Speaker 1: Hello, and welcome to the Psychology Podcast with doctor Scott
Speaker 1: Barry Kaufman, where we give you insights into the mind, brain, behavior,
Speaker 1: and creativity. Each episode will feature a new guest who
Speaker 1: will stimulate your mind and give you a greater understanding
Speaker 1: of yourself, others, and the world we live in. Thanks
Speaker 1: for listening and enjoy the podcast today. It's great to
Speaker 1: have Christopher Sabri on the podcast. Christopher is Associate Professor
Speaker 1: of psychology and co director of the Neuroscience Program at
Speaker 1: Union College, Adjunct Assistant Professor of Neurology at Albany Medical College,
Speaker 1: and a research affiliate at the MIT Center for Collective Intelligence.
Speaker 1: In his book The Invisible Guerrilla, co author with Daniel Simons,
Speaker 1: presents the results of research no Attension and other cognitive illusions.
Speaker 1: He also writes the new column game On in the
Speaker 1: Wall Street Journal. Thank you so much, Chris for being
Speaker 1: here today. Thanks for having me here. I really liked
Speaker 1: the title of that column, game On. Did you come
Speaker 1: up with that? And I had nothing to do with it?
Speaker 1: I gave them several suggestions and they were all summarily
Speaker 1: rejected and the editors picked a better one. Do you
Speaker 1: find that happens. Has ever happened to you before with
Speaker 1: like an article you wrote where they just like put
Speaker 1: this title that you're not happy with. I mean, obviously
Speaker 1: you're probably happy with this title. But in the past, though, yeah,
Speaker 1: that happens, I would say fairly often, although much more
Speaker 1: often than that, the title that the editors come up
Speaker 1: with is either better or probably result in more people
Speaker 1: reading it, which ultimately is what you want. I don't
Speaker 1: want to be writing stuff for a general audience or
Speaker 1: a popular audience and then have them not read it
Speaker 1: because the title wasn't sexy enough to make them click
Speaker 1: or something like that. So I've never complained to the
Speaker 1: editor that I can recall and told them to change
Speaker 1: the title, or told them I didn't like the title
Speaker 1: or something like that. But there's certainly been haven't been
Speaker 1: some times when I thought I had come up with
Speaker 1: something really clever, but it just didn't, you know, didn't
Speaker 1: make it in at all. What would be your limits though,
Speaker 1: in terms of quick beat, like where do you draw
Speaker 1: a line like if they're like click here, you know
Speaker 1: for naked penguins dancing, like would you be like not
Speaker 1: happy with that? And then it's and then it's my
Speaker 1: article about replication and psychology or something like that. Yeah, well,
Speaker 1: I think I would be I think I would be
Speaker 1: unhappy with that. I've seen some articles published where the
Speaker 1: title definitely actually contradicts, you know, what's being said, or
Speaker 1: makes or overly exaggerates the claims that are that are
Speaker 1: being made. And I think if the if the topic
Speaker 1: is science or behavioral science, or anything about you know
Speaker 1: that has even remotely to do with critical thinking or
Speaker 1: rationality or public policy, then the author should go back
Speaker 1: and say, you know that that title is misleading. And
Speaker 1: I think some some authors don't do that. I actually
Speaker 1: think probably academics who write for a popular audience are
Speaker 1: probably a little more sensitive to that because normally they
Speaker 1: write their own titles for journal articles, and they write
Speaker 1: the abstract and so on. But then when when when
Speaker 1: when the you know, when the editors of a newspaper,
Speaker 1: magazine or website sort of write the write the search
Speaker 1: engine text and all and all that stuff, I think
Speaker 1: you shouldn't go back to it and make sure it's
Speaker 1: it's accurate, because otherwise, you know, ninety nine percent of
Speaker 1: the readers will just read the title. They're never going
Speaker 1: to read past that, so they might think that Scott
Speaker 1: Barry Kaufman is saying something ridiculous when actually that's not
Speaker 1: what you said in the article. That's just what the
Speaker 1: editor put there. Yeah, and it's particularly frustrating when it
Speaker 1: takes all the nuance that you've spent your whole career
Speaker 1: working on out of it. So that happened to me
Speaker 1: in that case. And they took an excerpt from my
Speaker 1: book I Gifted in Slate and they called it basically
Speaker 1: the excerpt was about how we need to be more
Speaker 1: sensitive to the kinds of tests we use to assess
Speaker 1: learning disabilities and we need to like basically we need
Speaker 1: to like use the test more sensibly. But they called
Speaker 1: it why IQ tests are useless. And it's so funny
Speaker 1: that they also, probably, you know, shortly after that published,
Speaker 1: you know, articles by me and Zach Hambrick about why
Speaker 1: why i Q tests are so great? You know. So
Speaker 1: it's not as though they're even trying to push a
Speaker 1: consistent line, right, they're trying to get people to read
Speaker 1: the articles. Yeah, that's exactly. And you probably don't want
Speaker 1: to be on the record as saying IQ tests are useless.
Speaker 1: So did you ask them to change it and did
Speaker 1: they did they change it? I'm really trying to remember.
Speaker 1: I guess I need a Google to really remember if
Speaker 1: it was changed. I do think I did make a request.
Speaker 1: I was like, this is a bit strong in my experience.
Speaker 1: They're actually pretty sensitive to that. But it could be
Speaker 1: that I write It could be that the publications that
Speaker 1: I write for, you know, happen to have editors who,
Speaker 1: you know, either care about getting those things right or
Speaker 1: maybe care about having me write for them again, whereas
Speaker 1: there might be other websites that basically it's a difference
Speaker 1: between making money and losing money whether they can write
Speaker 1: an outrageous headline, and they might not be as receptive
Speaker 1: to that kind of to that kind of author feedback.
Speaker 1: I don't I don't know. I haven't really read into
Speaker 1: that yet. Yeah, their incentives might be different. Sure, Well,
Speaker 1: since we open I kind of just opened up this
Speaker 1: can of worms with IQ. I mean, why not, why
Speaker 1: don't we just dive into that topic? And there's a
Speaker 1: lot of topics we could talk about, but I think
Speaker 1: this is a good one, one of the good ones. Yeah.
Speaker 1: So you've done research some really interesting recent research on
Speaker 1: the genetics of IQ, finding that a lot of the
Speaker 1: genes that prior researchers have found are statistically associated, even
Speaker 1: though they're obviously very small effects, you found, they don't
Speaker 1: really replicate. Is that right, that's true. So the short
Speaker 1: story is that, you know, we've known for a long
Speaker 1: time that that IQ whatever you think it corresponds to
Speaker 1: in the real world or whatever the right sort of
Speaker 1: dictionary definition of it is. Whatever it is that IQ
Speaker 1: tests are measuring, is measured, you know, across the population
Speaker 1: very reliably, and it's always found to be significantly heritable.
Speaker 1: It's one of the most heritable behavioral traits that we
Speaker 1: know about. So we know that from twin studies and
Speaker 1: family studies and so on. And for about fifteen years
Speaker 1: people have been doing what are called candidate gene studies,
Speaker 1: which are studies where they think about a particular gene that,
Speaker 1: because of something known about its role in brain function
Speaker 1: or biology, you know, might have something to do with
Speaker 1: differences in intelligence between individuals, or at least in you know,
Speaker 1: an IQ test scores, and so they'll they'll collect a
Speaker 1: sample of people and genotype a bunch of them for
Speaker 1: some variants of this gene. Often these these genes are
Speaker 1: kind of things you think about, like dopamine related genes
Speaker 1: or you know, genes involved in the synapse or something
Speaker 1: like that. And the study will report the results of
Speaker 1: genotyping one gene. It'll say, well, lo, and behold, the
Speaker 1: people who have this particular variant, you know, score one
Speaker 1: point seven iq points higher for each copy of that
Speaker 1: variant that they have, or maybe even more than that.
Speaker 1: And this was significant p less thon point zh five.
Speaker 1: And what it turns out is that most of those
Speaker 1: results just purely do not replicate at all when you
Speaker 1: use a much larger sample. So these sample sizes are
Speaker 1: typically in the dozens to hundreds. Several colleagues and I
Speaker 1: I think we maybe had fourteen authors on this paper
Speaker 1: ultimately put together three data sets with about ten thousand
Speaker 1: total subjects and tested ten of these genes and found
Speaker 1: that basically none of them replicate. One of them replicated
Speaker 1: once in one sample, but then basically in the opposite
Speaker 1: direction another sample. So those kind of cancel each other out.
Speaker 1: And that literature is basically follow false positives, as a
Speaker 1: lot of the literature that you'll find that say, you know,
Speaker 1: there's a particular gene associated with trust, or a particular
Speaker 1: gene associated with altruism or a particular gene associated with
Speaker 1: neuroticism or something or something like that. Almost all of them.
Speaker 1: That research, I think regrettably is represents false positive results. Yeah,
Speaker 1: and some people could falsely like, especially how it's portrayed
Speaker 1: in the media, some people could falsely think that result
Speaker 1: suggests that there is no genetic component to intelligence or
Speaker 1: genetic component to IQ, and instead it suggests that it's
Speaker 1: like much, it's going to be much more difficult to
Speaker 1: find the ones, the many many, there's never going to
Speaker 1: be a single gene that replicates. Do you think it's
Speaker 1: a power issue? Do you think it's probably a combination
Speaker 1: of issues. What are some of the issues on the
Speaker 1: table for you? Right, So, it's a mistake to think
Speaker 1: that if we haven't found the gene for X, that
Speaker 1: that means that X is not genetic. Right, So, so X,
Speaker 1: you know, a trait could be genetic without having any
Speaker 1: one gene. In fact, most genetic traits are not single
Speaker 1: gene traits. Height is a perfect example. Right. Everybody knows
Speaker 1: that height is heritable and its genetic, and everybody accepts
Speaker 1: that obviously. You know, your height down to the millimeter
Speaker 1: is not determined by your genes. There's also diet and
Speaker 1: you know, and other exposed environmental exposures and and and
Speaker 1: so on them make a big difference. But within a population,
Speaker 1: most differences in height seem to be caused by differences
Speaker 1: in genes. But we found out through you know, gradual
Speaker 1: research by a lot of great researchers that this is
Speaker 1: because there are hundreds or thousands of genes that affect height,
Speaker 1: and each one, you know, gives you a fraction of
Speaker 1: a millimeter basically, you know which is which is not
Speaker 1: not very much. And our work and the work of
Speaker 1: especially of the Social Science Genetic Association Consortium, which which
Speaker 1: is really doing all this work with respect to behavioral
Speaker 1: traits with the largest samples, that work has found that
Speaker 1: the same is true for behavioral traits. So, you know,
Speaker 1: any any typical behavioral trait we think is based on
Speaker 1: hundreds or thousands of genes, each one of which has
Speaker 1: a very tiny effect. It's not to say that you
Speaker 1: can't be extreme on some trade because of a single gene.
Speaker 1: So there are many genetic variants which cause intellectual disability,
Speaker 1: you know, formerly known as mental retardation and so on,
Speaker 1: score cause cause scoring very low on on IQ tests
Speaker 1: like super you know, super low, like off the charts low,
Speaker 1: and that you know, fragile X. You know, there are
Speaker 1: many many are even known by by the names of genes.
Speaker 1: But we're talking about sort of like normal range variation
Speaker 1: doesn't seem to be caused by single genes or just
Speaker 1: a handful of genes, but hundreds or thousands, right, And
Speaker 1: again that doesn't mean that there is an environmental component
Speaker 1: as well. I just want to make I want to
Speaker 1: you know, I thought this podcast could be really good
Speaker 1: to kind of like talk about lots of misconceptions about
Speaker 1: lots of this stuff. So even if there is a
Speaker 1: there there are is a genetic component to i Q.
Speaker 1: I don't think that's in doubt at all. That doesn't
Speaker 1: mean that that there aren't a lot of genes involved.
Speaker 1: A lots of those genes UH are certainly interacting with
Speaker 1: each other as well as the environment. So so so
Speaker 1: so some people might like incorrectly con coul that just
Speaker 1: because of a genetic pone there's an environmental quote or
Speaker 1: that these things can change. What are your own personal
Speaker 1: thoughts on the changeability or trainability of IQ and do
Speaker 1: you think the current methods are for lack of a
Speaker 1: better word, crap, Well, there's a lot so that there
Speaker 1: are a lot of issues in in in what you
Speaker 1: and what you went over untacked some of it, yeah,
Speaker 1: so let me yes, so let me try to unpack
Speaker 1: those a little bit. I guess one of them is
Speaker 1: that it's certainly true that all traits, pretty much all
Speaker 1: behavioral traits are affected both by heredity and environment. The
Speaker 1: proportion may vary, and it's also important to keep in
Speaker 1: mind that you know all measures of the effect of
Speaker 1: environmental variation, which is which is mostly it turns out
Speaker 1: how individuals environments differ from each other. The effective family
Speaker 1: environments generally seems to be a pretty small and behavior
Speaker 1: genetic studies, so basically, the effect of which family you're
Speaker 1: raised in is smaller than the effect of all the
Speaker 1: other different environmental exposures you have in your life, which
Speaker 1: in turn tends to be smaller than the cumulative effective
Speaker 1: genetic variation. But that is all with respect to sort
Speaker 1: of our current you know, our current social and cultural
Speaker 1: arrangements and our current technologies. Right. So the classic example
Speaker 1: of this is eyesight. Uh, you know, visual acuity would
Speaker 1: is very visual acuity is very heritable. But of course
Speaker 1: we have this technology called glasses and contact lenses which
Speaker 1: basically you know, change everybody's effective vision back to the
Speaker 1: normal range. Even though just you know, in a world
Speaker 1: without glasses, then some people would see very badly, and
Speaker 1: you know that would be determined mostly by genes, right,
Speaker 1: But in a world with glasses, you know, where if
Speaker 1: everybody has access to glasses, then everybody's vision is is
Speaker 1: quite corrected. So you could imagine some technology which is
Speaker 1: like eyeglasses but for the brain, which sort of like
Speaker 1: ramp up everybody's brain function, you know, up into a
Speaker 1: level where everybody's within this narrow band like pretty much
Speaker 1: able to read the eye chart. Like we're all able
Speaker 1: to read you know, the first like five lines of
Speaker 1: the eye chart and that's enough you know, for successful functioning.
Speaker 1: And you know, in life, you can imagine that technology
Speaker 1: for height, you can imagine that technology for IQ. You
Speaker 1: can imagine it for you know, for anything. It hasn't
Speaker 1: you know, unfortunately, it hasn't been discovered yet. I think
Speaker 1: what's unfortunate kind of is that people seem to think
Speaker 1: or want to believe that the ability to raise your IQ,
Speaker 1: you know, whatever IQ actually is, people seem to want
Speaker 1: to raise it, and they seem to believe that the
Speaker 1: ability to raise it is a lot simpler and more
Speaker 1: easily to discover and readily available than it is. So
Speaker 1: you could go back to like the Mozart effect, right,
Speaker 1: just listening to you know, uh Mozart's music for ten minutes,
Speaker 1: you can go to uh, you know, playing you know,
Speaker 1: certain kinds of you know, video games, or training, certain
Speaker 1: kinds of you know, boring repetitive cognitive tasks like working memory,
Speaker 1: or you know, running current through your running electrical current
Speaker 1: through your brain to stimulate your PDS. The idea, yeah, yeah, yeah,
Speaker 1: transcranial direct current stimulation. Right, I mean there's there's all
Speaker 1: kinds of these these fads and in general, you know,
Speaker 1: the results of I think there are two interesting things
Speaker 1: about the results of those. One or that they have
Speaker 1: trouble replicating. Also, so often when independent labs try to
Speaker 1: replicate that that research, that they can't do it. This
Speaker 1: is what happened with the Mozart effect, this is what
Speaker 1: seems to have happened largely with working memory training. And
Speaker 1: the other thing to consider also is that making someone's
Speaker 1: score go up on an IQ test, uh is not
Speaker 1: the same as increasing their general intelligence. Right, So an
Speaker 1: IQ test is a good indicator of general intelligens you know,
Speaker 1: in some environments. But imagine an environment where everyone had
Speaker 1: all the answers to the test, right, Well, then it
Speaker 1: would no longer be a measure of intelligence, wouldn't be
Speaker 1: a measure of anything in fact, because everyone would get
Speaker 1: every question right, right, So that would just drop to
Speaker 1: zero sensitivity. Or imagine a world where you know, half
Speaker 1: the people you know had bought the answers to the
Speaker 1: test and the other half that people didn't even know
Speaker 1: they were for sale. Right, Well, then you're going to
Speaker 1: get you know, then the IQ test is no longer valid. Right.
Speaker 1: So it could be that if you if you make
Speaker 1: people better at taking IQ tests, it might not translate
Speaker 1: into an actual increase in intelligence, right, Not necessarily, I
Speaker 1: want to just clarify it. Not necessarily, but it is possible,
Speaker 1: actually that increase in IQ is indicative. Yeah, it's possible. So,
Speaker 1: for example, the increase in IQ over the last one
Speaker 1: hundred years or so that comes from the Flint effect
Speaker 1: I tend to believe is real. Some people laugh at
Speaker 1: me for that, and some smart people do and other
Speaker 1: people think it's an artifact and so on. But I
Speaker 1: sort of take seriously the idea that you know, the
Speaker 1: average twenty year old today is significantly smarter in some
Speaker 1: real sense than the average twenty year old one hundred
Speaker 1: years ago or fifty years ago. I agree, and I
Speaker 1: would I would I would narrow that down of fluid
Speaker 1: reasoning as being of critical development as opposed to maybe
Speaker 1: more like vocabulary and things of that nature. But let's
Speaker 1: talk a little bit about about the concept of intelligence
Speaker 1: and the measurement of IQ. First. The first question I
Speaker 1: want to ask you, do you think IQ is the
Speaker 1: best measure we have today of intelligence? And do you
Speaker 1: see any other things that that are missing in the
Speaker 1: IQ test that you think do belong under the umbrella
Speaker 1: conceptually of intelligence? I think, I think you know. It
Speaker 1: really of course depends on how you define intelligence, right,
Speaker 1: So if you're going to define intelligence as you know,
Speaker 1: any kind of useful ability you know, then no. If
Speaker 1: you're going to define intelligence as something close to traditional
Speaker 1: definitions of it that have been used in the field
Speaker 1: of psychology, then yes. And I think it's it's it's
Speaker 1: it's almost inevitably the answer is yes, because you know,
Speaker 1: I Q tests have sort of evolved almost by natural selection,
Speaker 1: you know, in a way to optimize the measurement of
Speaker 1: those things. Like when when you make an IQ test,
Speaker 1: you know, you get rid of the items that don't
Speaker 1: load on, you know, on the first factor, if you
Speaker 1: want to make a one measure IQ test, I mean
Speaker 1: you deliberately, you know, construct them that way. So it's
Speaker 1: almost tautological that they you know, that that that they
Speaker 1: measure you know, intelligence as defined in some traditional way.
Speaker 1: But what I sort of don't like. What I sort
Speaker 1: of don't like is I don't like very much the
Speaker 1: use of the term intelligence as a generic term for
Speaker 1: you know, any desirable skill. So I use the word
Speaker 1: social intelligence myself. I think there are sort of some
Speaker 1: legitimate uses of that. But once we start saying there's
Speaker 1: emotional intelligence, there's practical intelligence, there's social intelligence, there's kind
Speaker 1: aesthetic intelligence, there's all these things mating intelligence, right, I
Speaker 1: mean I I sort of you know, I sort of
Speaker 1: get the point there that like, you can do these
Speaker 1: things better or worse. You can have you know, there's
Speaker 1: certain you know, skills and abilities and so on which
Speaker 1: will make you better worse at these things. But I
Speaker 1: think we lose something when we just call all of
Speaker 1: those things different kinds of intelligence. Now, you know, maybe
Speaker 1: there are you know, I'm sure there are reasons, you know,
Speaker 1: to do that, but I think it I to me,
Speaker 1: it obscure is a little more than that it helps.
Speaker 1: I think I've softened my tone a little bit on
Speaker 1: that somewhat, you know, like I'm willing to use the phrase,
Speaker 1: I'm willing to use the phrase social intelligence because I
Speaker 1: sort of, you know, I've come to believe more and
Speaker 1: more that you know, there is a distinction within the brain.
Speaker 1: And I'm going to speak very broadly, you know, I'm
Speaker 1: not going to speak as sort of like it's any
Speaker 1: kind of detailed neuroscience level that I that I can't
Speaker 1: back up with citations, But I think there is pretty
Speaker 1: broadly a distinction between neural systems that seem to have,
Speaker 1: you know, evolved for the purpose of thinking about other people,
Speaker 1: and neural systems that seem to have evolved, you know,
Speaker 1: for the purpose of doing more abstract, you know, general
Speaker 1: kinds of reasoning. So an IQ test might be a
Speaker 1: very good method of assessing the function of one of
Speaker 1: those particular neural systems. One of my current research projects
Speaker 1: is to try to develop better tests of quote, social intelligence,
Speaker 1: which I conceptualize is like assessing the function of that
Speaker 1: other you know, that other network in the brain, or
Speaker 1: that other that other collection of brain regions. But all
Speaker 1: that's but all that said, and sorry to sort of
Speaker 1: keep on, you know, rambling here. All that said, I
Speaker 1: think it turns out that intelligence as measured by IQ tests,
Speaker 1: you know, whatever brain network is supporting that, and brain
Speaker 1: networks is supporting that and so on, is incredible turns
Speaker 1: out to be incredibly predictive of you know, a wide
Speaker 1: range of outcomes in present day society, you know, from
Speaker 1: you know, occupation, job performance, income, education, mortality, lifespan, I mean,
Speaker 1: all kinds of things. And there can be very complex
Speaker 1: pathways by which it is predictive of all those things, right,
Speaker 1: Like why does intelligence predict longevity? There could be lots
Speaker 1: of different reasons for that. But if we ignore that,
Speaker 1: if we ignore you know, those facts, we're going to
Speaker 1: wind up making wrong conclusions in all the policy we
Speaker 1: come up with about things like health, you know, and
Speaker 1: and you know, financial savings and you know, social organizations, schools,
Speaker 1: you know, and so on. I think I think we
Speaker 1: can't sort of pretend that you know, that doesn't exist
Speaker 1: or it's not a significant, you know, factor to take
Speaker 1: into into consideration. We shouldn't say that it's everything, but
Speaker 1: but nor should we pretend that it's nothing. So you
Speaker 1: said a lot of really good things there. I agree.
Speaker 1: I agree with an awful lot of that. I think
Speaker 1: a very tricky thing something's been difficult for me in
Speaker 1: my career is that I started off I wanted to
Speaker 1: learn as much as I could about intelligence, and I
Speaker 1: didn't step out into the real world at all. So
Speaker 1: I still you know, there was a there was a
Speaker 1: period of let's say ten years where I like did
Speaker 1: the most I try to do the most rigorous science
Speaker 1: I could, try to publish in the most highest scientific
Speaker 1: turnal articles and just understand what is the you know,
Speaker 1: biological and environmental basis of IQ. I studied with you
Speaker 1: know Nick Macintosh at Cambridge, who wrote I think the
Speaker 1: best textbook on the topic. By the way, he agrees,
Speaker 1: he would agree, he would He's he just passed away recently, unfortunately,
Speaker 1: but he would agree with you that that there's value
Speaker 1: in separating talent from intelligence, you know, specific talents from
Speaker 1: the general concept of intelligence or the concept of general
Speaker 1: intelligence put in differently, so you would say there's value
Speaker 1: in that. So I spent a good ten years trying
Speaker 1: to really study us up and then I, you know,
Speaker 1: got into this, this this very fascinating world called education
Speaker 1: where you have so many kids falling between the cracks,
Speaker 1: and there are so many reasons why kids are falling
Speaker 1: between the cracks. One major reason, I think is because
Speaker 1: of our of the teachers conceptualizations they bring to the
Speaker 1: classroom of of what are the indicators of potential or
Speaker 1: what are the indicators of what kids are capable of achieving.
Speaker 1: Do you think there's benefit because I do think there's
Speaker 1: benefit in an education context, and I still try it.
Speaker 1: By the way, I still published papers, and I still
Speaker 1: talk about the construct of intelligence. But when I enter
Speaker 1: the world of education, I see value in having a
Speaker 1: broader conceptuization of intelligence that at least allows for different,
Speaker 1: like different indicators from students that we could nurture. Well,
Speaker 1: not every concept that comes from scientific psychology, I think
Speaker 1: is necessarily right for sort of you know, direct insertion
Speaker 1: into any particular outside context. I mean, I'll give you
Speaker 1: an example. I'm not sure we're learning much directly from neuroscience,
Speaker 1: from cognitive neuroscience, from fMRI. That should really make a
Speaker 1: difference at all in how we in how we teach children.
Speaker 1: I think one day we will, but I'm not sure
Speaker 1: we're there yet. And yet it's sort of like the
Speaker 1: hot thing from my outsider's perspective, you know, educational neuroscience
Speaker 1: and and so on. I'm not sure that you know,
Speaker 1: I'm not sure that that's you know, that that's really
Speaker 1: you know, applicable. And also the fact that something as
Speaker 1: a construct like general intelligence predicts significant variation across you know,
Speaker 1: thousands of people in occupation or something like that, you know,
Speaker 1: obviously doesn't mean that for any one person it sets
Speaker 1: up or lower bounds. And I think that's that's a
Speaker 1: clear mistake that people make, you know, over and over again,
Speaker 1: is they they don't really quite appreciate the variability. Like
Speaker 1: if if you have someone who scores you know, if
Speaker 1: you have someone who scores you know, ninety on an
Speaker 1: IQ test, they're less likely to get a PhD in
Speaker 1: psychology than someone who scores you know, one hundred and thirty.
Speaker 1: But that doesn't mean it's impossible. So the mistake is
Speaker 1: to say, well, you're doomed. You know, you're never going
Speaker 1: to go any farther than this. And admittedly, people who
Speaker 1: you know studied IQ and you know, in you know, fifty,
Speaker 1: you know, sixty eighty, one hundred years ago, you could
Speaker 1: see these tables, you know, even even maybe more recently
Speaker 1: that said, like, here are the occupations that are suitable
Speaker 1: for you, you know, based on your test score. Right,
Speaker 1: But there's so many things that could have could cause
Speaker 1: low test scores. There's so many other you know, traits
Speaker 1: that could be important. There's so many other ways they
Speaker 1: could combine in any one person, you know, different ways
Speaker 1: of doing the same job and so on. It's it's
Speaker 1: sort of too narrow a conception for that. But at
Speaker 1: the same time, you can't throw you can't, you can't
Speaker 1: throw it out as a social you know, as a
Speaker 1: social science variable, as a social science variable, it's incredibly powerful,
Speaker 1: you know, and explains a lot about the way our
Speaker 1: present you know, present societies you know, are organized in function.
Speaker 1: But that doesn't mean that for any one person, you know,
Speaker 1: like look at you know, look at someone like Bobby Fisher,
Speaker 1: like you know, Bobby Fisher World chess Champion, like essentially
Speaker 1: was was schizophrenic. And I think a lot of people
Speaker 1: in chess are only now sort of coming to grips
Speaker 1: with that. You know that he was at least schizotypal,
Speaker 1: and you know probably you know, a very high but
Speaker 1: a very high functioning schizophrenic, like the best chess player ever.
Speaker 1: You know, it is something that's considered a very cognitive,
Speaker 1: intellectual you know, pursuit and so on. I mean, we science,
Speaker 1: you know, behavioral science is never good at explaining one person.
Speaker 1: Like how does behavioral science explain Hitler? Nobody? You know,
Speaker 1: you can't, like, you can't explain Hitler by doing surveys
Speaker 1: and calculating correlations and so on. You know, it's not
Speaker 1: gonna it's not gonna happen or even probably looking at
Speaker 1: his brain. Well right, yeah, you know, I mean it's
Speaker 1: it's this goes back to like a long standing you know,
Speaker 1: argument about what's right level you know of analysis in
Speaker 1: psychology and so on, Like you can't really understand how
Speaker 1: the brain works by looking at the neurons. It's even
Speaker 1: harder when you're trying to understand one person. Right, And
Speaker 1: the thing with Bobby Fisher is very interesting because schizotippy
Speaker 1: is correlated with apohemia, which is the human tendency to
Speaker 1: see patterns that don't really exist. Right, that he was
Speaker 1: like a master at like actually seeing patterns that have
Speaker 1: seeing patterns that do exist, that he's built up through
Speaker 1: many years of expertise. Well do you see my point?
Speaker 1: So I'm like, yeah, although uh in yeah, yes, and
Speaker 1: so in chess. So apparently you know this, This again
Speaker 1: speaks to the idea that you know, a lot of
Speaker 1: a lot of things that we can become experts in
Speaker 1: are really about domain specific learning, you know, not necessarily
Speaker 1: about any kind of limits set by our general intelligence
Speaker 1: or our personality traits. Right, So I'm sure that Bobby
Speaker 1: Fisher's ability to recognize patterns in chess, you know, was
Speaker 1: probably largely independent, almost entirely independent of his ability to
Speaker 1: recognize patterns in whether the Jews are controlling everything in
Speaker 1: the world and ruining his life. Right, those two kinds
Speaker 1: of patterns are really different patterns and probably governed, you know,
Speaker 1: you know, governed in some ways by by by different
Speaker 1: you know, systems, or at least all the chess knowledge
Speaker 1: he learned was sort of like probably encapsulated and set
Speaker 1: aside from, you know, from all of his other thinking difficulties,
Speaker 1: which manifested themselves more and more as his life went on.
Speaker 1: So that's right, that's that's I think that's probably the explanation.
Speaker 1: And you see that with John Nash as well, although
Speaker 1: well and his math suffered, his math suffered, I think, well,
Speaker 1: or if you if you right, okay, so if if
Speaker 1: you become completely psychotic, right, it's going to be hard
Speaker 1: to actually like devote time to you know, doing your
Speaker 1: work and so on. But but again going back to intelligence, right,
Speaker 1: I think it stands to reason that you know, someone
Speaker 1: who's starting out, you know, as someone who regularly scores
Speaker 1: one thirty on IQ tests will probably find it a
Speaker 1: little bit easier to become a chess grand master than
Speaker 1: someone who regularly scores a lot lower than that. But
Speaker 1: it doesn't mean that the lower scorers can't do it,
Speaker 1: or that they're somehow you know, incapable or whatever. So
Speaker 1: you know, there's talent and there's experience. There's there's both
Speaker 1: of those. There's both of those things, right, Yeah, so
Speaker 1: we can we can include general intelligence as a talent,
Speaker 1: just like you have any other kinds of talents. There's
Speaker 1: no reason why that source of human variation isn't just
Speaker 1: another talent, and it has meaningful implications in a more
Speaker 1: broader sense than maybe some other talents. You could have
Speaker 1: like some sort of hierarchy of generality of actually you do,
Speaker 1: it's called this, you know, like you can have like
Speaker 1: at least for in terms of general in terms of cognobilities.
Speaker 1: It's a hierarchy, right. A lot of people don't aren't
Speaker 1: aware of that. Yeah, yeah, I was gonna I was
Speaker 1: gonna actually say CC, but I was thinking like, well, no,
Speaker 1: it's how nerdy do we really want to get but
Speaker 1: that But that's just the idea that that there are
Speaker 1: sort of like more specialized abilities which are probably served
Speaker 1: by sort of more specific regions of the brain, but
Speaker 1: that those tend to be correlated a little bit, so
Speaker 1: that you have sort of like the second order you know,
Speaker 1: the these second order factors which contain several of those,
Speaker 1: and then you've got you know, higher order you know, uh,
Speaker 1: general factor. It's very It's not that I don't think
Speaker 1: it's that complicated. It's that complicated. Well, that's that's a
Speaker 1: funny statement. It's both it's both incredibly complicated and and
Speaker 1: at the end of the day, not the complicated at
Speaker 1: the same time. So you know, part of my day
Speaker 1: job is I'm on a like a mission. I don't
Speaker 1: know that's too strong of a word, but I can't
Speaker 1: think of any other word in its place. To come
Speaker 1: up with a new test of imagination that is, has
Speaker 1: set differential predictability and has his value and utility above
Speaker 1: and beyond an IQ test. Now, such a test, it's
Speaker 1: going to be very hard to for to not to
Speaker 1: have some saturation of G or general intelligence. Absolutely, but
Speaker 1: there I do believe there are there are skill sets
Speaker 1: and mental capacities there that are always partially distinct, so
Speaker 1: that that's one of our things we're trying to do
Speaker 1: as well. And I'm okay, by the way, this is
Speaker 1: really cool, Chris. You've said you've softened your views a
Speaker 1: bit on Yeah, I've softened me too, in a in
Speaker 1: a in it in the opposite direction, in a sense, yeah, no,
Speaker 1: in the opposite direction. So I am okay now actually
Speaker 1: different and I I'm gonna be in record saying this
Speaker 1: right now. Differentiating between general intelligence and creativity. I'm okay
Speaker 1: differentiating those too, because to me, or at least general
Speaker 1: intelligence and imagination, because I think you know what I
Speaker 1: would say, in like in a public spheres, I think,
Speaker 1: you know, general intelligence involves a whole set of cognitive
Speaker 1: proceeds that are very good at ascertaining what is you know, learning,
Speaker 1: you know, what is reading, comprehension, et cetera. And I
Speaker 1: think imagination is a set of partially overlap non overlapping
Speaker 1: set skill sets associated with what could be that kind
Speaker 1: of that kind of thinking. So I'm actually okay differentialing
Speaker 1: these two. But by the way, that's a big that
Speaker 1: was the imagination different from creativity in your in your view?
Speaker 1: And I'm sure of curious about what because people, of
Speaker 1: course have been trying to come up with creativity tests
Speaker 1: for decades and with sort of somewhat unsatisfying results, and
Speaker 1: you know, in my view, they they you know, they
Speaker 1: have some reliability and so on, but they just don't
Speaker 1: really seem to, you know, I don't know, get at
Speaker 1: the core of something. I could. They just leave me
Speaker 1: with sort of like a vaguely unsatisfied feeling even after
Speaker 1: I use them in my own research. So I could
Speaker 1: pletely agree. And so we're funding We just selected sixteen
Speaker 1: research projects three million dollars total to for there to
Speaker 1: be new innovative ways of measuring imagination. I'm really excited
Speaker 1: about some of the approaches. We're gonna have our big
Speaker 1: press release of the projects. You can see where they
Speaker 1: are soon, so I can't mention them just yet, but
Speaker 1: I at least they go beyond. So we wanted to
Speaker 1: make sure that for most of the proposal, for all
Speaker 1: the proposals, that they went beyond divergent thinking in some way.
Speaker 1: You know, there are diversion thinking tests like how man
Speaker 1: uses are there for a brick? So I agree with that. Now,
Speaker 1: let me tell you the way I've been thinking about this,
Speaker 1: because we just got a paper accepted in Nature Scientific
Speaker 1: Reports that I think presents the framework in a way
Speaker 1: that makes sense to me. So you could I view
Speaker 1: creativity as a combination of general intelligence and imagination, or
Speaker 1: at least the interaction of the two large scale of
Speaker 1: brain networks that are differentially associated between those two with
Speaker 1: those two constructs. So we could think of the executive
Speaker 1: attention network as really strongly tied to variation in general intelligence. Right,
Speaker 1: there's so much research supporting that. But we also, you know,
Speaker 1: the recent discovery of the default mode network or I
Speaker 1: call it, you know, in a q qt C way,
Speaker 1: the imagination network is associated with a different source of variation,
Speaker 1: and I think that that's a source of variation that
Speaker 1: is part of creativity. It's necessary. I think it's necessary,
Speaker 1: but not sufficient for creativity. So what you see in
Speaker 1: people with schizophrenia is very difficult executive functioning, but they
Speaker 1: are up the kazoo on their default mode network functioning.
Speaker 1: They're like a walking default mode network. They have trouble
Speaker 1: distinguishing between reality and fantasy and fact, which, like b
Speaker 1: A ten, we know is super important for that right,
Speaker 1: Like the you know, the very tip of the prefontal
Speaker 1: corte of the frontal cortex is crucial for distinguishing fantasy
Speaker 1: and reality. So those who are just really really creative
Speaker 1: are are have a very strong capacity to be very
Speaker 1: flex and switching between these modes of cognition. So that's
Speaker 1: sort of how I viewed. I view a creative creativity's
Speaker 1: umbrella sort of thing that consists of general intelligence as
Speaker 1: well or executive functioning as well as imagination. And I
Speaker 1: view imagination is necessarily but not sufficient for creativity. So
Speaker 1: it sounds like I should have applied for it. Sounds
Speaker 1: like I should have applied for one of your grants. Yeah, yeah,
Speaker 1: if anyone turns if anyone turns it down, you can
Speaker 1: always throw a hundred thousand my way. I'm kind of
Speaker 1: doing something similar, you know, really with with social intelligence
Speaker 1: right now. And incidentally, I think, you know, the default
Speaker 1: the default network is in a little bit one of
Speaker 1: the way one of those Worshock tests, right, Like, for
Speaker 1: some people it's the mind wanting network. For some people
Speaker 1: it's creativity, imagination. Other people it's social. You know, it's
Speaker 1: sort of like what what does this do? It seems
Speaker 1: like it's everything, But i Q you know, is another
Speaker 1: way of you know, when I think about sort of
Speaker 1: like what would you know, what would a large scale
Speaker 1: brain organization have evolved to do? Yeah, I'm not so
Speaker 1: sure about imagination and creativity. I think I could be convinced,
Speaker 1: like someone who had really thought that through very carefully
Speaker 1: might be able to convince me. But I'm it's easier
Speaker 1: for me to convince myself that, you know, think thinking
Speaker 1: about other people might have been the evolutionary purpose. Now
Speaker 1: maybe you can harness a network you know that's useful
Speaker 1: for thinking about other people and now think about objects
Speaker 1: and you know, and and you know, animals and imaginary
Speaker 1: things you know, and so on. I mean, I'm not
Speaker 1: a good enough evolutionary psychologist or evolutionary neuroscientist to sort
Speaker 1: of sort all this out, but I think it's interesting
Speaker 1: that sort of this default network is sort of like,
Speaker 1: in a way, captured so much imagination, you know, captured
Speaker 1: so much of people's imagination and and made them you know,
Speaker 1: think about it in so many in so many different ways.
Speaker 1: One thing I did want to say is, uh, you know,
Speaker 1: I think you know what one metaphor that I find
Speaker 1: kind of useful for thinking about you know, intelligence as
Speaker 1: as as defined by general intelligence or IQ, is it
Speaker 1: is sort of your ability to use your brain to
Speaker 1: operate your brain like a computer. Uh, you know, so
Speaker 1: your your ability to do the things that computers are
Speaker 1: good at, right, like remember lots of stuff for a
Speaker 1: short period of time, you know, easily assimilate new information, uh,
Speaker 1: you know, do calculations, you know, step by step, go
Speaker 1: through things you know, like you know, juggle things you know,
Speaker 1: and memory and so on, all all the kind of
Speaker 1: stuff that you know, most animals can't do and and
Speaker 1: humans are actually really bad at, you know, you know,
Speaker 1: a ten year old can program a computer to do
Speaker 1: most of these things better than humans can do, but
Speaker 1: there's a lot of variation and how well humans can
Speaker 1: do them inside, you know, inside their own brains. And
Speaker 1: that's what you know, IQ is measuring, And maybe there's
Speaker 1: so much variation in it because it is a relatively
Speaker 1: recent evolutionary development that we have sort of a domain
Speaker 1: general working memory, and we're able to learn the meanings
Speaker 1: of lots of different things and just sort of store
Speaker 1: them forever in our lives, like vocabulary words you don't forget,
Speaker 1: you know, and so on. A vocabulary test, it turns out,
Speaker 1: are great great IQ tests, as are you know, tests
Speaker 1: of basically juggling mental operations like you know, working memory
Speaker 1: and and so on. But you could write a computer
Speaker 1: program and like ten lines that could that could kill
Speaker 1: any end back working memory task, you know, as high
Speaker 1: as you want to go, right, So it's your ability
Speaker 1: to like use your brain as though it's a ten
Speaker 1: line computer program. You know that you know, that's that
Speaker 1: simple and that complex at the same exactly right. But
Speaker 1: that but turns out like that's really easy for silicon
Speaker 1: chips to do and really hard for the brain. All
Speaker 1: of its marvels and wonders to do, you know, compared
Speaker 1: to something like recognizing faces or even you know, predicting
Speaker 1: whether Scott's going to be happy or sad at the
Speaker 1: end of this interview or something like that. You know
Speaker 1: that those things are much easier, even though computers would
Speaker 1: have no idea how to do them. You know, that's
Speaker 1: because that involves messy emotions to really answer that question.
Speaker 1: This is this is and I think that's where things
Speaker 1: you know, it's actually a great segue into intuition. What
Speaker 1: a perfect segue. Actually, let's let's segue into like intuition.
Speaker 1: Let's segue in artificial intelligence and try to understand what
Speaker 1: are the why they to that puzzle you just pose. So,
Speaker 1: I mean, this is a topic that I'm im mentally
Speaker 1: fascinated with. I mean, most people don't realize this because
Speaker 1: I never I never mentioned this anymore. I never did
Speaker 1: anything with a degree. But I have a degree in
Speaker 1: human computer interaction from Carnegie Mellon, and I was there
Speaker 1: was a time when it was a time in my
Speaker 1: life when I was like obsessed with with AI and
Speaker 1: like you know, and and accusing human computers and all
Speaker 1: that stuff. I don't know what happened to that Scott.
Speaker 1: But all my friends went off and got like six figures,
Speaker 1: you know, jobs right after undergrad and I went to
Speaker 1: grad school and made like one figure. But they're not
Speaker 1: they're not here interviewing me today. That's exactly right, that's
Speaker 1: exactly right missing out. So so Jeff Hawkins has this
Speaker 1: theory of intelligence. I don't know if you've read his
Speaker 1: book on intelligence, have you? I haven't. I haven't read
Speaker 1: it yet. I've sort of heard of the actually always
Speaker 1: one of the many books I own but haven't read. Okay, Yeah,
Speaker 1: so he he really argues that tells all comes down
Speaker 1: to pattern recognition. He's really big into this, this idea
Speaker 1: of and and pattern recognition. As we know, like our
Speaker 1: inteligence is very good at visual I wouldn't say really good,
Speaker 1: but you know it's it's it's okay at at like
Speaker 1: war level pattern recognition, it gets very but you know,
Speaker 1: our vision system is like infinitely better, right than an
Speaker 1: AI computer. So but there's like there's pattern recognition that's
Speaker 1: conscious and there's pattern recognition that's unconscious. And this was
Speaker 1: the basis for for my dissertation. I was fascinating to
Speaker 1: see if there are individual differences and impulsit learning, which
Speaker 1: I think is another form of pattern recognition. And and
Speaker 1: what was by the way you were, you were immenseally
Speaker 1: helpful back then we're talking like ten years ago, like
Speaker 1: the first time we ever talked, and you're very supportive
Speaker 1: of my dissertation. So I really appreciate that. And you know,
Speaker 1: I just I was fascinated to find that in pussit learning,
Speaker 1: individual difference in PUS learning are independent of individual differences
Speaker 1: in IQ, at least somewhat. And there's there's actually been
Speaker 1: further research on this topic. Some people have replicated some
Speaker 1: of those findings, and people are still doing research on
Speaker 1: statistical or individual differences in statistical learning. So but this
Speaker 1: suggests to me that we have these different systems. We
Speaker 1: have like this this intuitive probabilistic system that automatically soaks
Speaker 1: up like the probablistic real structure of the world and stuff.
Speaker 1: But then we also have this conscious system that we
Speaker 1: have like access. It's almost like IQ or general intelligence
Speaker 1: or fluid reasoning, like people really got Raven's advanced progressive
Speaker 1: matrices are able to somehow like access consciously to make
Speaker 1: a decision. Do you see what I'm saying, it's it's
Speaker 1: very interesting. Yeah, I think you know, the kind of
Speaker 1: intelligence if Hawkins says that intelligence is patterned recognition, to me,
Speaker 1: the kind of intelligence he's talking about is the kind
Speaker 1: of intelligence that lies behind you know, what we might call,
Speaker 1: broadly speaking, intelligent behavior, sort of the things that animals
Speaker 1: are able to do, you know, to survive and thrive
Speaker 1: and so on, you know, involves a certain kind of intelligence, right,
Speaker 1: recognizing their food, you know, recognizing their predators, recognizing their mates,
Speaker 1: you know, you know, doing motor behavior. Like, there's all
Speaker 1: kinds of incredibly complex stuff that is hard for computers
Speaker 1: to do, and it's legitimate to call that a kind
Speaker 1: of intelligence. And that's what artificial intelligence has been trying
Speaker 1: to get computers to do for a long time. Right.
Speaker 1: It turns out that the things that that we call intelligence,
Speaker 1: that are measured by intelligence tests, you know, easy for computers. Yeah,
Speaker 1: are pretty easy for computers, right. You know, so that
Speaker 1: the early you know, AI guys made a little bit
Speaker 1: of a mistake when they said, if we could just
Speaker 1: solve computer chess, you know, then we you know, game over. Right. Well,
Speaker 1: it turns out that was sort of like round one
Speaker 1: that was like the easy level. Yeah, exactly right, that
Speaker 1: was the easy level of the game, you know, And
Speaker 1: even with all the progress in deep learning and so on,
Speaker 1: you've still got you know, networks that are trained to
Speaker 1: recognize cats, but then they you know, they misclassify, you know,
Speaker 1: completely other things as cats and so on. It's it's
Speaker 1: it's it's a hard yeah. Uh, it's a hard problem.
Speaker 1: But I think it's legitimate to call that intelligence of
Speaker 1: a kind. And and by the way, I think your
Speaker 1: your finding was was exactly was exactly right about uh,
Speaker 1: you know, psychometric intelligence IQ tests not being very related
Speaker 1: at all to implicit learning, and I think there are
Speaker 1: many other cognitive abilities abilities of the brain which are
Speaker 1: not related to IQ, you know, so that this is
Speaker 1: you know, I I don't know if you ever go
Speaker 1: on quorra, the website Quora or not, but there are
Speaker 1: a lot of people on Quora who always ask questions
Speaker 1: about i Q as though they have the lay view
Speaker 1: that sort of IQ is you know, the only thing
Speaker 1: that determines the mental ability of a person, Right, It's
Speaker 1: sort of like IQ is everything there. And I don't
Speaker 1: know sort of why they why they think this, Yeah, uh,
Speaker 1: but it's clearly not the case. Right, You've got implicit learning.
Speaker 1: I've I found a while ago that face recognition and
Speaker 1: I'm many replications of this face recognition ability is not
Speaker 1: related to UH to IQ. UH find you find variation
Speaker 1: in that you present that in my class, I remember that. Yeah, yeah, no,
Speaker 1: it's it's you know, they're all like they all have
Speaker 1: small correlations, right like when you mentioned earlier, sort of
Speaker 1: like the saturation of general intelligence. These things I've been
Speaker 1: working on coming up with these social intelligence tests, and
Speaker 1: it turns out it's really hard to make, you know,
Speaker 1: to make a test of any kind that people who
Speaker 1: you know, score high on IQ tests don't also have
Speaker 1: a little bit of an edge, you know, don't seem
Speaker 1: to have a little bit of an edge on But
Speaker 1: some things are just much less related to intelligence and
Speaker 1: others and implicit learning and face recognition. I think a
Speaker 1: lot of the things that come from the default mode network.
Speaker 1: You know, well that's what I'm that's what i'm that's
Speaker 1: what I'm working on now. But but if you look
Speaker 1: at the ways people try to measure, you know, social ability,
Speaker 1: you know, those tests do low I mean, those tests
Speaker 1: also measure intelligence. I think that's method variance issue. I
Speaker 1: think you mean because they're asking questions that are come
Speaker 1: back words no, no, because there are things that tap
Speaker 1: executive that rely heavily on executive functioning, they're like on
Speaker 1: they're still on the spot time. You know, most of
Speaker 1: them are time tests, so I think you still get
Speaker 1: you get the executive function you know aspect in there
Speaker 1: as well. That's why I think I get the sense
Speaker 1: that it's I get the sense that on time tests,
Speaker 1: you know, wouldn't make like taking out the timing wouldn't
Speaker 1: really make that much of a difference. What about like
Speaker 1: actually like putting people though, like in front of each
Speaker 1: other is what I'm saying, Like, if we're talking about
Speaker 1: like social interactions, like I want more tests that where
Speaker 1: you actually like have people interact with each other. So
Speaker 1: I'm my here's my view, and it's it's not really
Speaker 1: based on too much data, but but my view is
Speaker 1: that you know, you're right in a sense that a
Speaker 1: test of looking at pictures and pushing keys is going
Speaker 1: to be you know, probably more g low, more more
Speaker 1: of an IQ test. Even if the pictures are human
Speaker 1: faces and the keys correspond to you know, emotions, that's
Speaker 1: probably going to be a bit more of a measure
Speaker 1: of IQ than having someone interact and seeing like whether they,
Speaker 1: you know, with someone else and seeing whether they you know,
Speaker 1: you know, make the right decision or something like that.
Speaker 1: But still, even in that latter case, you know, like
Speaker 1: face to face interaction very naturalistic and so on, I
Speaker 1: think you're still going to find some effective of general intelligence,
Speaker 1: not zero, You're going to find some effective general intelligence.
Speaker 1: So that's something about what's kind of fascinating about it,
Speaker 1: the idea that there is this sort of something that
Speaker 1: general I mean, you know, like if if you if
Speaker 1: you control for everything else that you can possibly think of.
Speaker 1: I bet you know Michael Jordan was a little smarter
Speaker 1: than the other basketball players, you know, I mean, you know,
Speaker 1: maybe maybe you know I shouldn't, you know, I shouldn't
Speaker 1: contradict myself and try to explain individuals right and so on,
Speaker 1: But I bet you would find that, like the players
Speaker 1: just score more points, you know, across all levels of basketball,
Speaker 1: are probably on average a little smarter than the players
Speaker 1: just score fewer points. And why why would that be? Well,
Speaker 1: maybe they spend time reflecting on how they played, and
Speaker 1: they're better able to sort of remember and think through
Speaker 1: like some strategic aspects of the decisions they made. And
Speaker 1: it's not all a physical game, you know, and everything
Speaker 1: involves some kind of mental challenge. And the idea that
Speaker 1: we can separate out, you know, executive function, working memory,
Speaker 1: you know, planning and things like that from from other
Speaker 1: things is a little bit of a myth because almost
Speaker 1: everything humans do involve some of those some of those things. Wow,
Speaker 1: you said so many different things that, Holy cow, Chris, Chris, Chris.
Speaker 1: First of all, I'm really glad that you made the
Speaker 1: correction when you made the Michael Jordan example and then
Speaker 1: and then phrased it in a more scientific accurate way,
Speaker 1: because I you know, you know, the saying I'm very
Speaker 1: passionate about is wholeheartedly not assuming you know someone's potential,
Speaker 1: an individual's potential for success or something just based on
Speaker 1: the IQ score. So but but I think that you're
Speaker 1: probably correct when we're in terms of averages. So I'm
Speaker 1: glad you made that quick correction. The second thing, so
Speaker 1: I think that you know as much as I've studied
Speaker 1: G and really trying to understand what the G factor
Speaker 1: for listeners, the G factors general is basically general intelligence
Speaker 1: the thing that I've I've learned is that it is
Speaker 1: so general because almost everything we do in life that
Speaker 1: doesn't involve being completely asleep taps into executive functioning. So
Speaker 1: I think that you're in a deep sense, you're absolutely right, Like,
Speaker 1: it's very it's gonna be very hard pressed to find
Speaker 1: any awake activity that doesn't involve some level of conscious
Speaker 1: integration of holding something and working memory of you know all,
Speaker 1: and you go down the list of all the kinds
Speaker 1: of cognitive functions that comprise the G factor. So I
Speaker 1: think in that sense, it's very, very difficult to find
Speaker 1: any test that doesn't significant or doesn't have a positive
Speaker 1: relationship to G or general intelligence, which is in a
Speaker 1: large reason what spurred me for my dissertation, and is
Speaker 1: that I was like, could maybe something unconscious, you know,
Speaker 1: be the thing? Could that be the thing? So so
Speaker 1: so I think I think we're on the same page
Speaker 1: with that. Yeah, And this could have something to do
Speaker 1: with why you see things like, you know, general intelligence
Speaker 1: being correlated with longevity, you know, or with health. Right,
Speaker 1: there could be lots of pathways, but one of them
Speaker 1: could be something as simple as you know, the better
Speaker 1: your executive function and the working memory, your working memory,
Speaker 1: the less likely you are to forget, you know, to
Speaker 1: transfer some piece of information from your nurse to your
Speaker 1: doctor that you thought you should make sure the doctor hears,
Speaker 1: you know, when you're in the hospital after an accident
Speaker 1: someday or something like that, and you accumulate enough of those,
Speaker 1: you know, incidents over a lifetime where you know a
Speaker 1: little bit of a you know, a breakdown and working
Speaker 1: memory or executive function or something like that cause you
Speaker 1: to like forget one thing or transpose one thing or
Speaker 1: something like that. And you know, the build up over
Speaker 1: a long period of time, you know, could be you know,
Speaker 1: could be significant. And that's that's I think you you make.
Speaker 1: You know, you make the excellent point that there's there's
Speaker 1: always a role for proper executive function in almost any
Speaker 1: you know, waking activity. You could be doing it, except
Speaker 1: perhaps when you're not aware of Right, That's that's exactly
Speaker 1: my point. That's exactly your point, right, you know. Yeah,
Speaker 1: And I think that it does matter though the dependent
Speaker 1: measure that you're what you're what you're trying to predict.
Speaker 1: So what I found really interesting was this paper that
Speaker 1: Colin Deung and I and uh and other corburetors published
Speaker 1: in Journal of Personality recently showing that i Q was
Speaker 1: essentially irrelevant to predicting artistic you know, predicting variation in
Speaker 1: artistic creative achievement. And I think that's that's a non
Speaker 1: trivial finding. Do you know what I mean? Because I mean,
Speaker 1: I mean there might be some scientists I think it's
Speaker 1: a trivial finding. But I think you and I would
Speaker 1: agree that. You know, there are so many different ways
Speaker 1: of expressing yourself in this world, of adding value to
Speaker 1: this world, of doing great in this world, and they're
Speaker 1: they're differentially related to how much they recruit general intelligence
Speaker 1: brain structures. Yeah, well, I think this is a good
Speaker 1: time to go back and and and and for me
Speaker 1: to go back and say that when I say that,
Speaker 1: you know, if I assert that I bet they're is
Speaker 1: some small contribution of intell general intelligence to creative achievement,
Speaker 1: it doesn't mean that I'm saying that that's the biggest contribution.
Speaker 1: It could be that it's like, you know, five percent
Speaker 1: of the variants or something like that, or two percent
Speaker 1: of the variance or something. It's just that it's not
Speaker 1: it's not going to be zero and and I'll bet
Speaker 1: you that. I mean, by the way, I just met
Speaker 1: Colin recently. He's a great you know, he's a great guy. Uh,
Speaker 1: you know, he's you know, you're you you know him,
Speaker 1: you know a thousand times more than I do. But
Speaker 1: he does really interesting stuff. You should have him on
Speaker 1: if you haven't yet, and uh plan to. I think that,
Speaker 1: you know, even in that case, like I think we
Speaker 1: have to be worried about we have to be worried
Speaker 1: about things like range restriction and measurement. Right, So, like
Speaker 1: if if we measure creative achievement, you know, some of
Speaker 1: the ways of measuring creative achievement, as you know, involves
Speaker 1: sort of like counting up external recognitions of creativity, like, right,
Speaker 1: did you ever win a prize? You know? Did you
Speaker 1: ever sell a work? You know? And things like that,
Speaker 1: and the ability to sort of negotiate, you know, that
Speaker 1: environment of you know, and during contests, you know, remembering
Speaker 1: to do things on time, you know, getting your work
Speaker 1: done and so on might be separate from the level
Speaker 1: of creativity, inspiration, technical skill, all of those things. So
Speaker 1: you know, it could be another case of where you know,
Speaker 1: when you when you try to you know, measure the
Speaker 1: relationship between two things. It's still going to sort of
Speaker 1: be there because because of the same you know, sort
Speaker 1: of thing we've been talking about. But that doesn't mean that,
Speaker 1: like your IQ score should have any sort of determination
Speaker 1: over whether you decide to pursue art. Right now, that
Speaker 1: would be the stupidest thing in the world to decide
Speaker 1: whether or not to pursue art because of your IQ score.
Speaker 1: I would be more likely to use the basis the
Speaker 1: extent to which you have artistic talent, but maybe even
Speaker 1: not then I probably would get some hate mail from
Speaker 1: artists for saying that, But but I would be more
Speaker 1: likely to use that as an indicator than i Q.
Speaker 1: You see, I'm saying, yeah, it's, it's, it's and it's
Speaker 1: there's some Well. The other thing, of course, is that
Speaker 1: there's so much of a huge you know, compared to
Speaker 1: how well you do something the first time you try it,
Speaker 1: or even the first ten times or twenty times. There's
Speaker 1: such a huge range of what's possible, right, I mean
Speaker 1: we know that. Like, look, so someone learns how to
Speaker 1: play chess. You know, they get a rating of one
Speaker 1: hundred on the Chess rating scale, but then ultimately they
Speaker 1: could get a rating of twenty or twenty five hundred,
Speaker 1: and what that means, every two hundred points means you've
Speaker 1: got a three to one chance of beating the person
Speaker 1: two hundred points below you. So you go from one
Speaker 1: hundred to three hundred, you've suddenly become good enough to win,
Speaker 1: you know, seventy five percent of the time against your
Speaker 1: old self. And you go to five hundred, and now
Speaker 1: it's seventy five percent. And they are like so many
Speaker 1: levels of that that humans can get to just with
Speaker 1: the brains we've got, right that probably don't have that
Speaker 1: much to do with intelligence, Right, it's good to start
Speaker 1: out being a higher IQ person, but you know, the
Speaker 1: higher the high super high IQ person playing is first
Speaker 1: game of chess, you know, compared to the low IQ
Speaker 1: person playing his first game of chess is no difference
Speaker 1: compared to like once you've literally learned how to do
Speaker 1: something with the first time you do it, there's so
Speaker 1: much of a bigger jump than you can make, you know,
Speaker 1: through training and practice and you know and experience and
Speaker 1: so on, than the variation you would see just in
Speaker 1: in the level of you know, incoming talent that people
Speaker 1: have that it's it's the talent cannot possibly be a limitation.
Speaker 1: You know, it's only a bye. It's only a it's
Speaker 1: only a bias or a nudge, you know, in terms
Speaker 1: of what you how easily you learn things and pick
Speaker 1: up on them and so on rate of learning you
Speaker 1: I agree. So one of your this is related to
Speaker 1: one of your critiques of the ten thousand hours rule.
Speaker 1: I'm putting this in close, but you can't see it
Speaker 1: because there isn't video. I mean you could see it,
Speaker 1: but my listeners can't see it. Yeah. So, by the way,
Speaker 1: I can't find in ch Anders Eriksson's papers he uses
Speaker 1: that term. It looks like something that Malcolm Gladwell coined.
Speaker 1: So this tech and I think Ericson has an article
Speaker 1: even where he says, like to stop blaming this on me,
Speaker 1: it's journalists who do did it correct? Correct? And now
Speaker 1: you had this a little bit of a of an
Speaker 1: intellectual version of a boxing match with Malcolm Gladwell. I
Speaker 1: found that that very very interesting to watch. I was
Speaker 1: like eating my popcorn, you know, like this going one
Speaker 1: of your criticisms of the way that that pop or
Speaker 1: popular writers including Maquebwell, has represented the ten thousand hours
Speaker 1: or the nature of success. Well, you know, what are
Speaker 1: some of your abeasts of that? I think you I
Speaker 1: think a lot of things you already said relate to it,
Speaker 1: but I thought i'd give you a chance to speak
Speaker 1: more openly about that. Uh. Well, I guess as far
Speaker 1: as the ten thousand hour rule goes, I think it's
Speaker 1: you know, from what I know, it's one hundred percent correct,
Speaker 1: and we shouldn't blame that on on Ericson. Maybe he
Speaker 1: said something like that to Gladwell wants an interview or
Speaker 1: something like that, you know, or maybe it was Gladwell's
Speaker 1: you know, you know, way of summarizing how he interpreted,
Speaker 1: you know, Ericson's work. I do think Ericson is pretty
Speaker 1: far out, you know, on the tip of the view
Speaker 1: that you know, the nature doesn't matter, that there's no
Speaker 1: such thing as talent for basketball players or something, yeah,
Speaker 1: or something is nature yeah yeah, yeah. Well, in in
Speaker 1: this well, in in this debate, it would would be
Speaker 1: would be grouped in the same you know, in the
Speaker 1: same place. So I do think Eericson, you know, for
Speaker 1: all his protestations, you know, he does take a very
Speaker 1: sort of extreme environmentalist, you know view, and then about
Speaker 1: particular kinds of practice being all that matter and so on,
Speaker 1: And from from the work that I've seen, it seems like,
Speaker 1: you know, there's a lot of variability in how much
Speaker 1: deliberate practice people put in to reach master levels of skill.
Speaker 1: And one wonders, then, what explains why some people can get,
Speaker 1: you know, in four thousand hours to a place that
Speaker 1: some people take ten or twelve thousand or other people
Speaker 1: never get to? You know. Then we're back to talent
Speaker 1: and you know, and and and other things in preparation
Speaker 1: for preparation for learning, and you know, and and so on.
Speaker 1: And I thought that, you know, one of the you know,
Speaker 1: I thought that Gladwell's book Outliers, which is where he
Speaker 1: wrote about this, one of one of his very many
Speaker 1: best selling books. And by the way, I own and
Speaker 1: have read every one of his books, and I will
Speaker 1: buy every other book he ever publishes, and I will
Speaker 1: read it. So because I personally always find out about
Speaker 1: interesting things from any well written book, you know, about
Speaker 1: social science or psychology or whatever. I find out things
Speaker 1: I didn't know before. I think you have to go
Speaker 1: and check up on them, you know, and like look
Speaker 1: at the sources you know and make you form your
Speaker 1: own opinions and so on. But I find them very
Speaker 1: enjoyable ways to learn about stuff. But in that book,
Speaker 1: so in Outliers, I think he does, you know, he
Speaker 1: puts a big thumb on the scale of you know,
Speaker 1: environmental factors determining people's ultimate success, when he doesn't really
Speaker 1: and I think he doesn't really give you know, much
Speaker 1: attention to variations in talent or cognitive ability. And it's
Speaker 1: in fact really hard to do a study that would
Speaker 1: actually let you disentangle those things, because if you do
Speaker 1: a retrospective study of people who achieved very high levels
Speaker 1: of performance, you may well find that the chess grandmaps
Speaker 1: put in more deliberate practice than the mere chess masters,
Speaker 1: you know. And what could explain that, Well, maybe it's
Speaker 1: the extra practice that made them into grand masters, or
Speaker 1: maybe they were doing better at the game early on,
Speaker 1: so that increased their motivation to practice more, you know,
Speaker 1: or they started out with more talent, you know, and
Speaker 1: that made it easier for them to put in the
Speaker 1: practice because they were getting higher returns from the practice,
Speaker 1: because the more talent enables you to get more you know,
Speaker 1: learning out of a one hour or a two hour
Speaker 1: three hour study session. Or something. There's so many things
Speaker 1: that I think the data don't really let us explain,
Speaker 1: so we can't settle on sort of like one extreme
Speaker 1: interpretation and then build our build our lives and our
Speaker 1: social arrangements around that. That's part of my objection. I
Speaker 1: guess that's great. I thought I was going to be
Speaker 1: like disagreeing with you more. I don't know why I
Speaker 1: thought that, but no, I mean, well, it could be.
Speaker 1: It could be that when I you know, it could
Speaker 1: be that on Facebook and on Twitter, I say things
Speaker 1: you know more, you know more more and more categorically
Speaker 1: than I do in longer and longer conversations. I don't
Speaker 1: cry on Facebook. I feel like everybody else, everybody else
Speaker 1: is always so happy on Facebook. I'm just trying to
Speaker 1: balance it out. Look, you know, I want to bring
Speaker 1: something up with you that's kind of been half baked
Speaker 1: on my mind, but I want to try to articulate it.
Speaker 1: Something that's been bothering me about the way that researchers,
Speaker 1: scientists use the equate i Q with the word intelligence,
Speaker 1: or they'll say like smart, you know, They'll they'll go
Speaker 1: into shorthand and start saying smartness or brain power and stuff. Well,
Speaker 1: hopefully scientists don't use the word brainpower because it's a
Speaker 1: horrible word. But yeah, I feel like something that bothers
Speaker 1: me personally about that from a justice perspective and also
Speaker 1: from a truth perspective, is I'm not convinced that the
Speaker 1: low end of that poll is stupidity. I actually think
Speaker 1: that we need a new scale of stupidity where the
Speaker 1: high end is maybe like low stupidity, do you know
Speaker 1: what I mean? But but so for me, for general,
Speaker 1: So for me, for me, low general cognitive ability is
Speaker 1: not aquivalent of stupid and I think that's something that
Speaker 1: is a really I think it's it needs to be
Speaker 1: said more, you know, especially with how we treat children
Speaker 1: and treat people with certain IQ scores. You know, I
Speaker 1: think there are people with lower IQ scores that you know,
Speaker 1: I think that there are people with high IQ scores
Speaker 1: that are incredibly ignorant and say really stupid things in
Speaker 1: a consistent alpha reliability sort of way. And as far
Speaker 1: as I'm concerned, no matter how like hi your Q
Speaker 1: are is, you're stupid, you know, in my view. So anyway,
Speaker 1: this is this is the first time I've ever kind
Speaker 1: of talked about this out loud, but I'd love to
Speaker 1: hear your thoughts if there's any sense to what I'm saying. Well,
Speaker 1: I guess I have two thoughts. One one is that
Speaker 1: you know, the language we use in you know, casual
Speaker 1: conversation among adults, you know, is not necessarily the language
Speaker 1: we want to train, you know, children to use to
Speaker 1: think about the world. Right, So if if I say,
Speaker 1: you know, if I if I say, if I say
Speaker 1: to my wife, you know, boy, you know, you know
Speaker 1: so and so something stupid today at work work, that's
Speaker 1: much different from you know, encouraging your children and not
Speaker 1: correcting when they say, oh, that kild never does you know,
Speaker 1: that could never does well in the vocabulary tests. He's stupid,
Speaker 1: you know, Like, those are two completely different you know things.
Speaker 1: And I think it's okay and and I think it's
Speaker 1: okay to use you know, negative and critical words and
Speaker 1: so on when we're you know, when we're talking, you know,
Speaker 1: when we're talking as adults, and especially when we're talking
Speaker 1: about you know, acts, acts and not people, right, because
Speaker 1: even the smartest people can do stupid things, you know,
Speaker 1: and uh and and so on, and it's it's it's
Speaker 1: nice to have caller for language and not to be
Speaker 1: sort of like trying to take care with every word
Speaker 1: we say and you know, and sterilize all of our sentences,
Speaker 1: you know, so that they can't possibly offend even people
Speaker 1: who aren't listening, you know. So uh, you know, so
Speaker 1: that's that's on the one hand. On the other hand,
Speaker 1: I think if I were making a stupidity scale, I
Speaker 1: would make the high scores be lots of stupidity, right,
Speaker 1: like let's go all the way and like, let's make
Speaker 1: the high scores be lots of stupidity. And maybe what
Speaker 1: you're talking about is sort of it reminds me of
Speaker 1: like the inverse maybe of Keith Stanovich's you know, rationality,
Speaker 1: you know, attempt to measure rationality. I'm not sure, Like
Speaker 1: I really admire, you know, Keith Stanovich is one of
Speaker 1: my favorite researchers. I admire you know, everything he's done.
Speaker 1: I'm not sure he's going to have really that easy
Speaker 1: a time ultimately disentangling rational decision making from IQ because
Speaker 1: the kinds of problems that that look at, you know,
Speaker 1: rationality and decision making are very heavily verbal and involve
Speaker 1: you know, manipulating quantities and thinking about functioning or thinking
Speaker 1: about things that typically you know, are acquired in like
Speaker 1: late college or graduate school curriculum, you know, like probabilities
Speaker 1: and things you know, and things like that, right, you know,
Speaker 1: So I'm not sure he's going to succeed there, but
Speaker 1: I think conceptually he's in the right place in that.
Speaker 1: You know, you can imagine all the geniuses, you know,
Speaker 1: at at Lehman Brothers, you know, who blew their blew
Speaker 1: theirselves up, you know, through a series of what probably
Speaker 1: it's fair enough to say we're stupid decisions, right and
Speaker 1: maybe you know, and maybe characterizing in more granular detail
Speaker 1: what was stupid about those decisions might be a little
Speaker 1: better than calling them stupid, you know, maybe lack of foresight,
Speaker 1: you know, impatience, successive risk taking, you know, failure to
Speaker 1: consider alternative options, you know, be you know, following the herd.
Speaker 1: I mean, all of those things are kind of things
Speaker 1: maybe that you know, can be characterized in some ways
Speaker 1: as facets of stupidity in the modern in the modern environment.
Speaker 1: That's just the example that comes to mind. You may
Speaker 1: you may have completely other ones in mind, but certainly
Speaker 1: those guys were all scoring high in IQ tests. They
Speaker 1: wouldn't have got hired by Lehman Brothers. You know, most
Speaker 1: of them if they weren't people who scored high on
Speaker 1: IQ tests. But the way you're talking suggests that you
Speaker 1: do it tie IQ so fundamentally to the words smart
Speaker 1: and so I would actually challenge a little bit of
Speaker 1: what you said in the sense that, like, you know,
Speaker 1: the idea of like smart people doing dumb things. In
Speaker 1: my view, if you're doing a lot of dumb things
Speaker 1: like like like I don't care what your IQ score is,
Speaker 1: Like you're like that, like like to me, you're no
Speaker 1: longer qualified to be smart at that point. Yeah, yeah,
Speaker 1: I mean I'm willing to I'm willing to divorce the
Speaker 1: two at some point, you know in the real world,
Speaker 1: Like like stupid as stupid does would be like a
Speaker 1: really like shorthand way of saying that, Which is funny
Speaker 1: because I'm quoting this, this is actually very fitting to
Speaker 1: my point. I'm quoting Forrest Gump. There then he say
Speaker 1: stupid is what stupid does. And you know you see
Speaker 1: a lot of people, Yeah, you see a lot of
Speaker 1: people like with loroll i Q. So, I mean a
Speaker 1: lot of their implication here is that you can see
Speaker 1: people with the will IQ be I think you can
Speaker 1: still be highly intelligent, so I think, or at least
Speaker 1: be highly smart and and but of course we're me
Speaker 1: and you. When we're using these words like we were's
Speaker 1: kind of like a wink wink, like we know that
Speaker 1: we have the scientific knowledge to be able to just differentiate,
Speaker 1: like we we both in the same page of what
Speaker 1: general intelligence is. You know, I'm just conceptually saying, I
Speaker 1: don't think that your general cognitoobility needs to be so
Speaker 1: innomly tied to real world conceptions of smartness and stupidness.
Speaker 1: I guess that's what I'm trying to say. Well, maybe
Speaker 1: what needs, maybe what needs to happen, is that that
Speaker 1: it would it would be nice if we could wave
Speaker 1: our wand and sort of you know, make people in general,
Speaker 1: like all the people on Quora who are obsessed with IQ,
Speaker 1: you make them more aware of the reality of what
Speaker 1: I do test measure and what that and what that
Speaker 1: construct you know, means and doesn't mean. And I personally
Speaker 1: like tend to when I throw around the word smart,
Speaker 1: I'm sort of meaning, you know, intelligent in the sense of,
Speaker 1: you know, scores well on measures of general intelligence. But
Speaker 1: but you know, the language is language, and there are
Speaker 1: you know, twenty different definitions for smart. Yeah, I'm sure,
Speaker 1: just like that's not exactly my definition. Yeah, and so
Speaker 1: that's exactly your But I wouldn't I would use that,
Speaker 1: But I wouldn't use that in I wouldn't use that
Speaker 1: in you know, I wouldn't use that even in writing
Speaker 1: a popular book or a popular article, you know, let
Speaker 1: alone in the classroom or in a journal article. You know,
Speaker 1: I wouldn't say, you know, I wouldn't. That's just a
Speaker 1: way that I sort of tend to think about it.
Speaker 1: And maybe one reason I do is because I I
Speaker 1: do try. You know, one thing I think I've learned
Speaker 1: from behavioral science, from you know, all the time I've
Speaker 1: been in behavioral science, is it's sort of like a
Speaker 1: constant it's a constant struggle to try to think like
Speaker 1: a behavioral scientist in everyday life and not you know,
Speaker 1: and not think like and not think like, you know,
Speaker 1: just a regular person. And it's not to say that
Speaker 1: regular people are dumb or anything like that. But behavioral science,
Speaker 1: if if it means anything, means that we have learned
Speaker 1: some things scientifically about human behavior that we should then
Speaker 1: be able to turn around and use in our lives.
Speaker 1: So you know, I try to think about intelligence in
Speaker 1: daily life as the kind of intelligence that's measured by
Speaker 1: IQ test, because that's a very productive, you know, branch
Speaker 1: of behavioral science. And that's why I think I get
Speaker 1: a little bit bothered when people use intelligence to sort
Speaker 1: of mean, you know, any any any equality that that's good,
Speaker 1: that you know, that that that we like about about people,
Speaker 1: or that helps them, you know, solve some of their problems.
Speaker 1: You know. I would never say that my electrician has
Speaker 1: electrical intelligence, right, you know. I mean, even if he's
Speaker 1: a really the best electrician in the world, I would
Speaker 1: say he's a really good electrician, you know, he's incredibly
Speaker 1: skilled at his job, you know. Or I might even
Speaker 1: say he has a lot of talent, you know, you know,
Speaker 1: if I think for some reason that he's the kind
Speaker 1: of electrician you know, who was always talented at this
Speaker 1: although I'm not really sure where I would get the
Speaker 1: evidence for that, because all I can see is like, how,
Speaker 1: you know, what kind of job does on my house.
Speaker 1: But I like to try to be a little bit
Speaker 1: more precise in you know, in that way. So you know,
Speaker 1: but I agree with you that it's it's a it's
Speaker 1: a horrible mistake, you know, to call people stupid because
Speaker 1: they seem to be the kind of people who would
Speaker 1: score low on IQ tests and you know, and especially
Speaker 1: even even worse to you know, differentially treat them that way,
Speaker 1: you know, with respect to like opportunities. And so unfortunately,
Speaker 1: there's got to be some you know, there's limited resources,
Speaker 1: right there's there's there's scarcity. You know, economics is a
Speaker 1: real thing, you know, so there's got to be some
Speaker 1: allocation of resources. We don't you know, we don't have
Speaker 1: unlimited resources for everyone. But you can, at the same
Speaker 1: time just say that, like how people score on tests,
Speaker 1: you know, set some kind of sealing or rules out
Speaker 1: you know, rules out possibility, which is all the more
Speaker 1: reason why we needed we needed to do the testing intelligently.
Speaker 1: And that that's my whole point, you know, that's a
Speaker 1: big point, is that we need to be really intelligent
Speaker 1: how you know, what kind of data we are gathering
Speaker 1: and what kind of questions we're trying to answer to
Speaker 1: solve for person's needs. You know, I jokingly, but not
Speaker 1: half jokingly, but I made some day do this. I
Speaker 1: was talking to Adam, when I was talking to Adam Grant,
Speaker 1: and I said, people would be shocked but to hear this.
Speaker 1: But I think I want to write a book someday
Speaker 1: on why IQ matters or or or like write a
Speaker 1: book on like I just IQ because I and basically
Speaker 1: popularized Nick McIntosh's book because like, I'm so well ground
Speaker 1: I'm so grounded to like like knowing that perspective and
Speaker 1: knowing what it is when scientists are talking about it.
Speaker 1: And these misconceptions, by the way, you know, they drive
Speaker 1: me bonkers too, Like these there are so many misconceptions.
Speaker 1: I actually think there would be great utility and value
Speaker 1: for me to put aside all of my you know,
Speaker 1: maybe political beliefs and humanitarian and activist beliefs for for
Speaker 1: a moment and and talk about what the science of
Speaker 1: IQ means. And then maybe in the last couple of
Speaker 1: chapters maybe add in back in all that stuff and
Speaker 1: and and say what the implications are for activism. Anyway,
Speaker 1: I might do that something I've thought of. I've thought
Speaker 1: of writing the same the same book actually, And you know,
Speaker 1: one one point that I think is important, you know,
Speaker 1: it would be important to make is that, like, let
Speaker 1: let's say you're doing you know, a sociological study or
Speaker 1: something like that, and you're trying to you know, understand
Speaker 1: you know, why do some people you know drop out
Speaker 1: of school and some people not or something like that. Well,
Speaker 1: you could load all kinds of predictive variables into your
Speaker 1: your model, but if you didn't put in, you know,
Speaker 1: some measure of IQ, you'd probably be missing out, you know,
Speaker 1: on some relevant factor. Right, it's not going to explain everything.
Speaker 1: But if you don't include that in your model, you know,
Speaker 1: this is just the way, this is the way most
Speaker 1: varied analysis works. Right, If you don't include that in
Speaker 1: your model, you may you know, you may put weight
Speaker 1: on things that you know don't have the effects you
Speaker 1: think they do in you know, in the actual in
Speaker 1: the actual world. So you know, but at the same time,
Speaker 1: that doesn't mean that there couldn't be some other world
Speaker 1: in which things were different. Right, So so IQ was
Speaker 1: incredibly important for understanding like the world we have, but
Speaker 1: it doesn't you know, determine everything about the world. The
Speaker 1: future would be just like saying, like, you know, myopia
Speaker 1: is incredibly important for understanding you know, maybe you know
Speaker 1: how people did in life, you know, five hundred years ago,
Speaker 1: but then once they invented glasses and they became available
Speaker 1: for everybody. It no longer determines those things. When we're
Speaker 1: talking about group averages, we're talking about individual variation. You know,
Speaker 1: it is really uh, you'd be you'd be you'd be
Speaker 1: wise to put iq into your regression variable. But when
Speaker 1: it comes to within the variation and all the different
Speaker 1: ways that an individual person can mix and match, you know,
Speaker 1: things to achieve things in life, then you start getting
Speaker 1: some very individualized short of intelligence. So anyway, I don't
Speaker 1: know if that makes sense at all. I think there's
Speaker 1: a lot of misconception to correct, you know, about this
Speaker 1: concept of intelligence, because it has for some reason, you know,
Speaker 1: gotten into everybody's like every day thinking about you know,
Speaker 1: about the world, and that it can have a lot
Speaker 1: of you know, that can have a lot of consequences
Speaker 1: that they're not thinking straight about it. So I'm one
Speaker 1: hundred percent with you there. I really appreciate this interview, Chris,
Speaker 1: and I'm going to spread this far and wide because
Speaker 1: maybe maybe this will help, you know, correct some misconceptions.
Speaker 1: So thank you so much for your time today. Okay,
Speaker 1: I'm looking forward to hearing it myself. Thanks for having
Speaker 1: me Thanks for listening to The Psychology Podcast with Doctor
Speaker 1: Scott Barry Kaufman. I hope you found this episode just
Speaker 1: as performing a foker, look you write it. If you don't,
Speaker 1: as read the show notes for this episode or here
Speaker 1: past episodes if you go to the Psychology Podcast dot
Speaker 1: com