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Speaker 1: Hey, welcome to Stuff to Blow Your Mind. My name

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Speaker 1: is Robert Lamb and I'm Joe McCormick, and it's Saturday.

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Speaker 1: Time to go into the old vault. This time we're

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Speaker 1: looking at an episode that we originally released in November

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Speaker 1: of Yes. Uh, this was motivated numerousy and the politics

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Speaker 1: ridden brain. It's so, it seemed like a good good

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Speaker 1: year to roll this one back out in. Oh boy,

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Speaker 1: let's dive right in. Welcome to Stuff to Blow Your

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Speaker 1: Mind from how Stuffworks dot com. Hey, you welcome is

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Speaker 1: Stuff to Blow your Mind. My name is Robert Laham

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Speaker 1: and I'm Joe McCormick. And Robert, I want to hit

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Speaker 1: you with a quote. I'm sure you've heard this one

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Speaker 1: a million times before. It's a quote from the American

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Speaker 1: writer Upton Sinclair. Uh, and the quote goes like this.

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Speaker 1: He says, it is difficult to get a man to

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Speaker 1: understand something when his salary depends upon his not understanding it. Well,

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Speaker 1: that's pretty apt. I'm not sure I've actually heard that

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Speaker 1: one before, but but that certainly has a ring of

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Speaker 1: truth to it. Really, you never heard that. I think

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Speaker 1: I've heard that one. People roll that out all the

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Speaker 1: time when they're talking about, you know, industry shills, paid spokespeople,

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Speaker 1: pr types. Um. Yeah, yeah. So. Upton Sinclair ran for

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Speaker 1: governor of California in the nineteen thirties, and he claimed

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Speaker 1: in a campaign retrospective that he used to tell his

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Speaker 1: rally audience is this and it's a great line. There's

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Speaker 1: plenty of truth to it, right. Yeah. By the way,

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Speaker 1: for anyone who's not familiar. Upton Sinclair lived seventy eight

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Speaker 1: through nineteen sixty eight, and he was the author of

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Speaker 1: The Jungle and perhaps more known to some of our

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Speaker 1: listeners for his story Oil, which was loosely adapted into

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Speaker 1: the two thousand seven film There Will Be Blood. Always

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Speaker 1: going to be remembered for a movie first, But did

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Speaker 1: he also write Boogie Nights the original version? Maybe so, John,

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Speaker 1: maybe so? But but no, not just an author but

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Speaker 1: also a politician. Yeah. So he was used to talking

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Speaker 1: about issues of public policy. I mean, he was a

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Speaker 1: politically concerned writer. I think a lot of times people

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Speaker 1: put him in categories like like with Charles Dickens. You know,

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Speaker 1: somebody who's known for writing fiction but also for exposing

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Speaker 1: the plight of the politically disadvantaged. And so, yeah, this

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Speaker 1: quote comes up a lot, like if you're talking about

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Speaker 1: a lawyer representing big tobacco back in the day, who

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Speaker 1: would come on TV and say the science isn't settled yet,

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Speaker 1: there's no proof cigarettes cause cancer, or maybe a coal

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Speaker 1: industry lobbyist, maybe literally the same exact person comes on

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Speaker 1: TV a few decades later and says, don't listen to

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Speaker 1: the climate alarmist, that there are scientists on both sides.

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Speaker 1: You know, climate change isn't settled yet. When you're hearing

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Speaker 1: from people like this who are like paid to represent

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Speaker 1: a particular point of view, you obviously don't have to

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Speaker 1: be a super skeptic to realize you shouldn't just take

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Speaker 1: their word for it. Um, But people who get paid

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Speaker 1: to tell you that the grass is pink and the

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Speaker 1: sky is green are going to keep saying that. You know,

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Speaker 1: you're not going to change their mind by offering them

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Speaker 1: evidence or making good points or something, because they're not

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Speaker 1: here to figure out what's true. They're here to say

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Speaker 1: their lines. Yeah, I'm I'm always reminded of the The

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Speaker 1: Doctor character who would inevitably show up in the late

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Speaker 1: night infomercials for various products. Um, you know, clearly they

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Speaker 1: didn't just do a cold call and get get somebody

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Speaker 1: in there to uh to to shill for this product.

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Speaker 1: Only Marrow Burrow stimulates your cue zone when it comes

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Speaker 1: to people like that. I guess this is kind of

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Speaker 1: a tangent. But when it when it comes to like

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Speaker 1: people who shill for a particular you know, point of

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Speaker 1: view or spokespeople for some kind of line on TV,

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Speaker 1: I always kind of wonder like, do they end up

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Speaker 1: really truly believing the thing that they're paid to say

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Speaker 1: or is there some kind of cognitive dissonance in their brain.

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Speaker 1: I don't know what it's like to be in that mind. Yeah,

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Speaker 1: that's a great question though, because I mean it's one

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Speaker 1: thing for just like an individual to endorse a product,

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Speaker 1: you know, yeah, like reading an ad yeah you know,

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Speaker 1: or or even saying hey, I tried out this product.

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Speaker 1: It's really great. You guys should give it a try

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Speaker 1: as well, which obviously we do on the show. But

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Speaker 1: but but when you get to that level where you

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Speaker 1: have an expert, when you have say a medical doctor, um,

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Speaker 1: appearing on an infomercial or appearing even um you know,

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Speaker 1: in some sort of governmental body and saying yes, I

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Speaker 1: stake my reputation on this, I stay my professional um expertise.

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Speaker 1: Uh I put it on the line in support of

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Speaker 1: this product or this industry and directly contradicting what appears

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Speaker 1: to be the preponderance of the evidence. Right. That that's

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Speaker 1: what these industry shills come out to do, Right, They

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Speaker 1: come out to tell you that the scientists are wrong.

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Speaker 1: But anyway, given evidence that has emerged in recent years,

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Speaker 1: I think maybe later on in this episode we should

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Speaker 1: come back and try to do an updated version of

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Speaker 1: this Upton Sinclair quote, because I think that the scope

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Speaker 1: of this quote is actually too limited by just focusing

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Speaker 1: on the salary. So so we'll come back to this.

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Speaker 1: But today we're gonna be talking about a form of

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Speaker 1: motivated reasoning, a form of motivated reason thing called motivated

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Speaker 1: numerous ee and specifically how that relates to the idea

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Speaker 1: of identity protective cognition. And this has come up on

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Speaker 1: the show before. We talked about it in an episode

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Speaker 1: a while back called Science Communication Breakdown. I think that

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Speaker 1: was like a year and a half ago or so

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Speaker 1: I believe so, But it was based on when you

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Speaker 1: had gone to the World Science Festival and seen a

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Speaker 1: talk that included the work of the Yale psychologist Dan Kahan,

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Speaker 1: who is he does a lot of really interesting research

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Speaker 1: about biases and motivated reasoning and the ways in which

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Speaker 1: our brains failed to be rational in one way, sometimes

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Speaker 1: by being uh sort of subversively rational in another way. Yeah,

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Speaker 1: isn't it interesting how we sometimes uh as seem to

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Speaker 1: outsmart ourselves in these matters? Yeah? So I want to

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Speaker 1: start by thinking about two different kinds of disagreements that

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Speaker 1: come up when people talk about politics. There are obviously

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Speaker 1: lots of different ways people can disagree about politics. Here

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Speaker 1: here are two different kinds of currently politically re ev statements.

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Speaker 1: One is somebody who says the government shouldn't have a

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Speaker 1: right to tax my income. Right you might talk to

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Speaker 1: like a libertarian who says that. And then here's a

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Speaker 1: different politically relevant statement, human activity is the primary driver

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Speaker 1: of global climate change. Now, people have political arguments over

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Speaker 1: statements like both of these two all the time, But

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Speaker 1: these are not at all the same kind of statement.

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Speaker 1: One big difference is that the first statement is a

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Speaker 1: statement about values, like you can't do a bunch of

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Speaker 1: empirical experiments to determine if it's correct or not. That

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Speaker 1: the government should be allowed to tax people. That's just

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Speaker 1: a question about what you believe should be the case.

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Speaker 1: What about values and priorities, and about the priorities of

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Speaker 1: the person making the statement, right, it's a it's a

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Speaker 1: it's a commentary on how you think, or how one

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Speaker 1: group thinks politics should work, or how government should work. Rather, uh,

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Speaker 1: And we shouldn't be confused by the idea of political science.

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Speaker 1: Political science, though a serious field, is a different matter

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Speaker 1: compared to the natural sciences. Well, it's certainly true that

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Speaker 1: with questions about like whether or not you should tax income,

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Speaker 1: you can approach that question from the point of optimizing

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Speaker 1: for certain goals, Like if you specify a goal and

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Speaker 1: you compare different methods of achieving that goal, then you

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Speaker 1: can do that. But like, absent all of that kind

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Speaker 1: of framework, that's just a statement about values. On the

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Speaker 1: other hand, you've got the human activity is the primary

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Speaker 1: driver of global climate change. That statement is not like that.

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Speaker 1: There simply is a fact of the matter, either human

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Speaker 1: activity is the primary cause of global climate change or

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Speaker 1: it isn't. And you can do empirical experiments to test

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Speaker 1: this hypothesis. And of course the answer is that yes,

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Speaker 1: we now know that it is the primary driver of

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Speaker 1: global climate change with like a you know, ninety something

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Speaker 1: per cent certainty. It's we really, really strongly know this. Now,

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Speaker 1: this is undoubtedly the scientific consensus. Even though this question

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Speaker 1: is politically controversial, it's not scientifically controversial. And if you

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Speaker 1: doubt this, you actually have the ability to go look

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Speaker 1: up the evidence yourself. Especially, that's one thing that the

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Speaker 1: internet is great for. You can go read the most

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Speaker 1: recent I p c C report, you can read the

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Speaker 1: thousands of individual studies. You can look at the data

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Speaker 1: and read the climate scientist's own words about how their

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Speaker 1: conclusions are drawn from the data of their experiments. And

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Speaker 1: if you actually do that, I think any reasonable person

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Speaker 1: should be able to conclude, of course, human activities the

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Speaker 1: primary cause of climate change. And yet that's not what happens,

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Speaker 1: is it? Questions like this remain politically controversial, with people

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Speaker 1: often judging the answer in a way that aligns with

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Speaker 1: their political identity. Now, speaking of politics, I just want

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Speaker 1: to throw in a quick fact Lloyd here about this episode.

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Speaker 1: We were recording this on election day. It will be

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Speaker 1: published after election day. So yeah, so we don't know

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Speaker 1: what the outcome is going to be yeah. So so

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Speaker 1: none of this, none of this is a commentary on

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Speaker 1: things that have not yet occurred as of this recording,

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Speaker 1: and it's not really a commentary on politics per se.

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Speaker 1: It's a commentary on psychology really that that is going

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Speaker 1: to be at play and people of all political persuasions.

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Speaker 1: So I think we should turn to look at the

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Speaker 1: big paper that we're going to be focusing on in

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Speaker 1: this episode. The the lead author was was Dan Kahan,

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Speaker 1: but the other authors include Ellen Peters, Rika Cantrell Dawson,

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Speaker 1: and Paul Slovak. And it's called Motivated Numerousy and Enlightened

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Speaker 1: Self Government, published in Behavioral Public Policy, I think first

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Speaker 1: published in Revised in seventeen, and they start off by

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Speaker 1: observing the same kind of thing we've just been talking

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Speaker 1: about that obviously there are questions where people can argue

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Speaker 1: about their political values, but that politics is also full

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Speaker 1: of these arguments about purely empirical questions, many of which

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Speaker 1: are no longer in fact empirically controversial, like is climate

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Speaker 1: change driven by greenhouse gas emissions? The answer is yes,

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Speaker 1: but this is still politically controversial. Other questions like this

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Speaker 1: that they give a big list of them. One would

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Speaker 1: be like could we improve public safety by storing nuclear

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Speaker 1: waste deep underground? And that one is a yes as well.

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Speaker 1: I believe that's the one that was brought up in

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Speaker 1: the panel of World Science Festival that Kahan spoke on,

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Speaker 1: and that was one that actually I seem to be

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Speaker 1: more divisive. Um, they kind of pulled the audience there

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Speaker 1: at the World Science Festival, so you know, for the

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Speaker 1: most part of very informed and curious bunch, but even

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Speaker 1: they were not as well informed on this issue as

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Speaker 1: they were on some of these other issues we're talking

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Speaker 1: about here. Yeah, Now, not all of these questions are

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Speaker 1: going to be as settled with as much confidence as

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Speaker 1: other ones are. So like, we have a very high

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Speaker 1: confidence now that greenhouse gas emissions are driving climate change,

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Speaker 1: but there could be other questions that are in theory

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Speaker 1: empirical even if we don't have a scientific consensus yet.

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Speaker 1: I honestly don't know where this this next question falls in,

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Speaker 1: whether it's more settled or less settled. But other questions

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Speaker 1: would include things like, uh, do gun control measures reduce

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Speaker 1: violent crime or increase it? Uh, does public spending in

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Speaker 1: the aftermath of an economic recession increase the length of

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Speaker 1: the recession? Or shorten it. And so with some of

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Speaker 1: these questions, we don't always yet know the correct answer,

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Speaker 1: but they are at least empirical. You can do tests,

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Speaker 1: and you can gather data, and you can find with

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Speaker 1: some degree of confidence that there is a correct answer.

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Speaker 1: It's not just going to be an endless contest of values. Yes,

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Speaker 1: it's in the domain of science, and science can have

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Speaker 1: at it. One of the interesting things about a lot

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Speaker 1: of these questions is that they, for some reason almost

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Speaker 1: always seem to concern questions or perceptions of risk. I

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Speaker 1: guess maybe that's just what politics is about. Yeah, I

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Speaker 1: think there is a lot of risk analysis in politics.

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Speaker 1: I mean, obviously there's there's there's always a certain amount

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Speaker 1: of fear mongering as well, Like how do you how

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Speaker 1: do you capitalize on the sort of risks that that

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Speaker 1: voters are considering? How do you potentially stir up the

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Speaker 1: flames or uh or or or tamp them down a bit,

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Speaker 1: depending on what kind of reaction you're looking for. Well,

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Speaker 1: I guess you could look at many major policy decisions

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Speaker 1: as um as conflicts between perceptions of different kinds of risks, right, Like,

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Speaker 1: so somebody will say, well, there's a certain amount of

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Speaker 1: Here the things that could result and somebody else's yes,

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Speaker 1: But if we do something about it, we risk I

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Speaker 1: don't know, we risk not making enough money or something

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Speaker 1: or or per perhaps it's yeah, we risk hurting ourselves

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Speaker 1: in the short term or a lot of a lot

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Speaker 1: of times, the short term risk versus long term risk,

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Speaker 1: immediate risk versus more you know, elusive risks. Yeah. Now, obviously,

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Speaker 1: when you look at these questions that have been pretty

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Speaker 1: convincingly answered with empirical evidence, and yet intense disagreement persists

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Speaker 1: in politics, this obviously isn't helpful. Like there's enough under

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Speaker 1: dispute over what values should drive public policy that it

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Speaker 1: really doesn't help to add to that, like unnecessary dead

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Speaker 1: end disputes about underlying empirical facts, when the science or

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Speaker 1: the facts are actually pretty clear. So the question is

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Speaker 1: why how come you can have a question where the

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Speaker 1: evidence is very clear, such as the cause of climate

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Speaker 1: change being related to the burning of fossil fuels, but

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Speaker 1: the public not being in general agreement about it. And

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Speaker 1: this This paper looks at two major competing hypotheses to

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Speaker 1: explain this, like why people don't accept the facts when

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Speaker 1: the facts are pretty clear. And the first one is

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Speaker 1: the hypothesis they call the science comprehension thesis or the SCT,

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Speaker 1: and basically it goes like this, the public in general

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Speaker 1: has a pretty weak understanding of science. We are likely

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Speaker 1: to misunderstand what scientists are telling us. If you put

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Speaker 1: a scientific paper in front of us, we're probably not

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Speaker 1: gonna understand it. Thus, we're likely to be misled by

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Speaker 1: people who are trying to deceive us to their own advantage.

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Speaker 1: And I think unfortunately, or well, I don't want to

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Speaker 1: preempt what we get to in a bit, but I

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Speaker 1: guess we could say unfortunately. This hypothesis is pretty common

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Speaker 1: among skeptics and science enthusiasts and even scientists themselves, and

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Speaker 1: I feel myself very drawn to it because if you

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Speaker 1: accept that the problem is, um, we're just not scientifically

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Speaker 1: literate enough to understand what's being talked about, in a way,

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Speaker 1: this is actually kind of hopeful, especially if you're an

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Speaker 1: educator or a science communicator, because the problem is simply

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Speaker 1: a lack of knowledge. There's just a deficit that can

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Speaker 1: be made up. And so if you just you know, community,

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Speaker 1: you give people better scientific education better communication of the

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Speaker 1: scientific reality. Under this hypothesis, if you just teach people

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Speaker 1: better scientific literacy skills, they will finally see the light

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Speaker 1: and come around and accept the empirically verifiable facts. Yeah,

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Speaker 1: there's hopingness because you can you can teach people about science.

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Speaker 1: You can you can teach people more about logical thinking

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Speaker 1: as well. Um, and though of course I think that's

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Speaker 1: clearly part of scientific literacy as well. But but I

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Speaker 1: can't help but think back to, for instance, harl Sagan's

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Speaker 1: discussion of on the Bologny detection kit, Like the problem

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Speaker 1: is people don't have the kit online, right, or they

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Speaker 1: don't have all the tools and the kit for instance,

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Speaker 1: just to just to blow through these really quickly. He

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Speaker 1: goes into far more detail in the demon Haunted World.

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Speaker 1: But the nine tools are again abbreviated Number one. Whenever possible,

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Speaker 1: there must be independent confirmation of the facts. Facts and

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Speaker 1: quotations uh. Number two encourage a substantive debate on the

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Speaker 1: evidence by knowledgeable proponents of all points of view. Number

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Speaker 1: Since number three, arguments from authority carry little weight. Authorities

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Speaker 1: have made mistakes in the past, they will do so

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Speaker 1: again in the future, and science there are no authorities.

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Speaker 1: At most there are experts. Number four, spin more than

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Speaker 1: one hypothesis. Number five. Try not to get overly attached

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Speaker 1: to a hypothesis just because it's yours. Number six. Quantify.

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Speaker 1: If whatever it is you're explaining has some measure, some

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Speaker 1: numerical quantity attached to it, you'll be much better able

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Speaker 1: to discriminate among competing hypothes seas. This is why numbers

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Speaker 1: are often useful in science. Ye exactly. Number seven. If

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Speaker 1: there's a chain of argument, every link in the chain

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Speaker 1: must work, including the premise, not just most of them.

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Speaker 1: Number eight Acam's razor. This is basically, when you have

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Speaker 1: um two hypotheses that explained data equally well, you choose

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Speaker 1: the simpler of the two. Right, So like a dream

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Speaker 1: or a hallucination is probably a better explanation for your

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Speaker 1: alien abduction experience than aliens coming here. Exactly. And then finally,

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Speaker 1: the knife tool in the Bologna detection kit always ask

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Speaker 1: whether the hypothesis can be at least in principle falsified

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Speaker 1: Propositions that are untestable or unfalsifiable are not worth much.

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Speaker 1: That's a really good kit, and I think Carl Sagan

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Speaker 1: I don't want to put words in his mouth, but

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Speaker 1: I do think he he seems to operate from that

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Speaker 1: kind of hopeful scientific comprehension thesis point of view. At

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Speaker 1: least as best I can tell, it seems like he thinks,

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Speaker 1: you know, the problem with the lack of scientific skepticism

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Speaker 1: among the people is just that they need access to

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Speaker 1: better tools like this, and if we can communicate those

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Speaker 1: tools to them, they can bring them online and then

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Speaker 1: they'll be more protected against the titular bologna. Yeah, I

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Speaker 1: think so. Now back to this paper, the authors write

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Speaker 1: that on this hypothesis on the science comprehension thesis, the

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Speaker 1: lack of comprehension skill causes people to over rely on

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Speaker 1: what's calling what's known as system one thinking when judging

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Speaker 1: empirical scientific questions like perceptions of risk. Now we should

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Speaker 1: mention a little bit about the difference between these concepts

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Speaker 1: of system one thinking and system to thinking. This is

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Speaker 1: big in the works of people like Daniel Kanemon who

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Speaker 1: have written about behavioral economics and the psychology of bias

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Speaker 1: and stuff. That's right. It was key to his two

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Speaker 1: thousand and eleven book Thinking Fast and Slow. Um, And

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Speaker 1: we've talked about system one thinking system to thinking on

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Speaker 1: the show before I Think, I think so Yeah. The

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Speaker 1: basic explanation here, System one thinking is all about fast, automatic, frequent, emotional,

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Speaker 1: stereotypic and unconscious thinking. This is the theory. This is

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Speaker 1: rule by heuristics, you know, shortcut ways of thinking. When

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Speaker 1: you when you look at two piles of things and

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Speaker 1: want to know how many, you know which pile has

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Speaker 1: more things in it? If you just judge by I

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Speaker 1: don't know your eyeball, it that system one system to

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Speaker 1: thinking would be what maybe you count the things in

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Speaker 1: the pile? Right? It is slow, effortful, infrequent, logical, calculating,

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Speaker 1: and conscious. This reminds me a lot of the two

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Speaker 1: fear networks that were recently discussed on the show Yeah

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Speaker 1: and the Slayer episode Yeah. System two is all about

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Speaker 1: avoiding the tiger haunted thickets. Well, if you rely on

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Speaker 1: system one and then you're more of a tiger racer,

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Speaker 1: a tiger boxer, or just I guess, just a straight

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Speaker 1: up tiger denier. And you know, both of those systems

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Speaker 1: are necessary actually because we don't always have time to

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Speaker 1: do deliberate, slow logical calculating conscious thought a lot. You know,

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Speaker 1: if we did that about every decision we made, we

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Speaker 1: couldn't live. That would be no way to survive. You

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Speaker 1: have to be fast and reactive and unconscious about all

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Speaker 1: kinds of things. And so the question is how do

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Speaker 1: you choose which types of decisions and scenarios to apply

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Speaker 1: these two different thinking schema to. On the science comprehension thesis,

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Speaker 1: I think the idea is that people are relying on

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Speaker 1: system one thinking to answer empirical questions about science that

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Speaker 1: are politically relevant, whereas they should be using their system

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Speaker 1: to thinking to get through the get through the fast, reactive,

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Speaker 1: stereotypic kind of thinking and come to the correct answer.

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Speaker 1: Fun fact, we used to be owned by a company

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Speaker 1: that called itself System one UH, named after this um

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Speaker 1: this mode of thinking. But that's not the only hypothesis

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Speaker 1: on offer. That's the science comprehension thesis. The other hypothesis,

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Speaker 1: the rival hypothesis, is what if the problem with controversies

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Speaker 1: over empirical questions is not that they're caused by a

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Speaker 1: deficit of knowledge or cognitive skill UH. And this other

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Speaker 1: idea the authors called the identity protective cognition thesis or

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Speaker 1: the I C t and they write, quote whereas s

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Speaker 1: CT attributes conflicts over decision relevant science two deficits in

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Speaker 1: science comprehension I set sees the public's otherwise intact capacity

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Speaker 1: to comprehend decision relevant science as disabled by cultural and

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Speaker 1: political conflict. In other words, it's not that people can't

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Speaker 1: understand the science, it's that they could understand the issue

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Speaker 1: if they were not politically charged. And it is specifically

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Speaker 1: the political charging of the issue that makes it impossible

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Speaker 1: for them to understand what they otherwise might be able to.

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Speaker 1: All right, so I have to try and put this

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Speaker 1: into tiger terms. Okay, So it's like having the capabilities

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Speaker 1: to avoid tiger kill zones but refusing to do so

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Speaker 1: for political reasons. Right, Yes, all your friends around you

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Speaker 1: maybe are saying, like, oh no, that the people who

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Speaker 1: say that the tigers hang out in the jungle are dumb.

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Speaker 1: They are the bad people, real people, really, the good

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Speaker 1: people all know that there are no tigers in the jungle,

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Speaker 1: that the tigers are somewhere else. I do admit I

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Speaker 1: love it anytime we can put things in terms of

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Speaker 1: big cat attacks. That always just seems to really help

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Speaker 1: explain the topic. You should know, I'm picturing not a

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Speaker 1: real tiger. But Tony the tiger. Yeah, Tony the tiger

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Speaker 1: mauling and killing people. All right, that works for me. Okay,

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Speaker 1: So here's the question. If this hypothesis is correct, why

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Speaker 1: would it be the case that political charging of issues

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Speaker 1: would make us unable to use our normal reasoning faculties. Well,

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Speaker 1: first of all, I mean, think about the Uptons and

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Speaker 1: Claire quote. It's difficult to make a person understand something

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Speaker 1: when their salary depends on it. Here we're not talking

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Speaker 1: about a salary, but about something else of immense psychic

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Speaker 1: and material value, and that is your membership, status and

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Speaker 1: standing within a social group that is in part defined

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Speaker 1: by its commitment to certain moral and political values. Well,

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Speaker 1: I think that's very much like salary. I mean, salary

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Speaker 1: is money, Money is life, money is happiness. I mean

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Speaker 1: we say it's not it is, uh, and then uh

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Speaker 1: and then but but it is the thing that allows

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Speaker 1: us to eat and live and be in most circumstances,

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Speaker 1: certainly in the world that we've we've we've made and

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Speaker 1: remade for ourselves. And likewise, in a more primal sense,

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Speaker 1: belonging to a group, being part of a group, that

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Speaker 1: is that is survival for for the Homo sapiens. Yes,

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Speaker 1: that is how we have historically and prehistorically managed to live.

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Speaker 1: It's psychically necessary to us. It's necessary for us to

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Speaker 1: have good mental end. In fact, I think in some

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Speaker 1: ways good physical health to be a member in good

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Speaker 1: standing of a social group and a social network. But

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Speaker 1: if you want to go into our you know, our

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Speaker 1: our evolutionary history, it is literally materially necessary to be

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Speaker 1: accepted as a member of the end group. If you're

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Speaker 1: driven out of your hunter gatherer tribe that things are

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Speaker 1: not looking good for you, you're just waiting to fall

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Speaker 1: into a tiger thicket at that point, right. And so,

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Speaker 1: if all your friends and allies believe one way about

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Speaker 1: any politically charged issue climb change or gun control or whatever,

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Speaker 1: and you put yourself at huge personal risk by advocating

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Speaker 1: a position that that group disagrees with, you could be

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Speaker 1: alienated from your social group. You could lose connections that

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Speaker 1: you depend on for mental health and survival. Thus, you

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Speaker 1: could definitely see identity protective cognition as a kind of

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Speaker 1: mental immune system. It protects the brain from beliefs that

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Speaker 1: could potentially cause you immense harm if you were to

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Speaker 1: express them. The brain detects a belief or an idea

430
00:23:30,200 --> 00:23:32,879
Speaker 1: that is a threat to your social identity, and it

431
00:23:32,960 --> 00:23:35,680
Speaker 1: puts up a wall against that belief and doesn't let

432
00:23:35,680 --> 00:23:37,800
Speaker 1: it in because it could hurt you, you know, And

433
00:23:37,840 --> 00:23:39,440
Speaker 1: I think we can all relate to this on one

434
00:23:39,560 --> 00:23:42,480
Speaker 1: level or another. You know, how many times have any

435
00:23:42,480 --> 00:23:44,320
Speaker 1: of us said, well, I refuse to believe that, or

436
00:23:44,359 --> 00:23:48,040
Speaker 1: I find that hard to believe. Um. And of course

437
00:23:48,040 --> 00:23:50,760
Speaker 1: there are a lot of examples that come up in

438
00:23:50,800 --> 00:23:53,960
Speaker 1: which they're the issues relate more clearly to personal belief

439
00:23:54,080 --> 00:23:57,720
Speaker 1: and and or just pure opinion and artistic value. For instance,

440
00:23:57,760 --> 00:24:01,000
Speaker 1: of a movie reviewer television review or tells me that

441
00:24:01,119 --> 00:24:04,880
Speaker 1: an upcoming Coen Brothers movie isn't worth seeing, I generally

442
00:24:04,920 --> 00:24:08,320
Speaker 1: find that hard to believe until I see it for myself,

443
00:24:08,359 --> 00:24:11,159
Speaker 1: and say, in the case of Inside Lewyn Davis, I

444
00:24:11,240 --> 00:24:14,520
Speaker 1: end up agreeing with what Inside Lewyn Davis. You know

445
00:24:14,800 --> 00:24:19,800
Speaker 1: it was wonderfully made. Prepare to be ostracized, but you

446
00:24:19,840 --> 00:24:21,640
Speaker 1: know it was wonderfully made. But it was just not

447
00:24:21,760 --> 00:24:24,080
Speaker 1: my cup of tea. Oh I loved it. I love

448
00:24:24,280 --> 00:24:26,800
Speaker 1: Oscar Isaac. It was Oh man, he's such a great

449
00:24:26,840 --> 00:24:29,280
Speaker 1: singer to the music and it was wonderful, the music

450
00:24:29,400 --> 00:24:32,800
Speaker 1: was was great. It just did not It did not

451
00:24:32,880 --> 00:24:36,520
Speaker 1: make me happy or make me sad in an interesting way.

452
00:24:36,840 --> 00:24:39,760
Speaker 1: You know, I will, I will do my best not

453
00:24:39,880 --> 00:24:44,199
Speaker 1: to fully alienate you and throw you out into the cold. So,

454
00:24:44,480 --> 00:24:46,399
Speaker 1: but that's one thing, right, ultimately coming down to art

455
00:24:46,440 --> 00:24:48,880
Speaker 1: in personal opinion. Uh and and there are I think

456
00:24:48,920 --> 00:24:51,120
Speaker 1: there are going to be certain areas where you are

457
00:24:51,160 --> 00:24:54,159
Speaker 1: going to be so attached to certain artistic values that

458
00:24:54,200 --> 00:24:57,480
Speaker 1: you're going to feel reluctant to state it because of

459
00:24:57,480 --> 00:25:00,560
Speaker 1: how it might affect your standing in a group. Oh yeah,

460
00:25:00,600 --> 00:25:03,560
Speaker 1: So that's a different kind of variation, Like there are

461
00:25:03,720 --> 00:25:08,840
Speaker 1: some unpopular aesthetic opinions that you're not really scared to

462
00:25:08,960 --> 00:25:12,119
Speaker 1: voice because you could abandoned them if you needed to. Maybe,

463
00:25:12,119 --> 00:25:15,320
Speaker 1: but I really deeply held aesthetic preference that would be

464
00:25:15,680 --> 00:25:19,000
Speaker 1: unpopular you maybe just don't even bring up. Yeah, Like

465
00:25:19,000 --> 00:25:22,160
Speaker 1: I imagine a band abandoning suddenly abandoning your favorite rock

466
00:25:22,200 --> 00:25:24,160
Speaker 1: band in high school, you know that sort of thing.

467
00:25:24,640 --> 00:25:27,120
Speaker 1: But but clearly, you know, a lot of these other

468
00:25:27,160 --> 00:25:29,360
Speaker 1: issues are also are going to be different. Matters, say,

469
00:25:29,359 --> 00:25:31,639
Speaker 1: matters of hearsay or something that's just not completely a

470
00:25:31,720 --> 00:25:34,119
Speaker 1: provable one way or another, uh say, some bit of

471
00:25:34,119 --> 00:25:36,000
Speaker 1: dirt on a political candidate that can need to be

472
00:25:36,000 --> 00:25:39,360
Speaker 1: confirmed or denied. But then we have to come back

473
00:25:39,359 --> 00:25:42,600
Speaker 1: to those empirical questions, the ones where science can and

474
00:25:42,680 --> 00:25:45,760
Speaker 1: does weigh in on the matter. Yes, and fortunately, as

475
00:25:45,760 --> 00:25:49,360
Speaker 1: the authors point out, not that many empirical questions are

476
00:25:49,440 --> 00:25:54,320
Speaker 1: really likely to trigger identity protective cognition. Only empirical questions

477
00:25:54,359 --> 00:25:58,320
Speaker 1: that are unfortunate enough to get tagged as politically significant

478
00:25:58,560 --> 00:26:02,520
Speaker 1: along partisan lines really acquired this taint. For example, you know,

479
00:26:02,560 --> 00:26:06,520
Speaker 1: there's been a partisan divide over the HPV vaccine, probably

480
00:26:06,520 --> 00:26:09,520
Speaker 1: because it has some kind of perceived relevance to sexual

481
00:26:09,560 --> 00:26:12,720
Speaker 1: morality and young people. But there's no partisan divide on

482
00:26:12,760 --> 00:26:16,679
Speaker 1: the use of antibiotics to treat bacterial infections. And most

483
00:26:16,840 --> 00:26:19,639
Speaker 1: questions are more like the antibiotics. There's just there's not

484
00:26:19,720 --> 00:26:24,040
Speaker 1: a partisan divide about it. What you know, temperature, water boils,

485
00:26:24,119 --> 00:26:28,280
Speaker 1: or scientific questions. There's just not really a partisan divide

486
00:26:28,320 --> 00:26:31,320
Speaker 1: on though. To come back to antibiotics, I see, I

487
00:26:31,359 --> 00:26:33,600
Speaker 1: see a dark future. I see there could be a

488
00:26:33,600 --> 00:26:37,480
Speaker 1: time where if members of one major political party but

489
00:26:37,640 --> 00:26:41,359
Speaker 1: not the other, happen to start talking about antibiotics. I

490
00:26:41,359 --> 00:26:45,159
Speaker 1: think you could quite easily see partisan associations arise, and

491
00:26:45,200 --> 00:26:48,760
Speaker 1: antibiotics could go from an issue that's non politicized where

492
00:26:48,760 --> 00:26:51,639
Speaker 1: pretty much everybody agrees to an issue that suddenly is

493
00:26:51,720 --> 00:26:55,639
Speaker 1: divided along partisan lines. Now that that seems sadly like

494
00:26:55,680 --> 00:26:57,320
Speaker 1: the kind of thing we would do. But to come

495
00:26:57,359 --> 00:26:59,800
Speaker 1: back on the other side, Okay, wait a minute, don't

496
00:26:59,800 --> 00:27:05,000
Speaker 1: be will also have an incentive to have correct beliefs obviously, right,

497
00:27:05,040 --> 00:27:07,800
Speaker 1: I mean right, yeah, I mean we It definitely pays

498
00:27:07,840 --> 00:27:12,080
Speaker 1: off to have a working, realistic model of how the

499
00:27:12,119 --> 00:27:14,880
Speaker 1: world works that you live in. But it pays off

500
00:27:14,920 --> 00:27:18,840
Speaker 1: in some ways that are much more personally immediately relevant

501
00:27:18,880 --> 00:27:22,119
Speaker 1: than others. Uh, depending on the issue. Think about it.

502
00:27:22,440 --> 00:27:26,080
Speaker 1: In policy relevant empirical questions like the impact of carbon

503
00:27:26,160 --> 00:27:31,120
Speaker 1: emissions or the impact of gun control policies, the consequence

504
00:27:31,160 --> 00:27:35,520
Speaker 1: of one individual person being wrong is vanishingly small. But

505
00:27:35,680 --> 00:27:39,040
Speaker 1: for that one person, the consequence of being alienated from

506
00:27:39,040 --> 00:27:43,240
Speaker 1: their identity group is potentially massive. So on one decision,

507
00:27:43,320 --> 00:27:46,399
Speaker 1: you potentially cast one vote out of millions for a

508
00:27:46,440 --> 00:27:50,119
Speaker 1: poorly reasoned public policy, and on the other decision, you

509
00:27:50,160 --> 00:27:54,360
Speaker 1: could alienate or weaken your most important friendships, your work relationships,

510
00:27:54,359 --> 00:27:57,199
Speaker 1: and even your sense of self. Um and so the

511
00:27:57,240 --> 00:28:01,200
Speaker 1: author's right quote, persistent conflict over risks and other policy

512
00:28:01,240 --> 00:28:05,960
Speaker 1: relevant facts reflects a tragedy of the science communications commons,

513
00:28:06,720 --> 00:28:11,720
Speaker 1: a misalignment between the individual interests that culturally diverse citizens

514
00:28:11,760 --> 00:28:15,440
Speaker 1: have informing beliefs that connect them to others who share

515
00:28:15,480 --> 00:28:19,000
Speaker 1: their distinctive understanding of the best life, and the collective

516
00:28:19,040 --> 00:28:21,800
Speaker 1: interests that members of all such groups share in the

517
00:28:21,920 --> 00:28:25,440
Speaker 1: enactment of public policies that enable them to pursue their

518
00:28:25,640 --> 00:28:29,639
Speaker 1: ends free from threats to their health and prosperity. Okay,

519
00:28:29,640 --> 00:28:31,240
Speaker 1: maybe we should take a quick break and when we

520
00:28:31,320 --> 00:28:34,040
Speaker 1: come back we can take a look at how we

521
00:28:34,119 --> 00:28:40,720
Speaker 1: can compare these two hypotheses. Thank alright, we're back. So, yeah,

522
00:28:40,760 --> 00:28:43,840
Speaker 1: we're gonna look at ways to compare these two hypotheses. Now,

523
00:28:43,840 --> 00:28:46,440
Speaker 1: of course, in all of this, I can't help but think, well,

524
00:28:46,520 --> 00:28:49,479
Speaker 1: why can't it be both? Why can't what we can

525
00:28:49,600 --> 00:28:52,960
Speaker 1: we have like both of these, uh, these these reasons

526
00:28:53,000 --> 00:28:57,200
Speaker 1: in play? You mean that? So we've got the two apotheses,

527
00:28:57,280 --> 00:29:00,080
Speaker 1: the science comprehension thesis, which says that people come to

528
00:29:00,280 --> 00:29:05,600
Speaker 1: incorrect beliefs about scientifically are politically relevant empirical questions because

529
00:29:05,680 --> 00:29:09,560
Speaker 1: they lack the scientific literacy skills to understand the issues.

530
00:29:09,600 --> 00:29:11,640
Speaker 1: And then the other one says, it's not that they

531
00:29:11,720 --> 00:29:14,479
Speaker 1: lack the skills to understand the issues, it's that they

532
00:29:14,480 --> 00:29:19,840
Speaker 1: are being selectively blinded from proper reasoning by identity protective

533
00:29:19,840 --> 00:29:23,800
Speaker 1: cognition that is socially conditioned. Right, the idea coming back

534
00:29:23,800 --> 00:29:25,719
Speaker 1: to Segand's tool kit, it's like, do I not have

535
00:29:25,760 --> 00:29:28,000
Speaker 1: the tools or is there just this like this, there

536
00:29:28,080 --> 00:29:31,600
Speaker 1: is a social and psychological reason for not using the

537
00:29:31,640 --> 00:29:34,080
Speaker 1: tools that I have. Well, I think technically you could

538
00:29:34,080 --> 00:29:36,400
Speaker 1: have both in a way. So the question would be, um,

539
00:29:37,680 --> 00:29:40,640
Speaker 1: can you show that these are are mutually exclusive, and

540
00:29:40,640 --> 00:29:42,720
Speaker 1: that would come through in the evidence. But you certainly

541
00:29:42,720 --> 00:29:48,120
Speaker 1: could have a population that has fewer science comprehension skills

542
00:29:48,200 --> 00:29:51,000
Speaker 1: than it could and so you could educate people in

543
00:29:51,040 --> 00:29:54,880
Speaker 1: science better and we would have higher scientific comprehension skills.

544
00:29:54,920 --> 00:29:59,080
Speaker 1: But also within that population, identity protective cognition could be

545
00:29:59,200 --> 00:30:02,480
Speaker 1: highly salient. And so that's a good question. But if

546
00:30:02,480 --> 00:30:06,040
Speaker 1: you want to pit these two hypotheses against each other,

547
00:30:06,080 --> 00:30:09,479
Speaker 1: you can create just create conditions where they're obviously going

548
00:30:09,520 --> 00:30:13,040
Speaker 1: to be antagonistic as far as the data is concerned.

549
00:30:13,360 --> 00:30:17,920
Speaker 1: So here's one idea. If the science comprehension thesis is correct, right,

550
00:30:18,000 --> 00:30:21,680
Speaker 1: the problem is a deficit and understanding science. People who

551
00:30:21,720 --> 00:30:26,080
Speaker 1: are better at drawing correct conclusions from scientific data will

552
00:30:26,120 --> 00:30:29,000
Speaker 1: be better at it, whether or not the data concerns

553
00:30:29,080 --> 00:30:32,960
Speaker 1: politically relevant issues. Right, So it should mean that if

554
00:30:33,000 --> 00:30:36,240
Speaker 1: the s CT is correct, the science comprehension thesis, it

555
00:30:36,320 --> 00:30:40,560
Speaker 1: should mean that if you have scientific understanding skills like

556
00:30:40,840 --> 00:30:43,920
Speaker 1: numerous E, which is skill at using numbers and drawing

557
00:30:43,960 --> 00:30:48,480
Speaker 1: conclusions from from quantitative data. If you have high numerous E,

558
00:30:48,880 --> 00:30:52,440
Speaker 1: you should be better at drawing the correct conclusions from data,

559
00:30:52,760 --> 00:30:56,880
Speaker 1: whether or not that data flatters your political perceptions. Um.

560
00:30:57,120 --> 00:30:59,960
Speaker 1: On the other hand, if the identity protective cognition these

561
00:31:00,000 --> 00:31:02,880
Speaker 1: this is correct, people who are better at drawing correct

562
00:31:02,920 --> 00:31:07,120
Speaker 1: conclusions from scientific data will see this skill significantly hampered

563
00:31:07,120 --> 00:31:10,760
Speaker 1: by the introduction of a political identity threat. All right,

564
00:31:10,800 --> 00:31:12,239
Speaker 1: so I have a feeling we're gonna we're gonna look

565
00:31:12,240 --> 00:31:16,400
Speaker 1: at some experiments. Yes, so the experiment is big sample

566
00:31:16,600 --> 00:31:20,080
Speaker 1: of one thousand, one hundred and eleven demographically diverse and

567
00:31:20,120 --> 00:31:23,880
Speaker 1: ideologically diverse US adults. Uh, and you sort them according

568
00:31:23,920 --> 00:31:26,760
Speaker 1: to a couple of major factors. One is political ideology,

569
00:31:27,040 --> 00:31:29,480
Speaker 1: so they're sort of on on a scale of how

570
00:31:29,560 --> 00:31:32,840
Speaker 1: liberal or conservative they rate themselves. And then the next

571
00:31:32,920 --> 00:31:36,040
Speaker 1: is their numeracy skills, determined by a numeracy test. The

572
00:31:36,040 --> 00:31:39,800
Speaker 1: author's right quote a well established and highly studied construct

573
00:31:39,800 --> 00:31:43,440
Speaker 1: and numerousy encompasses not just mathematical ability, but also a

574
00:31:43,480 --> 00:31:47,920
Speaker 1: disposition to engage quantitative information in a reflective and systematic

575
00:31:47,960 --> 00:31:51,040
Speaker 1: way and to use it to support valid inferences. So

576
00:31:51,160 --> 00:31:53,400
Speaker 1: it's not just being good at math, but it's being

577
00:31:53,440 --> 00:31:56,239
Speaker 1: able to say, look at data in a study and

578
00:31:56,320 --> 00:31:59,320
Speaker 1: figure out what that data should tell you. So the

579
00:31:59,360 --> 00:32:02,800
Speaker 1: authors came up with a couple of fictional experiments, and

580
00:32:02,840 --> 00:32:05,840
Speaker 1: they took the results of these fictional experiments and asked

581
00:32:05,880 --> 00:32:09,200
Speaker 1: the participants to draw conclusions based on the results they

582
00:32:09,200 --> 00:32:12,560
Speaker 1: showed them. Now, both the results of the fictional experiment

583
00:32:12,600 --> 00:32:15,480
Speaker 1: and the topic of the experiment were manipulated to create

584
00:32:15,480 --> 00:32:18,520
Speaker 1: different test conditions, so the same results were offered in

585
00:32:18,560 --> 00:32:21,560
Speaker 1: the context of either being about quote the effectiveness of

586
00:32:21,560 --> 00:32:24,960
Speaker 1: a new skin rash treatment or quote the effectiveness of

587
00:32:25,000 --> 00:32:28,320
Speaker 1: a ban on carrying concealed weapons in public one of

588
00:32:28,320 --> 00:32:30,560
Speaker 1: those is going to be more controversial than the other. Right,

589
00:32:30,720 --> 00:32:33,600
Speaker 1: so what they're saying is they they expect that the

590
00:32:33,640 --> 00:32:36,440
Speaker 1: skin rash treatment is not going to have any partisan

591
00:32:36,520 --> 00:32:40,320
Speaker 1: significance unless I don't know, major Republicans or Democrats start

592
00:32:40,360 --> 00:32:43,360
Speaker 1: talking about skin rashes a lot, but at this point

593
00:32:43,360 --> 00:32:46,760
Speaker 1: it was not politically relevant. The other is of course

594
00:32:46,840 --> 00:32:49,080
Speaker 1: being about guns, which is one of the most highly

595
00:32:49,160 --> 00:32:54,400
Speaker 1: charged politically charged topics where people break down along partisan lines. Okay,

596
00:32:54,400 --> 00:32:56,400
Speaker 1: so imagine you're one of the people who's a subject

597
00:32:56,440 --> 00:33:00,120
Speaker 1: in this experiment. They will give you a table of

598
00:33:00,200 --> 00:33:03,160
Speaker 1: results to look at, and it might say it's say

599
00:33:03,160 --> 00:33:05,960
Speaker 1: it's you're in the skin rash condition. It might You'll

600
00:33:06,000 --> 00:33:08,760
Speaker 1: have a table of four numbers, and the different numbers

601
00:33:08,800 --> 00:33:12,560
Speaker 1: represent patients who did use a new skin cream and

602
00:33:12,640 --> 00:33:15,400
Speaker 1: patients who did not use a new skin cream. And

603
00:33:15,440 --> 00:33:18,120
Speaker 1: then the other axes of the table will be patients

604
00:33:18,120 --> 00:33:21,840
Speaker 1: whose rash got worse and patients whose rash got better.

605
00:33:21,920 --> 00:33:24,280
Speaker 1: And then you need to determine, based on the numbers

606
00:33:24,280 --> 00:33:27,600
Speaker 1: and the table, whether the skin cream is more helpful

607
00:33:27,760 --> 00:33:30,880
Speaker 1: or more harmful, and then substitute in the exact same

608
00:33:30,920 --> 00:33:33,960
Speaker 1: thing for instead of using patients using a skin cream,

609
00:33:34,280 --> 00:33:38,320
Speaker 1: cities that did or did not ban carrying concealed handguns

610
00:33:38,320 --> 00:33:41,040
Speaker 1: in public, and instead of the rash getting worse or

611
00:33:41,080 --> 00:33:43,800
Speaker 1: the rash getting better, it's crime went down or crime

612
00:33:43,840 --> 00:33:47,440
Speaker 1: went up. So the authors had three hypotheses three that

613
00:33:47,480 --> 00:33:50,640
Speaker 1: they would test here. One is that they guessed subjects

614
00:33:50,640 --> 00:33:53,280
Speaker 1: scoring high in numerousy would be more likely to get

615
00:33:53,320 --> 00:33:57,280
Speaker 1: the right result in both skin treatment conditions. And this

616
00:33:57,320 --> 00:33:59,880
Speaker 1: is pretty straightforward. Basically, they're saying people who have higher

617
00:34:00,040 --> 00:34:03,560
Speaker 1: numercy skills are more likely to use deliberate system to

618
00:34:03,760 --> 00:34:06,840
Speaker 1: thinking to work out the covariance between the results and

619
00:34:06,920 --> 00:34:09,400
Speaker 1: draw the correct conclusions, they're more likely to get the

620
00:34:09,400 --> 00:34:13,080
Speaker 1: skin rash thing right. Hypothesis too, is based on the

621
00:34:13,080 --> 00:34:16,760
Speaker 1: science comprehension thesis, So if the science comprehension thesis is correct,

622
00:34:16,880 --> 00:34:20,839
Speaker 1: they predict that subjects scoring higher in numeracy quote would

623
00:34:20,840 --> 00:34:23,759
Speaker 1: be more likely to construe the data correctly not only

624
00:34:23,800 --> 00:34:27,360
Speaker 1: when it was consistent with their ideological predispositions, but also

625
00:34:27,760 --> 00:34:31,239
Speaker 1: when it was inconsistent with them, and thus they were

626
00:34:31,520 --> 00:34:36,040
Speaker 1: likely to display less ideological polarization than subjects lower in numeracy.

627
00:34:36,239 --> 00:34:39,080
Speaker 1: In other words, on the science comprehension thesis. If you're

628
00:34:39,120 --> 00:34:43,200
Speaker 1: better at understanding quantitative science, your interpretation of the results

629
00:34:43,239 --> 00:34:46,120
Speaker 1: of the gun band thing should be less affected by

630
00:34:46,160 --> 00:34:49,440
Speaker 1: political bias. And then finally, they have a third hypothesis

631
00:34:49,480 --> 00:34:54,480
Speaker 1: based on the identity protective cognition thesis. Quote, ideological polarization

632
00:34:54,560 --> 00:34:57,800
Speaker 1: in the gun band conditions should be most extreme among

633
00:34:57,880 --> 00:35:02,560
Speaker 1: those highest in numerous E. Under this hypothesis, people high

634
00:35:02,560 --> 00:35:06,480
Speaker 1: and numerous E are not immune from identity protective cognition

635
00:35:06,760 --> 00:35:09,880
Speaker 1: and will, like everyone else, always seek ways to affirm

636
00:35:09,920 --> 00:35:15,200
Speaker 1: their existing political beliefs. But using their NUMEROUSY skills, they

637
00:35:15,200 --> 00:35:19,440
Speaker 1: can use system to thinking to draw correct but counterintuitive

638
00:35:19,480 --> 00:35:23,480
Speaker 1: inferences from the data when it flatters their beliefs, but

639
00:35:23,640 --> 00:35:27,040
Speaker 1: detect that they should skip this and use quick heuristics

640
00:35:27,080 --> 00:35:31,560
Speaker 1: to arrive at the wrong answer when that flatters their beliefs.

641
00:35:31,640 --> 00:35:35,560
Speaker 1: So quote, if high NUMEROUSY subjects use their special cognitive

642
00:35:35,560 --> 00:35:41,280
Speaker 1: advantage selectively only when doing so generates an ideologically congenial answer,

643
00:35:41,400 --> 00:35:45,120
Speaker 1: but not otherwise, they will end up even more polarized

644
00:35:45,160 --> 00:35:48,600
Speaker 1: than their low numerous EY counterparts. And so here we

645
00:35:48,600 --> 00:35:51,560
Speaker 1: get to the results. So first thing worth noting is

646
00:35:51,600 --> 00:35:55,440
Speaker 1: that detecting covariance is difficult if you're not experienced in it,

647
00:35:55,719 --> 00:35:59,680
Speaker 1: so across all test conditions, most people got the answers wrong.

648
00:36:00,360 --> 00:36:04,440
Speaker 1: All test conditions combined, fifty nine percent of subjects supplied

649
00:36:04,440 --> 00:36:07,440
Speaker 1: the incorrect answer uh. And this is probably because if

650
00:36:07,440 --> 00:36:09,439
Speaker 1: you just look at the numbers and use a quick

651
00:36:09,480 --> 00:36:12,440
Speaker 1: heuristic or system one thinking you're likely to draw the

652
00:36:12,440 --> 00:36:15,120
Speaker 1: opposite of the correct conclusion, you'd actually have to do

653
00:36:15,239 --> 00:36:17,880
Speaker 1: the math and compare some ratios to come up with

654
00:36:17,880 --> 00:36:21,920
Speaker 1: the correct answer. But the results found hypothesis one, which

655
00:36:22,000 --> 00:36:24,200
Speaker 1: was that if you're high in numerous E you're you've

656
00:36:24,239 --> 00:36:27,160
Speaker 1: got a better chance of getting the skin rash results correct.

657
00:36:27,440 --> 00:36:30,239
Speaker 1: That was supported by the data. The better yard at numeroucy,

658
00:36:30,320 --> 00:36:33,359
Speaker 1: the more likely you are to draw correct inferences from

659
00:36:33,360 --> 00:36:36,759
Speaker 1: politically neutral data, though most people were not very good

660
00:36:36,760 --> 00:36:40,960
Speaker 1: at this um hypothesis too, and which would be consistent

661
00:36:41,000 --> 00:36:44,520
Speaker 1: with the scientific comprehension thesis that people high in numeracy

662
00:36:44,760 --> 00:36:48,319
Speaker 1: will show less polarization on the gun band condition, this

663
00:36:48,480 --> 00:36:52,960
Speaker 1: was not supported by the data. Conversely, hypothesis three was

664
00:36:53,040 --> 00:36:55,360
Speaker 1: supported by the data, and and that one was that

665
00:36:55,400 --> 00:36:59,880
Speaker 1: people with high NUMEROUSY skills will show even more ideologically

666
00:37:00,000 --> 00:37:03,240
Speaker 1: holarized judgments about the results in the gun band condition.

667
00:37:03,600 --> 00:37:06,160
Speaker 1: And so what the authors conclude is that high numerous

668
00:37:06,200 --> 00:37:10,880
Speaker 1: E partisans use their skills selectively. When a laborious system

669
00:37:10,960 --> 00:37:14,399
Speaker 1: to calculation will yield results that are flattering to your

670
00:37:14,440 --> 00:37:17,600
Speaker 1: political point of view, you'll do it. But when it

671
00:37:17,760 --> 00:37:20,640
Speaker 1: threatens your point of view, you'll skip it. You'll skip

672
00:37:20,680 --> 00:37:25,800
Speaker 1: system to reasoning and just draw incorrect heuristic conclusions. Uh.

673
00:37:25,840 --> 00:37:28,399
Speaker 1: And so a few takeaways here I think we should

674
00:37:28,440 --> 00:37:31,360
Speaker 1: think about while we're discussing this. One is that I

675
00:37:31,400 --> 00:37:34,640
Speaker 1: should stress this study doesn't show that science education and

676
00:37:34,680 --> 00:37:38,680
Speaker 1: science communication efforts are pointless or bad or anything like that.

677
00:37:39,239 --> 00:37:43,160
Speaker 1: Science comprehension skills, including numerous E are crucial for answering

678
00:37:43,200 --> 00:37:46,560
Speaker 1: all kinds of questions accurately when a system one heuristic

679
00:37:46,600 --> 00:37:48,920
Speaker 1: model would cause you to come to the wrong conclusion.

680
00:37:49,160 --> 00:37:51,360
Speaker 1: So it's kind of the baseline, right, you've got to

681
00:37:51,440 --> 00:37:56,000
Speaker 1: have scientific comprehension skills. But if these results are valid,

682
00:37:56,080 --> 00:37:59,040
Speaker 1: what they do show is that science comprehension skills are

683
00:37:59,080 --> 00:38:03,400
Speaker 1: not necessarily protection against getting politically charged science questions wrong

684
00:38:03,719 --> 00:38:08,160
Speaker 1: because the brain uses its science comprehension skills selectively it's

685
00:38:08,200 --> 00:38:10,400
Speaker 1: more likely to bring out the big guns if they

686
00:38:10,440 --> 00:38:13,360
Speaker 1: will help it protect its identity, and it's more likely

687
00:38:13,400 --> 00:38:17,080
Speaker 1: to surrender to heuristic thinking if that's what protects your identity.

688
00:38:17,520 --> 00:38:20,359
Speaker 1: Another way of putting it, political identity can make you

689
00:38:20,480 --> 00:38:24,080
Speaker 1: selectively bad at math, even if you're normally good at math.

690
00:38:24,800 --> 00:38:26,520
Speaker 1: And so in this week, this is where we get

691
00:38:26,520 --> 00:38:28,880
Speaker 1: into some of these areas where we see, say, you know,

692
00:38:28,920 --> 00:38:33,680
Speaker 1: an individual um that that has a scientific background or

693
00:38:33,880 --> 00:38:36,920
Speaker 1: PhD or what have you, that you see showing up

694
00:38:37,160 --> 00:38:40,480
Speaker 1: on the side of say climate change deniers, or or

695
00:38:40,520 --> 00:38:44,200
Speaker 1: even something more ridiculous like a like a like a

696
00:38:44,200 --> 00:38:47,719
Speaker 1: flat earth belief system. Yeah, I almost never see it

697
00:38:47,760 --> 00:38:49,759
Speaker 1: with flat earth beliefs, but you do see it with

698
00:38:49,880 --> 00:38:53,320
Speaker 1: climate change, with definitely what you notice with climate changes

699
00:38:53,480 --> 00:38:57,239
Speaker 1: that like um Sometimes people come up with lists of

700
00:38:57,280 --> 00:39:00,440
Speaker 1: scientists who don't agree with the consensus on climate change,

701
00:39:00,480 --> 00:39:03,719
Speaker 1: and usually almost none of them work in fields relevant

702
00:39:03,719 --> 00:39:06,520
Speaker 1: to climate change. Uh, you know, they're they're not like

703
00:39:06,640 --> 00:39:09,880
Speaker 1: climate scientists. I'm not saying there are no climate scientists

704
00:39:09,880 --> 00:39:12,520
Speaker 1: that disagree, but they're almost none. They tend to be

705
00:39:12,760 --> 00:39:15,400
Speaker 1: somebody like one example that often comes up, and I

706
00:39:15,719 --> 00:39:18,839
Speaker 1: honestly can't remember to what extent his disagreement is with it.

707
00:39:19,120 --> 00:39:22,080
Speaker 1: But say, Freeman Dyson is an individual of note who

708
00:39:22,160 --> 00:39:26,400
Speaker 1: has at least at times cast some doubt in the area,

709
00:39:26,440 --> 00:39:29,680
Speaker 1: but is brilliant. Is Freeman Dyson isn't was? He's not

710
00:39:29,719 --> 00:39:32,360
Speaker 1: a climate scientist, right, It's it tends to be people

711
00:39:32,400 --> 00:39:35,879
Speaker 1: commenting outside their area of expertise, and yet they still

712
00:39:35,920 --> 00:39:38,480
Speaker 1: have the aura of credibility because it's like, well, these

713
00:39:38,480 --> 00:39:41,600
Speaker 1: are smart people, they're scientists, right. Uh So, you know,

714
00:39:41,680 --> 00:39:44,160
Speaker 1: you'll see a list of scientists who don't accept the

715
00:39:44,719 --> 00:39:47,960
Speaker 1: consensus on climate change, and they might be like petroleum

716
00:39:48,000 --> 00:39:50,480
Speaker 1: engineers and stuff like that. You know, so it's like,

717
00:39:51,080 --> 00:39:54,239
Speaker 1: not like petroleum engineers aren't smart. I mean, I'm sure

718
00:39:54,280 --> 00:39:56,480
Speaker 1: all all these people are very smart people. But it's

719
00:39:56,480 --> 00:40:00,520
Speaker 1: just that having scientific comprehension skills does not tech to

720
00:40:00,560 --> 00:40:06,400
Speaker 1: you against arriving at malinformed bad conclusions that support your identity. Now,

721
00:40:06,400 --> 00:40:08,680
Speaker 1: of course, one of the tools and seconds tool kit

722
00:40:08,800 --> 00:40:12,239
Speaker 1: I had to do with replication. Yes, uh so that's

723
00:40:12,239 --> 00:40:14,920
Speaker 1: always a big question. And in fact, I found one

724
00:40:14,960 --> 00:40:17,520
Speaker 1: thing that I wanted to explore real quickly. If you

725
00:40:17,560 --> 00:40:21,360
Speaker 1: follow psychology research and you saw something about motivated numeracy

726
00:40:21,440 --> 00:40:25,240
Speaker 1: failing replication in a recent study. I think that's probably

727
00:40:25,280 --> 00:40:28,960
Speaker 1: a reference to a conference paper draft presented in seventeen

728
00:40:29,400 --> 00:40:31,960
Speaker 1: that claimed, as part of its findings to fail to

729
00:40:32,040 --> 00:40:35,840
Speaker 1: replicate the motivated numeracy effect. And then Dan Kahan and

730
00:40:35,840 --> 00:40:38,279
Speaker 1: Ellen Peters, two of the original authors of the first

731
00:40:38,320 --> 00:40:42,200
Speaker 1: paper we were talking about, in response, defended their paper

732
00:40:42,239 --> 00:40:45,240
Speaker 1: as best as I can tell, quite successfully by pointing

733
00:40:45,239 --> 00:40:48,360
Speaker 1: out that the study that failed to replicate the motivated

734
00:40:48,400 --> 00:40:52,000
Speaker 1: reasoning effect UH number one had a very small sample

735
00:40:52,040 --> 00:40:55,759
Speaker 1: size and fifty five, and was ideologically homogeneous. It was

736
00:40:55,920 --> 00:41:00,359
Speaker 1: basically liberal, and in a paper called rumors, the non

737
00:41:00,400 --> 00:41:05,120
Speaker 1: replication of the motivated numeroucy effect are greatly exaggerated, uh

738
00:41:05,360 --> 00:41:09,520
Speaker 1: Kahan and Peters. They so they argue against this supposed

739
00:41:09,520 --> 00:41:12,879
Speaker 1: failed replication, and they also present the results of their

740
00:41:12,920 --> 00:41:16,120
Speaker 1: own replication attempt with a with a sample size of

741
00:41:16,280 --> 00:41:20,600
Speaker 1: fife in which they did successfully replicate the findings of

742
00:41:20,600 --> 00:41:23,880
Speaker 1: the original very closely. And so, as far as I

743
00:41:23,880 --> 00:41:28,279
Speaker 1: can tell, motivated numerousy through identity through identity protective cognition

744
00:41:28,719 --> 00:41:31,959
Speaker 1: is still pretty solid. It looks solid to me. And also,

745
00:41:32,000 --> 00:41:33,560
Speaker 1: as far as I can tell, that's not just me

746
00:41:33,719 --> 00:41:36,759
Speaker 1: defending a cherished belief that's important to my identity through

747
00:41:36,800 --> 00:41:40,480
Speaker 1: motivated judgment, because in fact, I find I strongly dislike

748
00:41:40,640 --> 00:41:44,800
Speaker 1: the idea of identity protective cognition. I think I would

749
00:41:44,840 --> 00:41:46,880
Speaker 1: much rather live in the world of so many of

750
00:41:46,920 --> 00:41:51,120
Speaker 1: our anthropogenic climate change accepting peers, and where, you know,

751
00:41:51,160 --> 00:41:53,440
Speaker 1: it's the world where if you could just educate people

752
00:41:53,600 --> 00:41:57,200
Speaker 1: enough with better science literacy skills, these dead end public

753
00:41:57,239 --> 00:42:01,040
Speaker 1: disputes over pretty solid empirical science could be resolved. What

754
00:42:01,120 --> 00:42:05,120
Speaker 1: means you could essentially win an argument over these issues

755
00:42:05,160 --> 00:42:08,279
Speaker 1: by presenting facts, presenting data. And that's how a lot

756
00:42:08,320 --> 00:42:10,640
Speaker 1: of these you know, like science people want it to

757
00:42:10,680 --> 00:42:13,520
Speaker 1: be like that, right, science people want to say, well

758
00:42:13,600 --> 00:42:15,839
Speaker 1: I can, I'll just bring more evidence. You'll show up

759
00:42:15,840 --> 00:42:19,680
Speaker 1: with even more references next time, and that'll get them.

760
00:42:19,680 --> 00:42:21,920
Speaker 1: But I'm afraid the evidence seems to be coming in

761
00:42:21,960 --> 00:42:25,200
Speaker 1: that it doesn't necessarily work that way. And maybe, and

762
00:42:25,560 --> 00:42:27,279
Speaker 1: you know, we shouldn't be all or nothing in the

763
00:42:27,280 --> 00:42:30,040
Speaker 1: way we talk about things. Different different types of appeals

764
00:42:30,040 --> 00:42:32,960
Speaker 1: will work with different people, but on average that does

765
00:42:33,000 --> 00:42:35,799
Speaker 1: not appear to be how people work. All right, Well,

766
00:42:35,840 --> 00:42:37,279
Speaker 1: on that note, we're going to take a break, and

767
00:42:37,280 --> 00:42:39,640
Speaker 1: when we come back, we're gonna expand on the the

768
00:42:39,680 --> 00:42:42,640
Speaker 1: concept a little bit and talk about what can possibly

769
00:42:42,680 --> 00:42:49,640
Speaker 1: be done and talk about Scott Steiner. Thank, alright, we're back. So, Joe,

770
00:42:49,640 --> 00:42:52,680
Speaker 1: were you familiar with the Scott Steiner before I mentioned

771
00:42:52,719 --> 00:42:55,799
Speaker 1: him to you? I was not tremendously familiar. But you

772
00:42:55,840 --> 00:42:59,640
Speaker 1: sent me the best video I've seen all week. Yes,

773
00:42:59,719 --> 00:43:02,480
Speaker 1: So this was a video, and this is readily available

774
00:43:02,880 --> 00:43:06,000
Speaker 1: online because it kind of went viral and became its

775
00:43:06,040 --> 00:43:10,760
Speaker 1: own meme. But it's a video of professional wrestler Scott Steiner,

776
00:43:11,239 --> 00:43:14,520
Speaker 1: a k A. Big Papa Pump. Okay, Yeah, well I

777
00:43:14,760 --> 00:43:16,680
Speaker 1: think I knew him better by that name. Yeah that

778
00:43:16,760 --> 00:43:19,680
Speaker 1: was Yeah, that was a moniker he adopted at one point. Uh,

779
00:43:19,719 --> 00:43:22,840
Speaker 1: And it's This is a clip from a wrestling promotion

780
00:43:22,880 --> 00:43:25,200
Speaker 1: that was known in two thousand eight is t n A.

781
00:43:25,440 --> 00:43:28,919
Speaker 1: The promotion is now called Impact, and Steiner launched into

782
00:43:28,920 --> 00:43:32,560
Speaker 1: a backstage promo that, in typical pro wrestling fashion, is

783
00:43:32,600 --> 00:43:37,200
Speaker 1: all shouty and laced in macho pravada, but in a twist,

784
00:43:37,440 --> 00:43:42,040
Speaker 1: it's also full of math and statistics. So he makes

785
00:43:42,040 --> 00:43:45,040
Speaker 1: the highly rigorous yes yes, and in this particular promo,

786
00:43:45,160 --> 00:43:47,080
Speaker 1: He makes the following claims, I'm just gonna roll through

787
00:43:47,080 --> 00:43:50,520
Speaker 1: these in a normal human voice. Okay, So he points

788
00:43:50,520 --> 00:43:52,879
Speaker 1: out that normally a wrestler has a fifty fifty chance

789
00:43:52,880 --> 00:43:57,320
Speaker 1: of winning a match, all else being equal. Sure, okay, yeah,

790
00:43:57,320 --> 00:44:01,960
Speaker 1: but given his uh big Papa pump superior genetics, um,

791
00:44:02,000 --> 00:44:05,680
Speaker 1: his opponent Samoa Joe only has a chance of winning.

792
00:44:06,719 --> 00:44:08,440
Speaker 1: But it's a three way match as well, and it

793
00:44:08,480 --> 00:44:12,280
Speaker 1: involves Kurt Angle. So each participant here has a thirty

794
00:44:12,280 --> 00:44:15,279
Speaker 1: three and a third percent chance of winning. But he

795
00:44:15,480 --> 00:44:19,040
Speaker 1: but since Kurt Angle, according to to Steiner, knows that

796
00:44:19,120 --> 00:44:23,280
Speaker 1: he cannot win, he won't try. Uh So Steiner presses

797
00:44:23,320 --> 00:44:26,879
Speaker 1: the following point quote, So, Samoa Joe, you take your

798
00:44:26,920 --> 00:44:29,959
Speaker 1: thirty three and one third chance minus my twenty percent chance,

799
00:44:30,000 --> 00:44:32,719
Speaker 1: and you have an eight and one third chance of

800
00:44:32,760 --> 00:44:35,880
Speaker 1: winning at Sacrifice, sacrifice being the name of the pro

801
00:44:35,920 --> 00:44:39,560
Speaker 1: wrestling event. But when you take my seventy five percent

802
00:44:39,640 --> 00:44:42,000
Speaker 1: chance of winning, if we were to go one on

803
00:44:42,000 --> 00:44:46,080
Speaker 1: one and then add sixty six and two thirds per cents,

804
00:44:46,120 --> 00:44:49,080
Speaker 1: I got one and forty one and two thirds chance

805
00:44:49,120 --> 00:44:52,879
Speaker 1: of winning at Sacrifice. See Samoa Joe. The numbers don't

806
00:44:52,920 --> 00:44:56,879
Speaker 1: lie and they spell disaster for you at Sacrifice? Did

807
00:44:56,880 --> 00:44:59,759
Speaker 1: you watch Sacrifice? Were you there? I did not? I

808
00:45:00,120 --> 00:45:02,439
Speaker 1: not there. I did watch some clips from it looks

809
00:45:02,440 --> 00:45:06,279
Speaker 1: like it was, you know, pretty hard hitting match. Interestingly enough,

810
00:45:06,560 --> 00:45:11,640
Speaker 1: um Samoa Joe one oh Man. However, Kurt Angle was

811
00:45:11,680 --> 00:45:13,920
Speaker 1: injured and had to be replaced by another wrestler, so

812
00:45:14,000 --> 00:45:17,640
Speaker 1: one assumes that would have changed the equation somewhat despite

813
00:45:17,680 --> 00:45:23,279
Speaker 1: having a negative forty one chance of winning one. So yeah,

814
00:45:23,640 --> 00:45:27,279
Speaker 1: but as Steiner says, the numbers don't lie or do

815
00:45:27,320 --> 00:45:31,120
Speaker 1: that is this admittedly ridiculous example? Is this is this

816
00:45:31,160 --> 00:45:34,280
Speaker 1: Scott Steiner falling prey to a lack of understanding regarding

817
00:45:34,680 --> 00:45:38,040
Speaker 1: numeracy or is it motivated numeracy? Is he just so

818
00:45:38,160 --> 00:45:41,400
Speaker 1: highly motivated by his dislike of Samoa Joe and his

819
00:45:41,480 --> 00:45:43,880
Speaker 1: belief in his own superior genetics that he just so

820
00:45:44,320 --> 00:45:47,680
Speaker 1: uh you know, readily mishandles them. That might be a

821
00:45:47,680 --> 00:45:52,560
Speaker 1: better example of a mathematical incarnation of the Dunning Krueger effect. Sure,

822
00:45:52,680 --> 00:45:54,960
Speaker 1: but this is where you believe that you have more

823
00:45:54,960 --> 00:45:59,359
Speaker 1: fluency in a particular area than you actually do. Yes,

824
00:46:00,080 --> 00:46:02,120
Speaker 1: the we we should we should get into it at

825
00:46:02,120 --> 00:46:04,719
Speaker 1: one time the Dunning Kruger effect because there's a I know,

826
00:46:04,920 --> 00:46:07,480
Speaker 1: there is a more nuanced understanding of it than you

827
00:46:07,560 --> 00:46:10,560
Speaker 1: usually see when it's deployed in the media and stuff.

828
00:46:10,560 --> 00:46:13,400
Speaker 1: But the basic idea is that with the Dunning Kruger effect,

829
00:46:13,480 --> 00:46:16,520
Speaker 1: if you are not very good within a skill set

830
00:46:16,600 --> 00:46:19,760
Speaker 1: or within a knowledge domain, you also lack the meta

831
00:46:19,760 --> 00:46:25,040
Speaker 1: cognitive capacities to understand what would make somebody good at it. Thus,

832
00:46:25,120 --> 00:46:29,160
Speaker 1: you fail to grasp your own shortcomings. And thus people

833
00:46:29,200 --> 00:46:32,239
Speaker 1: who are very low skilled or very low knowledge and

834
00:46:32,280 --> 00:46:36,239
Speaker 1: a certain domain tend to vastly overestimate their skills or

835
00:46:36,280 --> 00:46:39,000
Speaker 1: their knowledge because they can't know they can't know what

836
00:46:39,080 --> 00:46:41,440
Speaker 1: they don't know. All right, Well, I realized that this

837
00:46:41,480 --> 00:46:45,400
Speaker 1: example was was maybe more entertaining than helpful. Still my

838
00:46:45,440 --> 00:46:48,880
Speaker 1: only opportunity to really work Scott Steiner into an episode.

839
00:46:48,880 --> 00:46:51,319
Speaker 1: Come on, we've been plowing through a psychology paper. We've

840
00:46:51,320 --> 00:46:54,560
Speaker 1: gotta have a little wrestling to lighten the load. Alright, Well, well,

841
00:46:54,560 --> 00:46:56,879
Speaker 1: now that we've lightened the load, let's let's come back

842
00:46:56,920 --> 00:47:00,920
Speaker 1: to like the big remaining question you have. If motivated numeracy,

843
00:47:01,200 --> 00:47:04,839
Speaker 1: uh is the key thing that's happening here? If this

844
00:47:05,080 --> 00:47:07,920
Speaker 1: is the the enemy, the threat, then how do we

845
00:47:08,040 --> 00:47:11,200
Speaker 1: deal with Yeah? Like, what what can be done? And so?

846
00:47:11,480 --> 00:47:13,600
Speaker 1: One thing I would take away from this research is

847
00:47:13,640 --> 00:47:17,719
Speaker 1: that good science education and science communication are necessary, but

848
00:47:17,920 --> 00:47:22,239
Speaker 1: not sufficient. Necessary but not sufficient to produce a correctly

849
00:47:22,280 --> 00:47:26,040
Speaker 1: informed citizen. Read. You can't have people making good judgments

850
00:47:26,080 --> 00:47:29,840
Speaker 1: without understanding the facts. But the better they understand the facts,

851
00:47:29,920 --> 00:47:33,440
Speaker 1: the more they'll use their understanding to support their identity

852
00:47:33,520 --> 00:47:37,080
Speaker 1: derived point of view. So Kahan and others proposed that

853
00:47:37,160 --> 00:47:40,799
Speaker 1: the way to beat motivated reasoning is not necessarily to

854
00:47:40,960 --> 00:47:45,240
Speaker 1: improve the reasoning, but to remove the motivation. To remove

855
00:47:45,400 --> 00:47:48,560
Speaker 1: the motivation, I like that. That reminds me so much

856
00:47:48,719 --> 00:47:52,719
Speaker 1: of Krishna's words to Argina in the Hindu epic the

857
00:47:52,719 --> 00:47:56,000
Speaker 1: Baka vad Gita. Uh oh yeah, yeah, yeah, if if,

858
00:47:56,320 --> 00:47:58,160
Speaker 1: if I may, I'd like to read, you know, because

859
00:47:58,320 --> 00:48:01,000
Speaker 1: having come from the quoting Scott's Ironer, I obviously want

860
00:48:01,000 --> 00:48:04,520
Speaker 1: to move on the other high literature. Yes, uh so

861
00:48:04,760 --> 00:48:08,160
Speaker 1: this is these are the words of Krishna, that man

862
00:48:08,160 --> 00:48:11,759
Speaker 1: alone is wise, who keeps the mastery of himself. If

863
00:48:11,800 --> 00:48:16,319
Speaker 1: one ponders on objects of the sense, there springs attraction

864
00:48:16,560 --> 00:48:21,920
Speaker 1: from attraction grows desire, Desire flames to fierce passion, Passion

865
00:48:22,040 --> 00:48:27,080
Speaker 1: breeds recklessness. Then the memory, all betrayed, lets noble purpose

866
00:48:27,160 --> 00:48:31,120
Speaker 1: go and SAPs the mind till purpose, mind and man

867
00:48:31,160 --> 00:48:35,040
Speaker 1: are all undone. But if one deals with objects of

868
00:48:35,080 --> 00:48:38,640
Speaker 1: the sense, not loving and not hating, making them serve

869
00:48:38,760 --> 00:48:42,640
Speaker 1: his free soul, which rests serenely, Lord Low, such a

870
00:48:42,719 --> 00:48:46,960
Speaker 1: man comes to tranquility, and out of that tranquility shall

871
00:48:47,080 --> 00:48:50,680
Speaker 1: rise the end and healing of his earthly pains. Since

872
00:48:50,760 --> 00:48:53,960
Speaker 1: the will governed sets the soul at peace. Oh, I'd

873
00:48:53,960 --> 00:48:56,319
Speaker 1: say the will governed as much as you're said, than done,

874
00:48:56,360 --> 00:48:58,600
Speaker 1: isn't it. Oh? Yeah, I mean that's why we've clearly

875
00:48:58,600 --> 00:49:00,560
Speaker 1: we're still struggling with it. And you know, and I

876
00:49:00,560 --> 00:49:02,400
Speaker 1: don't want to, you know, obviously this is a this

877
00:49:02,480 --> 00:49:07,200
Speaker 1: is a work of immense literary significance and in deep philosophy.

878
00:49:07,239 --> 00:49:10,240
Speaker 1: But but yeah, this idea of of acting without passion

879
00:49:10,360 --> 00:49:14,440
Speaker 1: seems to to line up reasonably well with this idea

880
00:49:14,680 --> 00:49:20,279
Speaker 1: of tackling various um uh, you know, innumerable um problems

881
00:49:20,600 --> 00:49:24,280
Speaker 1: without bringing in this political motivation. Yeah, though, of course

882
00:49:24,840 --> 00:49:27,000
Speaker 1: it seems very unfortunate that I think a lot of

883
00:49:27,000 --> 00:49:30,399
Speaker 1: this motivation comes in unconsciously right, because I mean we

884
00:49:30,400 --> 00:49:32,279
Speaker 1: we I guess we haven't really addressed this so far.

885
00:49:32,360 --> 00:49:35,480
Speaker 1: But you have to assume that people are not generally

886
00:49:35,520 --> 00:49:37,640
Speaker 1: and you probably know from your own experience at least

887
00:49:37,640 --> 00:49:40,759
Speaker 1: if it's like mine, they're not generally thinking like, Okay,

888
00:49:40,800 --> 00:49:43,640
Speaker 1: how should I trick myself right now to come to

889
00:49:43,719 --> 00:49:47,400
Speaker 1: the wrong conclusion because it would be socially acceptable. It

890
00:49:47,480 --> 00:49:50,360
Speaker 1: doesn't feel like that to think about political issues that

891
00:49:50,440 --> 00:49:54,320
Speaker 1: are you know, are empirical issues that are politically relevant. Um,

892
00:49:54,360 --> 00:49:56,239
Speaker 1: it just feels like, well, I'm just trying to figure

893
00:49:56,280 --> 00:49:58,520
Speaker 1: out what's right, but obviously I must be doing this

894
00:49:58,560 --> 00:50:01,160
Speaker 1: at least sometimes Yeah, which just kind of where we're

895
00:50:01,200 --> 00:50:03,919
Speaker 1: often just we're swimming through life. We're not necessarily thinking

896
00:50:03,960 --> 00:50:06,759
Speaker 1: about the individual strokes. You know, it all kind of

897
00:50:06,800 --> 00:50:09,160
Speaker 1: comes together and we end up making these mistakes and

898
00:50:09,200 --> 00:50:12,160
Speaker 1: cognition and to reemphasize what the authors of that original

899
00:50:12,200 --> 00:50:15,440
Speaker 1: paper we're talking about, I mean, in a way, this

900
00:50:15,680 --> 00:50:18,960
Speaker 1: is rational. It's rational in a perverse way, not in

901
00:50:19,000 --> 00:50:21,480
Speaker 1: a good way that ultimately creates the most benefit, but

902
00:50:21,520 --> 00:50:24,520
Speaker 1: in a kind of short term perversity. It is rational.

903
00:50:24,560 --> 00:50:28,200
Speaker 1: Like you will sometimes hear people talking about or lamenting

904
00:50:28,239 --> 00:50:31,040
Speaker 1: in politics, how others just won't do what's rational. But

905
00:50:31,200 --> 00:50:35,480
Speaker 1: given a certain interpretation of rational self interest, this irrational

906
00:50:35,560 --> 00:50:40,360
Speaker 1: relationship with empirical questions makes perfect sense. The author's right quote,

907
00:50:40,640 --> 00:50:43,480
Speaker 1: what any individual member of the public thinks about the

908
00:50:43,480 --> 00:50:47,160
Speaker 1: reality of climate change, the hazards of nuclear waste disposal,

909
00:50:47,440 --> 00:50:51,560
Speaker 1: the efficacy of gun control is too inconsequential to influence

910
00:50:51,640 --> 00:50:54,279
Speaker 1: the risk that that person, or anyone he or she

911
00:50:54,400 --> 00:50:58,600
Speaker 1: cares about faces. Nevertheless, given what positions on these issues

912
00:50:58,640 --> 00:51:02,520
Speaker 1: signify about a person's finding commitments, forming a belief at

913
00:51:02,520 --> 00:51:05,720
Speaker 1: odds with the one that predominates on it within important

914
00:51:05,719 --> 00:51:08,600
Speaker 1: affinity groups of which such a person as a member

915
00:51:08,800 --> 00:51:11,360
Speaker 1: could expose him or her to an array of highly

916
00:51:11,440 --> 00:51:17,040
Speaker 1: unpleasant consequences. Thus, like, we know that it's radically consequential,

917
00:51:17,160 --> 00:51:21,040
Speaker 1: what in general public policy is about climate change or

918
00:51:21,080 --> 00:51:24,480
Speaker 1: gun policy or something. You know, these are hugely important questions,

919
00:51:24,840 --> 00:51:29,960
Speaker 1: but the impact of one individual person's opinion feels small

920
00:51:30,080 --> 00:51:34,439
Speaker 1: enough that you basically the consequences of that are almost irrelevant.

921
00:51:34,880 --> 00:51:37,680
Speaker 1: It's like, what's really relevant is how is this affecting

922
00:51:37,680 --> 00:51:39,480
Speaker 1: me in my day to day and how it's primarily

923
00:51:39,520 --> 00:51:41,760
Speaker 1: affecting you in your day to day is the social

924
00:51:41,760 --> 00:51:45,279
Speaker 1: consequences of the beliefs you express. But obviously that's not

925
00:51:45,360 --> 00:51:48,640
Speaker 1: what we want, right, Like, we want everybody making rational decisions,

926
00:51:48,680 --> 00:51:52,160
Speaker 1: having correct empirical information to reason from. Of course they're

927
00:51:52,200 --> 00:51:54,759
Speaker 1: still gonna argue about political values, but at least having

928
00:51:54,760 --> 00:51:58,480
Speaker 1: everybody except the same set of correct facts when correct

929
00:51:58,520 --> 00:52:01,319
Speaker 1: facts are on the table, right, I mean, a lot

930
00:52:01,320 --> 00:52:03,200
Speaker 1: of it comes kind of comes down to the fact

931
00:52:03,200 --> 00:52:07,080
Speaker 1: that we are a short sighted species that can, you know,

932
00:52:07,160 --> 00:52:10,359
Speaker 1: barely see beyond our own horizon. But but we are

933
00:52:10,400 --> 00:52:13,840
Speaker 1: attempting to see beyond that horizon. We are trying to

934
00:52:13,840 --> 00:52:17,040
Speaker 1: to to maintain a world or create a world that

935
00:52:17,080 --> 00:52:20,120
Speaker 1: can be sustained in some fashion. We you know that

936
00:52:20,280 --> 00:52:23,439
Speaker 1: the the old addage, of course, is making thinking about

937
00:52:23,480 --> 00:52:27,480
Speaker 1: your children and your grandchildren when when you're making decisions

938
00:52:27,719 --> 00:52:31,640
Speaker 1: such as these. But historically it's not the sort of

939
00:52:31,680 --> 00:52:34,839
Speaker 1: thing that we're great at as a species. And yeah,

940
00:52:34,880 --> 00:52:38,239
Speaker 1: and so it's clearly not enough just to tell people like, well,

941
00:52:38,360 --> 00:52:41,000
Speaker 1: here's a problem with how you're probably thinking. You're probably

942
00:52:41,040 --> 00:52:44,000
Speaker 1: doing identity protective cognition, and you need to stop it.

943
00:52:44,480 --> 00:52:47,080
Speaker 1: You know that that's just obviously not going to work,

944
00:52:47,120 --> 00:52:49,160
Speaker 1: as you're just asking somebody to shut their mind their

945
00:52:49,200 --> 00:52:51,360
Speaker 1: ears off, like like, oh, yeah, they're really going to

946
00:52:51,440 --> 00:52:53,520
Speaker 1: listen to you now, buddy. Yeah, I mean, and they're

947
00:52:53,560 --> 00:52:56,040
Speaker 1: they're probably not even doing it on purpose, right, I mean,

948
00:52:56,160 --> 00:52:58,359
Speaker 1: you and I are doing it sometimes we're not doing

949
00:52:58,360 --> 00:53:01,279
Speaker 1: it on purpose. The people who do this, they're not

950
00:53:01,360 --> 00:53:05,040
Speaker 1: doing it out of a will to deceive themselves. Is

951
00:53:05,080 --> 00:53:08,280
Speaker 1: just happening as part of what the brain does, even unconsciously.

952
00:53:08,880 --> 00:53:12,600
Speaker 1: So the question is, could you do something external? Could

953
00:53:12,640 --> 00:53:15,759
Speaker 1: you create a state of affairs that would change the

954
00:53:15,800 --> 00:53:18,840
Speaker 1: incentive structure? Do what the author said and somehow change

955
00:53:18,920 --> 00:53:22,960
Speaker 1: the motivation. If you can't change the reasoning and motivated reasoning,

956
00:53:23,160 --> 00:53:26,319
Speaker 1: maybe you can change the motivation and motivated reasoning. So

957
00:53:26,520 --> 00:53:30,640
Speaker 1: here's one thing I'm thinking about most politically relevant. Numerous

958
00:53:30,680 --> 00:53:34,439
Speaker 1: E is basically recreational, right, Like you need to get

959
00:53:34,440 --> 00:53:37,759
Speaker 1: the numbers right when you're calculating your bank balance. But

960
00:53:37,800 --> 00:53:39,799
Speaker 1: if you get the numbers wrong when you're talking about

961
00:53:39,840 --> 00:53:44,759
Speaker 1: gun control or climate change, there's no immediately detectable consequence

962
00:53:44,800 --> 00:53:46,319
Speaker 1: to you, as long as you get them wrong in

963
00:53:46,320 --> 00:53:49,359
Speaker 1: the way that your social group approves of and this

964
00:53:49,480 --> 00:53:52,880
Speaker 1: is not true of every person in every context. For example,

965
00:53:53,120 --> 00:53:57,560
Speaker 1: why does scientists working within their own fields uh tend

966
00:53:57,800 --> 00:54:00,400
Speaker 1: usually to get the numbers right? Of course, not always,

967
00:54:00,480 --> 00:54:04,280
Speaker 1: but usually, like, regardless of whatever their political opinions are,

968
00:54:04,480 --> 00:54:07,400
Speaker 1: if they're doing work within their field, they tend to

969
00:54:07,440 --> 00:54:10,719
Speaker 1: get it right most of the time. Well, because they're

970
00:54:10,719 --> 00:54:12,759
Speaker 1: gonna be other scientists that are going to be attempting

971
00:54:12,800 --> 00:54:15,799
Speaker 1: to uh to perform the same experiment to see if

972
00:54:15,800 --> 00:54:18,400
Speaker 1: they get the same results. There can be people reading it,

973
00:54:18,440 --> 00:54:20,319
Speaker 1: and if they see the error they are going to

974
00:54:20,880 --> 00:54:22,960
Speaker 1: they are going to correct them on it. I mean,

975
00:54:23,000 --> 00:54:25,799
Speaker 1: that's part of the process. Yeah, there's a strong incentive

976
00:54:25,840 --> 00:54:28,640
Speaker 1: to get the numbers right. Failed numeracy in your own

977
00:54:28,680 --> 00:54:32,520
Speaker 1: published research is potentially a major blow to your credibility,

978
00:54:32,560 --> 00:54:35,600
Speaker 1: to your career, to your standing among your professional peers

979
00:54:35,640 --> 00:54:38,920
Speaker 1: and stuff. So I wonder if it's possible to change

980
00:54:38,960 --> 00:54:42,759
Speaker 1: the incentive structure for non scientists to somehow be more

981
00:54:42,880 --> 00:54:46,120
Speaker 1: like that. This might be just completely impossible fantasy, but

982
00:54:46,719 --> 00:54:48,360
Speaker 1: is there a way you could make it so that

983
00:54:48,480 --> 00:54:52,920
Speaker 1: getting the factually correct answer is incentivized in in in

984
00:54:53,000 --> 00:54:56,920
Speaker 1: the social situations of lay people and arriving at conclusions

985
00:54:56,920 --> 00:54:59,920
Speaker 1: in agreement with your social group is not especially incent

986
00:55:00,040 --> 00:55:03,479
Speaker 1: devised that maybe is that just a totally unrealistic hope

987
00:55:03,520 --> 00:55:06,160
Speaker 1: can human nature change that much? And it does sound

988
00:55:06,200 --> 00:55:08,600
Speaker 1: kind of daunting, like you like, what kind of structure

989
00:55:08,800 --> 00:55:12,360
Speaker 1: system would enforce that? And then how does it know?

990
00:55:12,440 --> 00:55:14,680
Speaker 1: How do you roll it out successfully? And some I'm

991
00:55:14,680 --> 00:55:18,280
Speaker 1: sure some tech billionaire has some kind of nightmarish idea

992
00:55:18,320 --> 00:55:20,160
Speaker 1: for an app that would do that, but in fact

993
00:55:20,160 --> 00:55:23,400
Speaker 1: we just destroy everything. They're all sorts of sort of

994
00:55:23,400 --> 00:55:26,839
Speaker 1: black mirror esque solutions that come to mind, but they

995
00:55:26,840 --> 00:55:29,000
Speaker 1: all have like a black mirror s twist where you

996
00:55:29,040 --> 00:55:31,359
Speaker 1: can see how it would screw things up, or where

997
00:55:31,360 --> 00:55:34,239
Speaker 1: people would essentially rebel against it and say, like, you

998
00:55:34,239 --> 00:55:37,560
Speaker 1: know what, I don't I don't really want Facebook or

999
00:55:37,560 --> 00:55:40,879
Speaker 1: Twitter or what have you coming along and calling me

1000
00:55:41,040 --> 00:55:43,799
Speaker 1: on things that I've said that we're incorrect in the past.

1001
00:55:43,840 --> 00:55:49,120
Speaker 1: Maybe about just why my account instead suffering that embarrassment. Yeah, okay,

1002
00:55:49,120 --> 00:55:51,960
Speaker 1: here's another idea. Maybe some way to fight the motivation

1003
00:55:52,120 --> 00:55:56,719
Speaker 1: perhaps this social support networks and structures that are not

1004
00:55:56,920 --> 00:56:01,400
Speaker 1: dependent on ideological agreement, Like if people really strongly felt

1005
00:56:01,440 --> 00:56:05,160
Speaker 1: confident that their friendships and their work and family relationships

1006
00:56:05,160 --> 00:56:08,280
Speaker 1: were safe and would not suffer at all, no degree

1007
00:56:08,280 --> 00:56:12,960
Speaker 1: of alienation or weakening of relationships from disagreement over political issues.

1008
00:56:13,520 --> 00:56:16,239
Speaker 1: Maybe that would remove the incentive. Does that make sense?

1009
00:56:16,280 --> 00:56:18,440
Speaker 1: Like if people felt that they could disagree with their

1010
00:56:18,480 --> 00:56:21,560
Speaker 1: social group and not not risk anything by doing that,

1011
00:56:22,080 --> 00:56:26,480
Speaker 1: then there would so no longer be a protective motivation

1012
00:56:26,719 --> 00:56:29,560
Speaker 1: in what beliefs you hold. So you saying basically, make

1013
00:56:29,600 --> 00:56:32,919
Speaker 1: our the social groups, making they're more making them more

1014
00:56:33,640 --> 00:56:37,399
Speaker 1: open to free discussion, more accepting of disagreement. I guess.

1015
00:56:37,400 --> 00:56:41,040
Speaker 1: So I mean that at least seems like a possibility. Um.

1016
00:56:41,120 --> 00:56:43,640
Speaker 1: And maybe the way, maybe one way of addressing that

1017
00:56:43,760 --> 00:56:46,400
Speaker 1: is not that you can really change the nature of

1018
00:56:46,480 --> 00:56:49,759
Speaker 1: people's family and friendship relationships like that all that much,

1019
00:56:50,160 --> 00:56:53,040
Speaker 1: but if you could have I don't know, uh, supplemental

1020
00:56:53,200 --> 00:56:57,520
Speaker 1: social dynamics like this may be one thing that community

1021
00:56:57,719 --> 00:57:01,640
Speaker 1: style groups like church congress gations and things like that

1022
00:57:01,680 --> 00:57:05,000
Speaker 1: are useful for, and that they provide sort of like

1023
00:57:05,160 --> 00:57:07,640
Speaker 1: outside of the family and the small friend group, they

1024
00:57:07,640 --> 00:57:12,160
Speaker 1: provide like a backup social situation where you you can

1025
00:57:12,200 --> 00:57:15,600
Speaker 1: retreat if you are feeling down in your other relationships.

1026
00:57:15,640 --> 00:57:18,560
Speaker 1: Though not to say that no certain church congregations have

1027
00:57:18,640 --> 00:57:22,600
Speaker 1: ever made people feel alienated for disagreeing. Oh yeah, I mean,

1028
00:57:22,920 --> 00:57:24,520
Speaker 1: I guess the thing. But you know, I'm just saying,

1029
00:57:24,520 --> 00:57:28,160
Speaker 1: like supplemental social safety nets, I guess right. Well, I

1030
00:57:28,160 --> 00:57:31,000
Speaker 1: could see where different groups, I mean, different social groups

1031
00:57:31,040 --> 00:57:33,880
Speaker 1: can serve as the backup depending on what's happening in

1032
00:57:33,920 --> 00:57:35,720
Speaker 1: your life. I mean, I can imagine a scenario in

1033
00:57:35,840 --> 00:57:39,680
Speaker 1: which certainly a church could be the the fall back,

1034
00:57:40,160 --> 00:57:42,880
Speaker 1: but also scenarios in which work social group could be

1035
00:57:42,920 --> 00:57:45,840
Speaker 1: the fallback or just uh, you know, your your your

1036
00:57:45,880 --> 00:57:48,640
Speaker 1: home life, so your home social your family can at

1037
00:57:48,680 --> 00:57:51,080
Speaker 1: times be the fall You know, well, my friends are

1038
00:57:51,080 --> 00:57:52,840
Speaker 1: mad at me because of what I said about but

1039
00:57:52,880 --> 00:57:56,080
Speaker 1: at least nuclear waste. At least I'm doing okay work.

1040
00:57:57,400 --> 00:57:59,160
Speaker 1: I don't know it. Like one of the idea, it

1041
00:57:59,200 --> 00:58:00,880
Speaker 1: seems one of the it comes to mind here, is

1042
00:58:00,920 --> 00:58:04,760
Speaker 1: like you'd almost want to have just social groups that

1043
00:58:04,880 --> 00:58:09,960
Speaker 1: are more adherent to scientific consensus. I hate to come

1044
00:58:09,960 --> 00:58:14,640
Speaker 1: back to to that, but because ultimately you have if

1045
00:58:14,760 --> 00:58:17,200
Speaker 1: if that is not present in uh, in one of

1046
00:58:17,240 --> 00:58:19,840
Speaker 1: these social structures, I mean, it's there's going to be

1047
00:58:19,840 --> 00:58:24,600
Speaker 1: a high possibility that some other factor is going to

1048
00:58:24,760 --> 00:58:28,000
Speaker 1: be more pressing in the worldview, and certainly one sees

1049
00:58:28,080 --> 00:58:30,600
Speaker 1: that in religious groups. I mean not all religious groups,

1050
00:58:30,680 --> 00:58:33,840
Speaker 1: but there are certainly religious groups out there, uh that

1051
00:58:34,000 --> 00:58:39,240
Speaker 1: have have beliefs that are run very counter to scientific consensus.

1052
00:58:39,320 --> 00:58:41,520
Speaker 1: Now do they do so in a detrimental fashion? I

1053
00:58:41,560 --> 00:58:43,960
Speaker 1: mean that's it's going to depend Yeah, again, I don't.

1054
00:58:44,120 --> 00:58:46,920
Speaker 1: I mean, as with all these questions like, is there

1055
00:58:46,960 --> 00:58:50,680
Speaker 1: any way to actually engineer that or is that just impossible? Well,

1056
00:58:50,720 --> 00:58:52,280
Speaker 1: I know, I think we have we need to create

1057
00:58:52,280 --> 00:58:55,200
Speaker 1: a new religion. That's what I coming down to, you know, Uh,

1058
00:58:55,840 --> 00:59:00,200
Speaker 1: the an open discussion science first, religion. Uh, they can

1059
00:59:00,240 --> 00:59:04,760
Speaker 1: just sweep across the sweep across the land from shore

1060
00:59:04,800 --> 00:59:07,640
Speaker 1: to shore and uh and and make a better world

1061
00:59:07,680 --> 00:59:09,880
Speaker 1: for the future. Well, I'll let you carry the croak

1062
00:59:09,880 --> 00:59:13,560
Speaker 1: of priests and profit on that one. But Okay, here's

1063
00:59:13,600 --> 00:59:16,920
Speaker 1: maybe one more way another. Basically, I'm just offering different

1064
00:59:16,920 --> 00:59:19,440
Speaker 1: ways you could approach the motivation problem. I don't know

1065
00:59:19,480 --> 00:59:22,320
Speaker 1: of any specifics that you could create, But here's another

1066
00:59:22,360 --> 00:59:24,880
Speaker 1: way of approaching it. What if there is a way

1067
00:59:24,920 --> 00:59:29,160
Speaker 1: to shield facts from acquiring in the first place. What

1068
00:59:29,280 --> 00:59:34,480
Speaker 1: Cahan and co authors call quote antagonistic cultural meanings. In

1069
00:59:34,520 --> 00:59:37,560
Speaker 1: other words, if you can't fix public and understanding by

1070
00:59:37,640 --> 00:59:41,400
Speaker 1: making people better at science comprehension, and you can't program

1071
00:59:41,480 --> 00:59:44,440
Speaker 1: people not to be incentivized first and foremost by a

1072
00:59:44,440 --> 00:59:47,720
Speaker 1: sense of partisan social belonging, maybe the best way to

1073
00:59:47,760 --> 00:59:50,919
Speaker 1: protect facts is to find a way to never let

1074
00:59:50,960 --> 00:59:55,320
Speaker 1: them become politically charged in the first place. If there's

1075
00:59:55,320 --> 00:59:57,720
Speaker 1: a if somebody could figure out a way to do

1076
00:59:57,760 --> 01:00:00,400
Speaker 1: that or at least lessen the probability that would happen,

1077
01:00:00,800 --> 01:00:03,600
Speaker 1: that also seems like a very useful thing, a good

1078
01:00:03,640 --> 01:00:05,640
Speaker 1: way to fight this problem. But it may also be

1079
01:00:05,720 --> 01:00:10,320
Speaker 1: impossible because there's again political incentive for people to politicize

1080
01:00:10,360 --> 01:00:13,280
Speaker 1: certain issues. Yeah, I believe k Kahan has definitely talked

1081
01:00:13,320 --> 01:00:16,160
Speaker 1: about this before. I believe he touched on the idea

1082
01:00:16,240 --> 01:00:20,800
Speaker 1: of of not necessarily like alright, preventing, but like identifying

1083
01:00:20,840 --> 01:00:24,400
Speaker 1: when it is beginning to take place, and in finding

1084
01:00:24,440 --> 01:00:28,280
Speaker 1: ways to intervene and keep it from being so highly politicized,

1085
01:00:28,320 --> 01:00:30,360
Speaker 1: because it's like you know, barnacles building up on a

1086
01:00:30,360 --> 01:00:33,520
Speaker 1: ship or something. Right, Yes, like when you detect and

1087
01:00:33,560 --> 01:00:36,320
Speaker 1: maybe you have a process for when you detect that

1088
01:00:36,520 --> 01:00:40,720
Speaker 1: an empirical scientific question is starting to become an issue

1089
01:00:40,760 --> 01:00:44,160
Speaker 1: of political significance. Suddenly. What you want is to get

1090
01:00:44,160 --> 01:00:47,800
Speaker 1: all the politicians and political actors to stop talking about

1091
01:00:47,800 --> 01:00:53,680
Speaker 1: it immediately and instead get politically neutral celebrities and spokespeople

1092
01:00:53,720 --> 01:00:56,960
Speaker 1: and stuff to talk about it. Yeah. I feel like

1093
01:00:56,960 --> 01:00:59,160
Speaker 1: that's a pretty good idea. I think it probably has

1094
01:00:59,200 --> 01:01:01,880
Speaker 1: a thirty three and one third percent chance of success.

1095
01:01:01,920 --> 01:01:03,960
Speaker 1: But if you add that to the forty six and

1096
01:01:04,000 --> 01:01:07,400
Speaker 1: one half percent chance, then you're really getting steinorific. Yeah,

1097
01:01:07,400 --> 01:01:10,960
Speaker 1: you might get up to two thirds chance of winning.

1098
01:01:12,880 --> 01:01:15,160
Speaker 1: You know. One of the things that the Khan had

1099
01:01:15,200 --> 01:01:17,800
Speaker 1: all right in their paper that I thought was really

1100
01:01:17,840 --> 01:01:21,480
Speaker 1: interesting is that they point out that people, even when

1101
01:01:21,560 --> 01:01:26,120
Speaker 1: experts in other fields are primarily as humans experts about quote,

1102
01:01:26,400 --> 01:01:30,160
Speaker 1: identifying who knows what about what. That sort of is

1103
01:01:30,200 --> 01:01:32,480
Speaker 1: the main way our brains work, Right, That's like our

1104
01:01:32,520 --> 01:01:38,000
Speaker 1: primary capacity is figuring out who knows about what things? Right? Yeah,

1105
01:01:38,000 --> 01:01:39,920
Speaker 1: I mean to come back to Sagan's point of view,

1106
01:01:39,920 --> 01:01:42,360
Speaker 1: you know, it's it's it. It should be certainly less

1107
01:01:42,360 --> 01:01:44,680
Speaker 1: about trying to figure out who's the authority and just

1108
01:01:44,760 --> 01:01:46,560
Speaker 1: looking at who is the best and expert in a

1109
01:01:46,600 --> 01:01:49,880
Speaker 1: given field and being able to sort of weigh what

1110
01:01:49,960 --> 01:01:52,520
Speaker 1: they're saying and why they're saying it. But oftentimes we

1111
01:01:52,680 --> 01:01:55,440
Speaker 1: use this capacity of looking at who knows what about

1112
01:01:55,480 --> 01:01:58,560
Speaker 1: what not to figure out who has the real who's

1113
01:01:58,600 --> 01:02:01,720
Speaker 1: got the best expertise to offer? But with the best

1114
01:02:01,760 --> 01:02:05,520
Speaker 1: expertise is saying what I want to hear said exactly? Yes,

1115
01:02:05,720 --> 01:02:07,840
Speaker 1: who is saying what I want to hear said or

1116
01:02:07,840 --> 01:02:11,400
Speaker 1: what my social group believes in the best way? So

1117
01:02:11,520 --> 01:02:14,320
Speaker 1: I can say it the same way? Anyway, Eugenius is

1118
01:02:14,360 --> 01:02:17,880
Speaker 1: out there? Who who can think of more specific and

1119
01:02:18,200 --> 01:02:21,840
Speaker 1: possibly effective ways to undercut the motivation part of motivated

1120
01:02:21,880 --> 01:02:27,000
Speaker 1: reasoning and uh, politically relevant empirical questions? Let us know

1121
01:02:27,160 --> 01:02:29,720
Speaker 1: what are those ideas you have? Indeed, this is one

1122
01:02:29,720 --> 01:02:32,720
Speaker 1: of those areas where this this hypothesis is so new

1123
01:02:32,800 --> 01:02:35,480
Speaker 1: I don't even think we probably have the science fiction

1124
01:02:35,560 --> 01:02:38,080
Speaker 1: to level at it. So you, the listener will be

1125
01:02:38,120 --> 01:02:41,880
Speaker 1: creating the science fiction uh that might in some way

1126
01:02:41,920 --> 01:02:45,120
Speaker 1: inform what we actually do about it. Yeah, and this

1127
01:02:45,160 --> 01:02:48,920
Speaker 1: whole field identity protective cognition in a way is still developing,

1128
01:02:48,960 --> 01:02:51,680
Speaker 1: so more research could change what seems to be true

1129
01:02:51,680 --> 01:02:54,600
Speaker 1: about it today. But I don't know. It's one of

1130
01:02:54,640 --> 01:02:57,680
Speaker 1: those where I feel like I'm very interested in this research,

1131
01:02:57,760 --> 01:03:01,160
Speaker 1: but it's not necessarily encouraging. I want to go back

1132
01:03:01,200 --> 01:03:04,080
Speaker 1: to the science comprehension thesis world. I want to live

1133
01:03:04,120 --> 01:03:06,480
Speaker 1: in the place where you can just where you can

1134
01:03:06,520 --> 01:03:10,280
Speaker 1: just tell people more, share more knowledge, with more enthusiasm,

1135
01:03:10,320 --> 01:03:13,040
Speaker 1: model the correct kinds of critical thinking and all that

1136
01:03:13,160 --> 01:03:16,280
Speaker 1: and uh and bring people aboard. But it's just not

1137
01:03:16,400 --> 01:03:18,960
Speaker 1: that easy, is it right? Or it's just not enough? Uh?

1138
01:03:19,440 --> 01:03:21,240
Speaker 1: I mean it kind of comes back though, again to

1139
01:03:21,720 --> 01:03:25,440
Speaker 1: the GETA and and and other older works that taught

1140
01:03:25,480 --> 01:03:28,280
Speaker 1: about like self awareness, because that's ultimately what we're talking

1141
01:03:28,320 --> 01:03:33,000
Speaker 1: about is new ways to become aware of how our

1142
01:03:33,040 --> 01:03:36,240
Speaker 1: brains are working and how in some cases we our

1143
01:03:36,280 --> 01:03:40,120
Speaker 1: brains our minds are are tricking ourselves into um and

1144
01:03:40,400 --> 01:03:43,880
Speaker 1: clinging to beliefs that simply don't hold up. Yeah. Oh

1145
01:03:43,960 --> 01:03:45,880
Speaker 1: and one of the things, of course, we've always got

1146
01:03:45,880 --> 01:03:48,720
Speaker 1: to mention. We mentioned this and pretty much anytime we

1147
01:03:48,760 --> 01:03:51,440
Speaker 1: talk about bias or something, you're sitting out there thinking,

1148
01:03:51,520 --> 01:03:54,960
Speaker 1: right now, yeah, this is what other people do. Yeah,

1149
01:03:55,000 --> 01:03:58,200
Speaker 1: but it's we can all look to examples in our

1150
01:03:58,240 --> 01:04:01,800
Speaker 1: own lives, big ones, small, all ones. Uh, ones you

1151
01:04:01,800 --> 01:04:05,600
Speaker 1: you can't recognize and don't even know you do. Yeah, exactly,

1152
01:04:05,680 --> 01:04:08,600
Speaker 1: I got to remove that plank. All right. Well, on

1153
01:04:08,640 --> 01:04:10,960
Speaker 1: that note, we're gonna go ahead and close out this episode.

1154
01:04:11,640 --> 01:04:13,800
Speaker 1: As always, head on over to stuff to Blow your

1155
01:04:13,840 --> 01:04:15,920
Speaker 1: Mind dot com because that is our mothership. That is

1156
01:04:15,920 --> 01:04:18,720
Speaker 1: where you will find all the podcast episodes. You'll find

1157
01:04:18,800 --> 01:04:21,760
Speaker 1: links out to our various social media accounts. There's also

1158
01:04:21,800 --> 01:04:23,520
Speaker 1: a tab at the top of the page where you

1159
01:04:23,520 --> 01:04:25,680
Speaker 1: can go to our store and get all sorts of

1160
01:04:25,920 --> 01:04:29,680
Speaker 1: cool merchandise. Some of its show specific like uh, the

1161
01:04:29,720 --> 01:04:33,720
Speaker 1: Great Basilisk or the Cambrian Life shirts. Other stuff is

1162
01:04:33,760 --> 01:04:36,320
Speaker 1: just has to do with our logo, but it's a

1163
01:04:36,320 --> 01:04:38,440
Speaker 1: great way to support our show if you want to

1164
01:04:38,440 --> 01:04:40,280
Speaker 1: spend a few bucks and get something cool to stick

1165
01:04:40,280 --> 01:04:42,960
Speaker 1: on your laptop or your shirt. On the other hand,

1166
01:04:43,000 --> 01:04:44,920
Speaker 1: if you want to support the show without spending a dime,

1167
01:04:45,440 --> 01:04:48,120
Speaker 1: just rate and review the show wherever you have the

1168
01:04:48,160 --> 01:04:50,560
Speaker 1: power to do so. Thank you so much to our

1169
01:04:50,600 --> 01:04:54,560
Speaker 1: wonderful audio producers Alex Williams and Tarry Harrison. If you

1170
01:04:54,600 --> 01:04:56,720
Speaker 1: would like to get in touch with us with feedback

1171
01:04:56,760 --> 01:04:59,280
Speaker 1: on this episode or any other with your ideas of

1172
01:04:59,320 --> 01:05:02,760
Speaker 1: how to take the motivation out of Motivated numeracy and

1173
01:05:02,800 --> 01:05:06,120
Speaker 1: motivated reasoning. If you want to let us know where

1174
01:05:06,160 --> 01:05:08,080
Speaker 1: you listen from, how you found out about the show,

1175
01:05:08,240 --> 01:05:10,760
Speaker 1: or suggested topic for the future. If I didn't already

1176
01:05:10,800 --> 01:05:14,080
Speaker 1: say that either way, you can email us at blow

1177
01:05:14,200 --> 01:05:26,680
Speaker 1: the Mind at how stuff works dot com for moralness

1178
01:05:26,760 --> 01:05:29,280
Speaker 1: and thousands of other topics. Does it how stuff works

1179
01:05:29,280 --> 01:05:52,520
Speaker 1: dot com