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Speaker 1: Ridiculous Histories, a production of iHeartRadio. Welcome back to the show,

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Speaker 1: fellow Ridiculous Historians. Thank you, as always so much for

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Speaker 1: tuning in. Let's hear for the Man, the myth, the legend,

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Speaker 1: our super producer, Max Benney Williams not with Benne like

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Speaker 1: Jean Benet, similar to do don't have the relationship. Well,

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Speaker 1: we've got a h we've got kind of a dark

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Speaker 1: turn here. Uh. This episode is following on the heels

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Speaker 1: of our recent episode. We're quite proud, proud of the title.

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Speaker 1: Did lead lead to the fall of the Roman Empire? Right?

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Speaker 2: Yes, lead lead, lead lead, you know, maybe probably not spoiler.

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Speaker 1: Alert, Yeah, contributed to Maybe you'll have to check out

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Speaker 1: the episode, folks. That is none other than the legendary

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Speaker 1: mister Noel Brown. Hello, it's you, Ben, Is it you?

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Speaker 1: I think it's you. We are all, we are all vast.

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Speaker 1: We could take multitudes for tax purposes. That call me

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Speaker 1: Ben Bullen. He from the United States. We are bro.

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Speaker 2: I gotta tell you I made the mistake of briefly

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Speaker 2: dating a gen Z person. And she told me when

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Speaker 2: I said I contained multitude, said that is such a

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Speaker 2: millennial thing to say.

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Speaker 1: And I was really triggered by this. Has she not

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Speaker 1: read Whitman? The relationship did not go well? Unclear.

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Speaker 2: My whole thing is I really like there's a Bob

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Speaker 2: Dylan song called I Contain Multitudes, and obviously the Whitman

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Speaker 2: is what he was referencing. But it just felt like

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Speaker 2: such a dismissive thing to say. And she's the kind

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Speaker 2: of person that would say like Bedrod all the time. So,

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Speaker 2: you know, potato potato, To each their own. I wish

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Speaker 2: her well.

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Speaker 1: Dismissive dismissiveness is arguably, depending upon who you read, dismissiveness

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Speaker 1: is a sign of insecurity intelligence that do that?

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Speaker 3: Do?

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Speaker 1: Boy?

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Speaker 2: Oh boy, Ben, We're talking about a thing today related

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Speaker 2: to the Lead Leading with Lead episode in that there

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Speaker 2: purports to be a way that our society claims you

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Speaker 2: can measure one's intelligence, and it's those two golden letters

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Speaker 2: that people love throwing around. You know who loves thrown

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Speaker 2: around a lot? Are President as a diss low IQ individual?

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Speaker 3: Right?

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Speaker 2: Right? Uh, he's got some news coming his way, my guy. Well,

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Speaker 2: that metric, it turns.

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Speaker 1: Out not the best. We Actually I got a little

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Speaker 1: heated up during our Led Lead Roman Empire Fall episode

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Speaker 1: A little hit up, as they would say in Tennessee,

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Speaker 1: about the concept of IQ tests, and we had to

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Speaker 1: change the title to make this a little bit more

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Speaker 1: family friendly. Maybe the best way to begin, folks is

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Speaker 1: check out our Roman Empire episode. I think we did

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Speaker 1: an all right job, and then answer us this. We'll

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Speaker 1: do it first on air, fellow ridiculous historians, Noel Max,

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Speaker 1: have you guys ever taken an IQ test? No?

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Speaker 2: I did recently take one of those Enneagram tests that

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Speaker 2: measures you know, your feelings or whatever.

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Speaker 1: I NFJ.

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Speaker 2: I think I hold on, I've actually got a note

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Speaker 2: for you here. Oh no, I'm getting the beach ball

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Speaker 2: of death on my notes app So we'll come back

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Speaker 2: to that. But this was even like a step above

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Speaker 2: the regular Enneagram thing called like I think it was

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Speaker 2: called Youngian something or other. It was some kind of

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Speaker 2: Jungian thing. And it was interesting because it wasn't you know,

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Speaker 2: it wasn't like taking a test. It was like having

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Speaker 2: a conversation, and then the person that was administering it

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Speaker 2: was able to make all these notes. If I'm not mistaken, Ben, Yeah,

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Speaker 2: the old IQ test is much more of a by

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Speaker 2: the numbers, less interpretive kind of you know, bubbling in

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Speaker 2: the circles test.

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Speaker 1: Yeah, it's a weird thing. Max. Let's hear from you.

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Speaker 1: You ever took one of those tests?

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Speaker 3: But if I did, I can't remember. Maybe it had

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Speaker 3: that little impact on me that I can't remember it,

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Speaker 3: but I can't say I have.

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Speaker 1: It makes sense, right what we're saying when we say

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Speaker 1: I haven't taken an IQ test. The odds are most

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Speaker 1: certainly that you did if you grew up in the

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Speaker 1: United States, even if it was not explicitly cold an

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Speaker 1: IQ test. We have a lot of capstone things, standardized

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Speaker 1: test for every child in school, and if you ever

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Speaker 1: aspire to go to college or university, you take something

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Speaker 1: that is the kissing cousin of the IQ test. Things

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Speaker 1: we call the SAT or the ACT.

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Speaker 2: See that's funny, Ben, because when I was thinking about

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Speaker 2: whether or not I'd taken an IQ test, my mind

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Speaker 2: immediately went to Scantron World.

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Speaker 1: Yes, wouldn't that be a really boring amusement park? Scadorcantron World.

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Speaker 1: I maybeet me, but I really want to go because

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Speaker 1: you get your results at the end of the amusement park.

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Speaker 1: What is their roller.

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Speaker 2: Coaster looks like sort of the like the nerdy equivalent

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Speaker 2: of getting that picture you know where you're making the

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Speaker 2: O face when you're on the coaster or et saying

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Speaker 2: your name at the end of the et ride at Universal.

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Speaker 1: What would the roller coaster be? You know what it

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Speaker 1: could be. It could just be roller coaster of emotion.

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Speaker 2: Because kids, they're not a huge fan of these high

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Speaker 2: stress tests, and we know that. I think we've discussed

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Speaker 2: not on this episode, but maybe a conversation you and

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Speaker 2: I were having leading up to this episode, and maybe

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Speaker 2: a brief mention in the Rome episode about how even

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Speaker 2: some of the smartest people in the world notoriously don't

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Speaker 2: test well or specifically crumble.

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Speaker 1: Under the pressure of these timed high stress tests. Yeah,

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Speaker 1: I've got some stories to share. Also, maybe maybe we

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Speaker 1: can make a solid argument in this episode that instead

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Speaker 1: of a roller coaster of stats at your sat amusement park,

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Speaker 1: you're a q amusement park, you should have the roller

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Speaker 1: coaster of love. Courtesy of Red Hot Chili Peppers and

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Speaker 1: Anthony Keatis. Yeah, Dustry for that, right, Well, their version

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Speaker 1: is a banger. Who does the original?

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Speaker 2: I remember their version from Beavis and butt Head do

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Speaker 2: America soundtrack? Right, it's a lot of Fun of Love

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Speaker 2: and the Originals by the Ohio Players from nineteen hundred

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Speaker 2: and seventy five. Funk hit the top the US charts

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Speaker 2: in nineteen seventy six. Known for its energetic rhythm, the

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Speaker 2: song famously is an urban legend claiming a murder scream

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Speaker 2: was recorded in the background.

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Speaker 1: Oh fascinating. We have to get into that. We might

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Speaker 1: be an episode for another.

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Speaker 2: Time, maybe the very least a bullet point on a

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Speaker 2: on a listical episode about weird music urban legends that

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Speaker 2: we should. I'm just going to drop in on the

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Speaker 2: spot here right now invite our buddy Jordan Runtalk to

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Speaker 2: join us for.

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Speaker 1: Oh I miss you, Jordan. I hope you're tuning into

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Speaker 1: the show. I love that guy. I'll text him after this.

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Speaker 1: Another kind of thing, another sort of standardized test that's

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Speaker 1: going to be familiar to a lot of us in

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Speaker 1: the United States, is something called the ASVAB, the Armed

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Speaker 1: Services Vocational Aptitude Battery. This is what determines whether get

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Speaker 1: to work in Intel or whether you know you work

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Speaker 1: in the elevators, et cetera, et cetera. All jobs are

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Speaker 1: worthwhile the idea of placement test does make sense. They

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Speaker 1: can help set school children up for success. They can

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Speaker 1: help you get the right college or university. And of

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Speaker 1: course Uncle Sam loves the ASVAB because it helps you

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Speaker 1: figure out what a new soldier is especially talented at.

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Speaker 1: It's it's weird because going back to what you said, No,

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Speaker 1: all these things that we could loosely group as IQ

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Speaker 1: or intelligent quotient tests, they are attempting to understand not

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Speaker 1: your roat memorization abilities, but your cognitive abilities like reasoning,

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Speaker 1: problem solving, verbal comprehension, you know. And it's never The

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Speaker 1: tricky thing is it's not the same as say a

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Speaker 1: firearms test. Right. In a fire arms test, you are

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Speaker 1: measured by how accurate you are getting close to, say

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Speaker 1: a bullseye right with certain with certain weaponry. But with this,

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Speaker 1: your intelligence quotient attempts to quantify your level of smarts

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Speaker 1: in comparison to other people who are taking the test

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Speaker 1: or have taken the test in the past. So it's

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Speaker 1: a comparison thing, not an absolute measurement. Got it. So

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Speaker 1: you're part of the sample size of home that only

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Speaker 1: includes those who have taken the test before you or

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Speaker 1: with you. Sticky wicket right, A little bit, right, a

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Speaker 1: little bit, and well we'll talk a good bit about

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Speaker 1: why no one believes. Of course, I hope not. Anyway,

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Speaker 1: we all have things to learn.

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Speaker 2: That you're perfect, you're not spoiler alert, but I think

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Speaker 2: it's really important, you know, in order to human properly,

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Speaker 2: to know the things you don't know, and know that

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Speaker 2: it's probably a smart idea to continue to learn new things.

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Speaker 2: Humans still can't agree, however, on what that knowledge base

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Speaker 2: could perhaps be quantified. As you know, it's a combination

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Speaker 2: of the things you know, intuition skills, certain skills that

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Speaker 2: you might have, and that all bundled together we might

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Speaker 2: refer to as intelligence.

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Speaker 1: Right or competence or the ability to function in a

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Speaker 1: given situation. But as we said, no one thinks IQ

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Speaker 1: tests are perfect, even the biggest proponents or champions of it.

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Speaker 1: The issue is, can we really quantify all that stuff

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Speaker 1: that you just named, Noel? Can we accurately represent that

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Speaker 1: in something as boiled down as a three digit number?

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Speaker 1: How did we get here? Why do so many people

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Speaker 1: think IQ tests are you know, kind of malarkey? To

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Speaker 1: understand that, we have to understand how these things came

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Speaker 1: to be. And this is where we begin by introducing

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Speaker 1: everybody to a guy named Alfred Bennet. Now, when I

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Speaker 1: was research associate for this, I want to confess to

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Speaker 1: you guys, transparency's key to me. I accidentally wrote Alfred

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Speaker 1: Bidet quite frequently in this. It was just a slip

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Speaker 1: of the slip of the fingers.

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Speaker 2: Mm hmm.

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Speaker 3: Was it an autocorrect thing such as you've written Bedet

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Speaker 3: so many times as automatic changing to it or was

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Speaker 3: it just a mind autocorrect.

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Speaker 1: I just really liked our Beidet episodes well, and we

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Speaker 1: are all admittedly Bidet boys over here.

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Speaker 2: And if that isn't the name of a fun punk

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Speaker 2: rock band, then it absolutely should.

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Speaker 1: Be tattoos we should get. I'm good with my Toto

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Speaker 1: wash lit. I know you guys should get it. You

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Speaker 1: guys should get Bidet bros. Right like where the old

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Speaker 1: tramp stamp bros. Right at the right at your lombard.

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Speaker 1: I like it in theory, Ben, I don't think I

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Speaker 1: like it. I don't think you should do it. No,

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Speaker 1: I don't think you should do it. I think Jonathan

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Speaker 1: Stricklan should get it. Yeah right on. Oh geez, So

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Speaker 1: this guy Alfred Bennet b I n E T not

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Speaker 1: Bidey and no relation to the Ramses, right. Yeah, so

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Speaker 1: far as we know, he is born as Alfredo Benetti.

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Speaker 2: It was one of those americanizations, right, It must have

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Speaker 2: been gotta sound a little more, a little more native born.

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Speaker 1: It's common when people, you know, immigrated in those days,

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Speaker 1: especially in France, right in the mid eighteen hundreds. He's

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Speaker 1: born on July eighth, eighteen fifty seven, so his posthumous

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Speaker 1: birthday is coming up pretty soon. His dad was a doctor,

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Speaker 1: his mom was an artist. His parents separated when he

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Speaker 1: was very young, and he was raised primarily by his mother.

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Speaker 1: She moved with him to Paris later in life so

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Speaker 1: that he could attend law school. And guys, here's the thing.

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Speaker 1: He did get his qualifications as bona fides. He was

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Speaker 1: able to practice law in eighteen seventy eight. But he

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Speaker 1: looked around at the legal landscape of France in the

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Speaker 1: late eighteen hundreds and he said, no, I'm going to

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Speaker 1: be like my dad. I'm going to go into medicine.

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Speaker 1: And then soon after that he said, no, I'm going

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Speaker 1: to be different. I'm going to get into hypnosis. Cool.

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Speaker 2: A very reasonable progression there, a reasonable reasonable trajectory.

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Speaker 1: Yeah, so he's been several years becoming a sort of

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Speaker 1: a autodidact. He is teaching himself. He reads extensively. He

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Speaker 1: loves work by people like Alexander Bain, Charles Darwin from earlier,

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Speaker 1: John Stewart Mill. Eventually, no, he publishes his first article,

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Speaker 1: his first professional article. It is on hypnosis. He publishes

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Speaker 1: this in eighteen eighty and everyone hates it.

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Speaker 2: Yeah, people were not fond of this piece of writing

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Speaker 2: in eighteen eighty three.

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Speaker 1: However, he weathered the critiques and the poor reviews.

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Speaker 2: The throwing of the tomatoes, and he took a position

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Speaker 2: in the I'm gonna try my best here and make

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Speaker 2: Casey Pegrim proud that you got Sepatrier, Sepatrier cept Salpetriere.

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Speaker 1: There we go. Hospital.

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Speaker 2: I was about to say hospital, but that would be

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Speaker 2: a bridge too far. In Paris, it was a place

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Speaker 2: that allowed him to pursue research that focused on hypnosis.

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Speaker 2: He was greatly influenced by a guy by the name

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Speaker 2: of Charco and he published four articles during his time

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Speaker 2: there on hypnosis and the concept of animal magnetism, which

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Speaker 2: is another one that's a little bit of a sticky wicked.

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Speaker 2: I mean, I just my dog just growled when I

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Speaker 2: said animal magnetism.

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Speaker 1: What do you know that I don't know, buddy. Yeah,

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Speaker 1: we're referring to Jean Martin Charco. And this guy becomes

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Speaker 1: a mentor to our buddy Alfred. His work shines brightly,

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Speaker 1: but briefly because other peers in the world of hypnotism

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Speaker 1: or animal magnetism. Oh, Paula, can't hear me? Okay, he

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Speaker 1: sends you always seems to look in the past. I

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Speaker 1: love the vibe. So this guy is sort of his

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Speaker 1: mentor figure, right Charcot and Charco gets in a lot

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Speaker 1: of trouble because other scientists look at his work and say,

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Speaker 1: I don't know, man, this feels less like science. This

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Speaker 1: feels more like you sort of doing your own thing

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Speaker 1: and calling your opinions science. It's a massive, massive scandal.

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Speaker 1: It's a massive downfall, and unfortunately our buddy Al Bennet,

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Speaker 1: his reputation takes a big hit as well. It's my association. Yeah, yeah,

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Speaker 1: he caught some strays. As we would say on the

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Speaker 1: Breakfast Club.

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Speaker 2: Well we would if we were ever invited back, or

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Speaker 2: you know, for the first time, you know, Ben, This

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Speaker 2: makes me think of a recent discussion that we had

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Speaker 2: on our sister pod Stuff they Don't Want you to Know,

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Speaker 2: with the incredible host of the podcast series Mind Games,

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Speaker 2: about sort of the history of hypnosis, more specifically the

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Speaker 2: history of a controversial technique. What was the main thing

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Speaker 2: that we talked about with Zoe Lacaz Thank you, Yeah.

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Speaker 1: Focuses on the controversial group of tactics called neuro linguistic programming.

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Speaker 2: Right, and also the types of controversial forms of hypnosis

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Speaker 2: like memory regression therapy and this idea that it can

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Speaker 2: cause false memories to be quote unquote recalled. So it

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Speaker 2: makes sense to me that in the early days of

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Speaker 2: this kind of attempt to scienceify this practice, that it

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Speaker 2: might have been met with some backlash.

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Speaker 1: Oh right, And this stuff happens well after Bena has passed.

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Speaker 1: At this point where his mentor has an academic downfall

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Speaker 1: and gets hit with Look, his career is basically over.

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Speaker 1: Ben A has to pivot, as they would say in

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Speaker 1: corporate America. So he decides he is going to abandon

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Speaker 1: hypnosis in favor of studying psychological development. This is his

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Speaker 1: big switch, This is the decision that will later change

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Speaker 1: the world. And he starts. There's no other way to

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Speaker 1: say it. Folks. He starts experimenting on his own children.

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Speaker 2: Mmmmm, yeah, that's not great. I mean, we just talked

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Speaker 2: about that as well, Ben on stuff that I want

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Speaker 2: you to know in talking about the fine line between

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Speaker 2: scientific advancements in the concept of magic, and we've certainly

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Speaker 2: talked about folks that have gone all mad scientists about

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Speaker 2: things and in the pursuit of progress, but doing some

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Speaker 2: pretty horrific things in that pursuit, like human experimentation or

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Speaker 2: you know, self experimentation. Not great, definitely better than you know,

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Speaker 2: experimenting on someone who is not consenting. Not really sure

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Speaker 2: what the relationship was with the daughter. Maybe she was

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Speaker 2: into it, but still kind of doesn't matter to be honest.

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Speaker 1: Yeah, yeah, it's here's the thing. It's eighteen eighty four.

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Speaker 1: Bene Mary's his longtime spouse or a Balbiani, and together

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Speaker 1: they have two daughters, Madeleine and Alice. Madeleine's born in

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Speaker 1: eighteen eighty five, just a year after they get married.

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Speaker 1: Alice is born in eighteen eighty seven. And so this

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Speaker 1: guy is not to be clear, he's not drugging his children.

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Speaker 1: He starts to study how they think, or how they

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Speaker 1: think about thinking. Their metacognitive processes. And this means that

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Speaker 1: he is the weirdest beat me here, Max, He is

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Speaker 1: the weirdest guddamn dad ever. He's not hurting the kids,

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Speaker 1: but he's asking them very strange questions, and he's making

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Speaker 1: them do little experiments that inform his research on suggestibility

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Speaker 1: and attention. Now he starts saying, how do we measure intelligence? Right?

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Speaker 1: How do personalities or how does lineage affect intelligence? And

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Speaker 1: he publishes so much stuff at this point. If we

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Speaker 1: fast forward, it's eighteen ninety two, he gets a doctorate

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Speaker 1: in natural sciences from suborne and in eighteen ninety one, Bro,

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Speaker 1: I'm not sure how to say this, he kind of

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Speaker 1: gets a job at the Laboratory of Physiological Psychology. It

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Speaker 1: is a prestigious place, but we're saying kind of because

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Speaker 1: when he got the job it was an unpaid position.

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Speaker 1: He worked for a year and didn't see a dime

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Speaker 1: or a fronk.

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Speaker 2: Am I even do too much trouble for doing this

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Speaker 2: stuff with his daughters, because I mean it doesn't seem.

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Speaker 1: Like it's particularly.

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Speaker 2: You know, invasive of just studying suggestibility and attention. But

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Speaker 2: I guess when I immediately when I hear about someone experimenting

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Speaker 2: quote unquote on their family members, it does make me

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Speaker 2: kind of you know, ra eyebrows a little bit.

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Speaker 1: It's cringe. And we're right to be skeptical because even

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Speaker 1: if you're just asking the questions, you are never not

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Speaker 1: going to also be their parent, you know what I mean.

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Speaker 2: That's true, that's true. That can also lead to just

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Speaker 2: you know, it's just not good science, right.

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Speaker 1: Not great science. Yeah, agreed, And everybody in France disagreed

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Speaker 1: with our conclusion because they said, this guy is great.

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Speaker 1: He works for a year and we don't have to

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Speaker 1: pay him. Let's make him the director of this laboratory.

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Speaker 1: And there he meets his longtime collaborator, Theodore Simone. Theodore

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Speaker 1: Simone works with Bene to do doctoral research under Benet's supervision.

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Speaker 1: Bene does some things that are unequivocably very good things.

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Speaker 1: He starts the first French journal of psychology in eighteen

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Speaker 1: ninety five, and at first he is a huge fanboy

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Speaker 1: of a guy named Francis Golton. Francis Golton earlier worked

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Speaker 1: in developing what we will call standardized test and his

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Speaker 1: thing was, we can build out a rubric to measure

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Speaker 1: individual differences in a population. So Benee adopted this approach

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Speaker 1: in his work. He later, I think it's nineteen oh three,

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Speaker 1: he publishes an article that says, hey, guys, have you

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Speaker 1: ever asked your daughters off putting strange questions.

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Speaker 2: All the time? What have you ever dadd before? Kind

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Speaker 2: of comes with the territory, So Ben, shall we begin

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Speaker 2: ZiT tests?

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Speaker 1: Ah Wonderbach. Also he got a lot more love for

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Speaker 1: this nineteen oh three article I did about his hypnosis stuff.

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Speaker 1: He was getting there, man, he was doing the work.

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Speaker 1: You know. They were like Al's back, als back so hard.

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Speaker 1: And he and his collaborator, as we're alluding to, they

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Speaker 1: started working on a test that was meant to help

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Speaker 1: the kids, just like Wu Tang. They said, if children

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Speaker 1: have problems in learning, we got to figure out how

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Speaker 1: to assist those kids. This is what leads to the

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Speaker 1: thing we call the benez Simone Intelligence Scale, and it

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Speaker 1: was a government project.

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Speaker 2: Yeah, but I thought I'd maybe take a minute real

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Speaker 2: quick here, just as an aside to talk about something

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Speaker 2: that you and I talked about off Mike about this

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Speaker 2: subject in terms of helping kids to learn and this

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Speaker 2: knowledge that kids learned differently and that no two kids

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Speaker 2: are the same. I do appreciate where Bene is coming

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Speaker 2: from here specifically because my kid is given certain dispensations

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Speaker 2: through the public school system here in Atlanta, allowing them

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Speaker 2: for a little bit more time on tests. And it's

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Speaker 2: not something that you'd go so far as to maybe

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Speaker 2: call a learning disability, but it is something that after

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Speaker 2: an assessment, it is determined that a little bit of

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Speaker 2: extra time is helpful. And I just really appreciate all

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Speaker 2: the admins and teachers and you know, folks in the

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Speaker 2: school system that advocated for that kind of stuff because

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Speaker 2: to your point earlier, Ben Or we talked about some

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Speaker 2: really smart people just don't test well and it can

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Speaker 2: be a real source of anxiety if someone already has,

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Speaker 2: like say, just generalized anxiety. So just kudos to the teachers,

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Speaker 2: as we always says, and you know, this is a

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Speaker 2: it's been a very positive experience.

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Speaker 1: That's awesome. Yeah, that's not what's happening in early nineteen hundreds.

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Speaker 2: Not yet, definitely, not yet, but just again speaking to

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Speaker 2: the idea of you know, help helping the kids.

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Speaker 1: Yeah, the French government it's nineteen oh four, okay, and

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Speaker 1: the French government says we need to identify special needs

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Speaker 1: in children. Specifically, the Minister of Public Instruction over in

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Speaker 1: Paris says, we have to study existing tests, or we

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Speaker 1: have to create our own tests so that we can

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Speaker 1: ensure intellectually disabled children their words, not ours, can receive

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Speaker 1: an adequate education as best as the state can do.

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Speaker 1: The minister at the time, or the ministry, i should say,

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Speaker 1: is also concerned that children who have normal intelligence are

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Speaker 1: being placed in classes for disabled children, not because of

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Speaker 1: their cognitive abilities, but because of behavior problems. And so

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Speaker 1: they look around France and they say, oh, former creepy

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Speaker 1: hypnotist fanboy, Alfred Binet, you're the guy who should be

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Speaker 1: in charge of all of this. And he took the reins,

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Speaker 1: he took it went off run And by this point

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Speaker 1: I got to tell you, I think Bene is sort

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Speaker 1: of a mercurial dude. You go from the law to medicine,

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Speaker 1: to hypnosis to psychology.

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Speaker 2: That's funny, Ben, because it's like, when I think of mercurial,

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Speaker 2: I guess I sometimes think of somebody who might be

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Speaker 2: like a jack of all trades or sort of a polymath.

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Speaker 2: But I guess maybe that you're meaning more in terms

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Speaker 2: of a little bit on the flighty side.

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Speaker 1: A little bit. He's a little bit on the flight,

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Speaker 1: you know what I mean. The guy takes flights, but hey,

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Speaker 1: so do we.

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Speaker 2: So, speaking of which I need to book a return

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Speaker 2: flight before you know it could cost one.

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Speaker 1: Oh right, yeah, that's a good time. The best time

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Speaker 1: too if you're gaming the system, if you want to

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Speaker 1: take advantage of the AI pricing or dynamic pricing, wake

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Speaker 1: up at like two to three thirty in the morning.

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Speaker 1: That's when that's when the system resets. That is not

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Speaker 1: helpful or well, hopefully it's helpful. It is not relevant

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Speaker 1: to what we're talking about. Our buddy Benet in Classic

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Speaker 1: Mercurial Nature has already at this point rejected his adoration

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Speaker 1: of Galton and Galton's ideas. He said, look, this guy

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Speaker 1: was onto something with standardized tests, but they're only measuring

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Speaker 1: trivial abilities. They're measuring things like memorization. What we need

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Speaker 1: are tests that measure the more impactful, if abstract things

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Speaker 1: like judgment, comprehension, reasoning. These are much more difficult to measure,

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Speaker 1: and he knew that going in, but he was convinced

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Speaker 1: that doing so would yield more accurate results.

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Speaker 3: In this.

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Speaker 1: Question right, and again, this question was entirely about how

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Speaker 1: to set children up for success. Right, should the kids

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Speaker 1: who maybe have learning disabilities, should they go to special

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Speaker 1: classes in regular schools or should they be sent to asylums?

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Speaker 1: And who determines whether a kid has a learning problem

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Speaker 1: in the first place. The psychologists were kind of a

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Speaker 1: cartel at this point in France, and they said, oh, yeah,

431
00:28:23,080 --> 00:28:25,040
Speaker 1: you've got to go to our boys. You've got to

432
00:28:25,080 --> 00:28:28,159
Speaker 1: go to our crew of psychologists and they'll tell you

433
00:28:28,200 --> 00:28:32,520
Speaker 1: if your child is a broken egg. And Bene and

434
00:28:32,760 --> 00:28:36,240
Speaker 1: the crew that he led in opposition, they said, no,

435
00:28:36,720 --> 00:28:39,800
Speaker 1: that's weird. You guys are being weird. Don't get me wrong.

436
00:28:39,960 --> 00:28:43,200
Speaker 1: I experimented on my daughters as well, But we should

437
00:28:43,320 --> 00:28:50,240
Speaker 1: use objective criteria because humans are fallible, So what should

438
00:28:50,320 --> 00:28:55,560
Speaker 1: be the test? And that's where they started to create

439
00:28:55,600 --> 00:28:59,360
Speaker 1: what we call the first IQ test. It probably also

440
00:28:59,480 --> 00:29:02,280
Speaker 1: did not escape this guy, or at least, here's what

441
00:29:02,320 --> 00:29:05,480
Speaker 1: I like to think, it probably didn't escape him that

442
00:29:05,600 --> 00:29:09,719
Speaker 1: the future of a lot of children rested on his shoulders,

443
00:29:10,200 --> 00:29:14,400
Speaker 1: especially since he had those earlier missteps in the world

444
00:29:14,520 --> 00:29:18,000
Speaker 1: of hypnosis. He had to get this one right, he

445
00:29:18,160 --> 00:29:21,840
Speaker 1: sure did so. Soon enough, he and Theodore Simone had

446
00:29:21,880 --> 00:29:25,440
Speaker 1: created an early prototype of the IQ test. Is an

447
00:29:25,480 --> 00:29:27,800
Speaker 1: early test, a prototype, it has to be, I'm gonna

448
00:29:27,800 --> 00:29:28,120
Speaker 1: go with that.

449
00:29:28,480 --> 00:29:31,680
Speaker 2: It's a type of technology. And this was known as

450
00:29:31,720 --> 00:29:35,680
Speaker 2: the Benet Simone Tests. But they wanted a little bit

451
00:29:35,720 --> 00:29:39,479
Speaker 2: more input from some other folks in the field, so

452
00:29:39,520 --> 00:29:41,760
Speaker 2: they took this early version of the test over to

453
00:29:42,160 --> 00:29:45,080
Speaker 2: Stanford University across the pond.

454
00:29:45,920 --> 00:29:51,640
Speaker 1: Ah. Yes, and here we introduce our friends at Stanford University.

455
00:29:52,000 --> 00:29:55,320
Speaker 1: So in this sense, specifically, when we say friends, we're

456
00:29:55,320 --> 00:29:59,520
Speaker 1: talking about another psychologist. His name is Lewis Turman. He

457
00:29:59,600 --> 00:30:03,640
Speaker 1: built on Bene and Simone's work and he created a

458
00:30:03,880 --> 00:30:08,960
Speaker 1: version of their test called the Stanford Bene Intelligence Scale,

459
00:30:09,240 --> 00:30:14,000
Speaker 1: introduced in nineteen sixteen. This is the IQ test. A

460
00:30:14,000 --> 00:30:18,880
Speaker 1: lot of people take. It's been revised numerous times. It's

461
00:30:18,920 --> 00:30:22,840
Speaker 1: administered individually, so you're not sitting in a big room

462
00:30:23,120 --> 00:30:27,560
Speaker 1: like when you take an SAT, and it assesses individuals

463
00:30:28,120 --> 00:30:32,880
Speaker 1: as young as two years old. It primarily focuses on children.

464
00:30:33,240 --> 00:30:36,000
Speaker 1: I just can't imagine giving a two year old a

465
00:30:36,120 --> 00:30:39,880
Speaker 1: standardized test. What do you tell to you? What are

466
00:30:39,920 --> 00:30:40,480
Speaker 1: you talking about?

467
00:30:40,560 --> 00:30:43,840
Speaker 2: Shapes Yeah, pointing at animals like that. What's that one

468
00:30:43,880 --> 00:30:45,960
Speaker 2: for dementia that Trump's always bragging about?

469
00:30:46,400 --> 00:30:50,680
Speaker 1: Oh, man, woman, person camera, something like that. Yeah, hands

470
00:30:50,680 --> 00:30:54,960
Speaker 1: on the clock TV man woman person camera. Cool like that,

471
00:30:55,040 --> 00:30:59,680
Speaker 1: we're clear. We can name five words we heard earlier.

472
00:30:59,760 --> 00:31:02,280
Speaker 2: Is this it's a square peg round hole type situation

473
00:31:02,480 --> 00:31:04,200
Speaker 2: or like one of those ones where you're putting shapes

474
00:31:04,240 --> 00:31:05,920
Speaker 2: in different order. I mean, I know the square peg

475
00:31:06,000 --> 00:31:08,720
Speaker 2: round whole thing is it doesn't work. But you know

476
00:31:08,760 --> 00:31:11,120
Speaker 2: the one where you're like recognizing patterns and things like that.

477
00:31:11,520 --> 00:31:15,800
Speaker 1: Yeah, pattern recognition. Like you see a picture in a

478
00:31:15,880 --> 00:31:21,520
Speaker 1: grid and maybe let's say it's a three by three grid, right,

479
00:31:21,640 --> 00:31:25,560
Speaker 1: so nine squares and one of the squares is left blank,

480
00:31:25,920 --> 00:31:29,080
Speaker 1: and you have to pick the image that fits in there.

481
00:31:29,400 --> 00:31:34,200
Speaker 1: You know, you've got let's say, equilateral triangle and the

482
00:31:34,200 --> 00:31:37,040
Speaker 1: bottom left corner is missing, and then you have a

483
00:31:37,080 --> 00:31:41,000
Speaker 1: couple of choices for what image would best complete that

484
00:31:41,080 --> 00:31:44,120
Speaker 1: full picture of the triangle. That's an example. Then you

485
00:31:44,160 --> 00:31:47,080
Speaker 1: know what completes my full picture of a triangle? What's that?

486
00:31:47,480 --> 00:31:53,880
Speaker 1: You shucks? The full picture of the triangle in my heart? Cool?

487
00:31:54,400 --> 00:31:57,800
Speaker 1: Shout out to olt j Ed, shout out to Max Williams, man,

488
00:31:57,840 --> 00:31:59,360
Speaker 1: you're part of the triangle as well.

489
00:32:00,360 --> 00:32:05,760
Speaker 2: That oh Max is good, he's done with us speaking

490
00:32:05,800 --> 00:32:10,080
Speaker 2: of triangles, and oh dear, okay, let's not go. We'll

491
00:32:10,120 --> 00:32:12,360
Speaker 2: have to get back into Max's good graces. But Ben,

492
00:32:12,440 --> 00:32:15,840
Speaker 2: speaking of triangles and French stuff, have you heard of

493
00:32:15,840 --> 00:32:20,000
Speaker 2: this Montreal, This French Canadian band called Angeen de Poitrine.

494
00:32:21,400 --> 00:32:23,360
Speaker 2: So they have this whole mythology.

495
00:32:23,400 --> 00:32:24,040
Speaker 1: You'd love them.

496
00:32:24,400 --> 00:32:26,960
Speaker 2: They they wear these crazy costumes, and they purport to

497
00:32:26,960 --> 00:32:30,479
Speaker 2: be aliens from another planet, and they worship triangles and

498
00:32:30,520 --> 00:32:34,960
Speaker 2: they play microtonal math rock and they wear these bonkers

499
00:32:35,000 --> 00:32:37,719
Speaker 2: costumes and they're blowing up right now, and they're a

500
00:32:37,720 --> 00:32:40,400
Speaker 2: lot of fun. They kind of have King Gizzard vibes.

501
00:32:40,640 --> 00:32:42,480
Speaker 2: But I just love I know you love a mythology,

502
00:32:42,560 --> 00:32:45,640
Speaker 2: especially a triangle based one.

503
00:32:46,320 --> 00:32:48,800
Speaker 1: Yeah, thank you for the recommendation. What's the name of

504
00:32:48,840 --> 00:32:49,240
Speaker 1: the band?

505
00:32:49,640 --> 00:32:54,000
Speaker 2: They are called Angeen Dipatin, all right, And I'm linking

506
00:32:54,040 --> 00:32:54,680
Speaker 2: you to their.

507
00:32:55,160 --> 00:32:59,360
Speaker 1: I'm linking you to their k XP performance right now. Phenomenal.

508
00:32:59,440 --> 00:33:04,680
Speaker 1: I love k Look, we also know that this idea

509
00:33:04,960 --> 00:33:10,720
Speaker 1: of this idea of measuring intelligence is tricky because even

510
00:33:10,880 --> 00:33:14,840
Speaker 1: back then and in the current day humanity has no

511
00:33:15,640 --> 00:33:21,560
Speaker 1: universally agreed upon definition of intelligence. So Ever, since nineteen sixteen,

512
00:33:22,360 --> 00:33:25,880
Speaker 1: the boffins and the eggheads and the very smart badgers

513
00:33:25,920 --> 00:33:32,920
Speaker 1: have been revising this scale, this Stanford Benet Intelligence Scale.

514
00:33:33,400 --> 00:33:37,280
Speaker 1: They have also again, it's different from a firearm test

515
00:33:37,360 --> 00:33:42,080
Speaker 1: because it is a comparative score. So modern tests are

516
00:33:42,160 --> 00:33:45,280
Speaker 1: going to use what we call deviation. They're going to

517
00:33:45,320 --> 00:33:48,440
Speaker 1: assume the average score, like in the middle of the

518
00:33:48,440 --> 00:33:52,040
Speaker 1: Bell curve is one hundred. We can get into the

519
00:33:52,040 --> 00:33:56,840
Speaker 1: weeds there later. Let's standard deviation. If I'm not mistaken, Yes, yeah,

520
00:33:57,040 --> 00:34:01,040
Speaker 1: nailed it. Standard deviation of sixteen. So if you take

521
00:34:01,080 --> 00:34:05,280
Speaker 1: a test like this and your IQ score is above

522
00:34:05,400 --> 00:34:10,480
Speaker 1: one thirty, you are considered gifted. If it's below seventy,

523
00:34:11,320 --> 00:34:13,680
Speaker 1: they're going to look at you a little bit harder

524
00:34:13,719 --> 00:34:18,640
Speaker 1: for some sort of intellectual disability, Forst. Gump style. Right.

525
00:34:18,760 --> 00:34:21,160
Speaker 2: So, as this concept kind of starts picking up steam

526
00:34:21,200 --> 00:34:24,160
Speaker 2: and expanding throughout the world, you started to see other

527
00:34:24,440 --> 00:34:27,080
Speaker 2: sort of folks styling on it a bit, giving it

528
00:34:27,120 --> 00:34:30,000
Speaker 2: their own spin, which sort of led to some other

529
00:34:30,560 --> 00:34:32,640
Speaker 2: still to this day pretty well known tests and other

530
00:34:32,800 --> 00:34:36,360
Speaker 2: kind of ideas around testing, beginning to emerge stuff like

531
00:34:36,400 --> 00:34:39,920
Speaker 2: the Wes Adult Wessler perhaps I know this one adult

532
00:34:40,000 --> 00:34:45,760
Speaker 2: Intelligent Scale and the Westler Intelligence Scale for children, which

533
00:34:45,960 --> 00:34:51,040
Speaker 2: do yield an overall intelligence quotient score, as well as

534
00:34:51,160 --> 00:34:55,600
Speaker 2: separate ones for verbal and performance subtests.

535
00:34:56,239 --> 00:35:00,000
Speaker 1: Yeah, sort of like how you get yours a gifts

536
00:35:00,440 --> 00:35:04,920
Speaker 1: right one score for verbal or communicative in your SATs

537
00:35:05,040 --> 00:35:07,879
Speaker 1: wants one score for quantitative or mathematical.

538
00:35:08,200 --> 00:35:09,799
Speaker 2: Well, so, I guess the reason a lot of this

539
00:35:09,840 --> 00:35:12,360
Speaker 2: stuff rang true to many of us in the audience,

540
00:35:12,400 --> 00:35:17,440
Speaker 2: including myself, is because, as we're learning, the basis for

541
00:35:17,560 --> 00:35:19,720
Speaker 2: so many of these standardized.

542
00:35:19,080 --> 00:35:21,399
Speaker 1: Tests is in all of this stuff. So even if,

543
00:35:21,400 --> 00:35:23,520
Speaker 1: to your point, Ben, you haven't taken a quote unquote

544
00:35:23,560 --> 00:35:28,319
Speaker 1: IQ test, which is less of a thing, it's much

545
00:35:28,320 --> 00:35:31,480
Speaker 1: more of a spectrum, you've probably taken something that was

546
00:35:31,600 --> 00:35:36,160
Speaker 1: very much inspired by the work of these folks one

547
00:35:36,280 --> 00:35:39,400
Speaker 1: hundred percent. You know, for an example of a verbal test,

548
00:35:39,800 --> 00:35:43,880
Speaker 1: it would be a vocabulary question. Performance tests would be

549
00:35:44,080 --> 00:35:47,479
Speaker 1: picture arrangement like we described just a few minutes ago.

550
00:35:47,920 --> 00:35:53,760
Speaker 1: And for us folks, fellow ridiculous historians, this actually sounds

551
00:35:53,800 --> 00:35:57,080
Speaker 1: like a lot of fun because neither of those examples

552
00:35:57,120 --> 00:36:00,560
Speaker 1: requires you to be super good at math, which is

553
00:36:00,600 --> 00:36:04,160
Speaker 1: where no offense estinal. I think we both crapped the

554
00:36:04,200 --> 00:36:05,040
Speaker 1: bag a little bit.

555
00:36:05,320 --> 00:36:07,040
Speaker 2: Yeah, Now my thing, I got a near I mean

556
00:36:07,040 --> 00:36:08,720
Speaker 2: not to bragg or anything, but I got a nearly

557
00:36:08,760 --> 00:36:11,320
Speaker 2: perfect verbal score, as I'm sure you did on the SAT.

558
00:36:11,840 --> 00:36:14,319
Speaker 2: And I don't even remember what my math was, but

559
00:36:14,360 --> 00:36:17,480
Speaker 2: it was so bad that my overall SAT score weren't impressive.

560
00:36:18,040 --> 00:36:21,360
Speaker 2: But taking taking in, you know, as as the verbal one,

561
00:36:21,400 --> 00:36:23,280
Speaker 2: that's what I always lead with when I'm talking about

562
00:36:23,320 --> 00:36:24,879
Speaker 2: the SAT, just to.

563
00:36:24,760 --> 00:36:27,080
Speaker 3: Be this guy, I was a guy who did much

564
00:36:27,120 --> 00:36:28,360
Speaker 3: better in math than verbal.

565
00:36:28,840 --> 00:36:31,799
Speaker 2: Yes, yeah, And frankly, dude, that that makes sense. You've

566
00:36:31,800 --> 00:36:34,239
Speaker 2: got a very analytical brain in that respect. But you're

567
00:36:34,280 --> 00:36:37,080
Speaker 2: also a really good communicator, So go to hell.

568
00:36:37,680 --> 00:36:39,320
Speaker 1: It's got good SAT score in general.

569
00:36:39,400 --> 00:36:42,080
Speaker 2: So right, get off, get off here and be gone

570
00:36:42,840 --> 00:36:44,839
Speaker 2: into a well with you and we're not even gonna

571
00:36:44,880 --> 00:36:45,520
Speaker 2: send last.

572
00:36:46,239 --> 00:36:49,480
Speaker 1: Stop kissing up to each other, guys, is not what's happened,

573
00:36:51,600 --> 00:36:55,879
Speaker 1: and not the gay hockey kind. The decades to go on, right,

574
00:36:56,000 --> 00:36:59,560
Speaker 1: and as we said, new versions of similar test and merge,

575
00:37:00,239 --> 00:37:04,120
Speaker 1: these things are continually getting revised. As you pointed out,

576
00:37:04,800 --> 00:37:08,839
Speaker 1: now some version of this some grandchild of this sort

577
00:37:08,880 --> 00:37:12,239
Speaker 1: of idea is found in all sorts of places. There

578
00:37:12,320 --> 00:37:15,319
Speaker 1: is no escaping it. A good score can have a

579
00:37:15,480 --> 00:37:20,160
Speaker 1: significant impact on your future in terms of your career

580
00:37:20,239 --> 00:37:23,440
Speaker 1: path and vice versa. Of course, right, there's a bit

581
00:37:23,480 --> 00:37:26,920
Speaker 1: of a feedback loop, right, And this is the ridiculous part.

582
00:37:27,200 --> 00:37:32,680
Speaker 1: These tests have always been controversial since the early nineteen hundreds,

583
00:37:32,800 --> 00:37:34,640
Speaker 1: and a lot of people are going to tell you,

584
00:37:35,120 --> 00:37:39,799
Speaker 1: including us, that these tests are far less useful than

585
00:37:39,840 --> 00:37:45,840
Speaker 1: we have been led to believe. It's never going to die,

586
00:37:45,960 --> 00:37:49,960
Speaker 1: and so on paper, it sounds pretty nifty, right to

587
00:37:50,000 --> 00:37:52,400
Speaker 1: put it simply, We love black and white.

588
00:37:52,440 --> 00:37:54,920
Speaker 2: We love being able to boil things down to like

589
00:37:55,040 --> 00:37:59,319
Speaker 2: a formula or a score. It is a human brain thing,

590
00:37:59,600 --> 00:38:03,840
Speaker 2: but typically we know that stuff can sometimes it be

591
00:38:03,880 --> 00:38:06,000
Speaker 2: a little too good to be true, or a little

592
00:38:06,000 --> 00:38:07,560
Speaker 2: too broad to.

593
00:38:07,560 --> 00:38:19,440
Speaker 1: Be nuanced, if that makes sense. The idea of quantifying

594
00:38:19,719 --> 00:38:23,759
Speaker 1: every single member of the human population by bypassing all

595
00:38:23,800 --> 00:38:29,399
Speaker 1: those things you describe nuance right, the experience right, right,

596
00:38:29,520 --> 00:38:32,759
Speaker 1: soft skills, The idea that you can just treat a

597
00:38:32,840 --> 00:38:35,880
Speaker 1: person like a file or a unit and slap a

598
00:38:35,960 --> 00:38:40,640
Speaker 1: number on their forehead. It turns out that so similar

599
00:38:40,760 --> 00:38:44,080
Speaker 1: to so many other things that sound like amazing shortcuts.

600
00:38:44,560 --> 00:38:48,520
Speaker 1: IQ tests fall far short of what they are supposed

601
00:38:48,520 --> 00:38:51,840
Speaker 1: to do. I mean, the Stanford Bene test is used

602
00:38:51,840 --> 00:38:57,480
Speaker 1: to evaluate abilities, but it has also inescapably been used

603
00:38:57,480 --> 00:39:02,160
Speaker 1: to justify racist a list beliefs and policies.

604
00:39:02,200 --> 00:39:08,160
Speaker 2: No callback with phrenology just also just came up pretty recently,

605
00:39:08,600 --> 00:39:13,440
Speaker 2: typical of these types of again very black and white

606
00:39:13,600 --> 00:39:17,239
Speaker 2: boiling down, boilings down of something that is a much

607
00:39:17,440 --> 00:39:20,759
Speaker 2: more complex issue, like feeling the bumps on someone's head

608
00:39:20,800 --> 00:39:23,040
Speaker 2: and feeling like that allows you to say that they

609
00:39:23,080 --> 00:39:26,520
Speaker 2: are not a valid member of the human race.

610
00:39:27,200 --> 00:39:32,359
Speaker 1: Yeah. Yeah, this is the question efficacy. Efficacy for an

611
00:39:32,400 --> 00:39:38,120
Speaker 1: IQ test would be asking are these results an accurate

612
00:39:38,239 --> 00:39:42,759
Speaker 1: measure of a concept that human beings still struggle to

613
00:39:42,960 --> 00:39:49,000
Speaker 1: fully defy? Can your IQ score really predict your future performance?

614
00:39:49,120 --> 00:39:54,880
Speaker 1: The answer is, give me a record scratchbacks perfect, not

615
00:39:55,200 --> 00:39:59,240
Speaker 1: really not skirt skirt not really, not one hundred percent

616
00:39:59,239 --> 00:40:03,560
Speaker 1: of the time. Not fully. It's fairly common. I will

617
00:40:03,600 --> 00:40:08,320
Speaker 1: pause it that a lot of us know objectively brilliant

618
00:40:08,360 --> 00:40:12,799
Speaker 1: people who could maybe write amazing novels. They can make

619
00:40:13,120 --> 00:40:16,640
Speaker 1: phenomenal murals, they can do high level math, in their

620
00:40:16,680 --> 00:40:21,520
Speaker 1: heads without notes. But they still don't have financial or

621
00:40:21,680 --> 00:40:25,040
Speaker 1: social success. They're not at the top of society. And

622
00:40:25,080 --> 00:40:27,880
Speaker 1: it's not because they're dumb by any means. It's just

623
00:40:27,920 --> 00:40:32,320
Speaker 1: because they're good at taking one test, which is not

624
00:40:32,440 --> 00:40:34,160
Speaker 1: the same thing as being good at life.

625
00:40:34,280 --> 00:40:39,600
Speaker 2: Well, it's also, you know, worth mentioning the path dependency

626
00:40:39,680 --> 00:40:42,560
Speaker 2: maybe the wrong term. I'm a little bit stuck in

627
00:40:42,600 --> 00:40:47,839
Speaker 2: a conversation we recently had about oil and natural resources

628
00:40:47,840 --> 00:40:50,319
Speaker 2: and path dependency in that respect, but in terms of

629
00:40:50,400 --> 00:40:54,080
Speaker 2: the path towards success and this dependency that is sort

630
00:40:54,080 --> 00:40:57,640
Speaker 2: of pushed historically on kids to follow that path, and

631
00:40:57,920 --> 00:41:01,840
Speaker 2: including things like college and taking these tests and getting

632
00:41:01,840 --> 00:41:03,799
Speaker 2: good scores on these tests. We know that a lot

633
00:41:03,840 --> 00:41:06,920
Speaker 2: of that too, is sort of just gatekeeping for connections,

634
00:41:07,360 --> 00:41:09,640
Speaker 2: you know, and the types of people that you might

635
00:41:09,719 --> 00:41:12,719
Speaker 2: encounter that are ultimately the ones who put you in

636
00:41:12,760 --> 00:41:16,839
Speaker 2: the right rooms and get you, you know, a leg

637
00:41:16,960 --> 00:41:21,120
Speaker 2: up towards perhaps that journey of success. But these days,

638
00:41:21,719 --> 00:41:23,880
Speaker 2: I don't know, man, those paths are a little bit

639
00:41:23,960 --> 00:41:25,960
Speaker 2: less relevant than they used to be. And we know

640
00:41:26,080 --> 00:41:28,600
Speaker 2: that if you make the effort and put yourself out there,

641
00:41:29,480 --> 00:41:32,839
Speaker 2: you can find your people. You can find those connections

642
00:41:32,960 --> 00:41:35,840
Speaker 2: on your own, just by being part of the world

643
00:41:35,920 --> 00:41:38,719
Speaker 2: and being interested in stuff and perhaps being part of

644
00:41:39,239 --> 00:41:43,239
Speaker 2: Reddit groups or you know, making Internet content, or just

645
00:41:43,320 --> 00:41:46,000
Speaker 2: like hanging out and going to clubs and stuff like that.

646
00:41:46,040 --> 00:41:48,000
Speaker 2: So I'm not saying don't go to college, but I'm

647
00:41:48,040 --> 00:41:51,120
Speaker 2: also just saying that I think it's coming around. The

648
00:41:51,200 --> 00:41:54,439
Speaker 2: general knowledge maybe is that it's not exactly the only way.

649
00:41:55,040 --> 00:41:58,600
Speaker 1: Yeah, yeah, And part of that is because IQ tests

650
00:41:58,920 --> 00:42:02,680
Speaker 1: measure a very narrow slice of what we can call

651
00:42:02,880 --> 00:42:07,319
Speaker 1: mental horsepower. Right. It looks at your logic, your pattern recognition,

652
00:42:07,520 --> 00:42:11,399
Speaker 1: short term memory, problem solving. So these tests can tell

653
00:42:11,440 --> 00:42:15,080
Speaker 1: you how good you are taking an IQ test. They

654
00:42:15,080 --> 00:42:17,520
Speaker 1: can tell you how fast you can solve a puzzle,

655
00:42:17,880 --> 00:42:21,600
Speaker 1: but they don't they don't measure They're not able to

656
00:42:21,600 --> 00:42:24,439
Speaker 1: measure how you would do things like raise kids, or

657
00:42:24,520 --> 00:42:27,200
Speaker 1: stop your friends in the middle of a fight, or

658
00:42:27,239 --> 00:42:31,000
Speaker 1: even survive a week in the woods. The soft skills

659
00:42:31,440 --> 00:42:34,520
Speaker 1: are the key, Right. You can score incredibly high on

660
00:42:34,600 --> 00:42:38,319
Speaker 1: all sorts of tests, but you might not have emotional intelligence.

661
00:42:38,360 --> 00:42:42,240
Speaker 1: You might not be good at reading and understanding the needs,

662
00:42:42,360 --> 00:42:46,960
Speaker 1: perspectives and actions of others. Right. If you're very good

663
00:42:47,040 --> 00:42:53,440
Speaker 1: at math. But you don't feel that other people also

664
00:42:53,680 --> 00:42:57,279
Speaker 1: are equal entities in the world, then folks at your

665
00:42:57,320 --> 00:42:59,440
Speaker 1: job aren't gonna like you. You also might not be

666
00:42:59,480 --> 00:43:03,160
Speaker 1: good at hand stress. These are key things to success,

667
00:43:03,200 --> 00:43:06,160
Speaker 1: and I love what you pointed out there about things

668
00:43:06,239 --> 00:43:10,920
Speaker 1: like networking. IQ tests don't measure that, they don't measure

669
00:43:11,000 --> 00:43:13,320
Speaker 1: interpersonal intelligence.

670
00:43:12,680 --> 00:43:15,080
Speaker 2: Well, and we certainly all remember the No Child Left

671
00:43:15,120 --> 00:43:19,120
Speaker 2: Behind scandal and how inevitably scandal maybe is a strong word,

672
00:43:19,200 --> 00:43:24,160
Speaker 2: but how when these quotas are pushed upon already strained

673
00:43:24,640 --> 00:43:26,879
Speaker 2: educational systems, you're going to end up with a whole

674
00:43:26,880 --> 00:43:30,400
Speaker 2: lot of teaching the tests, which again is not a

675
00:43:30,440 --> 00:43:33,320
Speaker 2: good indicator of what that test is actually supposed to

676
00:43:33,400 --> 00:43:35,080
Speaker 2: measure in the real world.

677
00:43:35,160 --> 00:43:39,200
Speaker 1: One hundred percent. You know, Bene's original test was meant

678
00:43:39,200 --> 00:43:42,640
Speaker 1: to be a diagnostic tool, not some kind of leader board.

679
00:43:42,680 --> 00:43:45,319
Speaker 1: But the issue is, by the time it hit the

680
00:43:45,440 --> 00:43:48,959
Speaker 1: United States, the test and versions of it were being

681
00:43:49,040 --> 00:43:53,160
Speaker 1: used to brank people to gatekeeper opportunities and even to

682
00:43:53,520 --> 00:43:58,440
Speaker 1: justify eugenics programs like they would use the IQ test

683
00:43:58,800 --> 00:44:06,120
Speaker 1: results to to justify another pseudoscience up there with phrenology,

684
00:44:06,280 --> 00:44:10,440
Speaker 1: the idea that some people have to be sterilized. The

685
00:44:10,480 --> 00:44:14,759
Speaker 1: idea that you're perceived race means you are superior or

686
00:44:14,920 --> 00:44:16,480
Speaker 1: inferior to others.

687
00:44:16,880 --> 00:44:19,080
Speaker 2: And man, I'm not trying to be get on a

688
00:44:19,080 --> 00:44:22,640
Speaker 2: political soap box here, but that sure feels like the

689
00:44:22,640 --> 00:44:25,920
Speaker 2: flavor of the way the President is thrown around that term,

690
00:44:26,200 --> 00:44:28,440
Speaker 2: because he's often using it to refer to people of

691
00:44:28,480 --> 00:44:32,160
Speaker 2: color and referring to them as low IQ individuals and

692
00:44:32,160 --> 00:44:32,839
Speaker 2: stuff like that.

693
00:44:32,880 --> 00:44:35,120
Speaker 1: It just it just has echoes of what you're talking

694
00:44:35,160 --> 00:44:40,440
Speaker 1: about there, ben Oh, oh no, don't yield. We we can,

695
00:44:41,400 --> 00:44:43,960
Speaker 1: we could break, but we will not. Then it just grows.

696
00:44:44,040 --> 00:44:46,480
Speaker 2: It's again, not even if it's it's any political observation,

697
00:44:46,600 --> 00:44:49,520
Speaker 2: it's it's it's not nice. It's just rude and at

698
00:44:49,600 --> 00:44:53,879
Speaker 2: at at its very least and racist that it's at

699
00:44:53,880 --> 00:44:54,360
Speaker 2: its worst.

700
00:44:55,080 --> 00:44:58,880
Speaker 1: Yeah. In the early nineteen hundreds, Uncle Sam started using

701
00:44:59,320 --> 00:45:04,480
Speaker 1: uh these tests descended from Benay to sort students into programs.

702
00:45:04,719 --> 00:45:07,680
Speaker 1: So if you got a score on their version of

703
00:45:07,719 --> 00:45:10,960
Speaker 1: the IQ test that was above one hundred and fifteen,

704
00:45:11,360 --> 00:45:14,640
Speaker 1: that was your quotient, your deviation from the norm of

705
00:45:14,640 --> 00:45:19,080
Speaker 1: one hundred, then you were considered gifted and you then

706
00:45:19,239 --> 00:45:22,960
Speaker 1: got higher education opportunities. So you can make the most

707
00:45:23,000 --> 00:45:27,000
Speaker 1: of your abilities. If you're a normal kid, your score

708
00:45:27,040 --> 00:45:30,160
Speaker 1: is between seventy to one hundred and fifteen at this time,

709
00:45:30,480 --> 00:45:33,280
Speaker 1: you stay where you are. If your score is under

710
00:45:33,400 --> 00:45:36,920
Speaker 1: seventy for one reason or another and you don't often

711
00:45:36,960 --> 00:45:40,320
Speaker 1: get to retake the test, you are considered special needs.

712
00:45:40,440 --> 00:45:45,320
Speaker 1: You are sent to state schools, you are sent to institutions.

713
00:45:45,760 --> 00:45:49,759
Speaker 1: People begin to think that these special needs kids are

714
00:45:49,800 --> 00:45:54,360
Speaker 1: not fit for society. Only a few of them actually

715
00:45:54,400 --> 00:45:57,200
Speaker 1: had a cognitive disability. A lot of these kids were

716
00:45:57,200 --> 00:46:02,640
Speaker 1: from foster care, right, they didn't have earlier educational opportunities.

717
00:46:02,680 --> 00:46:07,000
Speaker 1: Their parents or their relatives may have substance issues, they

718
00:46:07,080 --> 00:46:10,640
Speaker 1: may have had their own sort of mental issues. These

719
00:46:10,760 --> 00:46:16,200
Speaker 1: kids get carted off to abusive foster homes and institutions.

720
00:46:17,560 --> 00:46:20,799
Speaker 1: And since we're a family show, can we just leave

721
00:46:20,840 --> 00:46:26,359
Speaker 1: it at this horrific stuff happened to these children, all

722
00:46:26,400 --> 00:46:31,160
Speaker 1: the kinds of abuse that you can imagine, and also sterilization.

723
00:46:31,960 --> 00:46:33,560
Speaker 2: Oh yeah, yeah, and there's you know, if you want

724
00:46:33,600 --> 00:46:38,239
Speaker 2: to dig deeper into that very disturbing topic, we've done

725
00:46:38,280 --> 00:46:40,640
Speaker 2: episodes about that very thing, on stuff that it wants

726
00:46:40,640 --> 00:46:43,680
Speaker 2: you to know. As well as our sister podcast stuff

727
00:46:43,719 --> 00:46:47,399
Speaker 2: you missed in history class, who have done I think

728
00:46:47,480 --> 00:46:52,440
Speaker 2: several episodes on sterilization and on this kind of horrific

729
00:46:52,480 --> 00:46:56,440
Speaker 2: treatment of children through these very types of programs that

730
00:46:56,440 --> 00:46:57,000
Speaker 2: we're talking about.

731
00:46:57,239 --> 00:47:01,120
Speaker 1: One hundred percent. Yeah, and these controvert continue in the

732
00:47:01,160 --> 00:47:05,279
Speaker 1: modern day. Critics will tell you intelligence tests have a

733
00:47:05,360 --> 00:47:11,200
Speaker 1: strong cultural bias, a favor people for more affluent backgrounds.

734
00:47:11,280 --> 00:47:16,880
Speaker 1: They discriminate against people from minority groups, right, whether that

735
00:47:17,000 --> 00:47:20,920
Speaker 1: be racial, ethnic, social, et cetera. We also know that

736
00:47:20,960 --> 00:47:25,080
Speaker 1: psychologists are responding to this by developing what they call

737
00:47:25,320 --> 00:47:31,680
Speaker 1: culture free tests, and the idea seems like very basic stuff. Say, say,

738
00:47:31,760 --> 00:47:34,880
Speaker 1: for instance, if we're testing kids who grew up in

739
00:47:34,920 --> 00:47:39,400
Speaker 1: the inner city, then we're going to use when we

740
00:47:39,480 --> 00:47:44,120
Speaker 1: ask questions, we're going to use urban or city settings

741
00:47:44,520 --> 00:47:48,200
Speaker 1: instead of like an outdated rural pastoral thing. Right like,

742
00:47:48,320 --> 00:47:52,560
Speaker 1: I'm I'm a kid in Queens, I'm an upper Queens.

743
00:47:52,880 --> 00:47:55,360
Speaker 1: Why are you asking me about this? Farmer? And is

744
00:47:55,480 --> 00:47:59,200
Speaker 1: rutabagas stop it? Ruda begas?

745
00:47:59,280 --> 00:48:02,480
Speaker 2: We love rudebaks. I still don't really fully understand what

746
00:48:02,600 --> 00:48:04,800
Speaker 2: they are do. Check out stuff they don't want you

747
00:48:04,880 --> 00:48:08,440
Speaker 2: to knowse Weekly Listener Mail episodes for a brand new

748
00:48:08,520 --> 00:48:12,480
Speaker 2: root of Bega Banger every single week from our incredible

749
00:48:12,520 --> 00:48:16,440
Speaker 2: super producer Dylan the code name Tennessee pal Fagan, And

750
00:48:16,719 --> 00:48:19,040
Speaker 2: I just wanted to really quickly mention that the specific

751
00:48:19,080 --> 00:48:21,840
Speaker 2: episode that I was referencing from stuff you missed in

752
00:48:21,920 --> 00:48:26,400
Speaker 2: history class is about the Calikak family and the study

753
00:48:26,680 --> 00:48:32,560
Speaker 2: of hereditary feeble mindedness, which is another really gross term

754
00:48:32,880 --> 00:48:35,000
Speaker 2: that was thrown around and tied to these types of

755
00:48:36,000 --> 00:48:37,280
Speaker 2: standardized test scores.

756
00:48:37,760 --> 00:48:41,560
Speaker 1: Yeah, that was weaponized language, for sure, But what we're

757
00:48:41,560 --> 00:48:46,359
Speaker 1: telling you is eugenics aside, cultural gatekeeping aside. There is

758
00:48:46,440 --> 00:48:50,400
Speaker 1: hope for the IQ test. These tests are not total garbage,

759
00:48:50,400 --> 00:48:54,520
Speaker 1: but they have and continue to have massive issues. They've

760
00:48:54,520 --> 00:49:00,080
Speaker 1: been weaponized, flagrantly misused. The results have been overestimated, and

761
00:49:00,239 --> 00:49:03,319
Speaker 1: on and on and on. And here's one of the

762
00:49:03,320 --> 00:49:06,120
Speaker 1: things I wish more people talked about when we talk

763
00:49:06,160 --> 00:49:09,520
Speaker 1: about IQ tests. This is one of the most ridiculous

764
00:49:09,560 --> 00:49:13,719
Speaker 1: flaws in the Origin story Noel Max. There is this

765
00:49:13,920 --> 00:49:18,640
Speaker 1: old adage in writing fiction, which is this, it is

766
00:49:18,719 --> 00:49:24,040
Speaker 1: incredibly difficult to write a super smart character because any

767
00:49:24,200 --> 00:49:28,239
Speaker 1: character can only be as intelligent as the author that

768
00:49:28,400 --> 00:49:32,520
Speaker 1: created them. IQ tests. I will posit cannot be immune

769
00:49:32,600 --> 00:49:36,359
Speaker 1: from that law. So the creators are very smart people, right,

770
00:49:36,400 --> 00:49:38,920
Speaker 1: the folks who make these tests, But they're probably not

771
00:49:39,040 --> 00:49:42,799
Speaker 1: the smartest people ever, ever, ever in history, and they're

772
00:49:42,840 --> 00:49:45,919
Speaker 1: probably not even the smartest people in their own lifetimes,

773
00:49:46,280 --> 00:49:50,880
Speaker 1: so they quite possibly are not the best candidates to

774
00:49:51,000 --> 00:49:54,120
Speaker 1: make these examinations in the first place. We need the

775
00:49:54,160 --> 00:49:58,759
Speaker 1: smartest people ever writing the test, and these are not them. No,

776
00:49:59,120 --> 00:50:04,200
Speaker 1: they're usually now, No they're not. And there's no statistical

777
00:50:04,280 --> 00:50:09,680
Speaker 1: association between your IQ score and hard measures like your wealth.

778
00:50:10,800 --> 00:50:17,080
Speaker 1: So look, this is a crazy thing. Humans are still

779
00:50:17,120 --> 00:50:20,840
Speaker 1: figuring out intelligence. We didn't even get to the Flynn effect,

780
00:50:21,000 --> 00:50:24,120
Speaker 1: which is kind of good news. Maybe we end on that. Noel,

781
00:50:24,160 --> 00:50:25,840
Speaker 1: have you heard of the Flint effect?

782
00:50:26,040 --> 00:50:29,440
Speaker 2: No, not till just now when I clocked it in

783
00:50:29,440 --> 00:50:32,520
Speaker 2: the outline. But please tell us about the Flint effect.

784
00:50:33,200 --> 00:50:39,160
Speaker 1: All right, here's the pickle. This is fascinating over time,

785
00:50:39,520 --> 00:50:43,399
Speaker 1: over decades and decades and decades, more than a century now,

786
00:50:43,880 --> 00:50:49,879
Speaker 1: IQ scores have shown a consistent increase across generations. It's

787
00:50:49,880 --> 00:50:53,760
Speaker 1: called the Flint effect because a guy named James Flynn

788
00:50:54,080 --> 00:50:59,200
Speaker 1: first first popularized this in the nineteen eighties and it

789
00:50:59,360 --> 00:51:02,560
Speaker 1: looks like people are scoring a higher on IQ tests,

790
00:51:02,600 --> 00:51:07,080
Speaker 1: not because they're necessarily getting smarter, but because the tests

791
00:51:07,200 --> 00:51:13,080
Speaker 1: themselves are changing. People have improved access to education and information,

792
00:51:13,560 --> 00:51:17,600
Speaker 1: and people, perhaps most importantly, have better health and nutrition.

793
00:51:18,800 --> 00:51:24,040
Speaker 1: The one thing that hasn't changed is genetic lineage. Your

794
00:51:24,160 --> 00:51:27,920
Speaker 1: genes have very little to do with your IQ test.

795
00:51:29,360 --> 00:51:34,240
Speaker 1: It's true, it's true. And so where do we land

796
00:51:34,280 --> 00:51:36,480
Speaker 1: on it? Guys? I know, always coming in a hot

797
00:51:36,480 --> 00:51:38,719
Speaker 1: and saying IQ tests are kind of beat the air

798
00:51:38,800 --> 00:51:43,120
Speaker 1: max bullshit, They're kind of dark, they're just overblown. They're

799
00:51:43,160 --> 00:51:43,640
Speaker 1: over blown.

800
00:51:43,719 --> 00:51:45,360
Speaker 2: It's true, and we already kind of knew that in

801
00:51:45,440 --> 00:51:47,920
Speaker 2: terms of these types of tests for the very reasons

802
00:51:47,920 --> 00:51:50,080
Speaker 2: that we mentioned, just the idea of it's really hard to.

803
00:51:50,800 --> 00:51:54,840
Speaker 1: Boil down the individual, unique snowflakedness that is a human

804
00:51:54,880 --> 00:51:56,760
Speaker 1: person into a number.

805
00:51:57,960 --> 00:52:00,160
Speaker 2: But then you do end the episode with a think,

806
00:52:00,160 --> 00:52:02,279
Speaker 2: a question that maybe on all of our minds is.

807
00:52:02,200 --> 00:52:05,720
Speaker 1: But who's the best, Who's got the best one, who's

808
00:52:05,800 --> 00:52:07,839
Speaker 1: the smartest? Remember when we were kids too.

809
00:52:07,880 --> 00:52:09,520
Speaker 2: That's why I think it's so funny that Trump throws

810
00:52:09,520 --> 00:52:11,120
Speaker 2: that around, where we used to probably make fun of

811
00:52:11,120 --> 00:52:15,600
Speaker 2: people by saying your IQ's negative zero or stuff.

812
00:52:15,280 --> 00:52:18,360
Speaker 1: Like that, not fully understanding anything about this world.

813
00:52:18,640 --> 00:52:21,400
Speaker 2: So who's got the highest IQ in the whole wide

814
00:52:21,440 --> 00:52:22,640
Speaker 2: world of sports?

815
00:52:23,040 --> 00:52:25,960
Speaker 1: Oh? Yeah, yeah, Oh, I've got to do one joke

816
00:52:26,360 --> 00:52:31,359
Speaker 1: for please, one joke for our Irish American friends. This

817
00:52:31,440 --> 00:52:33,799
Speaker 1: might get us in trouble, but let's do it and

818
00:52:33,920 --> 00:52:37,240
Speaker 1: Max get a MIC for this one. Hey, guys, what's

819
00:52:37,400 --> 00:52:42,640
Speaker 1: three miles long and has an IQ of forty? The

820
00:52:42,680 --> 00:52:44,320
Speaker 1: Saint Patty's Day Parade?

821
00:52:45,040 --> 00:52:50,719
Speaker 2: Because they're all really, did we even talk about what

822
00:52:50,760 --> 00:52:51,600
Speaker 2: the scale is?

823
00:52:51,640 --> 00:52:51,960
Speaker 1: Though?

824
00:52:52,880 --> 00:52:56,279
Speaker 2: The numerical scale like forty would be pretty bad, right,

825
00:52:56,480 --> 00:52:59,760
Speaker 2: forty is bad? And then we're talking about a cumulative

826
00:52:59,760 --> 00:53:03,120
Speaker 2: school or of forty. So man, they really whoever wrote

827
00:53:03,160 --> 00:53:04,640
Speaker 2: that joke really stuck it to the Irish?

828
00:53:04,719 --> 00:53:07,680
Speaker 1: Huh? It was probably a British guy, Probably it was

829
00:53:07,880 --> 00:53:13,240
Speaker 1: not us. So yes, to answer your question directly, as

830
00:53:13,760 --> 00:53:17,399
Speaker 1: as we can find in the research. Currently, we don't

831
00:53:17,400 --> 00:53:21,000
Speaker 1: know the actual smartest homo sapient alive right now, but

832
00:53:21,200 --> 00:53:25,800
Speaker 1: as of twenty twenty four, a doctor named Jung Hun

833
00:53:25,960 --> 00:53:30,719
Speaker 1: Kim has established the world record title for the world's

834
00:53:30,760 --> 00:53:37,400
Speaker 1: highest IQ person. Now, his intelligence quotient has been verified

835
00:53:37,680 --> 00:53:42,239
Speaker 1: as two one hundred and seventy six. I'm impressed. That's

836
00:53:42,440 --> 00:53:46,239
Speaker 1: what's a big number. I mean, does he do We're

837
00:53:46,280 --> 00:53:48,600
Speaker 1: not saying he's brilliant, No, you might just be very

838
00:53:48,640 --> 00:53:49,440
Speaker 1: good to take you the.

839
00:53:49,440 --> 00:53:55,440
Speaker 2: Test Crackerjack test taker. And good on you, doctor Junghun Kim.

840
00:53:55,760 --> 00:53:57,520
Speaker 2: And by the way, I do love the idea of

841
00:53:58,120 --> 00:54:01,200
Speaker 2: the non non Olympic record.

842
00:54:02,200 --> 00:54:06,239
Speaker 1: Yes, yeah, the International Non Olympic Committee. Yes, the International

843
00:54:06,280 --> 00:54:11,640
Speaker 1: Non Olympic Committee. It's very niche, very very specific. Yeah. Yeah, like,

844
00:54:11,840 --> 00:54:16,040
Speaker 1: oh uh, it's my first time going to committee meeting.

845
00:54:16,160 --> 00:54:19,800
Speaker 1: What are you guys about, well, you know, the Olympics, Yeah,

846
00:54:20,120 --> 00:54:24,439
Speaker 1: pretty much, nothing related to that. Everything else, everything, everything else.

847
00:54:24,480 --> 00:54:25,320
Speaker 1: In our house.

848
00:54:26,360 --> 00:54:29,319
Speaker 2: We also, of course have the World Memory Championships, the

849
00:54:29,360 --> 00:54:33,480
Speaker 2: World Memory Sports Council. These are wild Ben and the

850
00:54:33,480 --> 00:54:40,319
Speaker 2: official World Record trademark, right, yeah, whatever the R. What's

851
00:54:40,360 --> 00:54:43,239
Speaker 2: the R registered trademark? Yeah, it's the registered trademark. I

852
00:54:43,239 --> 00:54:46,960
Speaker 2: should remember that from our intellectual property series.

853
00:54:47,000 --> 00:54:48,960
Speaker 1: But Ben Man, excellent.

854
00:54:49,080 --> 00:54:50,920
Speaker 2: I don't know how what kind of test taker you are,

855
00:54:50,960 --> 00:54:53,759
Speaker 2: but you're sure good a research doc writer and this

856
00:54:53,960 --> 00:54:54,720
Speaker 2: was a fun one.

857
00:54:55,040 --> 00:54:59,120
Speaker 1: Ah shucks. Well, big big thanks to everybody for tuning

858
00:54:59,160 --> 00:55:03,759
Speaker 1: in big thanks to our super producer mister Max Williams.

859
00:55:04,040 --> 00:55:09,120
Speaker 1: A big thanks to Jonathan Strickland, who I bet will

860
00:55:09,200 --> 00:55:11,480
Speaker 1: lie about his IQ scores.

861
00:55:11,600 --> 00:55:13,400
Speaker 2: Maybe, and I bet he knows it too. He's the

862
00:55:13,440 --> 00:55:15,520
Speaker 2: type of guy that knows definite and that keeps it.

863
00:55:15,560 --> 00:55:16,920
Speaker 2: You know, He's probably a guy that written on the

864
00:55:16,960 --> 00:55:18,120
Speaker 2: back of his Mensa Carden.

865
00:55:18,480 --> 00:55:22,080
Speaker 1: Big thanks to aj Bahamas, Jacob's. Big thanks to Leave's

866
00:55:22,160 --> 00:55:25,640
Speaker 1: Jeffcoat and Christopher Hasiotis who else, who else? Who else?

867
00:55:26,000 --> 00:55:29,440
Speaker 2: All the people jeez Luise the Lovely Humans over a

868
00:55:29,480 --> 00:55:31,680
Speaker 2: ridiculous crime. If you dig our show, you will absolutely

869
00:55:32,040 --> 00:55:34,680
Speaker 2: dig theirs Alex Williams and composer our theme.

870
00:55:34,680 --> 00:55:36,360
Speaker 1: If you already said it, I'm staying in a second time,

871
00:55:36,480 --> 00:55:39,359
Speaker 1: I'm doing it. Oh, I'm just doing it. Good, Save good,

872
00:55:39,400 --> 00:55:43,520
Speaker 1: save forgot that one and one thing one thing I

873
00:55:43,640 --> 00:55:47,080
Speaker 1: never want to forget is a big thank you to you, Noel.

874
00:55:48,320 --> 00:55:50,239
Speaker 1: You're one of the smartest people I know and it's

875
00:55:50,280 --> 00:55:51,680
Speaker 1: always a pleasure to hang out with you.

876
00:55:51,760 --> 00:55:55,239
Speaker 2: Oh Ben same, you are the missing piece in the

877
00:55:55,360 --> 00:55:57,919
Speaker 2: triangle pattern recognition test of my heart.

878
00:55:59,080 --> 00:55:59,759
Speaker 1: Let's see you next time.

879
00:55:59,760 --> 00:56:10,040
Speaker 2: Put For more podcasts from iHeartRadio, visit the iHeartRadio app,

880
00:56:10,080 --> 00:56:13,200
Speaker 2: Apple podcasts, or wherever you listen to your favorite shows.