Speaker 1: Welcome to the Psychology Podcast, where we give you insights
Speaker 1: into the mind, brain, behavior and creativity. I'm doctor Scott
Speaker 1: Barry Kaufman, and in each episode I have a conversation
Speaker 1: with a guest. He will stimulate your mind and give
Speaker 1: you a greater understanding of yourself, others, and the world
Speaker 1: to live in. Hopefully we'll also provide a glimpse into
Speaker 1: human possibility. Thanks for listening and enjoy the podcast. Today
Speaker 1: we have Richard Hire on the podcast. Doctor Hire is
Speaker 1: Professor Emeritus in the School of Medicine, University of California, Irvine.
Speaker 1: His research investigates structural and functional neuroanatomy of intelligence using neuroimaging.
Speaker 1: He created an eighteen lecture video course, The Intelligent Brain,
Speaker 1: and authored The Neuroscience of Intelligence. He is co editor
Speaker 1: of the Cambridge Handbook of Intelligence and Cognitive Neurosis Science.
Speaker 1: He's editor in chief of Intelligence, a scientific journal, and
Speaker 1: Doctor Hare received the Lifetime Achievement Award from the International
Speaker 1: Society for Intelligence Research. Congratulations on that award and looking
Speaker 1: forward to talking to you today. Well, thanks very much.
Speaker 1: This has been a long time in coming. I've known
Speaker 1: you for years. I'm glad we are finally able to
Speaker 1: do this. Yes, I have known you for years. I
Speaker 1: remember us talking at this Harvard Visual Spatial conference that
Speaker 1: must have been like a decade ago at this point
Speaker 1: at least. Yeah, it was interesting because we had brain
Speaker 1: images of visual spatial tasks. At the time. By ten
Speaker 1: years ago, a lot of people were doing brain imaging.
Speaker 1: When I started, it was really an astounding new technology. Yes, well,
Speaker 1: let's go back, because you started off looking at waveforms, right,
Speaker 1: You did an EG Isn't that how you kind of
Speaker 1: start off? So can you tell us a little about
Speaker 1: your first initial findings, which actually I believe if i'm
Speaker 1: remember quickly surprised you. You weren't expecting to see what
Speaker 1: you saw. Well, let me go back and think about
Speaker 1: that EEG work. It was done at a time when
Speaker 1: EEG research was just beginning to do brain mapping with EEG,
Speaker 1: and by today's standards, it was pretty rudimentary, but it
Speaker 1: was kind of interesting to see waveforms move back and
Speaker 1: forth across the brain as thinking was going on or
Speaker 1: perception was going on. And I did some work, building
Speaker 1: on the work of a lot of other EEG work,
Speaker 1: looking at correlates between these electrical waveforms in the brain
Speaker 1: and intelligence test scores, and we found some interesting things,
Speaker 1: nothing really amazing. The real surprising work was when we
Speaker 1: moved from EEG to positronic mission tomography PET for short PET,
Speaker 1: and so I was one of the first psychologists that
Speaker 1: had access to this technology. I moved from Brown University
Speaker 1: out here to the University of California at Irvine because
Speaker 1: they had acquired one of the very first commercially available
Speaker 1: PET scanners in about nineteen eighty six. It was in
Speaker 1: the psychiatry department, of all places. This was extremely unusual.
Speaker 1: So I was recruited into the psychiatry department and I
Speaker 1: came because I had this access to this really amazing technology.
Speaker 1: And the first study I was able to do with
Speaker 1: PET was looking at brain metabolic rate while people solved
Speaker 1: reasoning problems on an intelligence test, and the result of
Speaker 1: that was extremely surprising because we did see areas of
Speaker 1: the brain that quote lit up that were more active
Speaker 1: while people were doing this test. But the surprising and
Speaker 1: unexpected thing was the more those areas lit up, the
Speaker 1: less well they did on the test. There were inverse
Speaker 1: correlations between glucose metabolic rate and his brain activity in
Speaker 1: these areas and how well they did the test, leading
Speaker 1: us to conclude that it wasn't how hard your brain
Speaker 1: was working that made you smart, but how efficiently it
Speaker 1: worked to make you smart. Oh, I'm just going to
Speaker 1: jump right into this sex differences. Why not? Why not?
Speaker 1: You know, I was going to start off with a
Speaker 1: whole bunch of other things, but I feel like why not?
Speaker 1: This kind of illustrates a point though, that I think
Speaker 1: is really interesting. So from all the data I've read,
Speaker 1: there is no average sex difference in intelligence or IQ
Speaker 1: in the general factor. There may be on specific factors,
Speaker 1: whereas males and average might have an advantage on certain tests,
Speaker 1: and females may have advantage on average and other tests,
Speaker 1: but at the global level, however, obviously, it's a well
Speaker 1: known fact that female brains are smaller on average than
Speaker 1: male brains in average, and so people have explained that
Speaker 1: in saying that female brains actually are more efficient. So
Speaker 1: do you see the link I just made there to
Speaker 1: what you were saying? Oh? Absolutely, that was one of
Speaker 1: the first questions I would get. No one has actually
Speaker 1: proved that female brains are more efficient, but there's a
Speaker 1: lot of evidence that supports that hypothesis. Our pet data
Speaker 1: would would be one. We also did a study where
Speaker 1: we correlated the amount of gray matter using magnetic residence imaging,
Speaker 1: a different kind of technology than PET that we could
Speaker 1: determine how much gray matter there was throughout the brain,
Speaker 1: and we correlated that with IQ scores, and we found
Speaker 1: there were certain areas where the more gray matter you had,
Speaker 1: the higher your IQ score. And that was interesting because
Speaker 1: the areas were basically in the front of the brain
Speaker 1: and in the parietal areas on the side in the
Speaker 1: back of the brain. But when we broke the sample
Speaker 1: out into men and women, it was the men who
Speaker 1: had the correlations in the varietal lobes and it was
Speaker 1: the women who had the correlations predominantly in the frontal lobes.
Speaker 1: This suggested that men and women equally matched on IQ
Speaker 1: score important dimension may have different parts of the brain
Speaker 1: involved in the kind of problem solving that IQ test measure.
Speaker 1: And so the simple way to think about that is
Speaker 1: profound in its simplicity. Not all brains work the same way.
Speaker 1: Now this will come as no surprise to most people,
Speaker 1: but in a field dominated by cognitive psychologists who regarded
Speaker 1: individual differences as error variants, and experiments designed to generate
Speaker 1: minimum individual differences, assuming they were looking at the general
Speaker 1: response of the brain that would be common to everybody.
Speaker 1: In fact, not all brains work the same way. Men
Speaker 1: and women may have brains that work somewhat differently to
Speaker 1: arrive at the same result. Now, that's because there's differences
Speaker 1: in the amount of white matter connections between men and women.
Speaker 1: These are average group differences. By the way, there's a
Speaker 1: lot of overlap. Yeah, I keep being sure to say that.
Speaker 1: It keeps saying average. Got to say that all the time,
Speaker 1: all the time, And so it's it's it's interesting to
Speaker 1: the brain imaging world that around the year two thousand,
Speaker 1: it's like two decades ago already, as more psychologists got
Speaker 1: access to MRIs and started doing their own brain imaging experiments,
Speaker 1: they were surprised generally at how the brains of the
Speaker 1: individual subjects look so different, so different on MRI, and
Speaker 1: by adding them together and taking a group average, they
Speaker 1: immediately recognized they were losing a lot of information. So
Speaker 1: I have always proposed to my cognitive psychology friends that
Speaker 1: they do the following experiment, that they take the most
Speaker 1: classic cognitive MRI study and replicate it separately in men
Speaker 1: and women, or separately in high IQ people and average
Speaker 1: IQ people. This is to just illustrate the potential power
Speaker 1: of an individual difference approach, because I believe individual differences
Speaker 1: is the key to understanding all kinds of neurobiology. For sure,
Speaker 1: I agree with that you're bringing back lots of memories.
Speaker 1: You know you will. Maybe you don't know this, and
Speaker 1: I'm sure my listeners don't know this, But I did
Speaker 1: my master's thesis at Cambridge University with Nicholas McIntosh. She
Speaker 1: was a well regarded intelligence researcher and my thesis with
Speaker 1: him was on how men on average and women on
Speaker 1: average solve visual spatial problems differently. And it was interesting
Speaker 1: because women on average tended to solve it using verbal
Speaker 1: labels in a way, and men on average tended to
Speaker 1: visualize it more than the women on average. We found
Speaker 1: that interesting. We're trying to explain differences in working memory
Speaker 1: based on different strategies, So you're taking me all the
Speaker 1: way back to kind of the start of my career
Speaker 1: looking at really interested in different strategy use and how
Speaker 1: that relates to intelligence and our visual spatial working memory
Speaker 1: for instance. So anyway, thanks for bringing me back. Well,
Speaker 1: I'm glad you mentioned that because I never met Nicholas McIntosh,
Speaker 1: and he wrote one of two classic textbooks in the field.
Speaker 1: I think his book was called IQ and Intelligence IQ
Speaker 1: and Human Intelligence IQ and Human Intelligence, and the other
Speaker 1: classic was Buzz Hunt's book Human Intelligence. And I have
Speaker 1: just finished a few days ago sending off the final
Speaker 1: manuscript for the second edition of Buzz Hunt's book Human Intelligence.
Speaker 1: We now call it The Science of Human Intelligence. And
Speaker 1: I wrote it with Roberto Colom. We were both friends
Speaker 1: of Buzz Hunt. And it's too bad. I really admired
Speaker 1: Nick macintosh's work up until yesterday. I had it right
Speaker 1: here on my desk because I would refer to it
Speaker 1: from time to time in writing our book. And he
Speaker 1: passed away about what two or three years A couple
Speaker 1: of years ago. It was a big tragedy. Big tragedy.
Speaker 1: By the way, did you know he actually gave an
Speaker 1: invited interview at an ISIR meeting. I saw the video
Speaker 1: of it. I had arranged that and then I couldn't
Speaker 1: go to the meeting. But that is online if people
Speaker 1: want to see his views on intelligence. Thank you. Thanks
Speaker 1: for putting that on behalf of Nick and I can
Speaker 1: put that on the show notes. For sure, he really
Speaker 1: inspired me so much as way of thinking so clearly
Speaker 1: about the time topic, and I would also say compassionately
Speaker 1: the way he covered things. He didn't shy away from
Speaker 1: any topic. If you look at his textbook, he's a
Speaker 1: whole chapter on race differences for instance. Yeah, he doesn't
Speaker 1: shy away from it, but one doesn't leave reading his
Speaker 1: discussion about it thinking oh, he's a racist, or thinking
Speaker 1: oh he's not being even handed. You know, you'd be
Speaker 1: hard pressed to walk away from reading Nicholas McIntosh feeling
Speaker 1: that you've been short changed intellectually. If that makes sense,
Speaker 1: it does. Buzz also had a chapter on that in
Speaker 1: his book, and it was one of the last chapters
Speaker 1: we wrote. And it's a tough needle to thread the
Speaker 1: eye of that, to say the least. When I did
Speaker 1: the eighteen video lectures for the Great Courses, I put
Speaker 1: in a whole lecture on race and IQ. I tell
Speaker 1: you the company was a little nervous about this, but
Speaker 1: I said, look, if we do it right, this will
Speaker 1: explain to pole why this is important to know about.
Speaker 1: And I was able to do a lecture that observers
Speaker 1: found balanced and informative. The hope was people would walk
Speaker 1: away without racist support or whatever racists get from this
Speaker 1: kind of stuff, and just kind of learn about why
Speaker 1: this doesn't go away. It's a topic that is important
Speaker 1: for many reasons, but it's so uncomfortable. It's just so uncomfortable,
Speaker 1: and it's so difficult to have a conversation about it. Well,
Speaker 1: my view is that I think it's actually unfortunate that
Speaker 1: discussion of the exciting findings of this the science of
Speaker 1: intelligence more generally consistently gets hijacked by that topic. So
Speaker 1: that's something that infuriates me because I find I find
Speaker 1: individual differences intelligence far more interesting and valuable to investigate
Speaker 1: than race differences. If you want, in my opinion, I
Speaker 1: could agree with you more. In fact, I never commented
Speaker 1: on the race difference thing up until I did this
Speaker 1: lecture in the end I recorded at the end of
Speaker 1: twenty thirteen, so I literally went decades without any public
Speaker 1: discussion of this. I know or have met most of
Speaker 1: the players in that space. It's a relatively small space
Speaker 1: compared to the rest of intelligence, and so just from
Speaker 1: a historical point of view, I had many, many private
Speaker 1: conversations with most of the key people, and in private
Speaker 1: conversation there was no racism. There was just kind of
Speaker 1: an interest in explaining away these test differences, or it's
Speaker 1: not necessarily explaining them away, but explaining where they came from.
Speaker 1: Arthur Jensen was famous for this. He was a bit
Speaker 1: had a bit of a touch of Asperger syndrome. Well
Speaker 1: that's interesting, is that what you were diagnosed? Have you
Speaker 1: met Did you meet him? Oh? I spent a lot
Speaker 1: of time with him at meetings. You're the first one
Speaker 1: to ever say that to me. Yeah, that's interesting. Well
Speaker 1: I didn't fully appreciate this until after he passed away,
Speaker 1: But it turns out I understand that a relative of
Speaker 1: his had Asperger syndrome, and suddenly it kind of fell
Speaker 1: into place. It clicks. It clicks because he was absolutely
Speaker 1: unflappable in the face of enormous hostility and criticism. He
Speaker 1: just sticks stuck to trying to explain to people what
Speaker 1: the data were. No matter how technical the data might be,
Speaker 1: he felt he could explain it in a neutral way,
Speaker 1: and he said publicly and privately he would be the
Speaker 1: first to change his mind about any interpretation of the
Speaker 1: data if there was data, if new data came along,
Speaker 1: and then he hoped that any hypothesis that he had
Speaker 1: could be disproved by data. Well, he wasn't afraid of
Speaker 1: that at all. He was really an advocate of the
Speaker 1: scientific method. Yeah, you know, I to be vulnerable a second.
Speaker 1: I had to admit, I think I'm a bit on
Speaker 1: that spectrum to a certain degree where I don't Sometimes
Speaker 1: I don't mean to get in trouble, and my curiosity
Speaker 1: leads first, and then I get in trouble and you know,
Speaker 1: the curiosity killed the cat sort of thing. And I
Speaker 1: truly don't have malevolent intentions, you know, I'm just being curious.
Speaker 1: And then if I've hurt anyone's feelings, of course I
Speaker 1: feel horrible about it because I also have a compassion.
Speaker 1: But I can resonate with you know, a group of
Speaker 1: people who are just absolutely just ravenously curious about all
Speaker 1: sorts of different topics and who really step in it
Speaker 1: sometimes as a result. Well, of all those people that
Speaker 1: I have met or knew mostly at meeting, often their
Speaker 1: work when presented at intelligence meetings was heavily criticized. You know,
Speaker 1: people from the audience would get up and say, you know,
Speaker 1: it just doesn't make sense or you're misinterpreting that. Only
Speaker 1: one of these people I won't say who in private
Speaker 1: conversation struck me as holding racist ideas, and that's one
Speaker 1: out of I know exactly who was in your head
Speaker 1: right now, just so you know, very probably you do,
Speaker 1: but I know there's no sense naming this person. So
Speaker 1: the point is that most of the people who engaged
Speaker 1: in that kind of research did it to understand education
Speaker 1: achievement differences and because they wanted to fix it. That's
Speaker 1: where the whole head start compensatory education movement came from.
Speaker 1: So it's got a venerable history of good intentions. It
Speaker 1: did get hijacked today. There's a tiny number of people
Speaker 1: who work in this area. I get papers submitted to
Speaker 1: the journal I edit on this we probably, I can't
Speaker 1: say for sure, but we probably reject more than we accept.
Speaker 1: You know, I don't have a policy of rejecting papers
Speaker 1: because they are in topics that we censor or anything
Speaker 1: like that. We kind of have a wide open gate
Speaker 1: when it comes to academic freedom in terms of getting
Speaker 1: papers into the process. But I make sure they get
Speaker 1: a fair peer review, and if they make the peer review,
Speaker 1: then we publish them. If they don't. We don't. Unfortunately,
Speaker 1: there are a small number of people on Twitter and
Speaker 1: other social media who seem to relish in debates about
Speaker 1: this this on Twitter in any reasonable way. The issues
Speaker 1: are too complex, The technical aspects of the data are
Speaker 1: really require a lot of explanation about what the data
Speaker 1: mean and what they don't mean. And I have really avoided,
Speaker 1: you know, Twitter fights about this. What I have noticed
Speaker 1: on Twitter occasionally, you know, somebody attacks me for doing
Speaker 1: intelligence research. It's very occasional, and it's, you know, easy
Speaker 1: to ignore. The hostility about intelligence really does. It's really
Speaker 1: a shame because, as you say, there's so much intelligence
Speaker 1: research that's interesting and provocative and positive. I've spent decades
Speaker 1: speaking to the public about intelligence. I can't even tell
Speaker 1: you how many public lectures I've given. There's a tremendous
Speaker 1: public appetite to know about intelligence and what the research says,
Speaker 1: and intelligence slowly and steadily has been moving more mainstream
Speaker 1: than it's been since the nineteen sixties, partly because of
Speaker 1: brain imaging work. Because the idea that intelligence test scores
Speaker 1: robustly correlate with things you can measure on brain imaging.
Speaker 1: That pretty much puts the argument to rest that intelligence
Speaker 1: test scores are meaningless and aren't real just statistical artifacts. Well,
Speaker 1: I think those are two different things. You know, something
Speaker 1: can be real and be meaningless. Well, okay, fair enough,
Speaker 1: come on, so but when you look, you know what
Speaker 1: I want to get to all the really exciting because
Speaker 1: there's a lot about intelligence research that obviously excites me.
Speaker 1: That is how I started the career. My career, and
Speaker 1: I would live in the library in Carnegie Mellen as
Speaker 1: an undergrad. I'd live in the library reading every book
Speaker 1: I could possibly get my hands on about human intelligence.
Speaker 1: So me and you absolutely can nerd out. I feel
Speaker 1: like I want to just address that annoying elephant in
Speaker 1: the room that keeps hijacking the discussion really quickly so
Speaker 1: we can just move on from it. So the race
Speaker 1: difference is now, this is probably this is a horrible
Speaker 1: time to even bring up that topic there because there
Speaker 1: are such racial tensions in America, and I think there's
Speaker 1: value in being sensitive to the fact that we have
Speaker 1: a long way to go in America to reduce racism.
Speaker 1: And I don't want to contribute to racism one iota.
Speaker 1: But I also enjoy looking at data, and I enjoy
Speaker 1: looking at various various sources of information to try to
Speaker 1: I'm a firm believer if we want to make changes,
Speaker 1: we need to look at reality as clearly as possible,
Speaker 1: and it needs to be built on reality. Change needs
Speaker 1: to be built on reality. The question is what is
Speaker 1: the reality? And I'm wondering if in like two three
Speaker 1: minutes we can summarize that state. And I'll tell you
Speaker 1: my summary of it is that there still exists a
Speaker 1: signific can difference on average group differences between blacks and
Speaker 1: whites on average on IQ scores. But I have yet
Speaker 1: to see one study showing that the cause of that
Speaker 1: that any of the group differences are explained to any degree,
Speaker 1: let alone a sizable degree by differences in genetics. And
Speaker 1: not only that, but I think the really important point here,
Speaker 1: and you correct me if I'm wrong, because I really
Speaker 1: do want to get into the exciting aspects of intelligence.
Speaker 1: Anything that we say today about the science of individual
Speaker 1: differences intelligence, you cannot automatically extrapolate that to the group level.
Speaker 1: And that's a point that I just really think needs
Speaker 1: to be hammered in these discussions so that we can finally,
Speaker 1: once and for all, have a nuanced, truthful and interesting
Speaker 1: discussion about individual differences intelligence without it being hijacked. So
Speaker 1: what do you do resonate with anything I just said
Speaker 1: with all of it, there's virtually nothing I disagree with.
Speaker 1: I would talk about it a little differently, though. You
Speaker 1: are correct that there has been a persistent finding over
Speaker 1: decades that different groups have average test score differences, and
Speaker 1: the presumption early on was that all of those differences
Speaker 1: were due to lack of educational opportunities or other social
Speaker 1: cultural aspects. The hypothesis that it might be partially genetic
Speaker 1: started to evolve as compensatory education efforts were tried to
Speaker 1: close those education gaps, hoping to see a reduction in
Speaker 1: the test score gap, which never happened, and so as
Speaker 1: frustration mounted about the inability to minimize that gap through
Speaker 1: educational opportunity and other programs, people started to wonder, maybe
Speaker 1: genetics has something to do with it. That was an
Speaker 1: incendivey train of thought in the late nineteen sixties when
Speaker 1: it really started to take hold right through the seventies
Speaker 1: and eighties as more was learned about genetics. However, the
Speaker 1: concept that genetics was a deterministic and limited factor kind
Speaker 1: of got that understanding of genetics evolved into a more
Speaker 1: sophisticated understanding that genetics essentially was probabilistic, not deterministic. And
Speaker 1: this really is a very important concept and it really
Speaker 1: changed the way people started to think about genetic propensities
Speaker 1: or genetic potential. So you might have the potential for
Speaker 1: heart disease, and you can you can minimize it or
Speaker 1: maximize the probability of you getting heart disease by doing
Speaker 1: lifestyle things. You know, you want to have heart disease.
Speaker 1: I can tell you what to eat and just sit
Speaker 1: there on the couch. You know, if you want to
Speaker 1: minimize your chance, you change your diet, you exercise, and
Speaker 1: so on. Whether intelligence is the same as that is
Speaker 1: really yet to be determined because we don't know anything.
Speaker 1: We don't know anything that in my view, increases intelligence,
Speaker 1: and we can talk about what that means because it
Speaker 1: depends on the definition of intelligence. I was going to
Speaker 1: start off with the question was intelligence, But we've gotten
Speaker 1: on this down this path. Okay, the good news about
Speaker 1: the genetics of intelligence, And I'm going to say something
Speaker 1: that is my idiosyncratic point of view. I don't know
Speaker 1: that what I'm about to say is widely accepted. But
Speaker 1: if there's a genetic component, and I'm talking now about
Speaker 1: individual intelligence, not these group averages, but if there's a
Speaker 1: genetic component to intelligence individual intelligenens, that means there's a
Speaker 1: neurobiology of intelligence. Because genetics works, there's no gene for intelligence.
Speaker 1: There has to be genes for neurobiology and neural mechanisms
Speaker 1: and an extraordinarily complicated cascade of neurochemical events that results
Speaker 1: in intelligent thinking. Okay, but it justifies a neuroscience of intelligence.
Speaker 1: And the field of intelligence research has been moving over
Speaker 1: the last two decades more and more towards neuroscience conceptualizations
Speaker 1: and methodologies to study intelligence. Now, one of the reasons
Speaker 1: this is important is that if you can understand intelligence
Speaker 1: on a neurobiological level, right down to the synapse or
Speaker 1: right down to the dendrites of neurons or the mitochondria
Speaker 1: in neurons, me one of a thousand different aspects of
Speaker 1: molecular of the molecular brain. If you can get some
Speaker 1: understanding of that, you might be able to tweak the
Speaker 1: relative systems to increase intelligence. So let me give you
Speaker 1: a statistic that startles most people, and you will recognize
Speaker 1: immediately based on the normal distribution of intelligence and the
Speaker 1: normal curve, that's sixteen percent of the population have IQ's
Speaker 1: under eighty five. Now, you don't have to believe in
Speaker 1: IQ or eighty five is not a magic number, but
Speaker 1: that means that in the United States, about fifty one
Speaker 1: million people have IQ's under eighty five. And of those
Speaker 1: fifty one million, there's about thirteen million children. Yes, okay,
Speaker 1: now you want to talk about serious social problems. You
Speaker 1: got fifty one million people. Doesn't matter, race, you know, doesn't,
Speaker 1: the religion doesn't, voting preferences doesn't matter. You got fifty
Speaker 1: one million people who do not have the mental abilities
Speaker 1: to hold high paying jobs and possibly even care for themselves.
Speaker 1: This is a very large number of people. Now, these
Speaker 1: people think a private humistic statement though, that's like a
Speaker 1: pretty deterministic statement that you just said. No, probablistically, it's
Speaker 1: probabilistic that. Look, in the United States, there are about
Speaker 1: forty three million people living below the poverty line is
Speaker 1: determined by some government agency that does this. So think
Speaker 1: of a vent diagram. You got forty three million people
Speaker 1: living in poverty. You got fifty one million people with
Speaker 1: IQs that are low enough to make it everyday life
Speaker 1: difficult for them. There's got to be overlap between those
Speaker 1: two universes, those two sets of people. So if you
Speaker 1: could tweak IQ by just a little bit and move
Speaker 1: people from eighty five to ninety or from eighty to
Speaker 1: a D five, this is going to have a gigantic
Speaker 1: ripple effect on many many social problems. Now I explain
Speaker 1: all this for your listeners who would like to see
Speaker 1: my logic on this. It's in section six point six
Speaker 1: of my book, The Neuroscience of Intelligence, and this entire
Speaker 1: section is free on my website. So if they go
Speaker 1: to Richard Hire dot com and click on the Neuroscience
Speaker 1: of Intelligence, they'll go to a pit in the show
Speaker 1: notes where they'll see a little tab where they can
Speaker 1: click on facts and quotes for journalists. Go to that,
Speaker 1: scroll down to the bottom, and you'll see section six
Speaker 1: point six of the book in its entirety, and I
Speaker 1: explain this idea of why it would be a good
Speaker 1: thing to be able to understand the neurobiology of intelligence
Speaker 1: so that we might come up with ways to increase intelligence.
Speaker 1: Think about shifting the entire intelligence distribution a little bit
Speaker 1: to the right. I think that would have enormous implications
Speaker 1: for society. And you know, the more it's genetic, the
Speaker 1: irony is. The more that intelligence is genetic, the more
Speaker 1: neurobiology might be involved, and the more impact. I mean,
Speaker 1: think fifty years into the future when there's a molecular
Speaker 1: biology research program worldwide for understanding intelligence, just like their
Speaker 1: molecular biology programs from understanding learning and memory, which by
Speaker 1: the way, are elements of intelligence. So that if you
Speaker 1: want to solve Alzheimer's disease, you have to understand the
Speaker 1: neurobiology of learning and memory. And someday a pharmaceutical company
Speaker 1: is going to be able to tweak the brains of
Speaker 1: people with Alzheimer's disease to ameliorate that illness, and then
Speaker 1: you're on your way to coming up with ways to
Speaker 1: tweak similar symptoms to people without Alzheimer's disease, possibly to
Speaker 1: increase their cognitive abilities. That's the excitement of intelligence research
Speaker 1: in a nutshell, and it could be fifty years away.
Speaker 1: Might never happen. Most of the people working in genetics,
Speaker 1: most of the people working in neuroscience, believe what I
Speaker 1: just said will never happen because the brain is too complicated.
Speaker 1: The interactions of all these systems are too complicated to
Speaker 1: sort out, let alone how environment mental factors like stress
Speaker 1: or other factors might influence the expression of genes throughout
Speaker 1: the lifetime. This is an extraordinarily complex set of problems
Speaker 1: to solve. But my view is we need to get started.
Speaker 1: I would love to unpack so much of what you
Speaker 1: just said, but I was just curious, what was your
Speaker 1: link there to the race differences thing, because I wanted
Speaker 1: to I wanted to end that that thread. You were
Speaker 1: starting to talk about it, and then you went off
Speaker 1: into the individual level. You summarized the findings. Fine, Oh cool, Okay,
Speaker 1: These average test score differences exist. They've been relatively stable
Speaker 1: over decades, where what the explanation for them is not
Speaker 1: known because everything that's been proposed as an explanation, the
Speaker 1: number of words spoken in the household of infants to genetics,
Speaker 1: none of that has yet been demonstrated in a compelling way.
Speaker 1: Although you know, people say that with the new giant
Speaker 1: databases of DNA being collected literally all over the world,
Speaker 1: maybe the genetics story now will have the sufficient data
Speaker 1: in large enough numbers to test some of these ideas.
Speaker 1: Other geneticists say, it doesn't matter how big the sample
Speaker 1: size is, it doesn't matter how sophisticated the genetic word
Speaker 1: DNA analysis is. There are just too many interactions to
Speaker 1: sort things out, and so you could never answer the
Speaker 1: question does genetics have anything to do with any group
Speaker 1: differences on complex traits? Time will tell That's my summary
Speaker 1: of where we are on that topic. Okay, So lots
Speaker 1: of unpack. So I know you're interested in the development
Speaker 1: of intelligence, and that's a topic a theme in your book.
Speaker 1: I'm wondering how you can possibly look at the development
Speaker 1: of intelligence by only staying at that biological level. You
Speaker 1: obviously need to look at how environmental factors interact with
Speaker 1: our biology. So are you you saying that you don't
Speaker 1: think there's a lot of that. We've really found out
Speaker 1: what those environmental factors are that are most important, and
Speaker 1: a lot of the ones that people have proposed turn
Speaker 1: out to not be as predictive. Is that is that
Speaker 1: along the lines of what you're arguing, that would be
Speaker 1: a fair summary of where I think the field is.
Speaker 1: You know, there are general environmental variables that undoubtedly must
Speaker 1: have an impact, like stress, okay, like poverty. Well, what
Speaker 1: aspects of poverty. How do you explain individuals who grow
Speaker 1: up in extreme poverty yet are intellectually extremely able, And
Speaker 1: how do you go about studying this in a systematic way.
Speaker 1: You know, when sometimes there's a misunderstanding when I say
Speaker 1: things like intelligence is the single most important variable that
Speaker 1: predicts various measures of success. That is an empirical fact.
Speaker 1: So if you could measure it doesn't mean that it's
Speaker 1: the only thing. It doesn't mean that it is philosophically
Speaker 1: the most important thing in success. It just means empirically,
Speaker 1: if you throw a whole bunch of variables into a
Speaker 1: quantified statistical procedure like a multivariate you know, regression equation
Speaker 1: to predict whatever measures of success you want to predict,
Speaker 1: the thing that always comes out first is some measure
Speaker 1: of general intelligence. Now does that matter what your dependent
Speaker 1: variable is? Surely what outcome you're looking at IQ is
Speaker 1: going to have greater or less than predictive validity, Like
Speaker 1: physics versus artistic achievement. We found in art data set
Speaker 1: shows widely different predictive validity. Like you, that's correct. And
Speaker 1: when I said, depending on what variable you want to predict,
Speaker 1: I'm talking about most of the variables that have actually
Speaker 1: been studied empirically to date that have some practical importance
Speaker 1: to most people, like academic success, like job success, those
Speaker 1: generic categories. But certainly, if you have had a metric
Speaker 1: of kindness, if you had a metric of caring for
Speaker 1: other people over and above the kind of the personality traits,
Speaker 1: who's to say that you wouldn't choose kindness over intelligence.
Speaker 1: Because I can tell you spent having spent decades in
Speaker 1: university medical schools, I could easily rattle off a list
Speaker 1: of names of liars, cheaters, and thieves among the tenured
Speaker 1: faculty without hesitation. On the other hand, I could also
Speaker 1: rattle off a list of names of people who are
Speaker 1: extremely kind and generous, and they're on the same faculty,
Speaker 1: and they would agree with me completely on who belongs
Speaker 1: to the other list, but that exists, and they're intelligent.
Speaker 1: They're highly intelligent people liars, cheaters and thieves as well.
Speaker 1: So it seems like, without asking you what do you
Speaker 1: think intelligence is, you seem to equate it with the
Speaker 1: kinds of cognitive process that are measured on on Q tests,
Speaker 1: which are an assortment of cognoprostss. It's that all seem
Speaker 1: to be positively correlated with each other relating to working
Speaker 1: memory and reasoning. Problem solving on the spot makes demands
Speaker 1: on executive functioning these sorts of things. Is that how
Speaker 1: you think about intelligence? I have a very narrow definition
Speaker 1: because it's based on what the research is about. Most
Speaker 1: of the research is about the general factor of intelligence,
Speaker 1: this general reasoning ability that you have across various kinds
Speaker 1: of different situations, called the G factor. Most of the
Speaker 1: research on intelligence is really about the G factor, and
Speaker 1: that's what seems to be most predictive and possibly possibly
Speaker 1: most genetic. Now what I just said is certainly open.
Speaker 1: I'm open to changing my mind on this as you know,
Speaker 1: new data come out. The difficulty is the assessment of
Speaker 1: the G factor from various tests. Psychometrically is very sophisticated.
Speaker 1: People don't really know what psychometrics does. But it's a
Speaker 1: way of test construction that eliminates things like bias and
Speaker 1: maximizes the fact that minimizes bias and maximizes the predict
Speaker 1: the predictability of something with the test. So it's sophisticated.
Speaker 1: It's not perfect, but it's sophisticated. By contrast, the statistical
Speaker 1: reliability and validity and psychometrics of tests of things like
Speaker 1: wisdom or even creativity is not as high. Now, imagine
Speaker 1: just just as a thought experiment. You work in creativity.
Speaker 1: Your work is you just read your imaging paper, fantastic,
Speaker 1: But imagine if you've got to measure of creativity and
Speaker 1: you decide to give it to different groups and different
Speaker 1: groups have different mean creativity scores. Okay, what are you
Speaker 1: going to do with that? And do you want to
Speaker 1: teach creativity in school and you want to take you know,
Speaker 1: kids in a group that have low creativity scores on average,
Speaker 1: and what can you do to increase their creativity? A
Speaker 1: lot of people have tried teaching creativity. It may even
Speaker 1: be helpful, but it doesn't really produce artistic geniuses. You know,
Speaker 1: you raise a really good point, and I think it
Speaker 1: might be a difference between us. I feel like I
Speaker 1: have two hats. There's one hat. I'm just the hat
Speaker 1: that I wear with you, and I'm wearing with you
Speaker 1: right now on the science of intelligence, doing studies on
Speaker 1: it at a group level, at not a group op
Speaker 1: but a population level and aggregate. But then there's the
Speaker 1: educational psychologist in me who is very, very wary about
Speaker 1: making statements about certain IQ bands and then pre judging
Speaker 1: individual person's future potential based on their IQ score. To me,
Speaker 1: that's a form of discrimination actually, because you're taking population
Speaker 1: level statistics and you're trying to infer what one individual
Speaker 1: in that population is capable of doing in their lives.
Speaker 1: So I'm more worried about that than I am doing
Speaker 1: the good science and things of that nature. So that's
Speaker 1: where I'm coming from. Just wanted to just share that
Speaker 1: with you. There's no difference between those two hats go
Speaker 1: on go on, because no one who's knowledgeable about the
Speaker 1: predictive bil of intelligence tests to job performance or to
Speaker 1: life success believes that where any individual is on that
Speaker 1: IQ in those IQ bands determines their life's success. These
Speaker 1: predictions are generic that are not perfect. Maybe they predict
Speaker 1: anywhere from a third maybe as much as a sixty
Speaker 1: percent of the variance, sometimes maybe a little bit more.
Speaker 1: But you could ask the question slightly differently than the
Speaker 1: way you proposed it. You can ask is there any
Speaker 1: value in knowing your IQ score? And most people who
Speaker 1: study IQ, and I include myself in this, would say
Speaker 1: not really. I get emails all the time from people
Speaker 1: who have read my book, then you'll test them. No,
Speaker 1: who follow me on Twitter, and it's more like they've
Speaker 1: been tested and they know their IQ and they say, look,
Speaker 1: my IQ is one hundred and ten, but I want
Speaker 1: to go to graduate school. Do you think I could
Speaker 1: be a successful graduate student? And my answer always is
Speaker 1: your IQ score has nothing to do with what you
Speaker 1: just asked me. I would have no way of knowing this.
Speaker 1: The only way you can find out is go to
Speaker 1: graduate school, try your best, and see what do you
Speaker 1: make of cases where there's a mismatch. This is an
Speaker 1: interesting question because I've been thinking a lot about this.
Speaker 1: What happens if your achievement trump's your so called potential.
Speaker 1: You know, I had a learning disability when I was
Speaker 1: a kid, and I don't want to harp on this story,
Speaker 1: but just briefly, because of auditory issues and various other issues,
Speaker 1: I didn't do too well and didn't do hot on
Speaker 1: IQ tests when I was seven years old or so.
Speaker 1: And if someone predicted try to predict, you know, sure
Speaker 1: based on those that snapshot of my life, they would
Speaker 1: be shocked to see that I got a PhD from Yale,
Speaker 1: you know, And so I did it. I tried it,
Speaker 1: and I did it. I was successful in it. So
Speaker 1: just like your advice, you know, go for it. What
Speaker 1: happens when your actual competence surpasses the test? Do you
Speaker 1: throw away the test? Like? Do you believe the tests
Speaker 1: or the truth? Or is the truth the truth? Like
Speaker 1: the truth of your competence? I think in the world
Speaker 1: your own question, obviously the truth is the truth. But
Speaker 1: I tell you my own story about this. I'd love
Speaker 1: to hear it. I'd love to hear it. When I
Speaker 1: went to graduate school at Johns Hopkins. I'm going to
Speaker 1: speak a little slowly here because I want to be
Speaker 1: careful the way I say this, there was a professor
Speaker 1: on the faculty in the psychology department who was a
Speaker 1: pre eminent psychometrician, and he literally believed everything you needed
Speaker 1: to know about a person you could tell from their
Speaker 1: test scores, So that whenever there was a conversation and
Speaker 1: a name would come up of a previous graduate student,
Speaker 1: for example, this member of the faculty said, oh, yes,
Speaker 1: so and so I remember him. His gre score was this,
Speaker 1: his Miller Analogy test score was this, and he and that,
Speaker 1: and he would then say something like yes and he
Speaker 1: did as well as you would expect from those scores
Speaker 1: words to that effect. And this faculty member was well known,
Speaker 1: a highly regarded individual, a very sweet person by the way,
Speaker 1: a gracious, terrific mentor person human being. But this is
Speaker 1: the way he viewed the relationship between test scores and people. Well.
Speaker 1: I corresponded with him shortly before he passed away. He
Speaker 1: was very elderly. It was many years after he left
Speaker 1: the university. I had not corresponded with him for many,
Speaker 1: many years, and then for various reasons, I did have
Speaker 1: a chance to correspond with him. And I was later
Speaker 1: told by somebody else, who also was much closer to
Speaker 1: him than I was, that he remarked to this other
Speaker 1: person about me, no rich, he seems to have achieved
Speaker 1: a lot more than I would have thought from his scores.
Speaker 1: How they know your scores? Well, he knew everybody on
Speaker 1: the facult You could see your application. It was all
Speaker 1: on the scores. All the scores were on your application
Speaker 1: at that time. And he looked at him, and he
Speaker 1: remembered him, and he believed them. And now I took
Speaker 1: this as one of the great compliments of my life.
Speaker 1: By the way, So yeah, I think the bottom line
Speaker 1: is you can't over rely on a test score. Is
Speaker 1: just a test score. Life is complex, you know, reducing
Speaker 1: people down to a few scores, you know, Physicians kind
Speaker 1: of do it all the time. You know, go to
Speaker 1: a physician, you say, well you remember me, Oh, yes,
Speaker 1: you're the person with blood pressure. O. You know this
Speaker 1: and that and your weight. I told you last time
Speaker 1: you had They remember you in terms of numbers. So
Speaker 1: it's not that outrageous a thing, except it's kind of
Speaker 1: an outrageous thing. Yeah, So I don't think I disagree
Speaker 1: on this at all. Well, I wanted to quarify. You
Speaker 1: said you didn't think that hat one and that hat
Speaker 1: two were different from each other, and then it seems
Speaker 1: like you're now agreeing they are different from each other.
Speaker 1: So I'm trying to clarify what you're saying there. Well,
Speaker 1: the scientist hat tells you what the prediction is population,
Speaker 1: and your education, psychology experience tells you that there are
Speaker 1: a lot of exceptions to the prediction. But the people
Speaker 1: who make the prediction wouldn't dispute that there are many exceptions.
Speaker 1: But the reason you can have some kind of science
Speaker 1: is because you have some level of predictability. It's not
Speaker 1: deterministic though, and there are many exceptions. So I know
Speaker 1: many many cases of kids that had dyslexia who grew
Speaker 1: up to be multi millionaires through their own business sense.
Speaker 1: Oh yeah, you know, there are many, many things. I think.
Speaker 1: The mistake is going the other way. The mistake, I
Speaker 1: think is that because of all the exceptions you and
Speaker 1: everybody else personally know, they say, well, the science can't
Speaker 1: be true. Oh I see, you see. Well, yeah, that's
Speaker 1: maddening to scientists. But you see that with everything though,
Speaker 1: that way of thinking. Right when we talk about sex
Speaker 1: differences and personality, for instance, we talk about down the
Speaker 1: line of the most controversial topics. Here's the thing, you know,
Speaker 1: how do we explain how do we do public good
Speaker 1: public science communication where we explain that, you know, the
Speaker 1: exceptions matter, but so do the generalizations. I wrote a
Speaker 1: tweet about that, actually, just a couple of days ago.
Speaker 1: I said, both matter, both are can be true at
Speaker 1: the same time. Yes, But did you like that tweet?
Speaker 1: I gave it a life. So how do we responsibly
Speaker 1: communicate that to a public that seems to want to
Speaker 1: take one side or the other. I can tell you
Speaker 1: I've been trying to do this for decades in my
Speaker 1: public speaking and the first step is you have to
Speaker 1: do public speaking. You have to engage the public. Not
Speaker 1: everyone can do it. Took me a while to kind
Speaker 1: of hone my public speaking ability. The the lectures I
Speaker 1: did for the Great Courses Company, which have been popular,
Speaker 1: that helped quite a bit, but I'm only one person.
Speaker 1: Scientific communication is not easy because scientists tend to qualify things,
Speaker 1: and they tend to before they get to the point.
Speaker 1: They tell you what the problem is and the method
Speaker 1: and the details of the method, then how it was analyzed,
Speaker 1: and finally they get to the result. And this is
Speaker 1: not the way you talk to the public. So you know,
Speaker 1: I start some of my public lectures with a picture
Speaker 1: of a well known person, an autistic savant, high functioning
Speaker 1: autistic savant. And one of the things he's done isrized
Speaker 1: the string of digits for Pie, and I start by
Speaker 1: asking the audience, you know, Pie is three point one four,
Speaker 1: and then there's an infinite series of numbers, and I
Speaker 1: tell the audience, how many do you think he memorized?
Speaker 1: He took a month, studied a computer print out, memorized
Speaker 1: a string, and then went on the BBC and publicly
Speaker 1: started regurgitating the sequence of pie as people checked along
Speaker 1: the way. How many digits of pie do you think
Speaker 1: he he did five hundred, you know, fifteen thousand? You know,
Speaker 1: the answer is twenty two thousand, five hundred and fourteen.
Speaker 1: Is that Dano Tammant? Yeah? Yeah, And he wrote he
Speaker 1: wrote an autobiography. I know him, I know him. Interesting person,
Speaker 1: isn't it? Yeah? Yeah, very interesting. But the point there's
Speaker 1: a brain that can do something most people cannot do,
Speaker 1: is he highly Is he a genius? And then we
Speaker 1: have a conversation about what these words, what these words mean,
Speaker 1: And then we talk about synesthesia, a condition that an
Speaker 1: unusual brain condition that apparently he has. So there are
Speaker 1: ways to engage the public without explaining what a multiple
Speaker 1: regression equation is, you know, starting there, you know. So,
Speaker 1: but it's it's highly important because there is a hunger
Speaker 1: to know these things. And in some ways the public
Speaker 1: is way ahead and their understanding and interest in intelligence
Speaker 1: than some academic departments, you know, where intelligence is a
Speaker 1: fighting word. Yeah, I hear you. You know. The excitement
Speaker 1: that I had for the field in early in my
Speaker 1: career was purely about the least controversial aspects of the field. Really,
Speaker 1: it was like I was just so curious, like, what
Speaker 1: are the environmental correlates, what are the neuro corelates? You know,
Speaker 1: if we decompose an IQ test to its various components,
Speaker 1: what are the different strategies people use? I mean really
Speaker 1: nerdy things that I never even imagined a million years
Speaker 1: would could be controversial, do you know what I mean?
Speaker 1: It was just like me just being really nerdy. Now,
Speaker 1: I just I and I'm going to keep saying this
Speaker 1: over and over again. I wish that the field would
Speaker 1: stop being hijacked by well a, it's passed. You know,
Speaker 1: IQ tests were used by by unsavory purposes in the
Speaker 1: turn of the twentieth century. I mean, you know, we
Speaker 1: sent it, we sent back a lot of immigrants. Uh,
Speaker 1: you know, we using the tests. We used it in
Speaker 1: the army for for uh various in various ways that
Speaker 1: probably weren't weren't right. You know, it has, it has
Speaker 1: had a history of abuse, But that doesn't necessarily mean
Speaker 1: the I mean, the test it self is a blunt instrument.
Speaker 1: It's not The test itself is not evil that they
Speaker 1: can't spot. Let me say two things about that. The
Speaker 1: first is the abuse empirically seems to be less than
Speaker 1: most people, including people like me in the field, have
Speaker 1: always believed. You know, Russell, Warren Russell has written a
Speaker 1: book thirty five Myths about Intelligence or words to that effect.
Speaker 1: It's just about to come out. He's talked about it
Speaker 1: on his Twitter feed and he goes into some of
Speaker 1: the detail of this, and at one point he actually
Speaker 1: went back to immigration records and found the number of
Speaker 1: people who were sent back as mental defectives based on
Speaker 1: tests and with some tiny proportion of one percent. I mean,
Speaker 1: it happened, but it's not this GigE gigantic male practice.
Speaker 1: That's the one thing. So it's not to excuse it,
Speaker 1: but I think it's been exaggerated without really an empirical
Speaker 1: investigation of the facts of it. And the second thing
Speaker 1: is there was an editorial in Nature, I think in
Speaker 1: two thousand and fifteen on the occasion of the publication
Speaker 1: of the largest genetic study of educational attainment, which is
Speaker 1: a proxy for iq snyders. So they published this in
Speaker 1: Nature and they found basically you could have polygenic scores
Speaker 1: that would predict education attainment and was a giant sample.
Speaker 1: I think memory serves, it's around three hundred people in
Speaker 1: the sample. Now we have a sample of one point
Speaker 1: two million doing the same thing. But that was a
Speaker 1: big deal in twenty and fifty. But those effects sizes
Speaker 1: are way too small. To the point is Nature published
Speaker 1: an editorial on the occasion of publishing this at the
Speaker 1: time was a landmark study. The essence of the editorial
Speaker 1: it was intelligence is a legitimate thing to study. It
Speaker 1: may have a bad history, but we have to move on.
Speaker 1: And they cited a special issue of the journal Intelligence
Speaker 1: at the time edited by Doug Detterman on teaching intelligence
Speaker 1: in universities. And I had a little piece in there,
Speaker 1: and other people had pieces in there, and the surprising
Speaker 1: thing was very few. There are very few courses on
Speaker 1: intelligence in undergraduate education at colleges and universities, very few.
Speaker 1: Most people don't want to teach it because you have
Speaker 1: to talk about someone some uncomfortable aspects of it in
Speaker 1: the context of the much bigger context of all these
Speaker 1: other interesting and important things. But Nature. I regarded that
Speaker 1: editorial in Nature as an absolute turning point because they
Speaker 1: basically said it's okay to study the genetics of intelligence
Speaker 1: and intelligence itself and this is the future. It was
Speaker 1: what they were the way I remember that editorial. So
Speaker 1: it does pain me also to see all of this
Speaker 1: fascinating and exciting and potentially extremely important research being hijacked
Speaker 1: by these old controversies, especially since racists don't give a damn.
Speaker 1: It doesn't matter what our data shows. They're going to
Speaker 1: find a way of everybody's going to change their mind
Speaker 1: if you show that your race, this ideology is based
Speaker 1: on empirically false things, you know. So the fact that
Speaker 1: that is even affecting the funding for intelligence research, you know,
Speaker 1: I thought there should be a National Institute of stupidity,
Speaker 1: just like there's a National Institute for other diseases, And
Speaker 1: of course the National Institute of Stupidity would have to
Speaker 1: fund research trying to cure stupidity, and that the only
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Speaker 1: Now back to the show. So intelligence, we're both agreement
Speaker 1: and intelligence is important, but it's not all there is
Speaker 1: to a human There are things, you know, there are caveats.
Speaker 1: I just I think we have responsibility to just say
Speaker 1: these caveats because people just misinterpret it when you say
Speaker 1: intelligence is important, that somehow you mean it's all that's
Speaker 1: important or that or that you equate it with human worth.
Speaker 1: I don't equate. I don't know about you, but I
Speaker 1: don't equate an IQ person's IQ score with the value
Speaker 1: as a human being. No, just the opposite. I mean,
Speaker 1: what I argue in my section six point six is
Speaker 1: that you can't hold it against someone if through no
Speaker 1: fault of their own, they don't have the mental skills
Speaker 1: to be really successful in society, and therefore the role
Speaker 1: of government is to give them a safety net to
Speaker 1: provide for them. Now, how you do that, you can
Speaker 1: discuss that. You can debate that I was leaning toward
Speaker 1: universal basic income for low IQ people. But then obviously
Speaker 1: if they have trouble managing money, that may cause more problems.
Speaker 1: So you need you need some discussion about how policies
Speaker 1: can help people. But people have to be treated as individuals.
Speaker 1: And clearly, just my example of the people I know
Speaker 1: in medical school who are liars, cheaters, and thieves, I mean,
Speaker 1: you cannot equate intelligence with human worth. I also say, however,
Speaker 1: and this might seem contradictory, but I also believe that
Speaker 1: all things being equal, more intelligence is better than less,
Speaker 1: and therefore we have a moral obligation to try to
Speaker 1: increase intelligence if we can. If environmental manipulations work, we
Speaker 1: should support it. So having smaller class sizes increased intelligence,
Speaker 1: I'd be all for it. Now, smaller class size has
Speaker 1: no relationship to the development of intelligence. I think that's
Speaker 1: really an interesting argument, because I think there's trade offs
Speaker 1: with all the different traits we have in the world,
Speaker 1: And it's fascinating when you look at the brain of
Speaker 1: the neural networks associated with imagination sometimes are exact opposite
Speaker 1: of the neural networks activated on IQ tests. Sometimes in
Speaker 1: order to be creative, you have to tone down that
Speaker 1: executive network. I think it depends a lot on what
Speaker 1: you're trying to do, what you want to do in
Speaker 1: your life, and well you want to I personally think
Speaker 1: i'd rather have a couple extra imagination points if I
Speaker 1: even if that means sacrificing five IQ points. So what
Speaker 1: do you think about what I just said? Nothing you
Speaker 1: just said contradicts what I said. They match. So I
Speaker 1: didn't say that IQ was the only important thing what
Speaker 1: I said. And also, I do think it's an empirical
Speaker 1: fact that more intelligence is better than less. That's all
Speaker 1: I said. More creativity is better than less, More kindness
Speaker 1: is better than less, More colerance is better than less.
Speaker 1: I don't know how to get people to be more tolerant.
Speaker 1: I don't know how to get people to be hided.
Speaker 1: You know, I don't know how to get people to
Speaker 1: be more intelligent. But I'd like to find out. I'd
Speaker 1: like to live to see it. So, yes, I think
Speaker 1: you can make a value judgment. Imagine a thought experiment
Speaker 1: where we have the ability to manipulate the intelligence of
Speaker 1: a child or an infant, and you give parents a choice.
Speaker 1: We can turn the thermostat up or we can turn
Speaker 1: it down. Who would select to have a less bright child?
Speaker 1: I can't even imagine that that would be. Now if
Speaker 1: you said you could have a choice between more intelligence,
Speaker 1: or more charisma or more physical attractiveness, now this might
Speaker 1: present people with a dilemma. Now if you start adding
Speaker 1: in other variables, you know, but intelligence. You know, there
Speaker 1: are plenty of people who are highly successful based entirely
Speaker 1: on their looks. I'm not one of them. I was
Speaker 1: going to say, like people like you are a good
Speaker 1: example that it's a burden. What can I say? Yeah,
Speaker 1: So when you talk about something like more intelligence is
Speaker 1: better than less, that doesn't mean that it makes you
Speaker 1: a better person. It just gives you more you know,
Speaker 1: reasoning ability, which you can use for good or for ill.
Speaker 1: And if I could make people kinder, I would work
Speaker 1: on that. But my field is intelligence. Yeah, no, I
Speaker 1: hear what you're saying. I have an allergic reaction to reductionism.
Speaker 1: So I am thinking about how is reducing intelligence to
Speaker 1: brain waves or neuroscience. I know that you use words
Speaker 1: such as astonishing in your book. You say astonishing neuroscience methods.
Speaker 1: I know you're very excited about it, and I don't
Speaker 1: want to take away that excitement because it kind of
Speaker 1: excites me when I see someone excited about new frontiers.
Speaker 1: I just am asking a question in the sense that
Speaker 1: how do you not view that as reductionistic for understanding intelligence?
Speaker 1: Many aspects of science require a certain amount of reductionism,
Speaker 1: So reductionism, you know, studying something without reductionism. I think
Speaker 1: it was EO. Wilson. I'm going to screw up this quote,
Speaker 1: but EO. Wilson said something to the effect that without reductionism,
Speaker 1: you have art. With reductionism, you have science. It's an
Speaker 1: interesting quote. I guess I suppose it depends what your purpose.
Speaker 1: You know, for scientific studies, reductionism sometimes is incredibly important
Speaker 1: to isolate a variable and to narrow your construct. But
Speaker 1: dealing with the messy reality of school children, for instance,
Speaker 1: and trying to give them resources and see who would
Speaker 1: benefit from what resources. What are people's kids' dreams, desires,
Speaker 1: what are their future goals. It seems like asking people
Speaker 1: what their future goals would be it would be more
Speaker 1: beneficial for understanding the human being than just looking at
Speaker 1: their brain patterns. Do you disagree with that? No, If
Speaker 1: you are a vocational counselor, you need to see the
Speaker 1: person in as big a context as you can imagine.
Speaker 1: If you are a therapist, you need to see the
Speaker 1: person in the biggest context you can imagine exactly. If
Speaker 1: you are a university admissions officer, this gets a more
Speaker 1: interesting because you can see a person in a context
Speaker 1: that has two elements. A subjective element of letters of recommendation,
Speaker 1: achievement in high school, how many nonprofits to the high
Speaker 1: school students started, how many famous friends their parents have
Speaker 1: that can write letters of recommendation? And you can have
Speaker 1: an objective component like a standardized test. And as you know,
Speaker 1: all the research shows that all that subjective stuff adds little,
Speaker 1: if any predictive value to the objective test. Now it
Speaker 1: goes against people's sensibility. When I was on the medical
Speaker 1: school admissions committee many years ago, my colleagues would sit
Speaker 1: and they would spend half an hour or more on
Speaker 1: a folder reading the personal state meant saying things like
Speaker 1: what do you think you got a dis grade in
Speaker 1: this course? And I would finish four folders in the
Speaker 1: time they were taking to do one because I waited
Speaker 1: the MCAT score, and then I looked for reasons in
Speaker 1: the folder. If a person had a solid m CAT
Speaker 1: score that was the criteria that met the criterion of
Speaker 1: our university, then I would just scan the folder to
Speaker 1: see if there were any red flags about why this
Speaker 1: person should not get an interview. And I knew I
Speaker 1: could not read the tea leaks. I could not extract
Speaker 1: nuances from the rest of the folder, except if there
Speaker 1: was something like, well, let me explain to you why
Speaker 1: I was arrested after that barroom fight. It was an
Speaker 1: actual case, by the way, Yeah, you know, flags like
Speaker 1: that got my attention. But by and large, the research
Speaker 1: shows the objective measures are as are as predictive as
Speaker 1: they can be without adding the other stuff in. So
Speaker 1: the goal of admissions officers is to make the fewest
Speaker 1: errors possible. Now they have many criteria. You know, they
Speaker 1: have diversity as a criteria as a criterion. That's that
Speaker 1: you can't really tell that by a test score. But
Speaker 1: test scores typically nowadays are only one of many, many
Speaker 1: factors that are used. Sometimes there's some test optional. Now
Speaker 1: University of California is stopping the standardized tests for five years.
Speaker 1: They're going to develop their own. This will be a
Speaker 1: very amusing to see what they come up with that's
Speaker 1: different and more predictive. They probably won't even use the
Speaker 1: word predictive, they'll just kind of call it useful. So
Speaker 1: I wish, I hear you, and I wish that we
Speaker 1: had better objective measures of more of the totality of
Speaker 1: a human. I resonate with your point that we have
Speaker 1: to be wary about relying on subjective measures just because
Speaker 1: our heart is telling us to do so. But I
Speaker 1: also think that it's important to have a heart. And
Speaker 1: I know you don't disagree with that, but I'm saying,
Speaker 1: you know, this is the point I wanted to make,
Speaker 1: you know. I wish that we had more reliable and
Speaker 1: valid measures of a child's soul, of a student's well determination.
Speaker 1: I should say, the fire in their eyes. You can't
Speaker 1: see an applicants fire in their eyes by test scores
Speaker 1: on a piece of paper, So these are maybe intangibles,
Speaker 1: but I wish that we did a better job scientifically
Speaker 1: measuring some of these seemingly intangibles. Well, that's why the
Speaker 1: interviews sometimes try to get at and interviews are notoriously unreliable,
Speaker 1: very subjective, and they're very subject to manipulation charm, right,
Speaker 1: you're talking about charm earlier. Yeah, Yeah, the first thing
Speaker 1: in a that when I counsel people on how to
Speaker 1: approach medical school interviews, first thing I tell them is
Speaker 1: your job is to make the interviewer like you, and
Speaker 1: the rest is downhill. And you have about forty five
Speaker 1: seconds from the time you start the interview to make
Speaker 1: that happen. Because he's going to make a he or
Speaker 1: she's going to make that judgment in about forty five seconds.
Speaker 1: Because they see a million people, you have to stand
Speaker 1: out and if you're likable, the rest of the interview
Speaker 1: will go well. And I think there's true in a
Speaker 1: lot of circumstances. You know, likability is important, it's important.
Speaker 1: A lot of characteristics of a human are important. But
Speaker 1: you mean to our topic today, so's intelligence. So I'm
Speaker 1: going to end on that note, and I want to
Speaker 1: thank you. I really respect the work you've done your
Speaker 1: career and it influenced me in my own dissertation. When
Speaker 1: I was working in my own dissertation on a broadening
Speaker 1: general intelligence to unconscious and PUSSIT learning measures and creativity,
Speaker 1: I found the PIFIT model you and Rex Young developed
Speaker 1: very very important for my work. So look, I want
Speaker 1: to thank you so much for being such a legend
Speaker 1: in the field of intelligence. And on one hand, that
Speaker 1: really is a warm, fuzzy feeling that I'm gott and
Speaker 1: I appreciate it. On the other hand, it's making me
Speaker 1: feel even older than now. You know, when I give
Speaker 1: talks now there are people in the audience who do
Speaker 1: very sophisticated brain imaging who literally were not born when
Speaker 1: I did my nineteen eighty eight study. So time marches on,
Speaker 1: and by the way, I will end on this note,
Speaker 1: this is why I am optimistic that very complex problems
Speaker 1: like figuring out the neurobiology of intelligence, it's a matter
Speaker 1: of time. And if you go back fifty years ago
Speaker 1: to where we are now and what we know about
Speaker 1: the brain and our methodologies white years and so imagining
Speaker 1: fifty years in the future, I think, you know, it's
Speaker 1: a lot is possible that seems impossible now, Well, thanks
Speaker 1: for coming on and talking to us about the future
Speaker 1: of human intelligence. Well, I appreciate the chance and my
Speaker 1: best wishes same to you. Thanks for listening to this
Speaker 1: episode of the Psychology Podcast. If you'd like to react
Speaker 1: in some way to something you heard, I encourage you
Speaker 1: to join in the discussion at the Psychology podcast dot com.
Speaker 1: That's the Psychology podcast dot com. Also, please add a
Speaker 1: reading and review of the podcast on iTunes and subscribe
Speaker 1: to the Psychology Podcast YouTube channel, as we're really trying
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Speaker 1: next time for more on the mind, brain, behavior, and creativity.