Speaker 1: Today, it's great to have Dean Keith Simonton on the podcast.
Speaker 1: Dean is Distinguished Professor Emeritus of Psychology at the University
Speaker 1: of California and Davis. His well over five hundred single
Speaker 1: authored publications focus on topics such as genius, creativity, esthetics,
Speaker 1: and leadership. In twenty eighteen, MIT Press publish his book
Speaker 1: The Genius Checklist, but he has also published many other
Speaker 1: books on these topics, on these various topics of genius
Speaker 1: and leadership and aesthetics. And I want to just personally
Speaker 1: say his book, Greatness, Who Makes History and Why is
Speaker 1: one of the major books that inspired me to go
Speaker 1: into the field that I'm in today. So Dean, it
Speaker 1: is just such an honor to chat with you today. Well,
Speaker 1: it's great finally be able to do this, Thanks Scott,
Speaker 1: finally finally. Uh you know, I remember we were on
Speaker 1: a I was on a cruise ship with my dad,
Speaker 1: maybe over a decade ago, and the only thing I
Speaker 1: wanted to do was sit in the cabin read your book, Greatness.
Speaker 1: We'll in our room, sit in our room. My Dad's like,
Speaker 1: don't you want to like go to like the shows
Speaker 1: and the buffets, And I was just captivated by this book,
Speaker 1: and I still have my copy with all of my
Speaker 1: underlings and circles. And I think I was still in
Speaker 1: college at the time, and it just, I mean, I
Speaker 1: knew that this is what I wanted to do in
Speaker 1: my life, you know, and you were such an inspiration
Speaker 1: to me. I wanted to study the science of greatness.
Speaker 1: And boy, it's just such a it really is such
Speaker 1: an hunter to chat with you today. I mean, you've
Speaker 1: done so much for our field. You really have done
Speaker 1: so much. I'll thank you much. So let's start. I
Speaker 1: want to start back nineteen seventy five. That's when, or
Speaker 1: even earlier nineteen seventy two, you're in Harvard's PhD program
Speaker 1: in Social SEXCES in social psychology and you want to
Speaker 1: study genius. Now, tell me what your advisors said when
Speaker 1: you're like, oh, yeah, hey, I want to study genius.
Speaker 1: You know, it wasn't really it wasn't really a legitimate topic.
Speaker 1: I wanted to study creativity and leadership. And first of all,
Speaker 1: they didn't see how they connected. And then it didn't
Speaker 1: help matters that I said, well, they're both connected because
Speaker 1: they both are related to genius, which made it sort
Speaker 1: of worse better because it's been a long time since,
Speaker 1: you know, genius or greatness or anything like that has
Speaker 1: been used in psychology. I think Terman was the last
Speaker 1: person you know, back in the nineteen fifties, and it
Speaker 1: wasn't a good connotation really, yeah, yeah, right, And creativity
Speaker 1: at that time was already kind of seen as a
Speaker 1: dying field, you know, essentially the big thing with Gilford
Speaker 1: and divergent thinking tests and all that kind of stuff
Speaker 1: kind of maxed out. And there I think the fundamental
Speaker 1: problem for me at that time, and why I thought
Speaker 1: this all fit with social psychology, is that I wanted
Speaker 1: to study people who actually exerted a big impact, people
Speaker 1: were influential. That's why for me, creativity and leadership were connected,
Speaker 1: because creators, really big creators you know, are sometimes called
Speaker 1: big C creators, are in fact leaders in their field.
Speaker 1: They're exerting just a different form of leadership, cultural leadership
Speaker 1: instead of political or military leadership. So I had a
Speaker 1: really hard time find anybody who wanted to mentor me.
Speaker 1: But I was very very lucky that they just hired
Speaker 1: a brand new PhD, David Kinney, and even though he
Speaker 1: had no real interest in the substantive side, of what
Speaker 1: I was interested in doing for my thesis. He was
Speaker 1: very curious about the methodology because I was going to
Speaker 1: be using econometrics, and nobody in psychology uses econometrics, right,
Speaker 1: And I was using econometrics because it was the ideal
Speaker 1: methods for the questions I want to address in my dissertation.
Speaker 1: And so and by the way, as you mentioned, David
Speaker 1: k just last year got the Distinguished Scientific Contribution Award
Speaker 1: after many, many years of effort. So he got it
Speaker 1: largely because of his mythological contributions. So that really helped
Speaker 1: because he was willing to supervise me. If you can't
Speaker 1: find something to supervise your thesis, you're dead in the
Speaker 1: water as a doctoral students. True, you know, well that
Speaker 1: approach turned into what you call the historiometric approach, the
Speaker 1: storiometric approach. At what point did you start to do
Speaker 1: that use the historiometric approach? And can you tell me more?
Speaker 1: Can you tell our listeners who probably have never heard
Speaker 1: of it, what that entails. Well, it's kind of interesting
Speaker 1: because it turns out histeorometry it's been around for a
Speaker 1: long time. The term was actually coined in the early
Speaker 1: part of the twentieth century to describe any kind of
Speaker 1: method where you take historical and biographical data, you quantify
Speaker 1: it and then subject it to sophisticated statistical analysis like
Speaker 1: multi ard analyzes and structural equation models and things like that.
Speaker 1: And when I did my dissertation, I hadn't heard of
Speaker 1: the term, so I just called what I did archival
Speaker 1: data analysis. But archival data analysis is too broad. It
Speaker 1: encompass a lot of things, and they're not necessarily historiometric.
Speaker 1: Just like going into the archives of a library to
Speaker 1: find out which books are checked out more often. That's
Speaker 1: not really history metric, but it's archival. For archival data
Speaker 1: to be historometric, it has to be data that has
Speaker 1: actual historical value, like major achievement, major creative masterpieces, artworks,
Speaker 1: major battles that were fought, things like that, things that well,
Speaker 1: things that achieve greatness and will in a particular domain,
Speaker 1: and so much greatness that they literally go down in
Speaker 1: history in the animals in terms of major achievements. So
Speaker 1: I learned that this very obscure guy, Frederick Wood, no
Speaker 1: one knows who he was. It was just a behavior geticist.
Speaker 1: He coined this term, and he pointed out that people
Speaker 1: had been doing histormetry historometry for a long time, but
Speaker 1: they never called it that. Like Francis Galton, he considered
Speaker 1: to be histometrician. And actually I found somebody who was
Speaker 1: doing histeometrics in eighteen thirty five, which makes his geometrics
Speaker 1: the oldest method used in the behavioral sciences before laboratory experiments.
Speaker 1: But that's a good point. Yeah, this guy is Catla
Speaker 1: and he's more famous for inventing the BMI index and
Speaker 1: also introducing the normal distribution, which he described he said
Speaker 1: would describe individual differences. But he also did this classic
Speaker 1: study and it's still valid today. I mean, he introduced
Speaker 1: all these control and whatever to look at the relationship
Speaker 1: between age and achievement to see whether or not there
Speaker 1: was a peak. And then I decline. He focused on
Speaker 1: the number one dramatists in the French and English dramatic
Speaker 1: traditions because they're very big and with lots of really
Speaker 1: outstanding examples like Moliere and Shakespeare. And that's the first
Speaker 1: and I was published in eighteen thirty five. And what
Speaker 1: I think is really amazing is there were studies that
Speaker 1: were published since his that didn't introduce other mythological controls
Speaker 1: that he introduced. So we don't always progress. Sometimes we regress. Anyway,
Speaker 1: once I realized that there was a term for it,
Speaker 1: and I realized that because I mentioned Lewis Urman earlier
Speaker 1: where he did the Genetics Studies of Genius. A lot
Speaker 1: of times people forget that volume two of Genetic Studies
Speaker 1: of Gnientry, which was published by graduate students of his.
Speaker 1: Catherine Cox did not actually look at his intellectually gifted children.
Speaker 1: She looked at three hundred and one actual geniuses in
Speaker 1: Western history. These were famous generals like Napoleon, famous musicians
Speaker 1: like Beethoven, famous artists like Nicolangelo, and studied not only
Speaker 1: their intelligence but also their personality characteristics. And she called
Speaker 1: what she was doing histrometry. Oh wow, someone I realized,
Speaker 1: and that was good for me because I was trying
Speaker 1: to validate what I was doing. And I said, well,
Speaker 1: this is old stuff, you know, it's already been around
Speaker 1: for now over one hundred years. So yeah, Cox did
Speaker 1: some really good work. I think that she should get
Speaker 1: more credit than Sherman sometimes. Yeah, well, I have a
Speaker 1: paper that just came out in the Gifts Child Quarterly
Speaker 1: where I review entire history of that volume, both the
Speaker 1: anti Satans and also subsequent influences on the field, including
Speaker 1: its influences on me, and what's kind of said about
Speaker 1: that book in some respects is sometimes termining its credit
Speaker 1: for it because it was just the volume and genetic
Speaker 1: studies of Genius. So he is the author of the
Speaker 1: entire series, but she is. That's the only volume that
Speaker 1: he is not co author on, only her. And sometimes
Speaker 1: you'll see on the Internet you'll see someone quote IQ
Speaker 1: estimates for various famous people. You can just go ahead
Speaker 1: and google like Mozart IQ and you'll get her i
Speaker 1: Q estimates, but on some sites are listed as uraments
Speaker 1: and not as hurts So and part of that is
Speaker 1: that he estimate is her estimate higher than Turman's estimate
Speaker 1: actually was one of the raiders I have checked out.
Speaker 1: I don't know, well, I think it's interesting is that. Uh.
Speaker 1: One of the reasons why I've been kind of an
Speaker 1: advocate for her is because I think she is very,
Speaker 1: very neglected, and it was the sophistication of what she
Speaker 1: did did was his off and overlooked. She had three
Speaker 1: independent raiders to rate the IQ scores herself termin and
Speaker 1: then mod Merrill, who was responsible for a later revision
Speaker 1: of the Stanford Rene. So these weren't dumb people where
Speaker 1: it's just you know, undergraduates who were told here, here's
Speaker 1: a scoring sheet. What always struck me about those ratings
Speaker 1: is Mozart didn't come out pretty. It didn't come out
Speaker 1: that high IQ. Yeah, I mean, he didn't come out
Speaker 1: as high as maybe you might think. But you got
Speaker 1: to remember that most of the information about Mozart where
Speaker 1: he would score high on has to do with musical precocity.
Speaker 1: And what's interesting is that there was actually a study
Speaker 1: done of Mozart that was published in Transactions of Philosophical
Speaker 1: Transactions in seventeen seventy when Motes and this was a
Speaker 1: study done of start Mozart and his father Leopold were
Speaker 1: visiting London on a concert tour and this guy, this scientist,
Speaker 1: heard about this incredible child apology and decided to give
Speaker 1: him a bunch of a bunch of tests to see
Speaker 1: how for coaches he actually was. And what was interesting
Speaker 1: is like one was a side reading thing, how good
Speaker 1: at your seg reading music? And Mozart when it came
Speaker 1: like anything musical, was better than his dad. So in
Speaker 1: that respect. He had a very high IQ, but when
Speaker 1: he wasn't seeing it at a keyboard, he was no
Speaker 1: different than a typical eight year old. If if he
Speaker 1: was paying at the piano and a favorite key walked
Speaker 1: into the room, he needily dropped everything and mean to
Speaker 1: go and pet the cat, or he would he'd hop
Speaker 1: around the apartment on a hobby horse, you know, tending
Speaker 1: he was a calorie miner or something. I don't know,
Speaker 1: And so in terms of metal development, he wasn't really
Speaker 1: that precocious, except when the King too Music saw where
Speaker 1: I think I Q introduct kind of being lowered a
Speaker 1: little bit. I like that explanation. You know, Well you
Speaker 1: see that a lot with prodigies, you know, yeah, you
Speaker 1: see it. It's like yeah, going. I mean, you have
Speaker 1: this kind of you know, the Savat syndrome where the
Speaker 1: disparity is huge, and then you have the prodigies that
Speaker 1: come somewhere in between where they're not, you know, totally
Speaker 1: slow in their development, but there's still nowhere near their
Speaker 1: their talent happens to be. You know. Another famous example
Speaker 1: of that is William James Sidis, who you know, when
Speaker 1: he started Harvard at I think was thirteen he delivered
Speaker 1: a presentation in higher level of mathematics in front of
Speaker 1: the math club that just blew everybody away. But when
Speaker 1: he wasn't talking about math, he walked around like a
Speaker 1: little kid, like he didn't belong in Harvard Yard, you know.
Speaker 1: So and that was and that ruined him because he
Speaker 1: couldn't adjust, you know, to his classes. They've already looked
Speaker 1: at him like he didn't belong in the classroom, even
Speaker 1: though he could, he could do the work, but he
Speaker 1: couldn't interact socially. I think that's so so interesting. Just
Speaker 1: there something so human about that. You know, we're all human, uh,
Speaker 1: you know. And there's multidimensionality and also it speaks to
Speaker 1: the multi dimensionality of us and and test scatter, all
Speaker 1: these things that you don't you don't get captured by
Speaker 1: a global IQ score. Right. Well, you know your career,
Speaker 1: you've you've done so many different approaches to get at
Speaker 1: this question about genius, the science of genius, science of greatness.
Speaker 1: You've published laboratory experiments, mathematical models, computer simulations, meta analyses
Speaker 1: likeometric investigations, secondary data analysis, single case studies, and interviews.
Speaker 1: You know, what is it that compels you to do
Speaker 1: use a pluralistic approach, what is it within you? You know, like,
Speaker 1: because not all researchers are so interested in that triangulation. Well,
Speaker 1: I think the main thing is from the very beginning,
Speaker 1: as a grand student I was trying to find I
Speaker 1: would start with the question, and then I'd say, what's
Speaker 1: the best way to answer that question? And most of
Speaker 1: the time I find that the questions I have that
Speaker 1: come up in my head are best answered using histometry.
Speaker 1: So the majority of my empirical studies are histometric, but
Speaker 1: there's sometimes where I want to deal with an issue
Speaker 1: where that does not seem to be the best approach.
Speaker 1: And this is a a petribute true for my theoretical work,
Speaker 1: where I've done computer simulations and mathematical modeling, because what
Speaker 1: you want to do is you set up, you start
Speaker 1: off with a set of assumptions, and then you want
Speaker 1: to work out the implications, and then later on you
Speaker 1: may collect data to test those predictions, but you got
Speaker 1: to first make the derivations from a set of assumptions.
Speaker 1: And so I've been doing mathematical modeling for ages. I
Speaker 1: started off as a chemistry major, and I took all
Speaker 1: these math courses and things like that. And then when
Speaker 1: I became a site major at thein of my junior year,
Speaker 1: I realized that all that math I took wasn't going
Speaker 1: to be useful. When I took stats, even advanced stance,
Speaker 1: I didn't have to do differential equations or you know,
Speaker 1: linear algebra or anything like that. So in a way
Speaker 1: it was kind of a waste. But once I start
Speaker 1: doing mathematical models, all that math that I learned when
Speaker 1: I was a chemistry major then became very very useful.
Speaker 1: So I, in a sense saved the first two years
Speaker 1: of college. That's wonderful. Well, just going back to be further,
Speaker 1: what were you like, you know, in middle school, in
Speaker 1: elementary in elementary school, high school, were you in gifted education?
Speaker 1: Were you really really good at math? What did teacher
Speaker 1: say about you about your promise? Did they say psychology?
Speaker 1: I was considered to be a scientifically talented student, and
Speaker 1: my teachers nominated me for a special when I was
Speaker 1: in junior high school, they nominated me for a special
Speaker 1: metropolitan wide this is in Los Angeles Metropolitan wide program
Speaker 1: for the scientific gifted. Turned out not that the ex
Speaker 1: fund as I thought it would be. You know, I
Speaker 1: had a commute across town and basically just do a
Speaker 1: bunch of laboratory experiments where you are already knew what
Speaker 1: the result was going to be, you know, like proving
Speaker 1: the gas law or something, and which I already knew
Speaker 1: I was going to turn out, but they wanted to
Speaker 1: see whether or not you could replicate it, you know,
Speaker 1: so you have you kept lab notes and whatever. So
Speaker 1: it was nothing really creative about it. But the main
Speaker 1: point is, both in junior high school and high school,
Speaker 1: I did see the reward for being top of my class,
Speaker 1: not math though, in social science and in the natural
Speaker 1: sciences and also English of all things. So I was acknowledged. Uh,
Speaker 1: I wouldn't consider myself gifted in a way that like, uh,
Speaker 1: some of the mathematical gifted people are, you know, and
Speaker 1: like the study of mathematic gifted it well, johns Hopkins
Speaker 1: and now Sad Vanderbilt, I mean those people, I mean,
Speaker 1: those guys are and Dallas are astonishing and and of
Speaker 1: course now some of them are now old enough that
Speaker 1: we they've become genius adults, you know, So it's uh,
Speaker 1: those people are off the map. In fact, just just
Speaker 1: to put it in perspective, the way I like to
Speaker 1: put it is, I took a physics class in high
Speaker 1: school and I was able to get a's in physics
Speaker 1: just by doing the problem sets and attending electors. Okay,
Speaker 1: So I was pretty proud of myself. But there was
Speaker 1: another guy in that class who the teacher realized, whoa
Speaker 1: you you just study what you want to study, okay,
Speaker 1: and turn in whatever you want to turn in. And
Speaker 1: he just gave him an automatic A without doing any
Speaker 1: of the tests and without doing any of the uh
Speaker 1: the sets. And that guy went on to cal Tech.
Speaker 1: So I mean he was he he was with brain.
Speaker 1: So that's the difference between being good in science and being,
Speaker 1: you know, a child prodigy. And so very fact that
Speaker 1: the physics prop would say, our instructor, you're on your own,
Speaker 1: do what you want. Do you need to be a
Speaker 1: child prodigy in order to be that good someday? Like
Speaker 1: are you allowed to be a warmer? You know? That's
Speaker 1: That's the thing that a lot of people sometimes forget
Speaker 1: is a lot of child prodigies don't grow up to
Speaker 1: become genius adults. Uh. They will often go through various struggles,
Speaker 1: not just because of preps social issues, but sometimes they
Speaker 1: have problems actually eventually finding what they want to do.
Speaker 1: David Filman did this interesting study of child prodigies and
Speaker 1: a lot of them were phenomenal, but they didn't stay
Speaker 1: in the same domain, and they went from one area
Speaker 1: to another area, to another area to another area. Some
Speaker 1: of them finally found their thing whatever they turned him
Speaker 1: on and then developed the necessary expertise. We still have
Speaker 1: to develop the expertise. Being a child code, it just
Speaker 1: enables you to acquire the expertise faster, right, But you
Speaker 1: know they not everybody found their thing, And a good
Speaker 1: example of that is William James Cittis. He never really
Speaker 1: found his thing. The only reason why he went into
Speaker 1: mathematics is because he was pushed by his dad, or
Speaker 1: as Citists who was a famous psychiatrist. But he didn't
Speaker 1: really want to do it. As soon as he got
Speaker 1: a chance, he got out of math. You know, that
Speaker 1: was dad's you know a thing. In fact, correctly, he
Speaker 1: didn't even go to his dad's funeral. He was so oppeeved. Wow,
Speaker 1: Well but what about the okay, so what about the reverse?
Speaker 1: Like can you not be a child prodigy and be
Speaker 1: it become a genius? Yeah? I mean that happens all
Speaker 1: the time. I mean, for example, Beethoven wasn't really a
Speaker 1: child prodigy. His dad tried to sell him as a
Speaker 1: child prodigy. He tried to make him into a Mozart.
Speaker 1: And fact, his dad evidently actually lied about Beethoven's age
Speaker 1: and said that he was two years younger than he
Speaker 1: actually was, so that he would seem more like a prodigy.
Speaker 1: And the thing is, he Beethoven never found this out
Speaker 1: until there was a legal issue. He was he was
Speaker 1: fighting for a custody of his nephew and they had
Speaker 1: to get some records like his birth records and stuff
Speaker 1: back in uh Bond that's where it was where he's born.
Speaker 1: And uh he said, be careful because it can cause
Speaker 1: confusion because there I have an older brother who was
Speaker 1: two years older than me, and he's he's passed away now,
Speaker 1: but he's also got the same name, so you got
Speaker 1: to get the right verse certificate. Well, they finally told them,
Speaker 1: we hate to tell you a little bit that you
Speaker 1: didn't have an older brother, so you're so. So the
Speaker 1: point is to get back to your original question, is
Speaker 1: that Beethoven was wasn't really a child pody. I mean
Speaker 1: he was he was competent very early in but not
Speaker 1: not anymore. A lot of musicians are relatively early when
Speaker 1: they find their thing. I mean, there's this program on
Speaker 1: public radio called From the Top where they interview these kids,
Speaker 1: you know, and they and there some of them are like,
Speaker 1: you know, thirteen. I think the youngest I've ever heard
Speaker 1: is like seven. And you know, because of the Suzuki
Speaker 1: method or whatever, they can master of violin at a
Speaker 1: very young age. But you know, you're not composing yet.
Speaker 1: They're not yet what we would consider to be adult virtuosi.
Speaker 1: So you do have a certain amount of precocity in
Speaker 1: music that's fairly common, but child pologies are relatively rare,
Speaker 1: even even in music, and Beethoven was definitely not a chipology.
Speaker 1: That's very interesting, you know, I just trying to understand,
Speaker 1: you know, where these things come from. Yeah, I know
Speaker 1: you spent your career trying to stay this. I really
Speaker 1: liked your work kind of talking about how genes need
Speaker 1: to sync up sometimes, you know, it's like the late
Speaker 1: like late bloomers can can burst on the scene when
Speaker 1: when certain genes that take many years, like sometimes you
Speaker 1: might have genes that code for certain traits that make
Speaker 1: you appear awkward at a certain age, and then you
Speaker 1: get to a certain age where it all kind of
Speaker 1: gels together, and then it appears as those own burst
Speaker 1: on the scene. I remember, you know, adopting some of
Speaker 1: your work along those lines in a in an article
Speaker 1: I wrote for psychology, my first ever article for a
Speaker 1: psychology for the for the public, general public. It was
Speaker 1: Confessions of a late Bloomer, where I drew it brought
Speaker 1: in a lot of your work on that. But in
Speaker 1: addition to genes, you know, like it's it's it's obviously
Speaker 1: like its nature via nurture, right, So what you know,
Speaker 1: do you just after studying it for so many years,
Speaker 1: do you feel like you have a do you get it?
Speaker 1: Do you feel like you get where genius comes from?
Speaker 1: I don't know about that, you know, yeah, yeah, I
Speaker 1: mean to me, it's it is a complex interaction between
Speaker 1: the environment and your generic genetic development, and it is
Speaker 1: rendered more complex for what you said is that we
Speaker 1: now have appreciated that a lot of teens don't fully
Speaker 1: manifest themselves until you're a lot older. So you may
Speaker 1: get a pretty good dove telling at one age, and
Speaker 1: then that dove tailing doesn't work later on, and sometimes
Speaker 1: it just may be some capricious event. One of my
Speaker 1: favorite examples we actually did that TV show together on
Speaker 1: late Bloomers, And one of the examples that I like
Speaker 1: to give is a Austrian nineteenth century composer, Anton Bruckner,
Speaker 1: who was a real, real late bloomer. He wasn't a
Speaker 1: late bloomer in terms of learning music. He always wanted
Speaker 1: to be a musician. He studied music a lot, but
Speaker 1: he only wanted to be a religious composer. He posed
Speaker 1: a lot of masses and hymns, and he was very,
Speaker 1: very religious, very it's about Ron mccathleen. Uh. He played
Speaker 1: Oregon in the Cathedral and all that kind of stuff.
Speaker 1: But he wasn't he didn't stand out he had he
Speaker 1: showed no talent. He couldn't find his thing. And then
Speaker 1: one time he went to see an opera by Richard Wagner,
Speaker 1: and all of a sudden he just had this epiphany
Speaker 1: that he wanted to write symphonies that sounded like Bogner operas,
Speaker 1: but without seeing you know, but the big orchestras and
Speaker 1: tubas and all this kind of stuff. And he actually
Speaker 1: the first chance he got when he met Wagner. He
Speaker 1: just grabbed him around his knees and it says, master,
Speaker 1: I worship you. It was really kind of crazy, I
Speaker 1: should say. There were a lot of things that were
Speaker 1: nuts about Bruckner, not just the way he treated Wagner.
Speaker 1: I mean, he loved to go to funerals because they
Speaker 1: had this obsession with looking at dead bodies. And he
Speaker 1: would only propose to girls who are a lot too
Speaker 1: young for him. So he never married. Okay, so he
Speaker 1: had a lot of weird things about him. But this
Speaker 1: fascination with Wagner changed his life. And so in his fifties,
Speaker 1: that's kind of a late start, he starts composing symphonies.
Speaker 1: And at first it took him a while, because you know,
Speaker 1: even though he's old, older and more mature, and he's
Speaker 1: composing it for a long time or too a while
Speaker 1: to finally get together into what it's sort of a
Speaker 1: typical sound of a book Mary and symphony. And later
Speaker 1: on he had a big influence and mother and so forth.
Speaker 1: But the point is if there had been no Wagner,
Speaker 1: there would be no Brokener. If I would daft, you
Speaker 1: would He needed to encounter that sound, that specific sound,
Speaker 1: and I don't know what it rang in his you know,
Speaker 1: his genetic makeup, because you know, part of it is
Speaker 1: just you know, there's a certain genetic tendency for being
Speaker 1: able to hear certain sounds, or taste certain tastes, or
Speaker 1: you know, smell certain smells of what happens to be.
Speaker 1: You know, I one interview with this major chef who
Speaker 1: says she doesn't understand why people put silantro in anything
Speaker 1: because she can't even smell it. And she's a chef,
Speaker 1: you know, but genetically she doesn't have whatever it is
Speaker 1: necessary for smelling that particular herb. So so get back
Speaker 1: to the the original question. There's something happening there where you
Speaker 1: have this dovetailing and a lot of times it doesn't
Speaker 1: come together. And so that's one reason why the mouth
Speaker 1: potential talent that becomes genius is a is a very
Speaker 1: small percentage. You know, the hit rate is very very low.
Speaker 1: If you if you if you think of let's say
Speaker 1: the number of talents each generation they become a Michelangelo
Speaker 1: or a Newton or whatever, is maybe ten percent. The
Speaker 1: actual percent is much smaller than that. You know, he
Speaker 1: needs to make it one percent. The actual percentage is
Speaker 1: smaller than one percent. So I fact, Galton even estimated it.
Speaker 1: I forget what he came out to be, but he
Speaker 1: estimated what what the shrink age is basically, even though
Speaker 1: he felt that you would if you had any kind
Speaker 1: of genius, you had inevitably become famous. But we know
Speaker 1: that's not true, well especially not true in the modern
Speaker 1: age of technology. With YouTube stars and Instagram stars. You know,
Speaker 1: would you say that they're all geniuses? Maybe they're they're
Speaker 1: beyond popular. There's there's a difference between popularity popularity is
Speaker 1: there is there a difference between popularity and genius, you
Speaker 1: know in this modern age? Well, that's an interesting question.
Speaker 1: You know a lot of technology while all this technology
Speaker 1: is so very new that you know, it's harder to
Speaker 1: how it's going to pan out towards the end. Are
Speaker 1: we going to have TikTok geniuses that are going to
Speaker 1: go down the annals of history or are not? I
Speaker 1: read a very interesting article in the New York Times
Speaker 1: about TikTok artists and how they face a real big
Speaker 1: problem that once they get recognized, so they start getting
Speaker 1: the following, and of course you can see how big
Speaker 1: your following is. Uh, two things can happen to you
Speaker 1: that undermine me. The first thing, you're in a tons
Speaker 1: of pressure to keep your audience interested. So you got
Speaker 1: to do another work and another work and another work
Speaker 1: and not repeat yourself. And it's as a tremendous amount
Speaker 1: of pressure to try to do that. And of course
Speaker 1: what the same kind of pressure happened, you know at
Speaker 1: a time of Beethoven, in a time of Nicolange, you
Speaker 1: just couldn't repeat yourself, but you were allowed a year
Speaker 1: or two in between work. But now, I mean on
Speaker 1: the internet, you know, the next day people are saying,
Speaker 1: what do you have for me? Now? You know, what
Speaker 1: do you have for me today? The other problem that
Speaker 1: the TikTok genius's artistic genius is space is that it's
Speaker 1: they get imitators very fast. So when you catch on,
Speaker 1: then somebody says, oh that's hot, and so they will
Speaker 1: start their own imitation of you and pull away from
Speaker 1: your audience unless you can figure some way of pulling
Speaker 1: them back. So the net result of this is that
Speaker 1: TikTok artists have a very short career. It's very hard
Speaker 1: for them to maintain themselves longer than I don't know
Speaker 1: if they've actually calculated their average, but your current to
Speaker 1: be over by the end of the year, you know.
Speaker 1: And one of the characteristics of genius is that they
Speaker 1: display a lifetime of creativity, a lifetime of productivity, and
Speaker 1: TikTok artists can't do that right now. If there's something
Speaker 1: about the genre that makes it so, it's it's inherently
Speaker 1: transient form of thing, and so I think, you know,
Speaker 1: that's that's going to be the norm, but I don't know,
Speaker 1: you know, and this other thing that's happening with it
Speaker 1: anti Oh see, there's a three letters, it's an anagram. Well,
Speaker 1: you get some some chips. It's a very common little thing,
Speaker 1: and you pay, like, you know, fifty dollars for it
Speaker 1: because it has some little part of it that says
Speaker 1: that this is the only copy and you own it.
Speaker 1: And yet it looks like anything else. You can't tell
Speaker 1: the difference except that one little part of the code
Speaker 1: that says that you paid for it. So what does
Speaker 1: that tell you? I mean, this is here, here's something
Speaker 1: that is deliberately not new, and yet you become an artist.
Speaker 1: I don't think that's gonna last for a long either.
Speaker 1: So I don't know. Maybe even in a stage where
Speaker 1: things haven't really worked themselves through to find out what's enduring.
Speaker 1: Let's just give you example of where it has become enduring.
Speaker 1: I'm not a big gamer. My stepson is big gamer,
Speaker 1: so you can say more about this than I can.
Speaker 1: But one of the things that happened when gaming became
Speaker 1: really big is you started having composers composed music for
Speaker 1: the games. And now these composers are recognizing their own
Speaker 1: right as being creative composent for creative musicians, and you
Speaker 1: can sometimes even hear their music on classical music stations.
Speaker 1: So that's the case where a genre which you would
Speaker 1: think would be pretty transient, but you got to remember
Speaker 1: a lot of these games they go through, you know,
Speaker 1: several versions, and there's there's a big demand for them,
Speaker 1: and the music, just like cinema, music plays a very
Speaker 1: important role in building up the suspense or you know,
Speaker 1: I don't I can't really get more elaborate than that
Speaker 1: because I'm not a gamer. But it is a genre
Speaker 1: that sort of compares to like opera or a musical theater,
Speaker 1: or you know, it's a form of background music or
Speaker 1: some other form of creativity. You know, I think of
Speaker 1: about one hundred years from now, the future Dean Keith
Speaker 1: Simonson in that generation is going to have to maybe
Speaker 1: use a different set of tools, or different set of analyzes,
Speaker 1: or a different set of definitions of genius than you
Speaker 1: have to look at genius in like the nineteenth century
Speaker 1: and twentieth century. Well, yeah, or even like the eighteenth
Speaker 1: st you go all the way back, that's seventeen sixteenth century.
Speaker 1: I feel like there's there's on the horizon a different,
Speaker 1: a whole different conceptualization of greatness, shall we say. That'll
Speaker 1: be interlinked to with technology. Technology, Yeah, sometimes you get
Speaker 1: to the same place by different means. I mean. One
Speaker 1: of the things I think really impressive right now is
Speaker 1: big data. And so there are these data projects where
Speaker 1: instead of what I used to do with oh, I'll
Speaker 1: take everybody who's in a biographical dictionary or in encyclopedia
Speaker 1: or whatever that's my criterion, they'll take everybody. You know,
Speaker 1: there's one study of scientific creativity that basically took everybody
Speaker 1: who had any kind of scientific career all and that
Speaker 1: includes nobel laureates in who's all noble laureates, but also
Speaker 1: a lot of people who never made it big. So
Speaker 1: they can actually do something I couldn't do. Go all
Speaker 1: the way to start at the very bottom of the
Speaker 1: distribution and see what people had to do to get
Speaker 1: their Nobel prize, you know. And what's interesting though, is
Speaker 1: the end up with the same conclusion that I had.
Speaker 1: Using different sources. They found that the number one predictor
Speaker 1: of when you came up with your let's say, your
Speaker 1: Nobel Prize winning research is the total amount of publication
Speaker 1: as you've produced. So the more prolific you were, the
Speaker 1: higher the probability. It's it's I call it. I call
Speaker 1: it the equods yeah, Ecoods rule. They call it the
Speaker 1: random impact rule. The same rule. It's the same rule.
Speaker 1: And in fact, they later on acknowledged it. They sign
Speaker 1: a paper that published and seche review and they had
Speaker 1: overlooked that and I I totally look back to that paper,
Speaker 1: talk about the equalods rule there, and that's your random
Speaker 1: impact rule. I don't want It's not a priority dispute
Speaker 1: or anything. But the point is is that using an
Speaker 1: entirely different method, namely big data, which is not his
Speaker 1: geometric it's actually archive. You're taking basically, you know, the
Speaker 1: Web of Science or Google or whatever, and using that
Speaker 1: to supply your data, and and and that day is
Speaker 1: not collected for historical reasons, is collected first scholarship, you know,
Speaker 1: to find out who's doing work on what, whose side too,
Speaker 1: and all that kind of stuff. So but at the
Speaker 1: same time they end up with the same conclusion that
Speaker 1: I end up. So they end up replicating. Well, they
Speaker 1: also came up some odeclusions that I didn't come up with,
Speaker 1: because they can do much more, you know, fine detail analysis.
Speaker 1: Given there are huge ends. I mean, they have ends
Speaker 1: that just boggle the mind. Yeah, I just want to
Speaker 1: explain to our audience who who might be a little
Speaker 1: bit lost right now about what the what this rule
Speaker 1: actually means in everyday parlance the way I say it,
Speaker 1: and I give talks some times to say, here's the
Speaker 1: secret to creative genius. Are you ready to get out
Speaker 1: your pen? Create? Create, create, create, create, create, create, create, create, create, create, create, create,
Speaker 1: create And basically the point there, you know, is that
Speaker 1: the more that you keep producing you know, trial and errors,
Speaker 1: whether if it's scientific creativity, you know, trial and error,
Speaker 1: you know, artistic creativity, keep expressing yourself over and over
Speaker 1: in many different ways, the higher the probability that someday
Speaker 1: one of them will be a masterpiece. Is that the
Speaker 1: cooquial fair way of describing it. Yeah, But you got
Speaker 1: to remember, it's not like you're deliberately trying to produce trash,
Speaker 1: trying to trash. It's just that any given you work
Speaker 1: of art or work of science is a very very
Speaker 1: complex thing, very complex product, and a lot of different
Speaker 1: things have to come together, and sometimes it just just
Speaker 1: doesn't quite work. You know. So a Beethoven Sports Symphony
Speaker 1: is a very nice symphony, but it's not playing anywhere
Speaker 1: near as often as his third or a s fifth
Speaker 1: because it's just doesn't I come together as a masterpiece.
Speaker 1: You know. You play it, orchestras play it largely because
Speaker 1: audiences are tired of hearing a third and the fifth,
Speaker 1: so you want to hear something in between, you know.
Speaker 1: But here's an interesting study that was done. I actually
Speaker 1: cite this in my Origins of Genius, which I think
Speaker 1: it is fascinating. This guy wanted to study to find
Speaker 1: out what would what is the fact that enables someone
Speaker 1: to become really creative in ceramics. So he had two conditions,
Speaker 1: two independent conditions, you know, a random assignment to two groups.
Speaker 1: All that kind of stuff. In one group, his students
Speaker 1: were told, okay, you have all term or quarter or
Speaker 1: whatever it was to produce a single masterpiece, a single ceramic,
Speaker 1: and so go to it. And so people will start
Speaker 1: working away, and a lot of times they just think.
Speaker 1: A lot of times, well, I got to come up
Speaker 1: with some idea first before I go to the potter
Speaker 1: wheel or whatever. In the other condition, he said, your
Speaker 1: grade is to be based on the total weight of
Speaker 1: the ceramics superdeers. And then at the end of the
Speaker 1: term he did something that he didn't tell him about.
Speaker 1: In the second group, he took the He had raiders
Speaker 1: pick out the best stuff of the big pile of
Speaker 1: ceramics that was produced to the wine class, and they
Speaker 1: didn't know what condition it was in, and the raiders
Speaker 1: rated the things from the productivity group. It's more creative
Speaker 1: than the ones who were supposed to be perfectionists, you know,
Speaker 1: just focused on one single afterpe. So there's an example
Speaker 1: of the equal odds rule working for you. Well, that's interesting,
Speaker 1: you know, how how to reconcile that with you know,
Speaker 1: the popularity of the concept of grit, you know, like
Speaker 1: one of the facets of grit is consistency of interest.
Speaker 1: That's on Angelo doctors grit scale. It seems like a
Speaker 1: lot of creators have a diversity of experiences. But you know,
Speaker 1: before you answer this question, I think that all because
Speaker 1: I know what you're gonna say, but because it's just
Speaker 1: so I know, I know. But there's a I feel
Speaker 1: like there's a more general pattern with all this stuff,
Speaker 1: is that there's just when you talk about creativity, there's
Speaker 1: paradoxes inherent. You know, there's you know, there's always like,
Speaker 1: well this is true, but then this seemingly opposite is
Speaker 1: also true. You know. So now I'll let you give
Speaker 1: your answer, But I feel like that's, you know, just
Speaker 1: like there's an overall pattern here with all these kinds
Speaker 1: of questions. I mean, as you know, one of the
Speaker 1: chapters and my Genius Checklist has to do with this paradox.
Speaker 1: I know. That's why I know the research. Yeah, you're
Speaker 1: a great, great blurb for that. By the way, of
Speaker 1: my favorite blurbs history anyway, one of the paradoxes is
Speaker 1: that one of the number one predictators created genius. And
Speaker 1: by the way, it's also predictor of leadership as well,
Speaker 1: like in presidential leaders is openness to experience, having a
Speaker 1: lot of interest, a lot of hobbies, willing to try
Speaker 1: out new ideas, and and being well versed in uh
Speaker 1: areas far removed from your actual domain. I mean a
Speaker 1: good example of that is the work that the ruth
Speaker 1: Ernstein's have done on Nobel laureates and found that the
Speaker 1: higher you are in the hierarchy of scientific achievement, they're
Speaker 1: more likely you are of having artistic hobbies. You know,
Speaker 1: maybe your painter or a photographer or whatever. And that's
Speaker 1: obviously going to be irrelevant to you know, working out
Speaker 1: the equations for some theory and quantum theory. But on
Speaker 1: the other hand, you do have to have this persistence,
Speaker 1: you know, this drive. So you know, you look at
Speaker 1: how long you know, Einstein worked on relativity theory and
Speaker 1: the unified field theory. It takes a tremenus amount a
Speaker 1: persistence and stick to limit in this. But it also
Speaker 1: knows you have to know when to quit, because you can,
Speaker 1: you know, you can become a drudge. It'd be very
Speaker 1: very persistent, and you've done yourself into a hole and
Speaker 1: you've got to get out of that hole to be
Speaker 1: able to find out if there's an alternative way. And
Speaker 1: you know, there's all sorts of research on this, you know,
Speaker 1: with a role of incubation, you know, and sol and
Speaker 1: things like that, and so it's it's both. You know,
Speaker 1: there was a time when Eystein would be working away
Speaker 1: on its equations and he finally reached a dead end
Speaker 1: and he says, it's time for me to go sailing,
Speaker 1: or it's time for me to play Mozart Sonatas on
Speaker 1: the violin, you know. And it's not that they gave
Speaker 1: him any ideas, but they but over the mind of
Speaker 1: I mean, who knows when he's on the sew boat
Speaker 1: if there was some kind of stimulus and environment or
Speaker 1: something you overheard conversation in the boat house, I don't
Speaker 1: know that could have you know, provided a seed for
Speaker 1: an idea. So and can I just say one thing
Speaker 1: about the great research that's off and overlooked. Most of
Speaker 1: the domains in which that is applied focus on areas
Speaker 1: that are very well defined, and there's there's a pretty
Speaker 1: established path to how you get to where you want
Speaker 1: to go, you know. I mean I'm a good example
Speaker 1: of that is you know, a military academy. Uh, that's
Speaker 1: that's the thing where everything is over a century, it's
Speaker 1: been set up. This is what you need to do
Speaker 1: if you want to get through the military academy. Right. Uh,
Speaker 1: spelling bees is another one that they've used in studies.
Speaker 1: Well that's another example, you know. Uh, here's a dictionary,
Speaker 1: you know. So yeah, I don't think they've actually done
Speaker 1: anything looking at GRIT with respect to creator geniuses. Do
Speaker 1: you know of anything? So only the research that Angela
Speaker 1: Duckworth and I collected that we never published because we're
Speaker 1: interested in this question, and we did, yes, and we
Speaker 1: found that the the two facets of GRIT had completely
Speaker 1: opposite predictions. So perseverance was very strongly positively quartab with
Speaker 1: our Creative Achievement Questionnaire. However, the consistency of interest facet
Speaker 1: was strongly negatively correlated. Yeah, we should probably publish that someday. Yeah,
Speaker 1: this is the c Q, the c a Q yep, yep,
Speaker 1: yeah yeah, Carson Peterson, yeah right, yeah, but you're going
Speaker 1: to publish that because it's interesting how that buy for
Speaker 1: cakes like that? I think we should. I'm going to
Speaker 1: reach out to Angela again. That's like, I mean, that's like,
Speaker 1: you know, I'm sure you have lots of data just
Speaker 1: like sitting on your computer. That's like you just you're
Speaker 1: like someday I'll get around to it, you know, yeah,
Speaker 1: oh yeah, you know. In fact I had and I
Speaker 1: have I have a graduate student and has a lot
Speaker 1: of data like that too. We're going to co author that. Well,
Speaker 1: that's well, that's that's interesting you bring that up because
Speaker 1: ninety three percent of your publications are single authored, so
Speaker 1: that would be a huge outliar if you did publish
Speaker 1: that with your with her. But everyone while I do coleborate.
Speaker 1: I mean, at the beginning, I couldn't find anybody who
Speaker 1: wanted to do histereometry. And and then once I started
Speaker 1: having graduate students, some of them would do histometric dissertations,
Speaker 1: but most of them not do a dictation topics or
Speaker 1: to get their dissertation and historometry. They would then get
Speaker 1: a post doc and pursue entirely different directions some of them.
Speaker 1: In fact, my two best graduate students, that's what they did.
Speaker 1: They got post docs. So you know, they did the
Speaker 1: dissertations using historiometry. Their current research programs don't. He's htey ametry. Okay,
Speaker 1: And let this example I gave earlier, wone saying, we
Speaker 1: got some really good history metric data you collected. We
Speaker 1: got to publish this, but she's doing something else now.
Speaker 1: It's almost like, you know, forcing her to regress to
Speaker 1: when she was a graduate student. So it's hard to
Speaker 1: get people to want to do what I do. So
Speaker 1: a lot of the collaborations I end up working on
Speaker 1: is where someone says a good example of this. I
Speaker 1: don't know if you've seen a study, but back in
Speaker 1: nineteen eighty five I published a article in Psychological Review
Speaker 1: which was a theory of the relationship between intelligence and
Speaker 1: influence in groups, and I show that under a certain
Speaker 1: set of circumstances having to do with a relationship between
Speaker 1: intelligence and problem solving and the relationship between intelligence and
Speaker 1: communication style, that there was a curve related relationship inverted
Speaker 1: you relationship between intelligence and your influence in the group.
Speaker 1: And it actually made a very precise prediction. It predicted
Speaker 1: that the optimal IQ would be one point two standard
Speaker 1: deviations above the mean IQ for the group. If we
Speaker 1: don't have too many point predictions and psychological theory in
Speaker 1: any case, I had a guy at the University of
Speaker 1: lasan And in Switzerland who said, I caught this some
Speaker 1: very interesting data they find this current line a relationship.
Speaker 1: And I was trying to find if there's any prior
Speaker 1: research on this topic, and I came across this paper
Speaker 1: that you published right back in nineteen eighty five, and
Speaker 1: it looks like my data supports your theory. And he says,
Speaker 1: do you want to kind of call author on this?
Speaker 1: And because he wanted somebody to want to want somebody
Speaker 1: responsible to the theory part in the introduction, and it's
Speaker 1: an amazing study. It looks at middle managers in a
Speaker 1: lot of businesses and uses a standard intelligence test s
Speaker 1: he want us to use for football players and one
Speaker 1: point to standard nations. And we have all these robust
Speaker 1: tests and significance tests to prove that the slope becomes
Speaker 1: negative right after one point two uh at the confidence
Speaker 1: interval is beautiful. And so when he's when he asked
Speaker 1: me to collaborate on that, and just ended up being
Speaker 1: published as a lead article in the Journal of Applied Psychology.
Speaker 1: So it's one of my best papers. I mean, I'm
Speaker 1: third author on it, Okay, because I didn't collect the
Speaker 1: data and I didn't do the analysis. I just provided
Speaker 1: the theory kind of retrospectively. You know. So that's an
Speaker 1: example where I'm I'm basically collaborating simply because I'm on
Speaker 1: somebody's study, I'm writing their works. Yeah, no, I got you.
Speaker 1: You're just you're very unusual in the field in in
Speaker 1: how many Well, first of all, how many publications you
Speaker 1: have period? But then how many are single authored? It's uh,
Speaker 1: it's it's it's remarkable. I mean, I I've just I've
Speaker 1: had conversations with James Kaufman and I know you know him.
Speaker 1: But for our listeners, a very prominent creativity research and
Speaker 1: we we're so puzzled how you even like, like, how
Speaker 1: do you know the math? Like how does it just
Speaker 1: come intuitively to you? Like we look at some of
Speaker 1: your papers and we don't know what the hell you're
Speaker 1: the formulas mean? Like how do you even know what
Speaker 1: those formulas mean? Like where's it come from? Where does
Speaker 1: it come from? With you? Well, well, I told you
Speaker 1: I took many when I was a chmicry major. Yeah,
Speaker 1: so I had the first two years of college. Man,
Speaker 1: I've had you know, your normal capitalists, which takes you
Speaker 1: to your first year, and then uh mecro geometry, linear algebra,
Speaker 1: and different differential equations. And of course I also have
Speaker 1: had advanced statistics as well, so that gave me a
Speaker 1: kind of a head start on it. I've always been
Speaker 1: good at math. I wouldn't say I was talented man,
Speaker 1: but I was someone who'd always get a's as long
Speaker 1: as I did the problem sets. You know, ten a lecture,
Speaker 1: do the problem set, and get an AI exam. You know.
Speaker 1: So I had a certain ability for the mathematics. Sometimes
Speaker 1: sometimes I'm able to and this is something unique to
Speaker 1: histeorometry that I have to mention. One things unique about
Speaker 1: historiometry is that the subjects are historical figures, so you
Speaker 1: can use your subjects over again the same people if
Speaker 1: somebody does a history of mythic study before you. We
Speaker 1: got back to Katherine Cox. Is an illustration. Catherine Cox
Speaker 1: published IQ scores for three hundred and one genius. WHOA,
Speaker 1: this is great. She did some analysis, but not very extensively.
Speaker 1: She was focused on natural estimates and whatever. She calculated
Speaker 1: a correlation between IQ eminence and found that it was
Speaker 1: positive significant, but no detail analysis. And so when I realized,
Speaker 1: wait a minute, she's got this data about these people.
Speaker 1: We already know who they are. I can get further
Speaker 1: biographical information. So one year after my dissertation was published
Speaker 1: in nineteen seventy six, I published a reanalysis of her
Speaker 1: data where I took her IQ scores and then added
Speaker 1: more data of my own. I looked at formal education,
Speaker 1: I looked at socioepandemic class I looked at their versatility,
Speaker 1: and then built a structural model based on that. But
Speaker 1: think about it, it costs me nothing to use her
Speaker 1: IQ scores. Right, that was a free beat, and all
Speaker 1: the data was already available. And I've done a number
Speaker 1: of histometric studies where I've taken on histometric study and
Speaker 1: then I've added more variables to it, so that it's
Speaker 1: sort of like a replication and extent thing. But you
Speaker 1: don't have to collect the data all over again. Well
Speaker 1: what did you find? Yeah, huh, Well, want to tell
Speaker 1: me more about what you found with your re analysis
Speaker 1: of Cox's data? Tell me like the nuances the nuances
Speaker 1: first of all. Actually APUs a couple of studies using
Speaker 1: her data, most recently in psycholoical Science in two thousand
Speaker 1: and nine. A lot of interesting things there. Oh, I
Speaker 1: should add miscisspeck to history elementary again. A graduate student
Speaker 1: of mine found that she had started a data analysis
Speaker 1: that she never completed, and she left the data in
Speaker 1: the archives in Akron, the university, and she found these
Speaker 1: data where she rated her geniuses on physical and mental health.
Speaker 1: And this data had never been used before. Wow. So
Speaker 1: I combine that data again, this is the same people,
Speaker 1: same subjects. Combine that data with her data and the
Speaker 1: data I collected to do some additional analyses, and it's
Speaker 1: a lot of fine. But one of the things very
Speaker 1: interesting I think is that you know, there's this thing about,
Speaker 1: you know, the mad genius controversy, and we know that
Speaker 1: artistic geniuses have higher proclivities towards mental illness. And in fact,
Speaker 1: one study that was done by Arnold Ludwig showed that
Speaker 1: poets were way up there in mental illness. There were
Speaker 1: eighty five percent of poets had some kind of may
Speaker 1: not necessarily clinical, although it often isn't and you can
Speaker 1: a suicide has considered a clinical menalists. But what's interesting
Speaker 1: is that what Cox had done is estimated the childhood
Speaker 1: evidence for a mental illness. And I should say she
Speaker 1: had an interest in this because she was actually a
Speaker 1: child psychologist. She became later and did clinical work with
Speaker 1: young kids and I was able to show that already
Speaker 1: in childhood and adolescents, poets start showing inferior mental health
Speaker 1: comparison to other future geniuses. So it's an early mindset phenomenon. Uh,
Speaker 1: you know, often depression and you know, feeling odd and
Speaker 1: weird and that kind of thing. Uh. And nothing that
Speaker 1: I showed is that there's a dramatic differences in intelligence
Speaker 1: across different groups. So like philosophers tend to be the
Speaker 1: highest in IQ when you think about their professional thinkers,
Speaker 1: it kind of makes sense. On the other hand, the
Speaker 1: group of the lowest IQ are the military leaders. I
Speaker 1: mean with Napoleon. Napoleon didn't come out great writing. You know,
Speaker 1: he would have, he would have made mensa, but he's
Speaker 1: he doesn't stand in the same rate me. You think
Speaker 1: about he's the greatest military leader in modern times, but
Speaker 1: he doesn't come close to Mozart and Beethoven or whatever.
Speaker 1: But that kind of makes sense because if you're a
Speaker 1: military leader, you're you're in fact, actually gets set back
Speaker 1: to the mathematical model military leaders league groups that have
Speaker 1: either average intelligence are below average intelligence. So yeah, data
Speaker 1: on that, and so that means that you want the
Speaker 1: effective leader for that kind of population. You can't talk
Speaker 1: over their heads. If you're going to aspect them, charge
Speaker 1: up to that hill and sacrifice to their life. You know,
Speaker 1: with accountaball, you'd be better be very understandable in your
Speaker 1: you know, raw raw ross speech. Yes, but what about
Speaker 1: like some wouldn't, like a multiple intelligence person say like, well,
Speaker 1: they certainly have leadership intelligence. Yeah, but that was part
Speaker 1: of it. That was part of it because one of
Speaker 1: the things that a lot of people overlook is that
Speaker 1: with Catherine Cox and mod Merrow and termin and I
Speaker 1: kind of meant touched upon this earlier simated IQ scores
Speaker 1: most of their development developmental information. I mean, they're supposed
Speaker 1: to measure intellectual development, but they're not lack measuring digit span,
Speaker 1: you know kind of thing. They're measuring intellectual development that's
Speaker 1: pretty much domain specific. So what that means is that
Speaker 1: when they were seeing the IQ of the leaders they
Speaker 1: were looking at example, early examples of on demonstration of
Speaker 1: leadership ability. So, for example, you do see in Napoleon
Speaker 1: very early him assuming leadership roles even when he was
Speaker 1: just a corporal, and so that was part of the
Speaker 1: IQ estimate. My favorite illustration of that is if you
Speaker 1: compare Pascal with Mozart. Not a single part of Pascal's
Speaker 1: IQ score was based on musical ability because he had none.
Speaker 1: Not a single part of Mozart's IQ score was based
Speaker 1: on mathematical ability because he had none. Yeah, he got
Speaker 1: a very high IQ score, and he got she got
Speaker 1: he got a very IQ score because they were primarily
Speaker 1: rated on things that were even musical. For mathematical Mozart,
Speaker 1: you said, Mozart, Yeah, well, sorry, so I thought I
Speaker 1: thought his estimated IQ was like one hundred though oh no,
Speaker 1: oh no, no I thought it. No, I am his
Speaker 1: higher than that. His IQ was well, first of all,
Speaker 1: there there's four different IQ scores that they estimated, okay,
Speaker 1: up to age sixteen and then sixteen twenty six, and
Speaker 1: then uh corrected the debt relay and then not and
Speaker 1: then raw not correct. We did. Really he was roughly
Speaker 1: around one hundred and fifty. Really, yeah, as around one
Speaker 1: hundred and thirty. No, he was not. Oh no, that's
Speaker 1: an insult. Mozart was born the same day I was,
Speaker 1: So you can't rag on mostart. I'm certainly not regging.
Speaker 1: I thought that when I had looked at there was
Speaker 1: so I thought there were some surprises. I remember when
Speaker 1: I looked at that data, there were some geniuses who
Speaker 1: had very average IQs, and maybe maybe I'm not it
Speaker 1: was but La Fontaine, the French fablist. I have an
Speaker 1: IQ which is barely above average. I think it was
Speaker 1: one hundred and five something around there. I remember it
Speaker 1: struck me. Yeah, okay, you stay there, Okay, I will,
Speaker 1: I will. I'm I'm curious about the Mozart one because
Speaker 1: I'm pretty sure it was like not that high. Okay,
Speaker 1: this is this is my bible, Okay, I love that.
Speaker 1: I love I'm looking at Dean Keith SIB's version of
Speaker 1: that of the Cock Studies. Yeah, this is and this
Speaker 1: is actually the nineteen sixty nine printing. So I got it.
Speaker 1: It came out when I was still a graduate student.
Speaker 1: I actually lean up my senior year of high school
Speaker 1: and you can see it's it's really a bad shape,
Speaker 1: terrible shape. But let me look up Mozart. Okay, so
Speaker 1: I can tell you actually what's interesting about her book.
Speaker 1: She has a whole section where she groups them according
Speaker 1: to their rating so that it's a little bit easier.
Speaker 1: Okayre IQs lois, she goes is, there's lots of IQs
Speaker 1: of one hundred and twenty and above. And that's kind
Speaker 1: of interesting because that's often used as you're in for
Speaker 1: intellectual giftedness. The lowest cases are there's one hundred and
Speaker 1: ten and oh man, she asked them from one hundred
Speaker 1: and ten. Okay, and uh and I said, la fontaine
Speaker 1: u his IQ estimated between one hundred and one hundred
Speaker 1: and twenty five. Okay, one hundred twenty five is the
Speaker 1: later one, you know, in adolescence. But there's some pretty
Speaker 1: famous people with relatively well servantes one hundred and five
Speaker 1: to one hundred and ten. Yeah, and a lot of
Speaker 1: that is because most of his early life doesn't exist.
Speaker 1: You know, we have no record, very much like Shakespeare,
Speaker 1: who a lot of yeah, a lot of unreliable Oh,
Speaker 1: a lot of unreliability there. But I'm just saying Shakespeare,
Speaker 1: that's a whole other can of worms with you, you know,
Speaker 1: who was the real Shakespeare. Shakespeare didn't take the sample
Speaker 1: because the data so it was so bad, I know.
Speaker 1: And you didn't. You didn't find Mozart, though you didn't
Speaker 1: find your your cheating Yeah about that, Yeah, okay, that's fine, Mozart.
Speaker 1: While you're while you're looking. Can you can you can
Speaker 1: you talk and chug him at the same time? Can
Speaker 1: you can you tell us about who was the real
Speaker 1: who was the real Bard? Who was the real in
Speaker 1: your analysis? Did you ever figure it out? I'll get
Speaker 1: to that a second. Okay, I'm almost as almost there. Okay.
Speaker 1: Mozart Okay, one hundred and fifty really firs childhood, and
Speaker 1: I hired fifty five for when he was an adolescent.
Speaker 1: But there's such there was such a palsity of data
Speaker 1: on his intellectual prowess. Although I told you we have
Speaker 1: we have, well, we actually have a scientific observation of
Speaker 1: him when he was eight years old, really were describing
Speaker 1: earlier transactions of philosophical society. So he was pretty well documented.
Speaker 1: And part of course, because Leopold, his father, was really
Speaker 1: really dedicated to documenting how precocious his young son was.
Speaker 1: I mean, he had a daughter, animal older sister who
Speaker 1: was also bread to coacious, but he realized Mozart was
Speaker 1: in another league. Altogether, very interesting. Let me answer your question. Okay,
Speaker 1: please do it. I haven't really found an answer to
Speaker 1: the Shakespeare authorship problem. But what I have done is
Speaker 1: I've done the data analysis as a content analysis of
Speaker 1: his plays, basically a stylometric analysis, and comparing that with
Speaker 1: and also content analysis of the fanatic material to see
Speaker 1: what he talked about and how that relates to events
Speaker 1: that occurred externally, focusing on political events. And what I
Speaker 1: showed is that the current dating is traditionally given for
Speaker 1: the plays, it's probably correct the high probability of being correct.
Speaker 1: So what that tells you is that whoever composed, whoever
Speaker 1: wrote the plays, was pretty much an exact contemporary of
Speaker 1: Shakespeare's and that does rule out a lot of people.
Speaker 1: Example rules out the current most popular candidate is the
Speaker 1: Earl of Oxford, who a lot of people believe composed
Speaker 1: of plays. But the problem is is that he died
Speaker 1: before a lot of the plays were yet to be written,
Speaker 1: so that kind of puts a kind of a monkey
Speaker 1: mention now attribution. But there's still other candidates. I just
Speaker 1: got an email a couple of days ago from We
Speaker 1: still have people who argue for Francis Bacon No stop
Speaker 1: it really yeah, because he wasn't exact contemporary of Shakespeare,
Speaker 1: so time wise he could have I don't believe it.
Speaker 1: I don't believe it either. I don't believe my favorite
Speaker 1: candidate right now is Henry Nevill and he fits really
Speaker 1: really welling. Yeah, I said, that's interesting. Certain things that
Speaker 1: happened in his personal life fit things that happen in
Speaker 1: the plays, so that, for example, there's a spot in
Speaker 1: the plays where they start becoming very very dark and
Speaker 1: and and you know, depressing and negative, and the tragedies
Speaker 1: you look at timing like Hamlet for example, Uh, he
Speaker 1: was tossed into the tire of London under a throat
Speaker 1: of having his head chopped off for his involvement and
Speaker 1: the Earl of Sussex rebellion against Elizabeth the First and
Speaker 1: he was very lucky to get out alive. Uh. And
Speaker 1: so he started putting his affairs in order and he
Speaker 1: never completely recovered that. I mean, he didn't have his
Speaker 1: head shopped off, but he lost a lot of his privileges.
Speaker 1: He wouldn't he was no longer able to be uh.
Speaker 1: He used to be able to be the carrier of
Speaker 1: the canopy when she would go on public things like that.
Speaker 1: So anyway, that's my answer is we don't. I actually
Speaker 1: don't think we'll ever have a complete answer. You know.
Speaker 1: It's just there's so much information It's like another example,
Speaker 1: I did a study which I know so you've actually
Speaker 1: signed in one of your blogs of Biethoven symphonies and
Speaker 1: showed how the even numbered symphonies are very very different
Speaker 1: from the odd numbered symphonies, are not being more popular
Speaker 1: and were frequently performed and all that kind of stuff,
Speaker 1: but the melodies, and this is but determined by the
Speaker 1: computerized content analysis, the melodies are different in the in
Speaker 1: the award symphonies than the even numbered symphonies. Wow. So
Speaker 1: the question is is that did he know that? And
Speaker 1: we'll never know that. We've never found any letter where
Speaker 1: he says, well, I just finished odd number of symphonies,
Speaker 1: so it's hapt for me to work on an even
Speaker 1: numbered symphony. What could be all the possible explanations that,
Speaker 1: I mean, the whole full space of possible explanations. There
Speaker 1: could be things we haven't even thought of, you know that,
Speaker 1: I mean to me, the most likely one, most likely
Speaker 1: explanation is Beethoven's odd number of symphonies were breakthrough symphonies
Speaker 1: where he went well beyond where he was before. And
Speaker 1: I think he had to step back, uh, after he
Speaker 1: did after he after he did this, well, he had
Speaker 1: his first symphony that was his first symphony hold and
Speaker 1: then his second symphony is regressive, it's actually more conservative
Speaker 1: than his first sympony. Then he does his third symphony,
Speaker 1: the Royka Symphony, and he really I mean, it was
Speaker 1: long and have a lot of innovations in it, and
Speaker 1: so he backs up into a sports symphony, which is
Speaker 1: more conservative. Then he has a swifth Symphony, and he
Speaker 1: backs into the sixth Symphony, which is more conservative, and
Speaker 1: then he goes to the seventh Symphony, which is another
Speaker 1: bold statement, and of course he finally ends on the ninth.
Speaker 1: So I mean, it's interesting to me, for example, that
Speaker 1: after he did the seventh Symphony, he composed an eighth
Speaker 1: symphony and it's full of jokes and a sense of humor,
Speaker 1: and it's also almost as short as the shortest symphony,
Speaker 1: the second Symphony, in so I think he needed kind
Speaker 1: of a break. And you see that for in the
Speaker 1: math MATERI for example, that the matic real is much
Speaker 1: less varied in melodic originality, and the differences in the
Speaker 1: level of melodic originality. I mean, it's he's just he's
Speaker 1: uh with fresh and he's he was unbuttoned when he
Speaker 1: did his even numbered space, whereas that kind of image
Speaker 1: you have a Beethoven of you know, uh, Fate knocking
Speaker 1: at the door and finding me in state that's what
Speaker 1: he did, is odd? I see. Well, okay, well this
Speaker 1: was this is this is great ellucination rate elucidation rate here.
Speaker 1: I think that's probably the most parsimonious. Yeah, but we
Speaker 1: don't know. I know, we never know. But it's fun.
Speaker 1: It's fun talking about probabilities of what probably haven't I'd
Speaker 1: like to double click on the madness genius link for
Speaker 1: a second, because you've done so much really cool work
Speaker 1: on that. In your book Genius. One on one you
Speaker 1: you point out a paradox, you say, here's some advice
Speaker 1: go stark raving mad, but also become the poster child
Speaker 1: for sanity. No. Now, but what is that about that paradox? Well,
Speaker 1: first of all, one of the things that I emphasize
Speaker 1: in that book, Genius Checklist, is that there's not one
Speaker 1: kind of genius, one size. It's called genius. And in
Speaker 1: a particular, a theme going throughout the book is the
Speaker 1: stark difference between scientific genius and artistic genius. And I
Speaker 1: have to say there's there's divisions within e. So like
Speaker 1: if you look at artistic geniuses in a generic sense,
Speaker 1: the class composers are more like scientists, and then the
Speaker 1: poets are more like prototypical and so. And actually uh
Speaker 1: Arnablithic has an interesting hypothesis on this. He says, and
Speaker 1: he cuts data to show this that the more logical
Speaker 1: and systematic and formal is the particular kind of creativity
Speaker 1: you're doing, the more likely you're going to be mentally healthy,
Speaker 1: because mental illness is going to get in the way.
Speaker 1: But the more adjective, the more informal, the more chaotic
Speaker 1: the particular form of creativity is, the higher the rate
Speaker 1: of some kind of not in a mental illness, It
Speaker 1: could be some clinical symptoms right of depression or whatever.
Speaker 1: And that's born now in not only his own research,
Speaker 1: but in my own research. Scientists are less likely to
Speaker 1: show mental illness and our artists. But then there's divisions
Speaker 1: within the scientists. So there's a nice study that was
Speaker 1: that was done by Cohen Kim are Kim and co
Speaker 1: one way or the other decree and researchers where they
Speaker 1: look at revolutionary scientists versus what they call paradigm conserving scientists.
Speaker 1: They didn't challenge the paradims they received, they just extended them,
Speaker 1: you know, and they found that the revolutionary showed much
Speaker 1: higher rates of male illness than did the paradigm conserving scientists.
Speaker 1: And that gets back to the explanation of arn A Lutheric.
Speaker 1: When you're when you are shattering the paradigm, then you're
Speaker 1: really in a very vulnerable position. You know, it's not
Speaker 1: all health breaks loose, and you're under lots of stress
Speaker 1: because you don't know if you'll be able to pull
Speaker 1: this off. Even if you're able to pull them off,
Speaker 1: you don't know if your ideas are going to be accepted.
Speaker 1: I have the poor Einstein, you know, he comes up
Speaker 1: with a beautiful theory of relativity and instead of being
Speaker 1: praised for it, that held him back from getting the
Speaker 1: Nobel Prize because the people on a particular one guy
Speaker 1: in particular, says that there's nets, that there's crazy, and
Speaker 1: so he had to wait to get his Nobel Prize
Speaker 1: because his theory went well. Was it challenged the classical physics,
Speaker 1: you know, and this person was a classical physicist. And
Speaker 1: then the same thing with an artist. You know, classical
Speaker 1: musicians deal with a highly formal area with a lot
Speaker 1: of emphasis on order and structure. There's rules of harmony,
Speaker 1: rules of counterpoint, where in the case of poets, it's
Speaker 1: like anything goes I am particularly now, where you know
Speaker 1: there's no rhyme or reason before you know, it's whatever
Speaker 1: you feel like doing, as long as that is successful,
Speaker 1: expresses which you want to express, and it's often a
Speaker 1: motion that you want to express us. So it's interesting,
Speaker 1: you know, you mentioned James Kaufman earlier. This is an
Speaker 1: interesting study on those poets that are most likely to
Speaker 1: have mental illness issues and often commit suicide, like Solvia
Speaker 1: Plath and Ansect, and for example, are confessional poets where
Speaker 1: you're spending a lot of time dwelling on horrific experiences
Speaker 1: or feelings to have, and that rumination, you know, pessimists,
Speaker 1: rumination is not good for your mental health, and it's
Speaker 1: not therapeutic because you know, there's there's talk therapies where
Speaker 1: it's therapeutic to talk about these things which you're supposed
Speaker 1: to work it through until you get at the end
Speaker 1: and see that there's another way of looking at all this,
Speaker 1: our more healthy way of looking at all this, And
Speaker 1: the confessional poets didn't do that. They just dwell on
Speaker 1: my daddy this and my daddy that. I can't take
Speaker 1: it anymore, you know it, It's time to you know,
Speaker 1: turn on stoke. Yeah. So, so the point is and
Speaker 1: that the paradox is that. Oh and here's one other
Speaker 1: aspect of that. And I actually have a whole paper
Speaker 1: I study published on this. It's kindly call it the
Speaker 1: mad Genius paradox, where I show that's actually technically possible
Speaker 1: for creativity to be positively correlated with mental health at
Speaker 1: the lower end, that negatively correlated with mental health at
Speaker 1: the upper end of the distribution. Mh and and and
Speaker 1: the reason for that is because the vast majority of
Speaker 1: creative people we're at the bottom end of the tribution.
Speaker 1: It's not a normal distribution, and the people are a percentage.
Speaker 1: So as a consequence, if you just kind of calculate
Speaker 1: to say, here's some creative people, here's some non creative people,
Speaker 1: who's the most mentally healthy, you'd find out that the
Speaker 1: creative people are more memorally healthy. But if you've catulate
Speaker 1: the correlation between the impact the creative achievement, you'd find
Speaker 1: a positive correlation with mental illness. So anyway to make
Speaker 1: a long story short, I can't really do that anymore.
Speaker 1: I already talk too much. It's you have to be
Speaker 1: very very careful because it's a very very complex relationship.
Speaker 1: And and the one thing that obviously if you go
Speaker 1: over the edge, you know, like Hemingway or Ansecton or
Speaker 1: you know, Sylvia Plath, your creativity is not helped at all.
Speaker 1: You know, No, I think it was committed an institution
Speaker 1: that was the end of its creative career. Sure, and
Speaker 1: obviously once he commit suicide. I mean, I guess in
Speaker 1: some cases, like Kirkabbine, your work can actually be even
Speaker 1: immortalized of all time. You know, the twenty seven year
Speaker 1: Old Club, I think a lot of them killed themselves
Speaker 1: so that they would forever be you know a myth right. Well,
Speaker 1: I mean the youngest interesting in the Cock Study, the
Speaker 1: youngest person who made it into it was eighteen years old.
Speaker 1: That's Thomas Chatterton. And he made a name for himself
Speaker 1: with that what are called a rally poems. They were
Speaker 1: all four forgeries. He said he found the middle medieval poetry,
Speaker 1: and he made up a kind of you know, the
Speaker 1: medieval vocabulary and dialect and so forth, and totally faked
Speaker 1: and fool people for a long time. But unfortunately, when
Speaker 1: it started coming out, people started being suspicious because you
Speaker 1: could never show the actual manuscripts. Right, Yeah, when people
Speaker 1: started getting suspicious, he decided to There was also an
Speaker 1: unrequired a love part of it story too. He took
Speaker 1: an overdose of arsenic. I guess a dose of arsenic
Speaker 1: is an overdose. So, but it's amazing at eighteen he
Speaker 1: was able to. Yeah, out of three hundred and one genius,
Speaker 1: he's in there because of his suicide, like your example. Well, yeah,
Speaker 1: that's right, that's right. I mean sometimes making that decision
Speaker 1: is what puts you in the history books. But I
Speaker 1: don't want to say that in a way that advocates
Speaker 1: for that choice. No, no, no, obviously, obviously I want
Speaker 1: to be clear. But you know, I look at the
Speaker 1: Frank Barron studies. He found that they did score above
Speaker 1: average in markers of mental illness, but they also scored
Speaker 1: pretty high on markers of mental health. And that's the paradox.
Speaker 1: I wanted to really zoom in here a second, because
Speaker 1: ego strength, ego resiliency. Yeah, and also even on the
Speaker 1: clinical symptoms, this is on the n MPI, on the
Speaker 1: clinical symptoms. Even though they were above average, they were
Speaker 1: still below the normal level you see for people who
Speaker 1: are actually clinically disabled by their mental illness. So they
Speaker 1: were right in between. It was like Dryden's saying that
Speaker 1: there was a thin border between madness, and he used
Speaker 1: with you know, madness and wit, and so that lower
Speaker 1: level in combination with ego strengths, or in the Cantel
Speaker 1: sixteen factor, it was self sufficiency. The same kind of
Speaker 1: thing would that Would that be great in today's world? Yeah,
Speaker 1: I don't know. You know, that's the one thing that's
Speaker 1: really kind of unfortunate about I think the main frustration
Speaker 1: for me when I start studying personality theory and measurement
Speaker 1: is that you get these new tests and they don't
Speaker 1: completely map on each other. So some perfectly good dimension
Speaker 1: of like the sixteen factor Personality Scale or MNPI ends
Speaker 1: up vanishing because it doesn't map out onto the five
Speaker 1: factor model. You know. Of course, later of people start
Speaker 1: adding more factories to the five factor model, and then
Speaker 1: especially I guess you'll get back to tell sixteen factors
Speaker 1: or whatever. But a lot of dimensions kind of disappear,
Speaker 1: uh and and and sometimes of course the dimensions that
Speaker 1: replace them are are composites of things that used to
Speaker 1: be separate dimensions, you know, like extra version and the
Speaker 1: Big five that's partly social dominance and partly liking to
Speaker 1: be with people, and those are not really the same thing,
Speaker 1: which which treat extroversion. Oh extra version. Yeah no, that's
Speaker 1: a really good point. Yeah yeah, yeah, yeah, yeah, it's
Speaker 1: a positive two major dimensions. Sometimes sorry, right yeah, sorry,
Speaker 1: sometimes what well, sometimes they split absolutely absolutely, there's actually
Speaker 1: general differences, and there's gender differences. But we don't we
Speaker 1: don't want to go there in the two facets. Yeah,
Speaker 1: you asked me, Like the stuff I've done on presidential
Speaker 1: leadership is kind of interesting. For example, that the president
Speaker 1: who had the lowest score on openness is uh Bush,
Speaker 1: the second Bush. Very it wasn't it was he never
Speaker 1: people stood the plane like an account who was never curious.
Speaker 1: He never would ask a question, you know, me of
Speaker 1: something that happened to me the other day. But there's
Speaker 1: one facet of the open experience he's worked very highly on,
Speaker 1: and that is receptivity to openness to emotion. So he's
Speaker 1: very very open to emotions, but he wasn't open to values,
Speaker 1: wasn't open to interests, et cetera. Exactly how many facets
Speaker 1: there are? So I can't. I can sometimes split was
Speaker 1: so was very He's one of the most open people
Speaker 1: ever in history. Uh, except for values. He knew what
Speaker 1: his values were and he were not He's not going
Speaker 1: to change him. Okay, Well, I got to ask you,
Speaker 1: because you've you've you've spent a career studying UH leadership.
Speaker 1: Where would you what's your take on President Trump? Don't ask,
Speaker 1: I mean you're a You're in a unique position to comment.
Speaker 1: First of all, can I say that I get a
Speaker 1: lot of mail. Some of that is trolling asking for
Speaker 1: me to give Trump's i Q. Okay, because he boasted
Speaker 1: about his i Q. I know, well, you can estimate it,
Speaker 1: but I haven't estimate made it anybody since the second Bush.
Speaker 1: And part of the reason was because I got so
Speaker 1: much flat. I still get flat for that study because
Speaker 1: people think it's highly partisan, and particularly because Bush ended
Speaker 1: up having a relatively low IQ estimate in comparison to
Speaker 1: his predetor Clinton. But I actually show in the study
Speaker 1: that there's no partisan bias that you live across all presidents.
Speaker 1: There's no difference in IQ scores. Obviously, there's going to
Speaker 1: be difference for particular presidents. I mean, Carter was really
Speaker 1: up there in IQ, but there's no parts of ad
Speaker 1: bias to it at all that people don't believe that
Speaker 1: people thought. I've actually been told that I had a
Speaker 1: job on the second Bush give him a low IQ score.
Speaker 1: And I didn't even give him a low IQ score.
Speaker 1: He was above average. You know, it was about one
Speaker 1: hundred and twenty five. That's not a low IQ score,
Speaker 1: but it was ten points below Cultain. So it's a
Speaker 1: hatchet job. Now Trump Another reason why I think he's
Speaker 1: difficult to test, beside the that be heids all development
Speaker 1: data in my one of the years, like his grades
Speaker 1: and how he actually got into Japan, is that he
Speaker 1: has other things to kind of interfere with estimating intelligence.
Speaker 1: And I'll go ahead and say it. His narcissism, you know,
Speaker 1: has been pretty well documented. It is sort of like
Speaker 1: what happened to the second Bush. He was actually brighter
Speaker 1: than he was given credit for, but because he was
Speaker 1: so close was minded, he ended up sounding less intelligent.
Speaker 1: He didn't want to process a lot of information. He
Speaker 1: just want he said, I am a decider. You know,
Speaker 1: they call it on a side or I don't need
Speaker 1: any data, and Trump is very similar. I think that's
Speaker 1: a really good point that we could probably just leave
Speaker 1: that there because his as with anyone with profound narcissism,
Speaker 1: it can cloud and distort all sorts of other traits
Speaker 1: and characteristics. So we'll leave that there. I want to
Speaker 1: end this interview with a with a topic that I
Speaker 1: think is really interesting and I've followed with your research
Speaker 1: on this topic, and that's the ten year rule for
Speaker 1: greatness or for expertise, world world class expertise as the elite.
Speaker 1: You know that that he passed Awake honders ericson recently.
Speaker 1: He was a I think, you know, he and I
Speaker 1: are about the same age. I consider him young. Yeah,
Speaker 1: sixty nine, that is well, that is young. That is young.
Speaker 1: It was really tragic. I considered him a friend, you know,
Speaker 1: I considered it. I think he's a he was a
Speaker 1: terrific scientist. But I think that this research you did
Speaker 1: kind of re analyzing it and and and arguing there's
Speaker 1: different rates of of of you know, there's variability there
Speaker 1: and how long it takes people, and you know that's
Speaker 1: been followed up by people who've done much better jobs
Speaker 1: on it than than I have. But the basic idea
Speaker 1: is that when he publishes original data like showing how
Speaker 1: many hours of practice pianists, you know, compiled for various
Speaker 1: categories you know, like novices, us virtuosi and that kind
Speaker 1: of thing, he didn't provide the range. Yeah, and the
Speaker 1: range is actually huge. And not only that, but that
Speaker 1: variation doesn't necessarily it depends on the field, but that
Speaker 1: variation doesn't necessarily correlate the way you'd expect it. Yeah,
Speaker 1: So that, for example, what I found for class of
Speaker 1: composers is that there's a huge range, and those who
Speaker 1: have the narrower range, who took less time to master
Speaker 1: the field, end up being the greater composers. And that
Speaker 1: seems to be the opposite of what I do. Is
Speaker 1: that you think the more expertise required the more the
Speaker 1: greater your genius. And in fact, when you think about
Speaker 1: that seems to support a talent interpretation. There's some people
Speaker 1: who just take less time to become masters of the material,
Speaker 1: and then because they're talented, they can do more what
Speaker 1: I call more bang for the buck. They could do
Speaker 1: more with it. So the talent means they get better, faster,
Speaker 1: and they get more bang for the buck. And you know,
Speaker 1: there's a lot of people who have done research on
Speaker 1: this in other domains. I focused on fast composers, but
Speaker 1: people look at other domains and it turns out the
Speaker 1: variation doesn't explain very much variance in a lot of fields,
Speaker 1: and the fields explains the most experiencing in our fields.
Speaker 1: That kind of makes sense, like sports, where practice, practice,
Speaker 1: practice is extremely important. Those people who you know, when
Speaker 1: I watch basketball and when I see people who miss
Speaker 1: more than fifty percent of their free throws, I go,
Speaker 1: you are not practicing. You know, there's gonna be variation
Speaker 1: to the talent. I have no doubt about that. But
Speaker 1: I think any professional basketball player should hit more than
Speaker 1: just another free throws. Yeah, people hit more than the
Speaker 1: three pointers. Yes, it's such a good point. Yeah, it's
Speaker 1: such a good Well, this finding was so interesting that
Speaker 1: you just that you mentioned, and it does suggest that
Speaker 1: talent isn't irrelevant and at at at uh, you know,
Speaker 1: at uh in one sense or but another sense, it
Speaker 1: could we say the talent is even more important than
Speaker 1: we give it credit for in those in those earlier studies.
Speaker 1: Did you ever talk to Ericson about it? Did you
Speaker 1: ever did you ever talk to I did more than
Speaker 1: talk or there. I don't know if you know that
Speaker 1: he and I had a public debate at Clarion. Is
Speaker 1: it online? Is it online? I don't know if they
Speaker 1: ever put this is This is a time when it
Speaker 1: wasn't automatic that they put things online. It was it
Speaker 1: was sponsored by the student government at Claremont, and they
Speaker 1: was quite a thing they put in the major, you know, auditorium.
Speaker 1: I don't remember what it was. And it was basically
Speaker 1: him versus me, and they took us out to dinner
Speaker 1: before it was the evening address, and he and I
Speaker 1: got into it. I agree with you, he said. He's
Speaker 1: a nice guy, but he has taken a very very
Speaker 1: strong position on talent. Okay, And one of the things
Speaker 1: that I find very surprising is in order to make
Speaker 1: his argument against talent, he often has to take arguments,
Speaker 1: make arguments that are just untenable. Like he and I
Speaker 1: at dinner had an argument about whether individual differences are real.
Speaker 1: He said, and he says, all individual differences that aren't
Speaker 1: physical differences like height are the measurement era you can't
Speaker 1: And I say, there are you got it? I gottaka,
Speaker 1: I said you've got admit their individual difference intelligence and
Speaker 1: the difference in personnel. He wouldn't. He wouldn't admit it.
Speaker 1: And of course the reason why is that the second
Speaker 1: youmit those individual differences, then you go to the genetic
Speaker 1: vapor geneticis reserves and identical twins reared apart, and see
Speaker 1: what the credibility go efficients are for those individual differences.
Speaker 1: And you know, like a most fertionality traits, it's around
Speaker 1: fifty percent. For intelligence, it's more than fifty percent. As
Speaker 1: you age, it gets it gets higher. Yeah, it gets bigger.
Speaker 1: It can get up to point eight point eight. Yeah. Yeah.
Speaker 1: So he and I really got on it, got at it,
Speaker 1: and it was I mean, fortunately it was moderated, so
Speaker 1: when either one of us got too we got cut off. Okay,
Speaker 1: that's good, that's good. Second between Trump and Biden, you know,
Speaker 1: they cost the microp what I would have given, given
Speaker 1: what I would have would given to have seen that,
Speaker 1: to have been there, or maybe I'm going to look
Speaker 1: to see if it's on YouTube, because you never know.
Speaker 1: Check Two. I can't remember the date it was in
Speaker 1: the early part of this millennium, like two thousand and
Speaker 1: three or four or something like that. I actually haven't listed.
Speaker 1: I have a list of all my presentations and I
Speaker 1: haven't listed there, and the search to Claremont and and
Speaker 1: see and then see if it shows up on YouTube
Speaker 1: or whatever. Yeah, I'm trying to look for Why have
Speaker 1: I have deep respect for for both of you obviously,
Speaker 1: and and and yeah, just to zoom in on you
Speaker 1: here and I'll kind of I'll end our episode today.
Speaker 1: Thank you so so much for being a real true
Speaker 1: legend in the field. And I think I think you're
Speaker 1: a genius of the science of genius. I me give
Speaker 1: me that that about me and said, I'm the first
Speaker 1: one since Goltham. Yeah, yeah, in a lot of ways.
Speaker 1: Well that's you know, I have a student who has
Speaker 1: account to that. I had a student who took my
Speaker 1: genius criteria in leadership class, and she says, I'm gonna
Speaker 1: write my turn paper on how anybody who studies genius
Speaker 1: can't possibly be a genius. I don't. I don't agree
Speaker 1: with that. I don't agree with that, but I think,
Speaker 1: you know, uh, you know, it's interesting with Golden. I
Speaker 1: think you're you're more of a genius than Galton because
Speaker 1: you were You're more open minded. I think you bring
Speaker 1: in more perspectives to the table. Well, I think you're
Speaker 1: even more nuanced in your consideration of the nature, nurture
Speaker 1: interactions and all the socio cultural factors. Like you know
Speaker 1: that you've studied and introduced into your models. I would
Speaker 1: make I could write a paper on why I think
Speaker 1: you're more of a genius than Galton. Yeah. Yeah, I
Speaker 1: don't know if we get published, but I could write it.
Speaker 1: I could write. But thank you so much Dean for
Speaker 1: chatting me today and for being such an inspiration to
Speaker 1: all of us scholars in the field. Great. I really
Speaker 1: I really appreciate it was really a fun thing to do.
Speaker 1: Do it me too. Thanks for listening to this episode
Speaker 1: of The Psychology Podcast. If you'd like to react in
Speaker 1: some way to something you heard, I encourage you to
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