The Jordan B. Peterson Podcast - 245. The Uncomfortable Truth Behind Economic Inequality ｜ Glenn Loury

00:00:00.000 Hey everyone, real quick before you skip, I want to talk to you about something serious and

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00:00:48.080 the first step towards the brighter future you deserve. Welcome to episode 245 of the JBP podcast.

00:00:58.260 I'm Michaela Peterson. In this episode, Dad and Dr. Glenn Lurie talked broadly about IQ, race,

00:01:05.260 and the economics of inequality. Dr. Lurie is an academic and economist who in 1982 famously became

00:01:13.320 the first black tenured professor at Harvard School of Economics. Dr. Lurie is the author of The Anatomy of

00:01:19.760 Racial Inequality and Race, Incarceration, and American Values. Also covered in this episode are topics like

00:01:27.140 the Pareto Principle, market failures, Charles Murray's infamous book, The Bell Curve, Christianity, Dad's genius

00:01:34.500 mathematician client, AA meetings, and climate change. As always, you can get rid of ads and you can get rid of me

00:01:41.340 telling you how to get rid of ads by going premium at jordanbpeterson.supercast.com. That comes with

00:01:48.480 a bunch of perks like exclusive show notes and monthly Q&As. Check out the whole list of benefits

00:01:53.240 at jordanbpeterson.supercast.com. Without further ado, Dr. Glenn Lurie.

00:01:59.240 Hello, everybody. I'm pleased today to have as my guest Professor Glenn C. Lurie, Merton P. Stoltz,

00:02:24.800 Professor of Economics at Brown University. He holds a BA in mathematics from Northwestern and a PhD in

00:02:32.080 economics from MIT. He's published widely as an economic theorist and researcher, has lectured

00:02:38.060 throughout the world, and is one of America's leading analysts of racial inequality. He's been

00:02:43.100 elected a distinguished fellow of the American Economics Association, a member of the American

00:02:48.020 Philosophical Society and of the U.S. Council on Foreign Relations, and is a fellow both of the

00:02:53.920 economic, sorry, Econometric Society and the American Academy of Arts and Sciences. His YouTube channel

00:03:01.140 podcast, The Glenn Show, often co-hosted with Professor John McWhorter, a linguist at Columbia and a recent

00:03:07.620 guest on my YouTube channel, has attracted an increasingly wide audience. I'm hoping to talk with Professor

00:03:14.040 Lowry about income distribution, the Pareto Principle, his shifting political and religious beliefs, racial

00:03:21.100 inequality, etc., and as well as his public presence on YouTube and via podcast. Thank you very much for

00:03:28.640 agreeing to speak with me today. I'm very much looking forward to this conversation. Good to be with

00:03:33.360 you, Jordan. I'm excited. Great, great. So maybe we could start by, I'd like to get to know you a little

00:03:39.280 bit. So how did you, how did it come about that you developed an academic career? Well, I was a

00:03:46.500 working class kid in Chicago and got to a junior college. I married quite young. I dropped out of

00:03:54.880 college. I found my way back to school at a junior community college in Chicago and had a math teacher,

00:03:59.920 calculus teacher, who saw that I was really, really good at differentiating and integrating. You know,

00:04:08.040 that I was, that I was good at these little mathematical puzzles. He said, you're a smart

00:04:11.140 kid, you know, and it was 1970. It was right, you know, at the height of the Vietnam protest and the

00:04:22.600 black power and all of that. Northwestern University wanted to recruit black kids from Chicago to come

00:04:29.520 and study there. And I got recommended to their attention. And I ended up with a full scholarship at

00:04:34.200 Northwestern where I discovered a serious quantitative study in mathematics and in economics. I took

00:04:44.040 graduate courses while an undergraduate at Northwestern in both math and econ and found myself at MIT as a

00:04:50.500 graduate student in the early 1970s, took a PhD there. Did you know that you had a mathematical

00:04:58.340 bent before you, before you were discovered, so to speak at the community college? I did. I was always

00:05:04.920 good at math. I was doing slide rule and logarithms and stuff. When I was in the sixth grade, I was

00:05:10.660 teaching my fellow eighth graders from a algebra, you know, problem set book after class, because it was

00:05:19.920 just a hobby that I, that I loved. I was always good at math. But I had not had the opportunity to get

00:05:26.300 a really serious education until I got to Northwestern. And that's when things, things took

00:05:33.160 off for me. And MIT, you know, it was the best, probably the best economics department in the world

00:05:37.980 in the early 1970s, with students from all over who were quite outstanding scholars. And, and I, I really

00:05:45.020 found my niche, found my niche there. What I loved about it was formal modeling applied to social

00:05:53.720 questions. I liked math, but it was arid and abstract. And it was the early 1970s, one wanted to be working on

00:06:01.740 social issues somehow. And economics was exactly right for me, because I found that you could explore these

00:06:09.960 questions with a kind of rigor and a kind of disciplined, quantitative specification and, you know, deductive

00:06:16.920 logic and, and applied mathematics, not deep, not really, really deep mathematics, but, you know, serious

00:06:24.260 applied mathematics. So it was a natural fit for me.

00:06:28.380 Yeah, I liked, I took a clinical research degree, and I liked the science a lot, the research science, but I

00:06:34.600 really liked the fact that my clinical practice enabled me to sort of nail that down to earth all the

00:06:39.520 time. So that was a lovely balance as well. And also sort of fed my interest in social issues more

00:06:45.440 at the individual level than say, the sociological level, where did you become convinced, I mean,

00:06:49.940 you've got this mathematical bent, and you were trained, at least at the bachelor's level in

00:06:53.820 mathematics, per se, how convinced are you that the application of mathematics to economic models

00:07:00.080 produces results that are actually applicable to the real world?

00:07:05.580 Oh, well, that's a big one applicable to the real world. I mean, I think what you're doing

00:07:11.240 in formal economics, this is a big question early in the 20th century, when people like Paul Samuelson,

00:07:18.260 who was one of my teachers was beginning to apply, you know, the kind of mathematics that you would see

00:07:24.900 in theoretical physics, on dynamical systems, or, you know, this kind of apply, and it was basically

00:07:32.760 differential and integral calculus, and differential equations, and so on, apply it to classical problems

00:07:38.860 and economics. And a lot of people thought, well, that's kind of taking us away from the real world. And

00:07:44.220 that's a kind of, you know, counting angels on the head of a pen, a kind of, you know, abstract, and it's true

00:07:50.500 that one can get lost in the abstraction. But I think there are deeper insights that can be generated

00:07:58.000 through the application of mathematics that are closely connected to the real world. This is not empirical

00:08:05.720 science. This is, this is theoretical, but it's, it's a, you kind of get to the bottom of it. I mean,

00:08:11.520 I could give an example. So, the invisible hand theorem from Adam Smith, this is the late 18th

00:08:17.620 century, as you know, is, if you let people pursue profit, their own interests, at prices that are

00:08:25.420 commonly observed by everybody, and they're in competition with one another, then the outcome is

00:08:31.520 going to be socially efficient. It's going to be Pareto efficient. You were talking about Pareto just

00:08:36.540 a minute ago. It's going to be Pareto efficient. Now, that's kind of a deep insight, and what does

00:08:44.200 it depend upon? And I, I think that the 20th century characterization of what we mean by competition,

00:08:55.580 what we mean by prices being common to all people, and profit-seeking and self-interested on the part of

00:09:00.400 consumers, it, it kind of crystallizes exactly what you have to be assuming about the behavior of

00:09:07.260 individuals and about the institutional setting in order for confidence in the efficiency of

00:09:13.260 capitalist enterprise to be justified. Now, it turns out that those conditions and people like Kenneth

00:09:20.340 Arrow, the late, great Kenneth Arrow, the economist, he was at Stanford at the end of his career,

00:09:25.460 and others, formalized this at mid-20th century. Turns out that those assumptions are fairly rigid.

00:09:33.200 Those are, those assumptions are fairly demanding. There's, there's plenty of reason to believe that

00:09:37.020 they may fail, and seeing what the consequences of the failure of those assumptions are is something

00:09:45.040 that is facilitated by formalizing the problem. And I mean, I could give other examples. In political

00:09:52.120 theory that Kenneth Arrow, again, he has a famous book called Social Choice and Individual Values, and in

00:09:58.120 that, that book is a theorem which he has to employ rigorous mathematics to demonstrate, but the theorem

00:10:03.580 says that if you're looking for a mechanism that for just about any kind of society can aggregate

00:10:09.780 individual preferences in a coherent and rational way in order to formulate a social decision rule

00:10:17.440 rooted in those individual preferences, unless your rule is dictatorial, where you designate one person

00:10:23.860 to be the decision maker for everybody else, you will be looking in vain. It's an impossibility theorem.

00:10:28.900 There are no mechanisms. Majority rule doesn't satisfy all the rationality requirements, etc., etc.

00:10:35.140 Okay, so let me, that's confusing to me in some ways, and enlightening in others. Let me see if I can

00:10:41.980 rephrase that and question you a little bit about that. So, well, when I think about these sorts of

00:10:47.280 problems psychologically, in terms of how people are able to make decisions to act successfully in

00:10:54.700 the world, I see that we're always contending, in some sense, with genuine uncertainty. And the future

00:11:02.540 is, in some sense, actually unpredictable. And so, and none of us are smart enough to figure out exactly

00:11:07.600 what's coming, and what we should do. And so, I tend to view the free market as a giant computational

00:11:13.360 device that does the best job that we can of computing what's valuable at any given point across

00:11:20.560 the, you know, as vast a number of individuals as we can possibly manage. And it isn't exactly that I

00:11:26.140 think that that works. It's that I think I can't see how anything else that we could possibly do could

00:11:31.580 work better. And so, I'm not an economist, and I'm certainly not a mathematician, there might be all sorts of

00:11:39.360 problems with that sort of line of theorizing, but I see it as distributed decision making that's, you know,

00:11:45.100 a consequence, at least to some degree, of the maximum free choice among the individuals concerned. Now, I know

00:11:51.400 there's such thing as market failures, and etc. But am I way out?

00:11:55.960 No, no, you're exactly right. You're, you're, you're in Friedrich von Hayek territory. I mean, you're, who, you know,

00:12:01.320 makes this argument in a very classical way. Because information is diffuse in society. And the idea that a central

00:12:08.900 bureau of government fiat could effectively manage all the different trade offs and coordination problems and relative

00:12:20.040 valuations and so forth, you know, the computer is not big enough to be able to do that. And moreover, the information

00:12:25.800 is not in one place, the information is in the hands of many, many different decision makers. But to the

00:12:33.160 engine that makes that intuition of yours work, is prices. It's the fact that people are seeing prices,

00:12:43.400 the prices carry all the information they need about the relative merits of one or another course of action

00:12:50.520 for themselves, already incorporating the kinds of calculations that a central decision maker would

00:12:56.200 find it impossible to, to carry out. So I think the way you summarize the problem of the market being a

00:13:05.560 mechanism for calculating very difficult allocation problems to the best effectiveness that's available

00:13:14.680 to us, not perfect to be sure. I think that's correct. And yes, market failures are when that

00:13:20.360 process goes wrong. And it's usually when the prices don't reflect all the different costs, as for example,

00:13:26.120 in the climate change. Yeah, well, that that's a problem of temporality to some degree, right? Because

00:13:32.200 we can't compute costs across all possible timeframes simultaneously. And so when you're talking about

00:13:39.800 something that might have a long term cost, it's like, well, how long term a cost can we expect to

00:13:44.840 adapt to? You know, if it's 150 years in the future, well, we're all dead. And it's very difficult for us

00:13:50.760 to take such things into account. And also our prediction, our margin of error expands terribly as

00:13:55.400 we move out into the future. So okay, so I want to reverse that for a second, this will have some bearing

00:14:00.840 on our later discussion, maybe. So I, I kind of like the idea that the future is unpredictable per se,

00:14:07.240 and that you need distributed decision making power. But I also spent a lot of time studying

00:14:11.400 cognitive ability and personality. And so what researchers have concluded, essentially,

00:14:17.720 is that if you study cognitive ability, which is something like the ability to manipulate abstractions

00:14:23.400 at some rapid rate, you find that it collapses statistically into a single dimension, whereas

00:14:31.960 personality collapses into five dimensions. And this is G essentially, yes. And it's not much

00:14:38.920 different. You could you can get a pretty rough approximation of G by taking any set of 100

00:14:44.520 questions that require abstraction to solve and just averaging the score. It'll be correlated with

00:14:50.120 G at like point seven or point eight, which is a whopping correlation by social science standards.

00:14:54.600 And so but anyways, you know, the thing about me, let me ask you a question. I'm sorry to interrupt,

00:14:59.240 but I'm not a psychologist. Here's my sort of statistically trained understanding of that,

00:15:06.360 which is that while we may not be able to put our finger on any particular neural pathway or any

00:15:11.640 particular biological process of going activity going on in the brain, nevertheless, we think that there is

00:15:18.920 an ability or an aptitude that manifests itself in the solution to these abstract kinds of cognitive

00:15:27.080 problems. We're going to call it G, and we're going to measure it by the confluence of a person's

00:15:32.840 performance across a range of different kinds of tests. There's some factor analytic kind of

00:15:38.280 extraction of a vector of and you're saying that no matter what the tests are kind of it all collapses down

00:15:44.200 to this this one. It doesn't matter what the tests are, you can take any set of 100 random

00:15:50.600 questions that require abstraction to solve, and you'll pull out something that will be correlated with

00:15:55.640 G if you average the scores at about point seven or point eight. It's remarkably unitary.

00:16:00.840 It's stunningly unitary. When someone like Stephen Jay Gould, as I recall him.

00:16:04.680 Yeah, he's wrong. Okay.

00:16:06.840 And here's why, you know, he took issue with, well, he took issue with factor analysis.

00:16:11.000 He said, well, that's not real. It's like, well, is the average real?

00:16:14.440 Yeah.

00:16:15.320 It depends what you mean by real. If it has a one factor solution, it's basically identical to the

00:16:19.960 average. Not exactly, because all the questions aren't related to that average equally. But

00:16:25.160 in the case of G, for all intents and purposes, it's indistinguishable from the average.

00:16:29.640 And any random set of 100 questions will do. I mean, I looked into this deeply because we built

00:16:34.760 personality models, my research team, and they'd be reasonably influential in the field of

00:16:40.440 personality. So I understand that there are phenomena that are associated with human psychology.

00:16:45.240 They don't have a unidimensional solution. But gee, man, it's a killer. It's a black hole.

00:16:49.800 It sucks all cognition into it, and there's no escaping it. So it's very, now, and why I brought

00:16:54.920 that up? We'll go back to that. But why I brought that up is because it's kind of weird to see that

00:17:00.280 there is this cognitive ability that does allow for prediction of the future that is associated

00:17:05.800 reasonably strongly statistically with long-term, say, life economic success. In some ways that

00:17:11.240 flies in the face of the idea that a central authority can't model the future. Because

00:17:16.440 we have a central authority. And I could speak about it biologically for a second. So

00:17:21.400 you move your body voluntarily with your motor cortex.

00:17:24.520 And the prefrontal cortex grew out of that over an evolutionary time frame. And what the prefrontal

00:17:31.720 cortex does is represent action in abstraction so that you can assess, well, its mechanisms,

00:17:38.520 but also its likely outcome before you implement it in action. And that seems to be, it's not a

00:17:43.960 specifically human skill, but we've developed that far more than any other creature.

00:17:48.920 And so, and it seems to work because people with higher IQs tend to do better, say, economically.

00:17:54.360 Well, they do better across a large variety of measures. So, well, that's sort of that.

00:18:01.000 But it does fly in the face of that need for distributed decision making.

00:18:05.080 I don't see that. I don't see how it is that the ability to predict a person's, I don't know,

00:18:10.680 income or whatever on the basis of their cognitive ability

00:18:15.000 correlates or connects to the ability of someone sitting in an office somewhere to know

00:18:20.360 how much, you know, farm material should be shipped here.

00:18:23.960 And yeah, maybe it's a matter of complexity, you know, maybe that's what

00:18:27.880 And diversity. And the fact that it's not a one dimensional thing, what we're after when we,

00:18:33.560 when we ask what people want, they have preferences that are complex. And they, and I don't know who is

00:18:39.960 the person who wants a cool room or a warm room in the wintertime. Uh, they have to reveal that to

00:18:44.680 me by the actions that they take something like that. Yeah. Well, so maybe it's a, maybe it's the

00:18:49.400 case that the central IQ authorities, so to speak, has a bounded universe that's basically private in

00:18:55.240 which it can make reasonable predictions. But once you scale the problem up to a certain degree of

00:18:59.240 complexity, you have to switch to more distributed forms of cognition. That could easily be the case.

00:19:04.680 Can I predict whose marriage is going to survive based on G?

00:19:09.400 Not that I know of, you can predict whose marriage is going to survive to some degree based on

00:19:15.080 trait neuroticism, which is the negative emotion dimension. And so higher levels of neuroticism

00:19:20.920 increase the probability of divorce. And that's part of the reason why most divorces are initiated by women. 1.00

00:19:27.320 That's gonna get you in trouble. Yeah, whatever. I get in trouble all the time. But I mean,

00:19:31.240 it's not a sexist thing to say. I mean, there's reasons that women are more sensitive to negative

00:19:35.080 motion. They're smaller. The, the cost of sex is higher for them. And they have to be finely attuned 0.95

00:19:42.360 to the dangers posed to infants. And so it's an evolutionary, there's nothing wrong with the fact

00:19:48.280 they have higher levels of negative motion. It's costly for them as individuals, to some degree,

00:19:52.280 because it's unpleasant and physiologically demanding. But it makes perfect sense, given that

00:19:56.760 the world's probably more dangerous for women, especially when they have infants. 1.00

00:19:59.880 Everything you said makes a lot of sense to me. Why is it so difficult to make statements such

00:20:05.640 as the ones that you've made about the intrinsic or natural differences between men and women,

00:20:10.120 based on the very argument that you gave, that there's good evolutionary reasons why?

00:20:14.120 Well, I can play devil's advocate for that. So as a psychologist, I do see a technical reason,

00:20:23.160 in some sense, for separating biological sex from the concept of gender.

00:20:28.440 And the reason for that is that I think the best description of gender is probably in personality.

00:20:34.920 And men and women's personality are more the same than they are different. So the curves overlap

00:20:39.560 more than they differ. The biggest differences are a negative emotion and compassion slash politeness,

00:20:45.640 which is agreeableness. And women are higher in both, reliably. But there are no shortage of 1.00

00:20:51.640 women who have a masculine temperament and no shortage of men who have a feminine temperament. 0.99

00:20:56.280 They're in a minority, but the diversity is there. And so when you say something like,

00:21:02.040 well, on average, females differ in this way, it's hard for people who don't think statistically 0.97

00:21:07.720 to sort of separate that out from, well, that means everyone's like that. And while they're not,

00:21:12.280 there's tremendous individual, five dimensions of variability is a lot of variability. And so,

00:21:19.480 and there is more similarity between men and women than there are differences. The biggest difference

00:21:23.640 is in interest, actually. And this is kind of interesting for someone mathematically minded,

00:21:28.040 because there isn't much evidence that women and men differ in mathematical ability at a cognitive

00:21:33.800 level. Maybe boys have a slight edge in spatial reasoning. And that might, yeah, yeah,

00:21:38.600 might be linked to testosterone. And I think that's probably true, but it's, it's slight,

00:21:43.080 but they have a whopping different difference in interest. And women are reliably more interested 1.00

00:21:49.240 in people and men are reliably more interested in things compared to the other sex.

00:21:54.200 I read Charles Murray's book, Human Diversity. And the section of that book on gender

00:21:59.160 is very powerfully into my mind. I thought he made many strong arguments there. And around this

00:22:07.080 point about differences in interest. And then, of course, that causes people to invest in different

00:22:12.200 kinds of behavior. And that leads to differentiation in their occupational profiles and other.

00:22:17.000 Well, it's especially true at the extremes. Because, you know, even if the curves overlap to a

00:22:22.920 large degree in the middle, so that most men and women are roughly the same, if the great mathematicians,

00:22:29.800 let's say are 1% of the population, which is probably an overestimate, then they're almost all going

00:22:35.000 to be men, despite that huge overlap. And despite the lack of cognitive difference.

00:22:39.960 I've been a, I've been a chess player, a chess player, I'm just going to say all my life. And

00:22:44.600 the, the dominance of men amongst world-class chess players is, you know, it's very, very prominent.

00:22:52.760 I mean, there basically are very few women who play at the top, top rank of, of chess players.

00:23:01.080 Yeah, well, you have to kind of be obsessed with something like chess, too, to get that far,

00:23:05.880 right? I mean, it's a real specialization at that level. And so if you're not compelled by your

00:23:10.520 interest, you won't do it, despite your ability. A relatively small difference in ability at the

00:23:15.960 right tail of the distribution and spatial cognition, for example, might lead to a very large difference

00:23:21.080 in the number of hours people allocate to developing their chess playing skills. And then that would

00:23:26.600 account for the gender difference and top chess performance.

00:23:31.400 Exactly. Yeah, well, and you also see this, I got in trouble for this a lot, but, but it's true.

00:23:36.280 So that's life. In the Scandinavian countries, it's proved very difficult to get women into 1.00

00:23:42.680 engineering and men into nursing. And as those countries have become more gender equal in their

00:23:47.880 legislation and their social policies, and likely their society, those differences have got bigger,

00:23:53.560 not smaller. So it's a stunning, it's a stunning finding.

00:23:59.240 I wonder what you would say to this argument, which is, okay, okay, maybe you guys have a point.

00:24:05.160 But the main political imperative is equality for men and women. That's a political imperative. And

00:24:12.040 that means that we have to sustain majorities in favor of the kinds of laws and regulations we need to

00:24:17.560 achieve that. When you talk candidly and casually, as Lawrence Summers did when he was president of

00:24:23.240 Harvard University, I'm sure you know the incident that I'm talking about about women and why there

00:24:29.080 aren't so many at the top of mathematics and the STEM disciplines. When you talk casually about that,

00:24:35.880 you give aid and comfort to the forces that want to resist equality and you kind of feed or fuel

00:24:43.320 something that needs to be opposed, not to be encouraged. So you ought to censor yourselves a

00:24:50.440 little bit, have some modesty in the way in which you talk about these issues because the stakes are

00:24:56.680 very high, something like that. Do you find that?

00:24:58.600 Yeah, well, I'd agree with, oh yeah, but you know, the way I deal with that is I don't speak casually

00:25:03.000 about such things. Like I did my research on these topics, this is years of research, and I was dead

00:25:09.560 serious about partly because we built practical tools to assess personality and cognitive ability,

00:25:14.920 as well as I studied it as a researcher and, you know, as an interested clinician. And so none of

00:25:21.960 this is casual. And no, I don't think that censoring myself is the right idea because I think to really

00:25:28.680 say if we wanted to eliminate those gender differences in occupation, the intensity of government

00:25:35.240 intervention that would be required would tilt things towards something that's too much, too

00:25:39.720 totalitarian. You'd have to interfere with people so much to accomplish that. It's a one standard

00:25:45.000 deviation, at least difference in interest between men and women and people and things. And then if you

00:25:49.880 do foster social equality, like the Scandinavians have clearly, they've clearly done that by any

00:25:54.920 reasonable measure. And the fact that those differences get bigger, it's like you just can't walk

00:26:00.040 away from that. It's not what anyone expected on the left or the right. No one expected that.

00:26:04.520 And what seems to happen is if you give men and women every opportunity, in some ways,

00:26:10.520 they get much more different. And so, you know, hey, we didn't expect that. But that's science,

00:26:16.360 isn't it? All very, very frequently things that you don't expect happen.

00:26:21.960 So, yeah. Okay, well, you persuade me on that one.

00:26:26.680 Yeah, well, it's, it's not easy to see how you could set up government policies that would violate

00:26:31.320 people's intrinsic interest. And one of the things you do learn as a personality researcher is that

00:26:36.600 those interests are deep. They're biologically rooted in many ways. So if you're an open person,

00:26:42.600 so that's create, that's creativity dimension. That's deep, deeply rooted inside of you. It's a

00:26:49.400 fundamental element of who you are. It can't be easily trifled with or safely trifled with by,

00:26:56.520 well, let's say by political interests. And I really saw that as a clinician,

00:27:00.920 because I'd have people who were creative as clients. And if they weren't doing creative work,

00:27:05.000 they could hardly stand to be alive.

00:27:06.600 Well, this is a theme that might apply across a number of areas, the theme being a pursuit of a

00:27:14.040 faux egalitarianism, an equality in a place where the natural order of things would not have equality

00:27:20.360 be expected. But the ideology of egalitarianism is set against the objective reality of the difference

00:27:30.760 that we're talking about. And people want to make equal in any case, we want to have, we want to force,

00:27:35.080 we want to force engineering departments to recruit women, so that they have a 50 50 balance, 1.00

00:27:39.720 or whatever it might be, we want to subsidize or tax or discourage and encourage people's behavior

00:27:45.080 so as to bring about this equal outcome. Well, you know, as a heuristic, you know,

00:27:49.800 as a heuristic, you might say that if you look at outcome, and you see gender differences or ethnic

00:27:55.960 differences or racial differences, sometimes you can reliably infer barriers and prejudice.

00:28:03.080 And so as a heuristic, it's not bad, right? Because that points to a place where there might be a problem.

00:28:08.680 But then we do have some areas where we have high resolution knowledge, like, let's say, with regard

00:28:13.800 to interest in people versus things. And so then we can say, well, wait a sec, that difference doesn't look

00:28:18.920 like it's a consequence of arbitrary prejudice. So what I think I don't, like, well, look, one of the

00:28:25.080 things I was interested in talking to you about, you've written a fair bit about racial differences

00:28:29.880 in incarceration in the United States. And you've made a case, and I don't want to put words in your

00:28:34.920 mouth, but I'm trying to sum up what I understand, that the fact of those differential incarceration rates

00:28:41.000 not only has a variety of negative medium and long term consequences for everyone,

00:28:47.080 but that it does point to a kind of system systemic problem that's fundamentally discriminatory.

00:28:54.360 And to some degree, that's use of that heuristic, I would say, and in a perhaps in an entirely

00:29:00.360 appropriate way. It's complicated. But it might have I got your argument reasonably?

00:29:05.640 I wouldn't have said or I wouldn't say today, in any case, fundamentally discriminatory,

00:29:10.520 without unpacking that. Yeah, I would say that the disparity, here you have the state that

00:29:17.080 deprives people of liberty, it's a very massive footprint, the incarceration in the United States,

00:29:22.440 and there's a huge racial disparity in it. There's also a racial disparity in criminal offending.

00:29:28.200 I would make the case that even if you could account for every single person incarcerated

00:29:34.120 by reference to, well, they broke the law, they did the crime, they're doing the time,

00:29:39.400 and even if you could count, roughly, that the African American overrepresentation in prison is

00:29:46.520 commensurate with their overrepresentation amongst criminal offenders. Still, the fact that this is

00:29:53.720 the state coming down with a hammer on people and confining them and depriving them of their liberty

00:30:00.840 at the scale that it's engaged in, given the history of our society where racial difference is such a

00:30:07.720 fraught and sensitive matter, given the existence of stereotypes in the minds of people that are

00:30:14.040 buttressed by the overrepresentation of African Americans in prison, given the political alienation

00:30:20.360 in the communities from which the prisoners are coming, and all that can be loaded onto that in terms of

00:30:25.960 of a lack of the granting of legitimacy to the forces of order in the society, given the history,

00:30:36.680 which is a history that is marred by racial, et cetera, et cetera, that it would be a bad thing

00:30:44.520 for that disparity to persist. And it's an outcome that government ought to work to counteract,

00:30:51.320 not because they think it's mainly a consequence of discrimination, at least ongoing current

00:30:57.240 contemporary discrimination, but because the ultimate stability of our social order depends upon

00:31:05.000 not allowing that to fester unattended. I've said a million cases, each one rightly decided,

00:31:12.600 can still add up to a great and historic wrong. And that's the sense in which I lamented this is

00:31:20.600 years ago. I don't write so much about it anymore. But in any case, I lamented the racial disparity

00:31:26.920 in incarceration. I thought it was bad for our society, even if it reflected mainly

00:31:33.480 disparity in criminal offending, because of course, criminal offending doesn't fall from the sky either.

00:31:37.400 It's a consequence of social structure and social organization to some degree, as well as the

00:31:42.280 personality and moral characteristics of different individuals in society. But yeah, I was concerned

00:31:50.440 about mass incarceration, primarily because I thought it made solving the American dilemma

00:31:55.960 all that much more difficult to accomplish.

00:31:59.000 Yeah, well, you also wrote to some degree about its effect on disrupting families on an ongoing and

00:32:05.720 continuing basis. And I've spent a fair bit of time trying to wrestle with the potential role that

00:32:13.080 fathers play in families in relationship, let's say, to the disciplinary structures that are applied both

00:32:18.040 to young men and young women. And it certainly seems to me that these differential incarceration rates are

00:32:24.840 tremendously destabilizing for the fundamental family structure among, well, what, and when you've looked

00:32:33.640 at that, let me ask you two questions. Do you, what do you think the data show about the severity of

00:32:42.520 sentencing for blacks versus whites in the US for crimes of the same magnitude? And I know that's not bottom 0.87

00:32:50.680 level data, but how do you see that? Because you talked about criminal offending.

00:32:54.920 Yeah. Now, you can find studies where they are going to see some modestly more severe punishment

00:33:03.640 conditional on the crime for the black offenders. But my general sense of the matter, and I rest here on 0.95

00:33:10.600 my service on a committee of the National Academy of Sciences that reported maybe seven or eight years ago

00:33:17.000 causes and consequences of high rates of incarceration in the United States. My understanding of that

00:33:22.360 literature from people like, he's up in years now, but he's been very influential, Alfred Blumstein,

00:33:27.640 he's a statistical criminologist at Carnegie Mellon University, who's kind of the godfather of these

00:33:32.760 studies. There are many other studies. My understanding is that you can account, cannot account for more than

00:33:40.280 people in prison. 15, 20% of the racial disparity in people in prison, by reference to differences in

00:33:48.520 the length of sentence or the likelihood of being convicted in sentence, conditional on offense.

00:33:55.480 Okay, so that's not nothing.

00:33:56.920 The great bulk of the, no, it's not nothing. It's not nothing. But it's the great bulk of the

00:34:00.760 disparity is differences in offending.

00:34:04.680 What about probability of being arrested for an offense?

00:34:07.240 Okay, I don't know.

00:34:08.440 Is that another 15 or 20%?

00:34:09.960 I don't know. Because it could easily be.

00:34:11.960 I don't know. Yeah, these things are going to be hard to estimate, aren't they?

00:34:18.360 Probably, because you're not observing the non-arrested offenders. You're observing user surveys of

00:34:25.400 people who have been offended against. And in those surveys, there'll be reports about the perceived

00:34:30.200 race of the person who's offending. So maybe you could attempt to back into some estimate of the

00:34:36.040 conditional likelihood of being apprehended, given race. And there might be some racial difference

00:34:44.120 there. 15% sounds like that could be a lot.

00:34:46.200 Yeah, well, it could go the other way, too, because it isn't obvious to me whether

00:34:50.280 the black community in the US is over-policed or under-policed. I think you could make a theoretical 1.00

00:34:55.640 argument for either. What do you think?

00:34:57.240 Indeed, and the reporting of offenses is also going to differ by social location. Domestic violence,

00:35:04.200 for example, may or may not be reported with the same degree of fidelity across social class and

00:35:10.680 racial identity. I actually don't know this to be the case, but it's certainly plausible. So it's pretty

00:35:17.800 slippery. But I'd say the majority of the racial disparity is a reflection of disparity and offending. 0.97

00:35:26.280 The difference in sentencing conditional on the fence may differ by race disfavoring blacks. Now,

00:35:32.680 in the drug area, that's a specific thing where it's observed that drug use patterns don't differ

00:35:38.760 nearly as much by race as drug incarceration patterns do. But I explain that in my mind by reference to the

00:35:47.000 fact that open-air drug markets are going to attract on the selling side people who don't have many

00:35:55.320 positive alternative opportunities to use their time. It's a low-paying and very dangerous trade. It's no

00:36:02.280 surprise that I have to go to the wrong side of the tracks in order to engage in a prohibited commerce,

00:36:07.720 that the people who are going to be engaged in that commerce will be disproportionately from

00:36:11.640 disadvantaged communities and so on. I talked to some psychologists for a fair bit of time. It was

00:36:19.960 Margo Wilson. Unfortunately, I can't remember the name of her. Martin Daly. Margo Wilson and Martin

00:36:30.040 Daly. They've done interesting work looking at the relationship between economic inequality and crime.

00:36:34.600 And what they've showed state by state and country by country is that, and county by county in the U.S.,

00:36:41.640 is that the higher the rates of inequality, economic inequality in a given geographical locale,

00:36:48.280 the higher the rates of aggression and criminality. And what they, and they studied Chicago,

00:36:54.440 the inner city of Chicago specifically in relationship to this research. And their hypothesis was that

00:37:00.840 young men, it's very important for the sexual success of young men to be on an upward path

00:37:07.400 in relationship to status. And in places with high inequality, that's an indication that their upward

00:37:14.200 mobility is truncated in various ways. And as a consequence, they're highly likely to turn to

00:37:19.800 violence and criminality as an alternative means of obtaining status. And that's part of what's driving

00:37:26.920 the sorts of things that you're describing. And they're, they're look, they show very high correlations

00:37:32.680 between income inequality, county by county and rates of, of male aggression, especially among young

00:37:38.920 men. And like the correlations are 0.6, 0.7, unbelievably high for social science. So.

00:37:45.640 Well, that's interesting. That's news to me, but that, that's a seeking status. And when you can't do it by

00:37:51.560 a high income, then you do it by, you do it by hook or by crook, because it's so

00:37:58.040 fundamentally important and especially for young men, because for there's, here's another gender 1.00

00:38:04.520 difference. They're competing for the services of young women. Is that, is that, yeah, absolutely.

00:38:08.600 Well, and young, and young women use status as a marker for competence, way more than young men do.

00:38:16.600 So young women are much choosier as sexual partners for obvious reasons. The cost of sex is a lot higher 1.00

00:38:21.800 for them. And what they are looking for is something like competence in climbing social ladders. And then

00:38:28.920 they use social status as a marker for that. So I have a question. If there are these deep psychological,

00:38:35.800 it's social psychological dynamics at work. How much influence can culture, you know,

00:38:49.320 play in affecting people's behavior? Can we change the script or are we locked in?

00:38:55.800 Are we locked in by these kind of very deep imperatives of the sort that you were just

00:39:00.760 describing? I would say that we're constrained, but within that constraint, there's, there's no

00:39:05.800 shortage of room for choice. You know, it's sort of like chess, there's rules, but man, there's a lot

00:39:11.560 of ways to, to, to affect the chess game. And these more biological factors are more like, they're more

00:39:18.360 like game rules. And it doesn't, in some real sense, doesn't decrease the range of choice. It shapes the game.

00:39:25.640 And then socially, well, status is going to be more important as a marker for male desirability

00:39:33.800 than for female desirability. We're not going to change that. But what we can do is restructure

00:39:39.000 social systems so that nonviolent means of obtaining status are available as much as possible to

00:39:45.640 everyone. And that's sort of the equality of opportunity argument, except maybe from a biological

00:39:50.360 perspective. And it's also the inequality issues also extremely interesting, as far as I'm concerned,

00:39:56.560 because what their work suggests, and it's pretty damn solid, I believe, that inequality, economic

00:40:04.440 inequality, as such, poses a destabilizing threat to societies as such. And the reason for that is that

00:40:11.320 it promotes young male violence, particularly. And so whether you're on the left or the right, it's like

00:40:17.540 inequality is a problem. If it gets too extreme, things get violent. So it lessens for conservatives

00:40:23.800 as well as as well as people on the left. So. Okay, but inequality is inevitable, is it not?

00:40:31.780 Well, that's another thing I wanted to talk to you about. Well, let's talk about that. And because

00:40:36.540 I had this client, who is a mathematical genius, clinical client, he taught me a lot of things I didn't

00:40:42.920 know, I hadn't learned as a statistician. And one of the things he talked to me about was the

00:40:46.360 Pareto principle. And so I went and looked into that in some depth. And so I found, for example, that

00:40:51.500 it's so such a strange phenomenon, it's like, the square root of the number of people operating in a

00:40:58.560 specific discipline produce half the output. That's the law. And so there's 1000 scientists

00:41:04.780 working on a particular in a sub dis in a discipline, 30 of them publish half the papers.

00:41:10.420 And you can look across, it's the same with basketball, hoops, successfully managed hockey

00:41:17.080 goals scored, soccer goals scored, records produced, books written, books sold, records sold. It's like

00:41:25.380 everywhere, this this law, this weird square root law, sometimes people sum that up as the 8020

00:41:30.960 principle. But yeah, that's the way I heard it. Yeah, it's way worse than that.

00:41:34.700 It's way worse than 8020. Yeah, well, it's it implies, for example, if you have an organization

00:41:40.040 with 10,000 people, 100 of them doing half the work. Now, if you have 10, it's three, and that's

00:41:46.700 not so bad. But at 10,000, it's 100. And you think no way. It's like, well, if you meet some of those

00:41:51.920 people who might be in that 100, you, you might think differently. So, and this looks like there's some

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00:44:49.380 You're interested in income distribution and so what do you make of this sort of thing?

00:44:55.840 Well, it reminds me of a classic paper by the late economist Sherwin Rosen, University of Chicago,

00:45:01.500 called The Economics of Superstars. And he starts it out by observing 80-20 like observations by,

00:45:08.220 you know, let's look at the earnings of tennis players and look at the rank. So how much total

00:45:15.040 prize money is won by tennis players and what proportion of it goes to people based on the

00:45:20.820 rank? And he gets something like an 80, you know, the top, you know, 20 or 25 tennis players are taken

00:45:26.160 in, you know, the vast majority of the winnings. And it, you know, record sales by musicians in various

00:45:34.180 genres of musical production and whatnot. Similarly, the top ones are getting those. So he says, how can

00:45:40.160 we account for this? And this, I think, should be a part of anybody's effort to explain the Pareto

00:45:47.480 principle as you've defined it or the 80-20 rule. He says, look, to produce something that people want

00:45:59.020 to see, you need talent, but you also need other resources. And so it's the combination

00:46:03.200 of the productivity of the talent, which is scarce and distributed in the population, and

00:46:10.280 the effectiveness of their ability to command other resources, which taken together determine

00:46:16.260 what they will be able to produce.

00:46:19.820 Right. So you need a combination. So imagine one distribution would be talent. And so you need to

00:46:25.420 be in, say, the top 10%. But that's not enough. You also need, I don't know, you need to be in the

00:46:30.600 top 10% of education, say, to be a successful research scientist. And the juxtaposition of those two

00:46:36.780 curves produces a real fractional percentage. And those people are hyper qualified for that particular

00:46:43.020 enterprise. It's something like that. Now, he adds another element, which is, let's take opera

00:46:48.440 singers. He uses this example. So in the old days, before you had high quality sound reproduction,

00:46:54.760 such that you could sit in your living room and listen to a recording of an opera singer

00:46:59.540 through your speakers that produced an effect that was almost as good as being in the opera house.

00:47:05.860 Before that, before that, you had to actually go to the opera house to hear opera. Now,

00:47:10.720 the opera house can only accommodate a couple of thousand people max. So the very, very, very best

00:47:18.340 opera singers could still only command an audience of a couple of hundred thousand people in any given

00:47:23.240 performance, which leaves plenty of room for the second, third, fifth, and thirtieth best to be able

00:47:28.840 to travel to the small towns and still make a living. But once it becomes possible for the best to record

00:47:36.140 their performance and the distributed in that way, the person sitting in the small town has a choice.

00:47:41.820 Do I go to hear a 20th rate opera singer in the local hall, or do I put a recording of the best one on my

00:47:49.360 device? Now, often they would choose to go with the recording rather than to go to the 20th best. And that

00:47:55.980 means that the top opera singers are not going to command an even greater share of the market. And the insight

00:48:01.960 there is that technological change, which permits the most talented to lever their talent to a larger

00:48:09.280 audience is the key to understanding why they get so much of the, of the take compared to that.

00:48:15.600 Right, right. Well, you can, so it's like the smaller, the game, the less the gain at the top, but we expand

00:48:23.940 the games continually with technology and recording is an excellent example of that. And so I guess what we hope

00:48:29.820 is that we produce enough new games so that everybody can win at something, but we're still,

00:48:35.560 we're still funneling a tremendous number of resources to people at the top of whatever the

00:48:40.040 game is, especially as these games become big. So, and you see that, you see that particular, well,

00:48:46.120 it's really obvious with money and people complain continually about the top 1%, but the problem is,

00:48:51.340 is that there's a book called Big Science, Little Science that was written in about 1962. And

00:48:56.140 the author escapes me at the moment, but he did exactly the same sort of analysis for the scientific

00:49:01.380 literature. It's exactly the same story. So hyper dominance of a tiny minority of people. And so

00:49:07.840 there's a natural, it's something like positive feedback loops too, isn't it? Because, and I've

00:49:12.840 noticed this as I've become more famous, I suppose, is that you get known and so more people know you,

00:49:18.600 and so more people are likely to attend to you. And then more people are willing to talk to you

00:49:22.160 because you have an audience. And so that drives the expansion of the audience and your connection

00:49:27.660 network grows at the same time and you have more resources. And so it just, it's a positive,

00:49:32.040 it's a bunch of positive feedback loops moving upward.

00:49:35.800 I think the word network is very important there. And I think what, with social media and whatnot,

00:49:41.400 and, and the magnifying the ability of individuals to have influence and to have influence on people who

00:49:49.880 have influence, the, the density of that network is a, is a tremendous asset for, uh, uh, you know,

00:49:59.380 uh, improving a person's competitive position.

00:50:01.900 Well, it makes the problem of inequality a real tough one from the political perspective, right?

00:50:06.320 Because we could, and conceptual for that matter, because we could perhaps agree that regardless of

00:50:11.200 whether you're on the left or the right, you might view inequality on the right as a threat to social

00:50:16.780 stability. So I know there's this, uh, native Canadian tribe on the West coast, Haida,

00:50:22.520 the quack quack quacks did the same thing, you know, in their societies, they'd have big chiefs and 1.00

00:50:28.520 the big chiefs would just accrue everything. And then now, and then they'd have a potlatch and give 1.00

00:50:34.520 it all away. And then their status was dependent on their ability to give a lot away. And that

00:50:40.760 stabilized their society. Now those were made illegal by the Canadian government, I think about 70 years ago

00:50:45.880 or so, but, you know, they were thought of just some pagan, an unnecessary pagan ritual, I suppose.

00:50:54.100 But I do believe that that was one of their so-called evolved solutions to the problem of

00:50:59.840 the terrible problem of inequality. The fact that, you know, goods tend to accrue in the hands of a

00:51:05.020 few and, and the lefties that I see, the left political thinkers, economic thinkers as well,

00:51:10.720 especially the ones on the extreme left, they tend to associate that with capitalism, but

00:51:14.560 that's a fundamental underestimate of the magnitude of the problem in my thinking. And that's a real

00:51:21.640 problem. If you're concerned about, you know, comparatively poor or actually poor people,

00:51:26.240 way bigger problem.

00:51:28.520 I wonder if we could apply the same kind of thinking that we use to explain why a athlete or musician or

00:51:36.520 even an entrepreneur might end up at the very right end of the distribution garnering for themselves a

00:51:43.900 great bulk of the reward. To apply that to the huge financial fortunes that are accumulated either

00:51:53.480 through, you know, savvy in the marketplace, you know, I'm a hedge fund guy, I know what to buy and win and

00:51:59.720 win the sell or to, uh, the, the fortunes of, uh, landholding, you know, uh, family, uh, fortunes and

00:52:07.640 things of this kind. Um, I, I, I, I wonder whether those simple, uh, insights, uh, extend to the

00:52:16.760 institutionalized wealth generating process.

00:52:20.360 Well, I think, I think they do to some degree. I mean, I studied entrepreneurial success as a

00:52:25.060 researcher for quite a long time too, because one of the personality factors that predict

00:52:30.080 entrepreneurial ability is this trait openness, which is essentially creativity. And what defines

00:52:35.560 creative thinkers in part is, so here's a simple creativity test and it actually is reasonably

00:52:41.000 predictive of creative capacity, both in terms of originality of thought and creative productions as

00:52:46.400 assessed by experts. How many uses can you think of a, for a brick in three minutes? Get to write

00:52:52.420 them down. Or even how many four letter words can you think of in a minute that start with C?

00:52:57.760 That'll be correlated at about 0.3 or 4 with your creativity, depending on how it's measured. Very

00:53:02.900 simple test. And what seems to happen is that creative people, when they think of one idea, the

00:53:08.880 probability that that will trigger an associated idea is higher, especially a distally associated

00:53:15.400 idea. So that likely means that creative people have more erroneous ideas as well. And then they have

00:53:21.680 to, you know, what would you say, edit them and select. But one of the things that makes creative

00:53:27.780 entrepreneurs successful is that they produce a large variety of creative products, and then they throw

00:53:34.760 them out in the marketplace, and most of them fail. But you just need one to hit that Pareto point, and then

00:53:40.520 you're successful. So you throw, you know, it's, you throw some, what do you do, throw a mess at the wall

00:53:45.320 and see what sticks, essentially. And most entrepreneurs, before they're successful, have had a very large

00:53:51.180 number of failures. Because even if you're intelligent and creative, the probability that you'll build a

00:53:56.740 product that's actually timed for the market is extremely low. So, well, what do you do? Well, you create

00:54:04.700 more, and that's what happens. That's what creative people are essentially biologically predisposed to

00:54:10.360 do. So I think that, yeah, I think that principle, that underlying principle of positive feedback loops,

00:54:17.100 and, you know, the combination of scarcity of, of, of ability and resources, I think it accounts for all

00:54:23.260 those inequalities. So, you know, the question is, what do we do about that? Well, you were saying

00:54:28.700 something I find interesting a moment ago about how even a right winger ought to be able to see that

00:54:33.860 inequality unrestrained could be dangerous to the stable social order, because the losers,

00:54:41.980 losers are going to end up having to say one way or the other at the end of the day. And you better

00:54:46.060 watch out, because if they don't have a stake in the system, and they're feeling aggrieved, and

00:54:50.240 without status and dignity, they may act out in ways that are hard. Oh, they will, especially if

00:54:55.600 they're young men. Absolutely, they will. They absolutely, they will. And that is definitely

00:55:00.220 dangerous. And so, you know, partly, we've tried to solve that, so to speak, we in the West by trying

00:55:06.140 to ensure something like equality of opportunity across a wide range of games. That's not a bad

00:55:11.260 sort of meta solution, right? It's like, well, we can't predict, we know that there's going to be

00:55:15.640 wild disparities in outcome. And we can't really do anything about that. But maybe we can give people

00:55:20.900 something approximating an equal shot at winning some game. And that would be better for everyone,

00:55:26.680 too, because then we can harness their creative resources. And it isn't obvious to me that there

00:55:31.100 is a better solution. Technically, even, I can't see, like, I don't understand. I don't know what a

00:55:36.780 better solution could be. Now, what does that mean in a world where the people who have engineering

00:55:41.620 degrees or got to law school or got a good, you know, education and are connected are making six

00:55:50.280 figures and living comfortably? And someone who dropped out of high school is working for $30,000

00:55:56.340 a year and just barely getting by. What is that latter guy's venue where he or she can feel like

00:56:03.560 they're winning the game? Well, I think it depends to some degree on each individual, you know, I mean,

00:56:09.980 you can find status and meaning in your family, you have your pursuits outside of your work. I'm not

00:56:16.260 saying that money isn't a good singular marker of relative status. It's probably the best singular

00:56:21.920 marker there is. But it's not the only one, right? There are diverse, there are diverse places where

00:56:27.460 you can attain status. And so, and you know, you can be poor and dignified. You've certainly met people

00:56:33.640 like that. You can be poor and admired within your family. You can be poor and of decent or outstanding

00:56:40.680 character, for that matter. And so, and that's not exactly a domain that's regulated socially,

00:56:48.200 like the economic domain, but it's not nothing. And so, and by the same token, you know, you can

00:56:53.660 sacrifice a lot of those things to economic pursuit, and then you'll have lots of money. But man,

00:56:58.260 your life sucks and in 50 different ways. So I don't know if that's a sufficient solution, 0.99

00:57:04.940 but it's not nothing. But this is not constantly laissez-faire, if I understand it. It's not saying

00:57:10.360 the government should just withdraw and let the chips fall where they may. It could be advocating for a

00:57:16.260 policy of some kind of, you know, everybody needs work that's meaningful. You know, everybody needs a

00:57:22.440 kind of sense of security, you know, that they're not going to get sick and not be able to pay the

00:57:26.180 bill, or they're not going to get old and not know where the next meal is coming from. Let's guarantee,

00:57:32.140 let's try to guarantee to the extent that we can. We know it's, the world's not just perfect, and we

00:57:37.240 may not be able to solve all these problems. Let's, let's try to make sure that there's decent housing

00:57:41.600 for someone that's not, so they don't have to sleep on their bridge, etc., etc. And then let, then we can

00:57:47.000 let the chips fall where they may be. Yeah, well, it seems to me that societies like, well, the U.S. to

00:57:51.960 some degree, but more specifically, I would say the Scandinavian countries, and probably Canada would

00:57:57.080 more or less fall into that, what, ballpark. I know we fall into a ballpark, it's pretty bad metaphor, but

00:58:03.620 you know, that's kind of what, what those democratic socialist countries have tried to

00:58:08.060 establish. Now, it seems to be easier to do that in a smaller country that's more homogenous in its

00:58:14.620 ethnic and racial grouping, and maybe also technically it's easier with a smaller population.

00:58:19.720 You, the U.S., it's so damn big, it gets very complicated to try to do the same thing, you know,

00:58:25.520 that those smaller polities have managed. And, and then, of course, there's, because you might think

00:58:31.180 of something like a guaranteed, a guaranteed income. Let, let me ask you something about that,

00:58:35.640 because I, maybe it'll bolster the idea. So, when I was a clinician, I worked with a lot of people who

00:58:41.700 were impaired in their cognitive ability, so they probably had IQs around 80 or lower. And so, and if, if,

00:58:49.600 if you're, if you have cognitive ability at that range, it's, it would be hard for you to master

00:58:54.940 something like folding a letter to get it into an envelope. And that's way harder than you think, because

00:58:59.880 you have to fold it exactly in thirds. You can't be out by more than about an eighth of an inch.

00:59:05.640 And so, I, I had one client, I probably trained him for 30 hours to do that well enough so that

00:59:11.140 the letters would go through an automated machine, so that he could keep his volunteer job. But

00:59:16.360 anyways, the U.S. military has been doing cognitive testing since World War I, about. And they

00:59:24.000 determined, I don't remember when, and this is part of American legislation, that you cannot be inducted

00:59:30.160 into the armed forces if you have an IQ, I think, less than 80. And the reason they determined that

00:59:36.520 is because they couldn't find any military job of any sort that someone who is that cognitively impaired

00:59:43.940 could manage proficiently. And you think about, that's, that's a killer issue, because it's not like

00:59:50.140 the military isn't highly desirous of pulling people in, especially among, from, say, the working

00:59:57.740 class. So, they were motivated to find the opposite. And that's like 10% of the population.

01:00:03.820 And so, here, we have a problem, and no one will face this, as far as I can tell, liberals or

01:00:08.260 conservatives. 10% of the population can't really function in a complex cognitive environment, and

01:00:15.180 that's what we're producing for everyone to live in. And we don't, we can't have a conversation about

01:00:20.500 that, because, you know, the liberal types think, well, everyone can be trained to do anything, 0.99

01:00:24.620 which is complete bloody rubbish. And the conservatives think, well, you know, if you just 0.97

01:00:28.600 buckle down and work, away you go. And there's some truth in that, because conscientiousness does

01:00:33.560 predict long-term economic success, but that doesn't deal with this other issue at all. It's

01:00:39.040 10% of the population. 10% of the population are so impaired in terms of their cognitive functioning

01:00:46.000 that there's no useful work for them. In the military. Well, you can take that for what it's

01:00:51.700 worth. But are we taking it beyond the military? Well, the reason I think the military example is

01:00:56.300 so compelling is for two reasons, is that, you know, America in particular has used the military

01:01:01.860 as a means of social mobility, right? Because it moves people from the working class upward. And

01:01:07.860 that's been a conscious policy decision in part. So, there's that. But the other part is,

01:01:12.520 you know, often the military is pretty damn hungry for people. And so, if they've decided

01:01:18.440 that, well, this doesn't work, it's hard to see, well, I buy it. And that's partly, well,

01:01:25.120 because I know how much intellectual variability there is between people. It's stunning and terrifying

01:01:29.840 at the same time. It's not a positive thing. It's really harsh.

01:01:34.520 I'm just resisting this idea that we can't find anything for them to do. I mean,

01:01:38.520 and to what extent does...

01:01:42.440 You remember the bell curve?

01:01:44.800 Yeah, who could not remember the bell curve?

01:01:46.120 Yeah, I was at Harvard when that came out, and Hearnstein was still a professor there. So,

01:01:50.040 and I only want to talk about a little bit of it. I read the bell curve a couple of times. And

01:01:53.660 one of the things Hearnstein and Murray said in that book that really stuck in my mind is that

01:01:59.160 academic types like you and me, we virtually never encounter anyone in the lower 50th percentile of

01:02:06.180 the cognitive distribution. You know, when we think an undergraduate's dim, they have an IQ of 110.

01:02:12.120 And that's like 80th percentile. And so, you get blinded as you move up the, especially the academic

01:02:19.080 ladder, you get blinded to the bottom 15% of the cognitive distribution, because you just never,

01:02:24.880 those people are not in your purview. They're not in your circle.

01:02:29.820 Okay, I'll take that point. I can't use my personal experience. But what I'm chafing at is that,

01:02:36.360 okay, I'm wearing glasses, because I don't see very well without them. And I'm undoubtedly in the

01:02:42.940 distribution of visual acuity in the bottom, I don't know, 10, 15%. But when I put on a pair of glasses,

01:02:49.840 I am able to function. And what I'm, what I'm missing here is a consideration of whether or not we can't

01:02:58.040 adapt our institutions of, you know, productivity or human service or education or whatever, so as to meet

01:03:08.100 this minimum requirement, which is taking everybody, almost everybody, and giving them something to do,

01:03:14.000 giving them something to do.

01:03:15.380 Yeah, well, that needs to be done. And look, I only had a couple of things to this. So,

01:03:20.620 in the IQ literature, because you might think, well, that's biology, and it's immutable. Okay,

01:03:25.020 no, not exactly. There's this Flynn effect has shown that over the last 100 years, IQ on average has

01:03:31.700 been rising. And a huge part of that is probably better nutrition in the lower quartile of the

01:03:37.300 population. So that made a huge difference. People got smarter because they weren't starving,

01:03:42.420 essentially, they weren't malnourished. And then there is evidence to that. So it's not like this

01:03:50.080 is exactly unremediable, but the distribution doesn't seem to change much. You know what I mean?

01:03:56.880 It doesn't pack tighter into the middle, you still have the problem that some people are extremely smart

01:04:02.360 and fast, and some people aren't. And so, well, it's a hard, it's a very, very hard problem to solve.

01:04:08.580 I'm not saying that we shouldn't solve it, and that we shouldn't pay some attention to the people

01:04:12.360 who are struggling at the bottom. We absolutely should. But it isn't obvious exactly, it isn't

01:04:17.580 obvious how to do it. So this guy worked with, I mean, like I said, he probably had an IQ of maybe

01:04:24.180 something around 80, I would have estimated, you know, and I tried to find him a job.

01:04:29.280 Now, it was really hard. He had a volunteer job in a bike shop for a while. And it was a bike bookshop,

01:04:36.040 a real, you know, small enterprise. And he could sort of put books in the shelf, although he couldn't

01:04:39.980 sequence them very well. And then that place couldn't pay him. And so then I got him a volunteer

01:04:44.960 job at a charity, and he couldn't do it well enough. They were going to fire him. And I went and talked

01:04:51.320 to the director of the charity. I said, you can't fire this guy, because it's going to kill him. It's

01:04:54.540 like, think about this. He's 40. He's got a volunteer job at a charity, and he's going to get fired.

01:05:03.300 It's like, how the hell do you recover from that? Now, he quit two months later anyways, and then he

01:05:09.920 got a job with someone who trained dogs, and that worked out just fine. But you get my point. It's

01:05:15.180 like, it was virtually impossible to find him a niche. And I tried for, with his mother, who was

01:05:22.020 extraordinarily devoted to him in a very positive way. We tried for three years, really, to slot him

01:05:28.780 in somewhere. And it was virtually impossible. So are you thinking that our homeless shelters and

01:05:37.580 the prisons of the country and so on are basically populated by people such as this who are unable to

01:05:45.800 get their foot on the bottom wrong? No, I wouldn't. The evidence for a relationship between IQ and

01:05:51.600 criminality, that's not very strong. So I wouldn't say that in relationship to incarceration.

01:05:58.380 I would say it's more likely, in homelessness and that sort of thing, that's more likely, where

01:06:03.840 people, you know, they fall out of the economy because there isn't anything they can find that

01:06:07.640 will pay them a wage that will enable them to live. So, but the IQ relationship with criminality

01:06:15.560 isn't very high.

01:06:16.300 I'm keenly aware of how politically incorrect this whole conversation you and I are having.

01:06:21.220 I just read a piece in The Atlantic, I think it was, about a woman, I believe she's a cognitive

01:06:26.080 psychologist. I don't recall her name just now. She was at the Russell Sage Foundation

01:06:29.880 and met with a fierce pushback when she had just attempted to assert that variation in human

01:06:39.760 intelligence was associated with variation in human populations with other kinds of, oh, genetics.

01:06:44.580 It was genetics, I'm sorry. Genetic variation. It wasn't just intelligence. It wasn't just

01:06:48.980 intelligence. But she was saying, look, people are different. The ability to first understand

01:06:55.200 the genome much better now allows us to document that to some degree. There's distribution in

01:07:00.540 the population and it's associated with the distribution of outcomes that we're concerned

01:07:04.740 about. And there was a firestorm of proteins.

01:07:07.160 Oh, yeah. Well, it's no wonder, man. You can't dive into the IQ literature without coming

01:07:11.940 away like shell-shocked in 15 different dimensions. I mean, because certainly a huge part of G proficiency

01:07:19.580 is biologically, what would you say? It has a biological foundation. I mean, I was reading

01:07:28.160 about John von Neumann the other day, you know, and people who knew him and Einstein thought

01:07:32.380 he was way smarter than Einstein. And that's not nothing. He could multiply eight-digit numbers

01:07:37.360 in his head when he was 10. Two eight-digit numbers.

01:07:41.240 Oh, that's a prodigy.

01:07:42.660 Yeah, yeah. Well, exactly. You know, he might have had the most magnificent mathematical mind

01:07:48.840 ever. And like, that's way out on the distribution, right?

01:07:53.500 I mean, he had a huge impact in economic theory, by the way. And that was just a hobby. It was

01:07:57.520 something he was doing out of his back pocket. It wasn't even what he really cared about.

01:08:00.600 Yeah, exactly. Exactly. And you meet people like that now and then, but not very often,

01:08:05.320 you know, and they're so damn smart, you just can't bloody well believe it. And that's the

01:08:11.160 case, you know. And then with regards to socialization, you know, well, it's pretty easy to make someone

01:08:16.380 dumber, but it's not that easy to make them smarter. And for obvious reasons, you know, 0.95

01:08:20.420 it's a lot easier to wreck something than it is to improve it. And so that is the fact,

01:08:24.760 this fact of that predetermination, in some sense, really is a sorrowful, what would you call it?

01:08:32.840 It's a sorrowful fact.

01:08:35.400 Yeah, a tragic reality might be one way of putting it, that it's simply given in our nature that we

01:08:43.540 have to reckon with. And the temptation to want to not see it and not accept it can be very powerful.

01:08:51.840 Well, and I can understand exactly why, because, well, first of all, generally, the people who

01:08:57.100 discuss such things don't have a lot of hands-on experience with people in the bottom

01:09:00.840 sestile, let's say, the bottom one-sixth. So they just don't know how much difference there is in

01:09:07.400 the range. And I've administered IQ tests to all sorts of people, and you can't believe what people

01:09:13.300 don't know and can't compute. It's beyond comprehension in some ways at the bottom. But then also at the top,

01:09:20.740 I had a graduate student at Harvard. She didn't know anything about statistics when I first met

01:09:26.180 her. And four months later, she was teaching statistics at a graduate level. She was unbelievable,

01:09:31.560 and she was almost that gifted verbally as well. Now, she had some social problems that might have 0.56

01:09:38.260 been associated with her remarkable cognitive ability. But, you know, it was unreal. She made

01:09:44.120 more progress in four months in the statistical realm than I did in 15 years.

01:09:47.820 Okay, so there are differences amongst us at both ends of the spectrum, and we need to learn how to

01:09:55.800 live with them.

01:09:57.120 Yeah, well, part of it is to admit it and to see if we can do that politically without getting,

01:10:01.720 you know, bogged down in accusations and the weeds. And that's a real difficult thing to do.

01:10:07.260 And it's not like I know exactly how to do it, but I'm not going to ignore what I learned.

01:10:13.300 And I'm not going to ignore the social consequences of it. It's like, life's a lot harder for people in

01:10:19.640 the bottom 10% of the cognitive distribution. There's no doubt about that.

01:10:24.120 The Southern Poverty Law Center has classified Charles Murray as a white supremacist.

01:10:29.180 This is an organization that is a watchdog for an extremist, a white supremacist.

01:10:37.320 Yeah.

01:10:38.820 I mean, not a lot of people are going to stick their head up out of the foxhole if that's what's

01:10:42.600 waiting for them.

01:10:44.360 Yeah, that's for sure. That's for sure. Well, you know, I would also say one other thing that,

01:10:48.660 you know, would probably make me unpopular among psychologists too, mostly, but there isn't a

01:10:54.100 single phenomenon documented in the social sciences that we know more about than the

01:10:59.800 psychometrics of cognitive ability. If you throw that out, you throw everything else out because

01:11:05.660 not the people who established psychometrics of intelligence also established all the

01:11:12.060 statistical techniques that all social scientists use to assess and evaluate their data.

01:11:17.660 You just don't get to throw it out. And that's also unfortunate because it's a dismal literature in

01:11:22.620 many ways because the differential between people is so unbelievably extreme and it matters.

01:11:29.620 Well, here's where we are in economics. There are people who are arguing in popular press and

01:11:35.020 magazines and so forth that you shouldn't put a cognitive ability measure on the right-hand side

01:11:40.280 of your regression equation when you're trying to explain wage variation in the population.

01:11:45.240 They think that that is a morally objectionable thing to do. Differences amongst people in earnings

01:11:54.940 are to be understood in any way that you can other than by attributing them. 1.00

01:11:59.580 It's completely idiotic. It's completely idiotic because part of, look, part of what puts you up in that 1.00

01:12:07.040 upper end of the distribution is something like speed, right? So imagine there's some desirable 1.00

01:12:13.600 place to get economically. Maybe you're designing computer chips. That's a good example.

01:12:18.780 Well, if you're faster, you're going to get there sooner and then you're going to reap the economic

01:12:22.980 rewards. And that speed is assessed with G. It's a function of G, that computational speed.

01:12:29.820 And so, and then, you know, you also might say, well, these damn tests are culture loaded. 0.98

01:12:34.760 And that's a reasonable potential objection. But I've never seen a culture fair test that has the 0.98

01:12:42.980 same validity. No one's ever been able to produce them. And basically, people gave up in the 1960s.

01:12:47.960 The best thing you've ever come up with is the Ravens progressive matrices. And it's a pretty good,

01:12:52.480 so imagine you took a bunch of single tests of intelligence. And then you've, you got the

01:12:59.420 manifold, which is the average across all tests. You could pick the test that correlated best with

01:13:05.540 that manifold. And that's the Ravens progressive matrices. And so, and it produces differences.

01:13:12.620 So, I don't know what to do with that. You know, you can't throw your hands up and say, well,

01:13:17.980 it's insolvable. But you can't not take it into account, because then you underestimate the burden

01:13:23.480 that people at the bottom end of the distribution carry when they're trying to struggle uphill.

01:13:27.460 You know, when you say, well, all you have to do is work hard, because that's the conservative

01:13:30.860 attitude. And conscientiousness is an indicator, it's personality trait, it's an indicator of

01:13:35.500 work ethic. And it's correlated with economic outcome at about 0.25, something like that.

01:13:41.960 But cognitive ability is correlated at about 0.5. So, yeah, work, hard work really matters,

01:13:50.020 but doesn't matter as much as intelligence. So.

01:13:52.820 Yeah, you don't have to convince me. I'm, again, just struck by the political climate

01:13:58.860 of the time and the fierce resistance to this kind of causal attribution to intrinsic

01:14:08.880 characteristics of individuals, especially those under genetic control. And when you put it in

01:14:14.300 a racial disparity context, then all bets are off. I mean, it just becomes impossible. 0.57

01:14:19.920 Yeah, well, or it compels you to look for a deep, a deeper reason. You know, let me give

01:14:27.100 you an example, a research example. I worked with Richard Tremblay, and he is one of the

01:14:32.300 leading experts on the development of aggressive behavior. And he was trying to ameliorate it

01:14:37.060 among children, and used interventions that got into younger and younger kids, and finally

01:14:43.560 decided that to really ameliorate. It's a small minority of kids who produce all the aggressive

01:14:49.020 acts, pre-distribution, same thing. They're almost, so, it's quite cool, actually, if you're

01:14:54.820 a scientist, I suppose. If you look at two-year-olds, you put them in a room, a small proportion

01:15:00.620 of the two-year-olds will kick, bite, hit, and steal. It's only 5%, and almost all of them

01:15:07.420 are male. Now, if you track those kids over the next two years, most of them get socialized

01:15:13.920 out of that. Those that don't tend to stay antisocial and develop criminal behavior later.

01:15:20.540 So, it's socializable. It can be rectified between two and four. The problem was, is that

01:15:26.200 if that's the case, imagine a government enterprise set up to ameliorate that. It gets pretty damn

01:15:31.840 invasive when the government has to start figuring out how you're going to raise your two-year-old,

01:15:36.300 right? So, and this cognitive ability problem might be something that's quite similar. Like,

01:15:42.140 one of the things that's interesting about kids that become literate versus kids that

01:15:47.340 don't, is that the kids that become literate are exposed to so many more books and words

01:15:52.560 that you can hardly believe it. It's another Pareto distribution. And I see, you know, my

01:15:57.660 kids, they were dragging books around when they were 12 months old, before they, well, before

01:16:02.360 they could read. But they were familiarizing themselves with the objects, and, you know, and becoming

01:16:07.500 friends with them in a kind of nonverbal way. Yeah. And we don't know the, we don't know

01:16:12.700 the pathway to that kind of, that kind of literacy or the nature of the relationship between that and

01:16:18.240 the development of cognitive ability. Well, this is a much more hopeful vision, isn't it? A one in

01:16:25.500 which there are perhaps not yet fully determined interventions that can ameliorate or compensate.

01:16:32.400 That's like the glasses that I'm wearing that allow me to see despite my genetic disability.

01:16:38.880 I thought the spirit of Charles Murray and Richard Herrnstein in 1994, when the Bell Curve was published,

01:16:46.880 was that, sorry, but the best that we could determine, these interventions, early childhood

01:16:52.880 education, or whatever that might be, don't seem to be able to have much of an effect.

01:16:57.200 So I studied that for about 20 years, looking at exactly that. And so the Head Start programs,

01:17:04.960 they, what happened to kids who went through Head Start, the hope was that if you got kids early

01:17:09.520 enough, you could give them a Head Start cognitively, and that that would spiral upward, you know, in one

01:17:14.880 of these positive loops. But that didn't happen. What happened was the kids who went to Head Start

01:17:19.920 Head Start, leapt ahead of their peers, cognitively, but the peers caught up by grade six, and all the

01:17:27.200 differences disappeared, except the Head Start kids were less likely to drop out of school, to become

01:17:33.360 criminal, and to become pregnant, you know, young. So it wasn't nothing, but it didn't work cognitively.

01:17:39.600 But, I looked into Head Start in more detail, you know, it was also a make-work program, so the people

01:17:48.320 who were the Head Start teachers weren't necessarily particularly trained. It's really hard when you're

01:17:54.160 dealing with, say, three-year-olds, to get one-on-one time with them, and teach them something like basic

01:18:00.880 literacy, because there's so many, if you have five three-year-olds, it's like, you're spending 90% of

01:18:05.760 your time making sure that they're alive, you know, dressing them and so forth. So the amount of time

01:18:11.040 in Head Start that was actually devoted to cognitive training was minimal. And so, we don't know, actually.

01:18:18.000 We don't know yet, I don't think. Now, what about the ability to enhance other traits, not in cognitive

01:18:27.280 ability, but, I don't know, perseverance, or, you know, resilience, or, you know.

01:18:36.560 Well, resilience. And compensate for the fact that they're not going to get any smarter at the

01:18:42.800 cognitive thing, but they might actually get to be much more effective people by enhancing these

01:18:49.200 other dimensions of their performance. Well, the fact that the Head Start kids didn't drop out of

01:18:56.000 school probably reflected, at least to some degree, the fact that they behaved better,

01:19:00.960 so they were more socialized. And the theory was that some of those kids were removed from

01:19:06.000 pretty terrible environments, and protected a bit by the fact that they were going to Head Start.

01:19:11.120 They got socialized earlier, so they're able to interact in groups better. They weren't as disruptive

01:19:16.560 in classrooms. So at the same level of cognitive ability, they were still more likely to get through

01:19:21.600 school. And that wasn't nothing. And so, yes, some of those things are perhaps more ameliorable.

01:19:28.640 Still not a simple thing. Because a lot of, you know, if that window for the socialization of

01:19:34.240 aggressive behavior among aggressive boys is between two and four years of age, then that's a tough

01:19:40.640 place for governments to, or society as such, to intervene. You know, because it gets invasive.

01:19:47.440 That's, that's, and that's a big problem. Because you don't also don't want to encourage government

01:19:52.240 overreach. Yeah.

01:19:57.600 So, okay, let me ask you some more questions here.

01:20:05.520 You're, yeah, one of the things I really got curious about when I was reading about you,

01:20:10.320 you claimed in a speech to Oxford, not a claim, you said, you know that your political views had

01:20:16.080 really shifted a lot in your life, from left to center to right, and then back,

01:20:20.480 I think, farther left than you were when you started. Is that, is that an accurate description?

01:20:25.520 Yeah. And then back right again. And I don't know if I'm farther right when I was, when I was right

01:20:29.280 before I was left. Yeah, that I have, I have vacillated a little bit over the years.

01:20:34.560 And so what's, what's driven that? And what do you make of that? Because I've noticed,

01:20:39.840 as my political opinions have changed, that I was just as convinced that I was right when I

01:20:44.160 thought the opposite thing as I am now. And so, you know, that sort of says more about me than

01:20:49.360 the beliefs, I suppose. But what do you make of that shift?

01:20:52.960 Well, I think it's, this is personal to me, I think the story that I'm telling

01:20:59.840 in the memoir that I'm working on now is, is that I needed to, let me, let me start at the beginning.

01:21:08.240 So I come up as a working class kid in Chicago and I'm black and it's the 1960s, 1970s. I'm sort of

01:21:14.800 naturally a liberal Democrat by disposition or by, you know, osmosis, by the atmosphere. Everybody was.

01:21:23.840 I get to graduate school and get a training in economics and I get a green eye shade on and I

01:21:29.680 start like wanting to do my sums. You know, I started like recognizing there's no free lunch,

01:21:33.920 you know, that, that there are incentives, that, you know, there's unintended consequences,

01:21:39.200 that there's cause and effect. There's not a program for everything that we have to worry about

01:21:43.840 inflation, that, you know, etc. So I become more of a neoliberal, what they would call today a neoliberal.

01:21:52.000 I become more of a free market economist. I become more conservative. And Ronald Reagan comes along in

01:21:58.880 the early 1980s and I'm one of the few black people on the planet who thought that he, he had it right 1.00

01:22:05.200 more than he had it wrong about a lot of these questions. At the same time, I am observing what's

01:22:11.680 going on in inner city America, in the big cities across the country. I grew up in Chicago, but I

01:22:18.720 taught at the University of Michigan. I happen to know a little bit about Detroit. I can read the newspaper.

01:22:22.960 I can see what's going on in, you know, Baltimore or St. Louis or Cleveland or Pittsburgh or New York or

01:22:28.320 Los Angeles, whatever, the inner city, the ghettos, the violence, the schools that don't work, the out 1.00

01:22:33.760 of wedlock births, the low employment numbers, the culture that's coarse and that's, that's leading to

01:22:41.280 a lot of dysfunction and a lot of problems. And I'm looking at the rhetoric of the Democratic Party

01:22:46.720 or of the civil rights leadership, which seems to me to be kind of completely out of touch with reality.

01:22:53.040 This is the early 1980s. And I find myself moving further and further to the right, and I end up

01:23:00.240 a Reagan Republican. This is going to be short, the short version. I go through some profound

01:23:07.120 life-changing traumatic experiences. I have a big public fall. I was up for a government job. I had to

01:23:14.240 withdraw amid sexual scandal. I have a drug addiction problem. I get caught by the police in possession of

01:23:20.160 illicit substances. I need to go into rehab. I spend months at a psychiatric hospital in Belmont,

01:23:27.440 Massachusetts, trying to learn how to not use cocaine. I come out of that through a religious 0.99

01:23:34.960 conversion. I mean, the plot thickens. I'm a born again Christian now. I'm a recovering cocaine addict.

01:23:41.440 I'm a, you know, a bad boy, black conservative who was given the, you know, his comeuppance with his 1.00

01:23:48.960 public humiliation. And I begin to rethink my politics moving in a left direction, in part, 0.90

01:23:54.480 I think, under the pressure of just wanting to be able to go home again, just wanting to find a place

01:24:00.560 where I could be comfortable within my own skin. In part, perhaps because I had some misgivings about some of

01:24:06.880 the, you know, dimensions of the conservative political frame that was writing off people

01:24:15.360 at the bottom and not thinking hard enough as you and I have been trying to think in this conversation

01:24:20.480 about what could really be done. So I find myself moving back to the left again. But then we get to

01:24:26.160 like 2009, 2010, 2011, 2012, 2013, 14, things like the Michael Brown thing and Ferguson, Missouri, and

01:24:38.320 the Trayvon Martin thing in Sanford, Florida, and the Eric Garner thing in Staten Island, New York,

01:24:44.240 and the Tamir Rice thing in Cleveland, Ohio, and all of that. And the Black Lives Matter movement comes up,

01:24:49.760 and the woke anti-racism movement comes up. And now I find myself, it's like deja vu all over again.

01:24:58.320 I find myself thrown back to the 1980s. And the instinct within me is to resist, resist, resist the political

01:25:06.000 correctness, resist the... Yeah, so some of that is you moving in your life, but some of that is the political

01:25:12.880 landscape also shifting around you, which it does continue. Indeed, so on racial issues, the political

01:25:17.120 landscape shifts hard to the left. And I find myself, again, I find myself lamenting some of the

01:25:24.720 earlier changes when I said, you know, my feelings about affirmative action, which I was instinctively

01:25:29.920 against before I was for it, before I was against it, my feelings, maybe they were right all along in

01:25:35.600 the first place. Maybe I should not have broken my friendship with Justice Clarence Thomas over the

01:25:41.600 California Civil Rights Initiative of 1996, which banned affirmative action in the state.

01:25:48.400 The Justice and I, who were friends, decided that we were not going to talk again, because I could not

01:25:54.240 support the anti-affirmative action move at that time. Ten years earlier, I would have supported it. Today, 0.97

01:26:00.240 I would support it. Yeah, well, it's a tough question that, and that's a really tough question. So it's no

01:26:05.600 wonder, you know, that a thoughtful person might vacillate on that, because there are profound things to be

01:26:10.720 said on both sides of that argument. Hey, can I ask you, and you don't have to answer this,

01:26:15.680 but I guess it's the clinician in me. So I studied alcoholism and drug abuse and addiction

01:26:21.920 as my primary research topic when I was a grad student. And one of the things that was well-known

01:26:25.920 among alcoholism researchers at that time, and hard-edged researchers, was that religious

01:26:31.120 transformation was about the only reliable treatment, so to speak, for alcoholism. No alcoholism

01:26:37.440 treatment programs work. And that's still the truth today, no matter what people say. They just

01:26:41.840 don't work. That doesn't mean people don't stop, because they do. But spiritual transformation seems

01:26:48.560 to be a ticket out of drug addiction. And it's interesting in that regard, for example, that

01:26:55.040 Roland Griffiths and his team investigating psychedelic mushroom psilocybin have shown that one dose

01:27:02.320 producing a mystical experience produces 75% permanent cessation in smokers.

01:27:10.080 Most powerful pharmacological intervention. That's unbelievable.

01:27:12.400 It's unbelievable. And that's not, he's done all sorts of other interesting, and he's a hard-edged

01:27:18.080 research scientist. This guy's no, like, pie-in-the-sky mystic. It's really something.

01:27:23.600 There's really something to this that we don't understand. And could I ask you, you said you were

01:27:28.400 struggling with addiction problems. That's a catastrophe. And you had this religious transformation. 0.83

01:27:35.120 What was that exactly? And why do you think it was relevant to the drug abuse issue? Why did it help

01:27:42.080 you stop? Okay, I'm not sure I know the answer to the question, but I understand the question. And

01:27:49.920 there were really two dimensions to my spiritual experience in the late 1980s, when I was a cocaine

01:27:56.880 addict, and it was killing me. It was killing me. One of them was explicitly religious. I was born

01:28:03.440 again. I became a born-again Christian. I was baptized at the age of 40. I believed, came to believe

01:28:10.720 that our Lord and Savior, Jesus Christ, as we would have put it, died for me personally, Glenn Lowry, and

01:28:18.400 that there was a path to my having a relationship with Almighty God through my belief in Jesus Christ.

01:28:25.680 Now, I'm not trying to proselytize here. I actually don't have the same degree of religious fervor

01:28:30.160 contemporary in my life now, as I did at that time. But I came to believe that the other thing

01:28:35.440 that was of a spiritual significance for me was the Alcoholics Anonymous program, you know,

01:28:40.240 the 12 steps, you know. I admitted that I was an alcoholic in my life. It had become unmanageable.

01:28:45.120 I came to believe that a power greater than myself could restore me. I made a decision to turn my will and my

01:28:50.160 life over to the care of God as I understood him. And one day at a time, I was going to not drink.

01:28:55.760 I was going to talk to my sponsor. I was going to go to my meetings. I was going to deal with

01:28:59.200 whatever came up in life without drinking because I know that I'm an alcoholic and my life had become

01:29:04.160 unmanageable and et cetera, et cetera. Right, right. Yeah, well, that program has a strong

01:29:08.640 spiritual-slash-religious underpinning, and that's part of the influence of Carl Jung, who was

01:29:13.520 instrumental as a thinker. I didn't know that. Yes, yes. The person who set up AA was in correspondence

01:29:19.520 with Jung quite intensely, and so it's influenced a lot by his thoughts about the psychology of

01:29:25.520 religion. But if you ask, I just want to respond to your question, which was, what did the spirituality

01:29:31.040 do for me? And it took me out of myself. It made me humble, and it made me patient, and it made me

01:29:37.120 wanting to stifle myself and to just, you know, let go and let God. That was another

01:29:45.760 one of the bumper stickers that we used to have, that I was my own worst enemy, that I needed to

01:29:51.360 surrender, that it was a kind of radical humility in it. Yeah, well, you need that radical humility

01:29:58.480 if you're dealing with an addiction problem. There's no doubt about that, because that's a

01:30:02.960 wicked devil to have in your head. And if there's any arrogance and pride in you, that's going to be

01:30:08.880 a real obstacle to any healthful recovery, that's for sure. Yeah. I'll tell you a story if you've got

01:30:16.320 time. I'm in the halfway house, and it's run by this grizzled old Irishman. Bob Brown is his name,

01:30:23.360 and he's been getting men sober for a quarter century. And I'm in this halfway house with

01:30:27.760 drunks who've been sleeping in boxes in the subway station, and people just come out of prison, 0.61

01:30:32.640 and, you know, just get out of the detox and whatnot. And I'm the only professor in the halfway

01:30:38.480 house. Okay. So one day, Bob Brown is listening to me interact with a counselor, and I'm snowing

01:30:47.520 the counselor with how much I know about the 12-step program, because I know, because I'm a professor,

01:30:52.000 and I have read the book, and I know it all. Okay. And Bob Brown, he turns to me, the director,

01:30:56.800 he overrides the counselor, and he says, you know what, Professor Lowry, if you're so smart,

01:31:02.320 answer me this. What were you doing out there in the streets of Boston, showing your ass just like 1.00

01:31:08.560 a N-word from the projects? He didn't say N-word. This is a white guy. He's an Irishman. He confronted 1.00

01:31:19.280 me with this slur and this insult. I'm professor at Harvard University, and this guy is talking to me

01:31:27.600 like I was, you know, an N-word from the projects. And my first instinct, this is just the point about 0.93

01:31:34.560 stifling yourself and about radical humility. My first impulse was to strike him, but then I looked

01:31:40.640 and he stood 6'3", and he weighed 280 pounds, so I decided against that. That seems wise.

01:31:46.880 My next alternative was the boat from the house. I didn't need to be there. There was no law keeping

01:31:51.120 me there to hell with him. I'm not going to allow anybody to talk to me like that. But my Christian

01:31:56.720 teaching allowed me to see that I did not know the answer to the question. The question was,

01:32:05.040 what was I doing out there doing what I was doing? I had no idea what I was doing.

01:32:09.920 Yeah, well, and a more specific question, right? It's like, clearly you're smart. And so how do you

01:32:15.440 reconcile the gap there? And that's like, that's a big question. And intelligence is not wisdom.

01:32:21.680 That's for sure. Okay. And so I decided that I had better stay put right where I was in that halfway

01:32:28.080 house. I took it. I took the insult without comment. I stayed there for another five months,

01:32:34.160 and I haven't used cocaine since. That was 1989. How did you have the confidence to regain your

01:32:42.240 position and to re-adopt it after having gone through that cataclysmic experience?

01:32:47.760 I had the loving support of my wife, Linda Lowry, who is no longer living. She died 11 years ago.

01:32:55.200 I had the very strong support of Harvard University and of my colleagues and friends there

01:33:00.880 who continued to afford me the opportunity to show that I was worth a dam and that I could get it back

01:33:06.960 together again. I ultimately left and moved across the street to Boston University, a very fine place,

01:33:13.280 and I had a good job there. And I left in a way because they were so nice to me at Harvard,

01:33:17.920 I couldn't bear it. I mean, I felt like I didn't deserve it. Yeah, exactly.

01:33:24.800 I didn't deserve their forgiveness at some level. I wanted to strike out and start again

01:33:31.040 someplace on my own. I didn't want to let them be as nice to me as they were being.

01:33:36.880 But I had support is one thing that I'm having. The other thing is I got back to science. I had been

01:33:45.360 drifting into a political, I was a big public intellectual in the 1980s. I was writing in

01:33:50.400 Commentary Magazine and in the New Republic Magazine when it was a place worth writing in.

01:33:57.120 And other such venues. And I had friends in the Reagan administration. I was friends with people

01:34:02.400 like the would-be, soon to be Justice Thomas and many others. I was a high-flying conservative Black

01:34:09.040 intellectual. Actually, I forgot what I was saying. You were saying you got back to the science.

01:34:22.800 Oh, that's it. Exactly. Exactly. I said, to hell with all this newspaper stuff,

01:34:30.560 all these arguments with all these people. Let me just try to remind myself what I fell in love with

01:34:36.400 when I became an economist in the first place. I had four papers in the American Economic Review

01:34:42.720 in 1993. You know, I mean, I was- Right, so that's basically the equivalent

01:34:49.440 for those who are listening. That's kind of like the equivalent of doing a whole PhD in one year,

01:34:53.440 I would say. Because you can get a PhD with three papers if they're well-crafted. So that's about what

01:34:58.400 that is. And I was publishing up a storm between 93 and 96, 97. I published, you know, six or seven really

01:35:04.640 strong papers that got thousands of citations and stuff like that. Even to this day, these papers

01:35:09.760 are cited. So I went back to doing economics. And that, I think, allowed me to get my feet under

01:35:15.520 myself and get grounded again. And I eventually have come back to doing public intellectual work,

01:35:21.440 obviously. But in those years, I- Why have you come back? And like, you have a YouTube channel,

01:35:27.040 and maybe we can close the discussion with this. It's kind of where I wanted to close.

01:35:30.240 Is you are a public figure again. You have a YouTube channel and a podcast. So you're trying to

01:35:36.400 you're trying to speak directly to the to the public again. And why are you driven to do that? And

01:35:44.880 how is it going? It's going okay, I think. The Glenn Lowry Show, it's the YouTube channel,

01:35:51.520 and GlennLowry.substack is the newsletter. And yeah, we're putting out content every week. And

01:35:57.280 we've got, you know, some followers and whatnot. I, you know, I'm able to see that if Brown University

01:36:04.880 were to somehow find a way of getting me off the payroll, I might still be able to make a living out

01:36:10.160 here in the in the world, because there are people who are following and who want to support. So that's

01:36:15.760 all good. And it's gratifying. I'm on a mission. Jordan, I'm glad you asked. I do collaborate with

01:36:22.880 John McWhorter. He's a fine guy. He writes for the New York Times. He teaches at Columbia University.

01:36:26.720 And twice a month, he and I hold forth. The other two weeks a month, I will have other guests.

01:36:32.640 We call ourselves the woke busters. Now, some people object, they say, oh, that doesn't rhyme with

01:36:39.280 Ghostbuster. And it's silly. But it captures the idea. The idea is the world has gone mad. 0.96

01:36:47.360 The race questions on diversity, equity, and inclusion on systemic racism, on cultural

01:36:52.640 appropriations, on microaggressions, on whatever. The world has gone mad, completely mad.

01:36:57.360 The universities are in danger. This is me. I don't want to speak for John McWhorter, but I don't think

01:37:02.000 he disagrees with this, because the barbarians are at the gates. No, they've overrun the gates,

01:37:07.920 and they approach the citadel. They are a threat to the great tradition.

01:37:12.560 Hey, I got some good news for you then.

01:37:14.800 Yeah, yeah, help me out.

01:37:16.400 Well, you know, I got disinvited to Cambridge University two years ago, two and a half years

01:37:22.080 ago. I was going to go there and study with some of their experts on Exodus, because I wanted to do

01:37:27.600 a public lecture series on Exodus. And a picture of me surfaced with this guy. I had like 15,000 photos

01:37:36.000 of me taken with people that year, by the way. Anyways, he wore a t-shirt that had

01:37:41.040 criticisms of Islam on it, and that surfaced, and they disinvited me. And I found out about it on

01:37:47.920 Twitter, which wasn't the best way to find out about it. In any case, people have been working

01:37:52.560 behind the scenes since then to modify the free speech policies at Cambridge, to make it impossible

01:38:00.240 to disinvite someone unless they're doing something illegal. And that passed with a full vote of the

01:38:06.560 faculty. 85% of them voted in favor of it. And it looks like there is going to be similar adjustments

01:38:14.480 made to UK law.

01:38:15.920 Oh, that's fantastic. Was it Os Guinness that you were going to work with?

01:38:20.640 No, it was James Orr and Nigel Bigger, primarily.

01:38:24.880 Oh, I see. I just saw a book of Os Guinness called The Magna Carta of Humanity, which argues

01:38:29.920 about the book of Exodus, that it's a foundational...

01:38:32.640 Oh, oh, I should know that book, then. I should write that down. What's it called?

01:38:36.560 It's called The Magna Carta of Humanity, and the author is Os Guinness.

01:38:43.520 Os Guinness. Okay, I will look that up. Yeah, well, it's a fundamental transformation,

01:38:48.640 narrative exodus. And it was... I wouldn't have been able to go anyways, because I was too ill,

01:38:52.560 and so was my wife. But that's beside the point. But, you know, this is a very positive thing,

01:38:57.200 this development. And hopefully, well, hopefully it will become UK law. That is the plan,

01:39:03.040 whether the legislation will pass. And that'll also set up an ombudsman, as I understand,

01:39:07.840 outside the university system. So if a professor gets nailed by the politically correct types,

01:39:12.960 or right-wing conservatives, for that matter, it won't matter. And he or she will have recourse

01:39:20.480 to this ombudsman to see if the fundamental right to free speech at UK universities has been violated.

01:39:26.560 And so it'll... Well, so that's all part of it. And so this is good news. And...

01:39:32.160 Well, you're a trailblazer in that regard, and may whatever has struck in Cambridge catch over here.

01:39:39.200 I just heard about this guy from Chicago, the planetary scientist who was giving a lecture at...

01:39:44.960 To give this big name lecture at MIT, who was canceled because he had spoken out in a magazine about

01:39:51.680 affirmative action, which he says, you know, let's not do that by race. Let's, you know,

01:39:56.080 do it on the basis of individual qualification. This is a defensible position, it seems to me,

01:40:01.920 but certainly not something a person should be canceled for. But so sensitive are the guardians of

01:40:08.880 virtue at these places that they're able to get away with that kind of thing now.

01:40:13.120 Yeah, yeah. Well, it's become bureaucratized to a large degree, too. And, you know, part of that's

01:40:17.280 the faculty's fault, too, because my observation of universities is that faculty, the faculty has

01:40:23.360 allowed administrative creep for about three decades without doing anything about it, because

01:40:27.840 it was easier not to. And so, you know, I think, as a faculty member, I regard all of us to blame for

01:40:34.080 precisely this, this tremendous growth in administration and the evolution of these DEI

01:40:41.760 empires, especially in HR. Yeah, well, you asked me, you know,

01:40:50.320 what I was, why I was being a public intellectual again, and what I hope to accomplish. And I just

01:40:55.520 wanted to add that after George Floyd was killed by Derek Chauvin, the police officer in Minneapolis,

01:41:03.440 and there were protests that broke out in cities around the world, especially cities around the United

01:41:08.640 States. And some of those protests turned violent. And there was riotous behavior and assaults on

01:41:14.560 police officers, and there was arson and looting. And there was there was general disorder. And it's a big

01:41:20.640 political football, and people are on all sides of it. And there are defenders of it, and so forth and so

01:41:24.960 on. But it occurred to me that I did not even know that the incident that happened with a white police

01:41:32.800 officer and the black gentleman who died, who was killed, was a racial incident. I say, I did not

01:41:39.200 know that it was a racial incident. All I knew was that the police officer was white and that the man who

01:41:44.320 was killed was black. It didn't follow from that, that it was a racial incident. We were making it 1.00

01:41:51.360 into a racial incident, we being all of us here in the United States, we were making it into a reenactment

01:41:57.360 of old American dramas of lynching and the murder of black people by rogue police and so forth and so on.

01:42:05.040 We took that thing. And we said, Yes, see, here we have proof of the knee on the neck of black America. 0.97

01:42:14.000 That's what Al Sharpton, the activist said at the funeral of joyfully said America has its knee on our neck.

01:42:20.640 And I thought this great country of 330 million people with 40 million black people.

01:42:28.320 And here we are 150 years after slavery and a half century since Martin Luther King was killed.

01:42:36.320 Really, that's going to be the narrative for our country's politics for the next decade,

01:42:42.480 for the next 15 years. This is what we're going to teach to our children. This is how we're going to

01:42:46.400 arrange our media coverage of these events. This is that's a disaster for this country.

01:42:52.320 OK, so how how can you say that when you also have spoken so eloquently on topics such as the

01:42:58.960 differential incarceration rate? This is not an assault on your statement, by the way. I'm very curious,

01:43:04.160 because obviously, you know, you've spoken profoundly about the danger of that differential

01:43:11.040 incarceration rate. And you can see that it's not that easy to conceptually disentangle, especially

01:43:16.640 if you're politically motivated. But even if you're not, the an event like that from that broader

01:43:21.520 narrative that something, you know, something's not right structurally, and perhaps this is a reflection

01:43:26.880 of it. But well, so I don't know how to reconcile those two viewpoints. I don't know how you reconcile

01:43:33.600 them. With difficulty, I suppose I could say, because they do point in slightly different, maybe even more

01:43:39.760 than slightly different directions. But I'm trying to keep my perspective, right? I do think that the

01:43:46.640 advent of what they call mass incarceration, two and a quarter million people under lock and key on a

01:43:52.080 given day, half of them are 45% of them being black people when we're 12% of the population. As a way of 0.66

01:44:00.400 doing business going forward, without any sense of urgency of reform, without any revisiting of, you know,

01:44:08.000 our drug laws or our sentencing or whatever, without any attention to what is supposed to happen when

01:44:13.840 someone is in prison, rehabilitation or whatnot, without any exploration of alternatives to

01:44:19.520 incarceration as ways of responding to criminal offending is bad for our country. I do believe

01:44:24.320 that. And I believe the racial aspect of that echoes with our history in ways that are

01:44:29.120 that are dangerous and that we dare not neglect. I'm the same guy. On the other hand, I think

01:44:37.920 if you racialized the discussion of crime and punishment, there was the woman who was murdered

01:44:43.680 at Columbia University a few years ago and her, she was killed by these kids who were just trying to

01:44:49.040 rob her and they ended up stabbing her to death. She was white. She was, you know, I'm sorry, I don't 1.00

01:44:54.640 remember her name offhand. But, you know, she was a lovely young woman and innocent is how she's going

01:45:01.680 to appear in the photograph. And she certainly did nothing to deserve what befell her. And she was white.

01:45:06.640 Mm hmm. Right. That's the other side of it. Yeah, right.

01:45:10.400 Tessa. Tessa something is her last name. I can't recall. The kids who killed her were black kids from

01:45:16.400 around Harlem. They were in the park. Yeah, they were looking for a quick score. They had a knife. The woman is 0.96

01:45:23.040 lying. She bleeds out. Now they've convicted. One of them has been convicted. And I'm looking at the

01:45:27.760 photo in the newspaper. And here's this black kid. He looks like a black kid who's 16, 18 years old.

01:45:32.960 He's a kid. He's from this impoverished neighborhood and he's black. And the woman is white. I don't want 1.00

01:45:40.320 that incident processed in terms of black kid murders white woman. Yeah. Yeah. Okay. So maybe it's an issue. 0.97

01:45:46.880 Maybe it's an issue of conflation, careless conflation of levels of analysis. Hey,

01:45:51.600 because you, you, you, you're talking about a high resolution analysis of structural problems in the,

01:45:59.200 in the penal system. And to, to put that George Floyd event, to cram that into the same narrative,

01:46:06.960 is sort of be speaks of undifferentiated thought. And so, and then you point out that the danger of that

01:46:12.800 is, well, if you're going to racialize the white cop against the black, uh, the black victim of,

01:46:18.480 of the, of the, of the homicide, well, then why can't the same thing be done exactly the same way

01:46:24.160 when the reverse happens? And maybe we shouldn't do any, or we should do as little of that as we

01:46:28.320 possibly can. That doesn't mean we shouldn't take a look at these bigger structural issues,

01:46:32.320 but we shouldn't cram it all together in one thing, because it's not.

01:46:36.480 That's very well put, Jordan. That's exactly what I'm trying to say. You said it better than I did.

01:46:40.480 I did. Well, I listened to you. So that was a big help, by the way, if we do cram it all in the one

01:46:47.040 thing, God help us because there are people, uh, and, and they're not going to speak out. There are

01:46:52.080 people, uh, who will see it, process it just as I hope they would not do black thug murders, 0.98

01:46:58.880 innocent white girl and, and, and harbor a resentment and nurse that resentment. And that's a tinder 0.99

01:47:05.600 box. That's a powder keg waiting to be lit and we can dismiss it if we want to, but those people

01:47:11.520 are not entirely wrong in their sentiment. They, they need to be disabused of that instinct,

01:47:17.280 that, that, that instinct to conflate those levels of analysis.

01:47:20.560 Yeah. Yeah. Yeah. Well, that's part of the problem I have with ideology is that that's ideology is so

01:47:26.800 low resolution. It, it does that conflation. It doesn't notice. And when you get educated,

01:47:32.400 you start differentiating. It's like, and that's kind of what you said happened to you when you

01:47:36.240 became more conservative, once you got more educated, it's like, oh, this is when I take this

01:47:40.720 apart and see all the moving pieces, this is way more complex than my low resolution representation

01:47:46.960 guided me to believe to begin with. And that's death. I mean, I've experienced that many times

01:47:51.520 in my life when I tried to take problems apart so they could be solved instead of just discussed.

01:47:56.400 Let's say you have to make a high resolution model before you can get anywhere. That's true in clinical

01:48:01.920 practice. And I think it's true in public policy and partly what we're doing when we're educating

01:48:06.320 people, if we're doing it right is saying, Hey, you know, you've got a map of the world, but it's,

01:48:11.200 it's not very detailed. And when you really look at it, well, you know, here's the complexity.

01:48:17.680 And that's what we're actually contending with. People don't like that because,

01:48:21.200 well, it's complex, right? And you have the simple solution at hand to begin with. But

01:48:26.160 the problem is it, it, it isn't the right tool for the job. You got to make it high resolution.

01:48:32.720 Now it takes a lot of work. So thank you very much for talking to me today. It was a real pleasure

01:48:39.040 discussing things with you. And I probably talk too much because I usually do, but I apologize for that.

01:48:44.720 But I enjoyed it very much. Nice to meet you, Jordan.

01:48:47.440 Thank you. It was a pleasure meeting you and good luck with your endeavors in the future. Hopefully

01:48:51.920 we'll meet some point and hopefully we'll get a chance to talk again and say hi to Dr. McWhorter for me.

01:48:57.440 I will do that. All right. All right.

01:49:10.240 Bye.

01:49:13.600 Bye.

01:49:19.440 Bye.

01:49:19.740 Bye.

01:49:20.060 Bye.

01:49:20.320 Bye.

01:49:20.660 Bye.

01:49:21.340 Bye.

01:49:23.040 Bye.

01:49:23.440 Bye.

01:49:24.280 Bye.

01:49:24.340 Bye.

01:49:27.040 Bye.

01:49:27.320 Bye.

01:49:28.880 Bye.

01:49:29.540 Bye.

01:49:31.540 Bye.

01:49:33.180 Bye.

01:49:34.000 Bye.

01:49:35.040 Bye.

01:49:35.980 Bye.

01:49:36.680 Bye.

01:49:37.160 Bye.

01:49:38.040 Bye.

The Jordan B. Peterson Podcast - April 18, 2022

245. The Uncomfortable Truth Behind Economic Inequality ｜ Glenn Loury

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