
Speaker 1: that to me is the thing that I just find

975
00:56:23,164 --> 00:56:25,804
Speaker 1: endlessly fascinating, you know, and I know you do a

976
00:56:25,804 --> 00:56:28,204
Speaker 1: lot of work on kind of like human nature and

977
00:56:28,284 --> 00:56:31,644
Speaker 1: decision making and stuff like that, like on why and

978
00:56:31,844 --> 00:56:35,924
Speaker 1: how our country, by and large, or at least half

979
00:56:35,964 --> 00:56:40,284
Speaker 1: of it went along with favoring a sort of like

980
00:56:40,284 --> 00:56:46,524
Speaker 1: epistelological model of life that favored theory over evidence.

981
00:56:48,004 --> 00:56:51,444
Speaker 2: What did the contrarians get wrong?

982
00:56:52,804 --> 00:56:55,004
Speaker 1: It's a good question. Well, it depends who you define,

983
00:56:55,244 --> 00:57:00,644
Speaker 1: you know, as a contrarian, and what that means. I

984
00:57:00,684 --> 00:57:05,284
Speaker 1: think some of them overstated harms from the vaccine distills.

985
00:57:05,684 --> 00:57:08,964
Speaker 1: I haven't seen that evidence yet. Maybe it exists and

986
00:57:09,004 --> 00:57:11,004
Speaker 1: it just had have been uncovered. I have not seen

987
00:57:11,044 --> 00:57:15,284
Speaker 1: strong evidence that that they caused the mass harm. You

988
00:57:15,324 --> 00:57:20,564
Speaker 1: know that some people purport them to be causing. I

989
00:57:20,604 --> 00:57:24,924
Speaker 1: think the contrarians. I think people on both sides, but

990
00:57:25,004 --> 00:57:33,644
Speaker 1: including the contraints, perhaps misjudged how to effectively argue for

991
00:57:33,724 --> 00:57:38,004
Speaker 1: their position. I don't know, tell me, maybe I'm missing something.

992
00:57:38,364 --> 00:57:42,804
Speaker 2: I do think there was over optimism among the speed

993
00:57:42,844 --> 00:57:47,684
Speaker 2: with which HERD immunity would be reached. Right. Look, a

994
00:57:47,724 --> 00:57:50,444
Speaker 2: lot of transmission was not being picked up. It was asymptomatic,

995
00:57:50,484 --> 00:57:53,964
Speaker 2: and you'd have these waves and there are complicated patterns

996
00:57:54,004 --> 00:57:55,764
Speaker 2: that you know that every time you feel like you

997
00:57:55,844 --> 00:57:58,484
Speaker 2: kind of got the hang of modeling, them. Then they

998
00:57:58,524 --> 00:58:01,324
Speaker 2: wouldn't quite hold up, right, But like I thought, they're

999
00:58:01,364 --> 00:58:03,124
Speaker 2: you know, there are people that thought, okay, well, actually

1000
00:58:04,004 --> 00:58:06,924
Speaker 2: sixty percent of people have already been infected, we think,

1001
00:58:06,964 --> 00:58:13,724
Speaker 2: and therefore there's heard immunity, you know, notwithstanding evidence about reinfections.

1002
00:58:13,764 --> 00:58:15,924
Speaker 2: You know, kind of I was in, I think the

1003
00:58:15,924 --> 00:58:20,564
Speaker 2: little denial about that. Clearly these reinfections were a problem.

1004
00:58:20,884 --> 00:58:23,044
Speaker 2: So I need to start wrapping up here. So let

1005
00:58:23,084 --> 00:58:26,524
Speaker 2: me kind of let me ask this. Let's say that

1006
00:58:26,524 --> 00:58:31,644
Speaker 2: there is a COVID twenty five pandemic, and let's say

1007
00:58:31,644 --> 00:58:33,964
Speaker 2: that we know this is going to be have roughly

1008
00:58:33,964 --> 00:58:39,204
Speaker 2: the same characteristics as COVID nineteen. For some reason, any

1009
00:58:39,244 --> 00:58:43,524
Speaker 2: immunity you had from previous COVID nineteen infections or vaccines

1010
00:58:44,204 --> 00:58:48,324
Speaker 2: provide no protection. So we're starting from scratch. How do

1011
00:58:48,324 --> 00:58:50,164
Speaker 2: you think the United States would react today?

1012
00:58:50,964 --> 00:58:54,444
Speaker 1: It'll be it'll be a nightmare, right, I mean, it

1013
00:58:54,564 --> 00:58:58,244
Speaker 1: was just I think the one area where there has

1014
00:58:58,324 --> 00:59:01,284
Speaker 1: been a softening though, is certainly on kids in schools.

1015
00:59:01,844 --> 00:59:05,204
Speaker 1: That's like the one kind of like the narrative initially

1016
00:59:05,324 --> 00:59:07,124
Speaker 1: was we have to do this, we got to protect

1017
00:59:07,124 --> 00:59:09,164
Speaker 1: the kids. Then the narrative shifted to well, the kids

1018
00:59:09,204 --> 00:59:11,564
Speaker 1: are OK, but we need to protect teachers. And then

1019
00:59:11,564 --> 00:59:14,124
Speaker 1: once it became obvious that like that, didn't you know

1020
00:59:14,164 --> 00:59:17,124
Speaker 1: that teachers were not at any greater risk than other professionals, which,

1021
00:59:17,124 --> 00:59:19,284
Speaker 1: by the way, Sweden had a study on this very

1022
00:59:19,324 --> 00:59:22,164
Speaker 1: early that showed this that teachers there were not at

1023
00:59:22,244 --> 00:59:25,564
Speaker 1: higher risk than the average professional, and on and on.

1024
00:59:25,564 --> 00:59:31,404
Speaker 1: Once once like all that's established, it's like then the

1025
00:59:31,484 --> 00:59:34,204
Speaker 1: narrative shifted to which like a year or two into

1026
00:59:34,204 --> 00:59:38,204
Speaker 1: the pandemic, it then shifted to, well, this was a

1027
00:59:38,324 --> 00:59:41,764
Speaker 1: regrettable decision, but they were building the plane as they

1028
00:59:41,764 --> 00:59:44,124
Speaker 1: fly it, you know, as a fog of war. But

1029
00:59:44,164 --> 00:59:46,244
Speaker 1: the key part, just to answer your question, is though,

1030
00:59:46,444 --> 00:59:50,124
Speaker 1: but the narrative did shift, at least to the extent

1031
00:59:50,164 --> 00:59:52,644
Speaker 1: that there was an acknowledgment that this was a mistake.

1032
00:59:53,004 --> 00:59:55,284
Speaker 1: They then come up with some you know, very kind

1033
00:59:55,284 --> 00:59:57,884
Speaker 1: of like exculpatory reasons for why it was a mistake

1034
00:59:57,884 --> 01:00:03,604
Speaker 1: that I think are are convenient and untrue. But the

1035
01:00:03,724 --> 01:00:06,724
Speaker 1: fact that this is now acknowledged that it's like even

1036
01:00:06,764 --> 01:00:10,924
Speaker 1: in like normy kind of liberal circles, most people I

1037
01:00:11,004 --> 01:00:14,764
Speaker 1: think today say like, yeah, that was a mistake. I

1038
01:00:14,804 --> 01:00:17,884
Speaker 1: think that suggests that if there's some you know, virus

1039
01:00:17,924 --> 01:00:20,964
Speaker 1: that behaves in exactly the same way, that there's going

1040
01:00:21,084 --> 01:00:25,964
Speaker 1: to be far far less tolerance for these kind of

1041
01:00:26,004 --> 01:00:29,164
Speaker 1: like long term closures and other interventions on kids. Like

1042
01:00:29,404 --> 01:00:31,164
Speaker 1: people just aren't going to tolerate it.

1043
01:00:31,364 --> 01:00:32,924
Speaker 2: You know. Look, I'm gonna be honest. I think they

1044
01:00:32,924 --> 01:00:37,804
Speaker 2: are like a certain number of people who uh might

1045
01:00:37,884 --> 01:00:40,764
Speaker 2: be more introverted, right, which is normal, But it felt

1046
01:00:40,764 --> 01:00:44,044
Speaker 2: like it felt like people weren't able to extrapolate from

1047
01:00:44,364 --> 01:00:46,724
Speaker 2: their situation. Where if you have like a nice home

1048
01:00:46,764 --> 01:00:49,004
Speaker 2: in the suburbs and you're someone who loves nothing more

1049
01:00:49,044 --> 01:00:51,964
Speaker 2: than like snuggling on the couch with your partner and

1050
01:00:52,004 --> 01:00:54,244
Speaker 2: your kids or whatever, right and watching movies, and you

1051
01:00:54,284 --> 01:00:59,284
Speaker 2: don't like going out, then maybe this seems good. You

1052
01:00:59,284 --> 01:01:02,084
Speaker 2: don't have any more fomo or guilt for like not worse,

1053
01:01:02,244 --> 01:01:04,604
Speaker 2: you know, Whereas other people I know where like they're like,

1054
01:01:04,684 --> 01:01:06,004
Speaker 2: this is not gonna work for even a week the

1055
01:01:06,044 --> 01:01:08,404
Speaker 2: social distancing thing, and are already going to like illicit

1056
01:01:08,484 --> 01:01:12,204
Speaker 2: parties in New York, and people vary along those dimensions.

1057
01:01:12,284 --> 01:01:13,964
Speaker 2: I'm not even sure what my point.

1058
01:01:13,764 --> 01:01:16,764
Speaker 1: Was, but my point is, so I know we're bouncing

1059
01:01:16,804 --> 01:01:18,964
Speaker 1: around here but just one more thing, you know, but

1060
01:01:19,044 --> 01:01:21,404
Speaker 1: much of this also has to do with class and

1061
01:01:21,644 --> 01:01:25,804
Speaker 1: and you know, social and economic class. That regardless of

1062
01:01:25,804 --> 01:01:28,684
Speaker 1: whether you're an introvert or not, if you had the

1063
01:01:28,804 --> 01:01:31,444
Speaker 1: means of living in a comfortable home and doing your

1064
01:01:31,484 --> 01:01:35,004
Speaker 1: work from home and not losing your income, that you

1065
01:01:35,044 --> 01:01:38,164
Speaker 1: were just going to experience the pandemic very differently from

1066
01:01:38,204 --> 01:01:40,684
Speaker 1: someone who had to leave their home to work, from

1067
01:01:40,724 --> 01:01:44,084
Speaker 1: someone who lives in a dump somewhere and you know,

1068
01:01:44,204 --> 01:01:47,204
Speaker 1: and their kids are jammed in some tiny apartment with them.

1069
01:01:47,484 --> 01:01:50,124
Speaker 1: It's just so it's like it wasn't just about an introversion.

1070
01:01:50,164 --> 01:01:54,924
Speaker 1: It's also about class. And this was a remarkably class

1071
01:01:55,324 --> 01:02:00,524
Speaker 1: based policies that were put in place during the pandemic

1072
01:02:00,604 --> 01:02:06,804
Speaker 1: that dramatically favored those who were comfortable and dramatically escalated

1073
01:02:06,644 --> 01:02:10,084
Speaker 1: the harms to the people who to not have those

1074
01:02:10,084 --> 01:02:12,884
Speaker 1: same means. I want to talk or close by talking

1075
01:02:12,964 --> 01:02:16,604
Speaker 1: about the United States and kind of social solidarity in

1076
01:02:16,644 --> 01:02:19,964
Speaker 1: the United States, because look, I am certainly like a

1077
01:02:20,004 --> 01:02:24,724
Speaker 1: libertarian leading person by acknowledge that pure libertarianism becomes problematic

1078
01:02:24,764 --> 01:02:29,564
Speaker 1: in a pandemic, right, So you could say, for example, okay,

1079
01:02:29,604 --> 01:02:32,284
Speaker 1: well if it is a time of high transmission.

1080
01:02:32,324 --> 01:02:34,724
Speaker 2: I want to go to a restaurant. The owner wants

1081
01:02:34,724 --> 01:02:37,324
Speaker 2: to keep the restaurant open. The waiter and the servers

1082
01:02:37,364 --> 01:02:39,804
Speaker 2: want to make money noon tomic income for their families,

1083
01:02:39,844 --> 01:02:42,484
Speaker 2: And so what's so bad about that we're all assuming

1084
01:02:42,484 --> 01:02:45,204
Speaker 2: the own risk. However, we are also creating a negative

1085
01:02:45,204 --> 01:02:48,604
Speaker 2: externality for like people in our community. More broadly, right,

1086
01:02:48,644 --> 01:02:51,644
Speaker 2: and these questions become easier to solve when the countries

1087
01:02:51,644 --> 01:02:53,804
Speaker 2: are more united, right. I mean, you have a quote

1088
01:02:53,804 --> 01:02:56,524
Speaker 2: in the book that you kind of flight at the top.

1089
01:02:56,604 --> 01:02:58,004
Speaker 2: All of this is not a book about COVID, It's

1090
01:02:58,044 --> 01:03:01,284
Speaker 2: about a country ill equipped to ac sensibly under duress.

1091
01:03:01,644 --> 01:03:04,044
Speaker 2: How much of this is about the United States? And

1092
01:03:04,084 --> 01:03:07,124
Speaker 2: has that made you more pessimistic about the United States's

1093
01:03:07,364 --> 01:03:11,884
Speaker 2: leadership abilities? State capacity is a fancy term for it

1094
01:03:11,964 --> 01:03:12,644
Speaker 2: going forward.

1095
01:03:13,404 --> 01:03:20,444
Speaker 1: I'm very pessimistic. I'm hoping my vook will act as

1096
01:03:20,484 --> 01:03:22,724
Speaker 1: some sort of corrective for people and serve as a

1097
01:03:22,764 --> 01:03:27,684
Speaker 1: record and also as a means of thinking through how

1098
01:03:27,724 --> 01:03:31,764
Speaker 1: these things happen, which will hopefully act as some degree

1099
01:03:31,844 --> 01:03:35,484
Speaker 1: of like a countermeasure. But the reality is, you know,

1100
01:03:35,764 --> 01:03:38,764
Speaker 1: when you have this kind of like constellation of all

1101
01:03:38,764 --> 01:03:45,044
Speaker 1: these different influential institutions, and through both political and kind

1102
01:03:45,044 --> 01:03:50,884
Speaker 1: of like personality inclinations, it created a very bad environment

1103
01:03:50,924 --> 01:03:54,884
Speaker 1: with bad incentives for people to be afraid to either

1104
01:03:54,964 --> 01:03:57,884
Speaker 1: think critically, or if they were thinking critically, then be

1105
01:03:58,004 --> 01:04:00,724
Speaker 1: afraid or told explicitly that they were not allowed to

1106
01:04:00,724 --> 01:04:07,804
Speaker 1: go against the purported consensus. Well, it certainly certainly permanently

1107
01:04:07,804 --> 01:04:12,284
Speaker 1: shifted my priors as far as kind of how wrong

1108
01:04:12,364 --> 01:04:17,564
Speaker 1: the expert consensus can be, and how wrong motivated by

1109
01:04:17,724 --> 01:04:22,204
Speaker 1: I think somewhat banal and obvious political motives, how how

1110
01:04:22,964 --> 01:04:26,204
Speaker 1: unsubtle the effort to maintain the consensus was. And you

1111
01:04:26,244 --> 01:04:29,804
Speaker 1: absolutely would get screamed at if you expressed views that

1112
01:04:29,884 --> 01:04:33,204
Speaker 1: were very centrist a and later proved to be mostly

1113
01:04:33,244 --> 01:04:36,364
Speaker 1: correct B. But they were very careful about how they

1114
01:04:36,364 --> 01:04:38,964
Speaker 1: are drawing, drawing the lines between what was acceptable and

1115
01:04:38,964 --> 01:04:42,164
Speaker 1: what and what was not. And I will never forget it,

1116
01:04:42,364 --> 01:04:44,324
Speaker 1: but I'm glad we're not going through it anymore.

1117
01:04:44,524 --> 01:04:46,404
Speaker 2: So, thank you so much for joining us, David.

1118
01:04:46,364 --> 01:04:48,284
Speaker 1: Thanks for having me, Nate, it's good to chat with you.

1119
01:04:51,604 --> 01:04:54,924
Speaker 2: That's all for this week. Premium subscribers can seek around

1120
01:04:54,924 --> 01:04:57,124
Speaker 2: for our answer to one of your burning listener questions

1121
01:04:57,164 --> 01:04:59,924
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1122
01:04:59,964 --> 01:05:02,684
Speaker 2: signing up for just six ninety nine a month. You've

1123
01:05:02,684 --> 01:05:05,564
Speaker 2: got access to premium content from us every week and

1124
01:05:05,724 --> 01:05:09,644
Speaker 2: if you're listening across Pushkin's entire network of shows. Steve

1125
01:05:09,684 --> 01:05:12,724
Speaker 2: Business is hosted by me Nate Silver along with Maria Kanakova.

1126
01:05:13,204 --> 01:05:16,244
Speaker 2: The show is a co production of Pushkin Industries and iHeartMedia.

1127
01:05:16,884 --> 01:05:20,364
Speaker 2: This episode was produced by Isabelle Carter. Our associate producer

1128
01:05:20,404 --> 01:05:23,204
Speaker 2: is Sonya Gerwit Sally helm As our editor, and our

1129
01:05:23,244 --> 01:05:27,604
Speaker 2: executive producer is Jacob Goldstein. Mixing by Sarah Bruguer. If

1130
01:05:27,644 --> 01:05:29,884
Speaker 2: you like the show, please rate and review us. You

1131
01:05:29,924 --> 01:05:32,404
Speaker 2: know we like we take a four or five. We

1132
01:05:32,524 --> 01:05:34,764
Speaker 2: take the five, rate and review us to other people.

1133
01:05:34,804 --> 01:05:35,604
Speaker 2: Thank you for listening.