h02w5E7FGlY.srt

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Good

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for decades,
ethnic groups have,

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on average,
scored significantly differently on Iq 

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tests.
According to psychology professor 

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Richard Harris,
whom you interviewed on your channel 

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Youtube,
there was no scientific consensus on the

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causes of these average differences in 
Iq test scores.

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Yet,
according to Haier,

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psychologists do generally agree that 
general intelligence exists that Iq 

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measures that well and in a non 
culturally biased way that Iq is highly 

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predictive of success and educational 
and professional terms and that for 

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decades,
ethnic groups have on average,

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scored significantly differently.
So assuming this is true,

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should we talk about it?
Sam Harris raised this question and a 

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podcast conversation with Charles 
Murray.

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Some argue that we should not talk about
this as doing so could fuel the racial 

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supremacist movements that you mentioned
with potentially horrific consequences.

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Others mainly on the intellectual dark 
web and to a very limited extent in 

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academia.
I think we should talk about this topic 

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because average differences in Iq scores
have existed for decades.

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They may have played a role in 
generating the disparate educational and

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professional outcomes that we observe 
and care about,

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and thus that we cannot properly analyze
these disparate outcomes unless we do 

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talk about the subject openly.
Geneticists,

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David Reich recently argued in the New 
York Times that have scientists do not 

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openly discuss the biological basis of 
race.

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Pseudo scientists could fill the vacuum 
with dangerous consequences.

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Furthermore,
you,

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Professor Peterson are highly critical 
of the oppression narrative that 

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permeates segments of the academy and 
activist left and knowledge about 

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average differences in Iq scores between
ethnic groups,

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while tough to assimilate could puncture
this narrative.

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So the question is,
what is your view on all that?

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I've just said,
Jesus,

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you guys already didn't take a long time
to prepare these questions.

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Didn't know.

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Alright,
so

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when I went to Harvard,
I came from mcgill and I had spent a lot

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of time with my advisor there and a 
research team that he had trying to 

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understand the genesis of antisocial 
behavior and him among adolescents,

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mostly so well as kids as well.
It's antisocial behavior is very 

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persistent.
So if you have a child whose conduct 

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disordered at the age of four,
the probability that they will be 

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criminal at the age of 15 or 20 is 
extremely high.

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It's unbelievably stable.
It's a very dismal literature because 

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you see these early onset aggressive 
kids and and it's persistent and then 

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you look at the intervention literature 
and you throw up your hands because no 

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interventions work and believe me,
psychologists have tried everything you 

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could possibly imagine and a bunch of 
things that you can't in order to 

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ameliorate that.
So we're really interested in trying to 

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understand,
for example,

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if you're antisocial by the age of four,
then there isn't an intervention that 

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seems to be effective.

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So,
and the standard penal logical theory is

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really quite horrifying in this regard 
because what you see is that male 

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aggression peaks around the age of 15 
and then it declines fairly 

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precipitously and,
and,

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and sort of normalizes again by the age 
of 27.

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And Standard penal logical theory 
essentially is this cold hearted.

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It's like if you have a mold,
if you have someone who is a multiple 

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offender,
you just throw them in prison til 

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they're 27,
then the age out of it,

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and that's all there is to it.
That's what we've got.

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Now,
there's some downside to that because 

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there's a corollary literature that 
suggests that the worst thing that you 

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can do with antisocial people is to 
group them together,

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which is what we do in prisons.
So,

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so that's a whole mess.
Anyways.

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One of the things we were doing was 
trying to see if there might be 

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cognitive predictors of antisocial 
behavior.

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And so we use this battery of 
neuropsychological tests that was put 

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together at the Montreal Neurological 
Institute,

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took about 11 hours to administer and 
hypothetically assessed prefrontal 

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cortical function.
We computerized that,

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reduced it to about 90 minutes and then 
assessed antisocial adolescents in 

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Montreal and found out that they did 
show deficits in problem solving ability

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that we were associated with,
uh,

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with prefrontal ability.
Um,

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when I got to Harvard,
I thought,

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well,
that's interesting.

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We could use the neuro psych battery to 
predict negative behavior.

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Perhaps we could use it to predict 
positive behavior.

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So I thought,
well,

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what if we turned the neuro psych 
battery and over and thought,

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well,
can we predict grades,

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for example,
because you know,

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that's a decent thing to predict.
So we ran a study,

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we ran a study that looked at Harvard 
kids,

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University of Toronto kids line workers 
at a Milwaukee factory and managers and 

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executives at the same factory.

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And what we found was that the average 
score across these neuropsychological 

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tests,
they were kind of like games.

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They were game like,
you know.

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So in one,
in one test you had,

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there were five lights in the middle of 
the screen and a box was associated with

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each light and you had to learn by trial
and error,

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which box was associated with,
with each light.

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That was one of the tests.
Um,

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so we took people's average score across
the tests because they seem to clump 

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together into a single structure.
You can do,

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you can find that out statistically.
If you take a bunch of tests,

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you can find out how they clumped 
together statistically by looking at 

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their patterns of correlations.
And you might get multiple clumps,

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which is what happens with personality 
research where you get five or you might

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get a singular clump,
which is what happens.

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Cognitive research.
And we got a single clump essentially.

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And then we were trying to figure out if
at the same time I was reading the 

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literature on performance prediction and
there's an extensive literature on 

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performance prediction,
a lot of it generated by the armed 

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forces,
by the way,

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I'm indicating that ICU is a very good 
predictor of longterm life success.

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And so here's the,
here's the general rule.

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If your job is simple,
which means you do the same thing every 

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day than Iq predicts how fast you'll 
learn the job,

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but not how well you do it.
But if your job is complex,

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which means that the demands change on 
an ongoing basis,

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then the best predictor of success is 
general cognitive ability.

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And uh,
and I learned that the general cognitive

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ability tests clump together into a 
single factor that's fluid intelligence 

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or Iq.
And then we didn't know if the factor 

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that we had found was the same factor as
Iq and it.

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And we still haven't really figured out 
whether or not that was the case because

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it kind of depends on how you do the 
analysis.

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But anyways,
I got deeply into the performance 

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prediction literature and I found out,
well if you wanted to predict people's 

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performance in life,
there's,

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there's a couple of things you need to 
know.

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You need to know their general cognitive
ability.

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If they're going to do a complex job,
you need to know their trait.

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Conscientiousness,
some of you might've heard that 

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rebranded as grit in a very corrupt act 
by the way,

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um,
because it's a good predictor of 

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longterm life success,
freedom from negative emotion.

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Low neuroticism is another predictor,
but it's sort of third on the hierarchy.

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And then openness to experience which is
a personality trait,

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is associated with,
with expertise in creative domains.

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The evidence that now I should tell you.

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So it's such a complicated question.
I should tell you how to make an Iq 

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test.
It's actually really easy and you need 

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to know this to actually understand what
Iq is.

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So imagine that you generated a,
a set of 10,000

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questions about anything.
It could be math problems,

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they could be general knowledge,
they could be vocabulary,

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that could be multiple choice.
It really doesn't matter what they're 

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about as long as they require 
abstraction to solve,

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so they'd be formulated linguistically,
but mathematically would also apply.

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And then you have those 10,000
questions.

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Now you take a random set of 100 of 
those questions and you give them to a 

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thousand people and all you do is sum up
the answers right from so some people 

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are going to get most of them right and 
some of some of them are going to get 

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most of them wrong.

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You just rank order the people in terms 
of their score,

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correct that for age and you have Iq.
That's all there is to it.

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And what you'll find is that no matter 
which random set of 100 questions you 

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take,
the people at the top of one random set 

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will be at the top of all the others and
it with very,

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very,
very high consistency.

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So one thing you need to know is that if
any social science claims whatsoever are

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correct,
then the ICU claims are correct because 

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the ICU claims are more psychometrically
rigorous than any other phenomena 

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phenomena that's been discovered by 
social scientists.

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Now,
the ICU literature is a dismal 

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literature.
No one likes it.

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Here's why.
Here's an example.

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So here's a little,
here's a fun little fact for you,

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for Liberals and conservatives alike,
because conservatives think there's a 

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job for everyone.

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If people just get off their asses and 
get the work and liberals think while 

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you can train anyone to do anything,
it's like,

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no,
there isn't a job for everyone and no,

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you can't train everyone to do 
everything that's wrong.

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And here's one of the consequences of 
that.

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So as I mentioned,
the Armed Forces has done a lot of work 

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on ICU when they started back in 19,
19.

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And the reason they did that was 
because,

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well,
for obvious reasons,

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say let's say there's a war and you want
to get qualified people into the officer

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positions as rapidly as possible or 
you'll lose.

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So that's a reason.
Now,

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the armed forces has experimented with 
Iq tests since 19,

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19,
and in the last 20 years I'm a law was 

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passed as a consequence of that 
analysis,

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which was that it was illegal to induct 
anyone into the armed forces who had an 

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Iq of less than 83.

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Now the question is why and the answer 
was all of that effort put in by the 

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armed forces indicated that if you had 
an Iq of 83 or less,

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there wasn't anything that you could be 
trained to do in the military that 

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wasn't positively counterproductive.
Now you got to think about that a,

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because the military is chronically 
desperate for people right there.

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It's not like they're so like people are
lining up to be inducted,

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right?
They have to go out and recruit and it's

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not easy and so they're desperate to get
their hands on every body they can 

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possibly manage and then especially in 
war time,

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but also in peacetime.
But then there was another reason too,

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which was the armed forces,
was also set up from a policy 

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perspective to take people in the 
underclass,

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let's say,
and train them and move them up at least

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into the working class or maybe the 
middle class.

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So there's a policy element to it too.
And so even from that perspective,

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you could see that the military is 
desperate to bring people in,

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but it well with an Iq of 83 or less,
it's not happening.

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Okay?
So how many people have an Iq of 83 or 

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less?

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Ten percent.
Now,

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if that doesn't,

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if that doesn't hurt you to hear,
then you didn't hear it properly.

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Because what it implies is that in a 
complex society like ours and one that's

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becoming increasingly complex,
there isn't anything for 10 percent of 

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the population to do.
Alright,

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well what are we going to do?
We're going to ignore that.

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We're going to run away from that and 
believe me,

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we have every reason to.
Or we're going to contend with the fact 

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that we need to figure out how it is,
how it is,

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how it might be possible to find a place
for people on the lower end of the 

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general cognitive distribution to take 
their productive and worthwhile place in

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society.
And that isn't just going to a matter of

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dumping money down the hierarchy because
giving people who have nothing to do 

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money isn't helpful.
It doesn't work.

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It's not that simple.
Well,

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so that's kind of an answer to the 
question of whether or not we should 

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deal with,
uh,

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with Iq forthrightly.
It's like,

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if you can find a flaw in that logic,
like just go right ahead.

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It's not like I was thrilled to death to
discover all of this by nose,

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by no stretch of the imagination.
Was that the case?

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So,
so what?

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So Iq is reliable and valid.
That's the first thing.

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It's more reliable and valid than any 
other psychometric test ever designed by

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social scientists by a factor of about 
three.

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That's fact number one.
Fact number two is it predicts longterm 

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life outcome at about point three,
point four,

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which leaves about 85 percent,
70 to 85 percent of the story 

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unexplained,
but it's still the best thing that we 

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have.
Well,

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it's also the case that in places like 
Great Britain,

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when Iq tests were first introduced,
they were actually used by the 

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socialists and they were used to 
identify poor people who had potential 

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cognitive potential and to move them 
into higher Ed Institutes of higher 

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education.
So there's an upside,

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you know,
social upside as well.

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Ethnic differences.

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This is something you can't say anything
about without without immediately being 

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killed.
So I'm hesitant to broach the topic,

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but I'll tell you one thing that I did 
in the last week that's relevant to 

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this.
So the,

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and this just shows you how complex the 
problem is.

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First of all,
we should point out that race is a very 

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difficult thing to define because racial
boundaries aren't tight,

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right?
So,

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and so when you talk about racial 
differences in Iq,

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you,
you're faced with a thorny problem of 

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defining race.
And that's a big problem from a 

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scientific perspective,
but we'll leave that aside and I wrote 

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an article this week.
Somebody stood up at one point,

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one of my talks and vice bless their 
hearts,

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00:14:00,820 --> 00:14:05,820
took this particular question and used 
it as an indication of the quality of 

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00:14:05,820 --> 00:14:07,360
the people who are my so called 
followers.

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And by the way,
the quality of my so called followers is

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pretty damn high.

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And you can find that out quite rapidly 
just by going looking at the youtube 

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comments which are head and shoulders 
above what the standard set of youtube 

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comments.
I can tell you that.

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So someone asked me that both the Jewish
question,

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right?
And the,

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the implication it was actually someone 
Jewish and the implication was that Jews

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are overrepresented in positions of 
authority and power and,

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and I was,
had just spoken for like an hour and a 

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half and you know,
this guy had an ax to grind and I 

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thought there is no God damn way I'm 
getting into this at the moment.

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And so I,
I said I'm.

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I said,
I can't answer that question,

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but that's not a very good answer.
So I wrote a blog post this week and I 

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said,
look,

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00:14:55,080 --> 00:14:55,610
here's the.
Here's the situation.

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All right,
Jews are overrepresented in positions of

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power and authority,
but then let's open our eyes a little 

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bit.

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Hey,
thank for like two or three seconds and 

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00:15:08,110 --> 00:15:08,110
think,
hey,

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guess what?
They're also overrepresented in 

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positions of competence and it's not 
like we have more geniuses.

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Then we know what to do with and if the 
Jews happened to be producing more of 

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00:15:17,381 --> 00:15:17,381
them,
which they are,

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00:15:17,381 --> 00:15:22,181
by the way,
then that's a pretty good thing for the 

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00:15:22,181 --> 00:15:24,731
rest of us.
So let's not confuse competence with 

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00:15:24,731 --> 00:15:27,611
power and authority,
even though that's a favorite trick of 

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00:15:27,611 --> 00:15:28,010
the radical leftists who always failed 
to make that distinction.

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00:15:28,460 --> 00:15:32,090
Well,
why does this over representation occur?

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00:15:32,330 --> 00:15:37,330
Because it does it also.
There's also overrepresentation in 

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00:15:37,330 --> 00:15:39,650
political movements including radical 
political movements.

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00:15:39,980 --> 00:15:40,730
Okay,
why?

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00:15:40,910 --> 00:15:43,820
Well,
answer one Jewish conspiracy.

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00:15:44,270 --> 00:15:46,190
Okay.
That's not a very good answer.

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00:15:46,460 --> 00:15:48,830
We've had.
We've used that answer before.

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00:15:49,250 --> 00:15:49,960
Alright,
but,

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00:15:50,330 --> 00:15:52,070
but do we have an alternative?
Well,

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00:15:52,071 --> 00:15:57,071
here's an alternative.
The average Ashkenazi Iq is somewhere 

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00:15:57,071 --> 00:15:58,430
between 1:10
and 1:15,

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00:15:58,880 --> 00:16:02,570
which is about one standard deviation 
above the population average.

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00:16:02,720 --> 00:16:07,720
And so what that means is that the 
average Ashkenazi Slash European Jew has

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00:16:08,211 --> 00:16:13,211
an Iq that's higher than 85 percent of 
the population that's a lot higher now,

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00:16:15,410 --> 00:16:18,560
that doesn't make that much difference 
in the middle of the distribution.

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00:16:18,650 --> 00:16:23,650
Okay?
But geniuses don't exist at the middle 

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00:16:23,650 --> 00:16:26,261
of the distribution.
They exist at the tails of the 

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00:16:26,261 --> 00:16:28,991
distribution and you don't need much of 
a move at the mean to produce walloping 

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00:16:29,661 --> 00:16:34,661
differences at the tails.
And the tails are important because a 

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00:16:34,661 --> 00:16:38,051
lot of where we draw,
we draw exceptional people from the 

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00:16:38,051 --> 00:16:38,990
exceptions.
Right?

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00:16:38,991 --> 00:16:43,991
So here's an example.
Here's another example of the same 

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00:16:43,991 --> 00:16:44,390
thing.
Most engineers are male.

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00:16:45,380 --> 00:16:50,380
Why?
Because men are more interested in 

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00:16:50,380 --> 00:16:51,890
things and women are more interested in 
people and you might say,

313
00:16:51,891 --> 00:16:53,200
well,
that's socio-cultural.

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00:16:53,270 --> 00:16:54,350
It's like,
no,

315
00:16:54,351 --> 00:16:58,220
it's not.
And we know that because if you stack up

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00:16:58,221 --> 00:17:02,180
countries by their,
by their egalitarian social policies,

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00:17:02,300 --> 00:17:04,070
which you can do quite effectively.

318
00:17:04,220 --> 00:17:09,220
And then you look at the 
overrepresentation of men in stem 

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00:17:09,220 --> 00:17:13,031
fields,
the overrepresentation increases as the 

320
00:17:13,031 --> 00:17:16,640
countries become more egalitarian.
So it's not socio-cultural.

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00:17:17,060 --> 00:17:20,660
Okay,
now men aren't that much more interested

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00:17:20,661 --> 00:17:23,150
in things than women.
It's one standard deviation,

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00:17:23,151 --> 00:17:25,040
which is about the same difference by 
the way,

324
00:17:25,100 --> 00:17:27,590
between the population norm in the 
Ashkenazi Jews.

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00:17:27,860 --> 00:17:32,860
But if you're looking at the person who 
the one person in 20 or the one person 

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00:17:32,860 --> 00:17:37,121
in 50 who's most who's hyper interested 
in things and that's likely to become an

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00:17:38,091 --> 00:17:40,490
engineer,
then most of them are men.

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00:17:41,000 --> 00:17:42,980
Here's another example of the same 
thing.

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00:17:43,820 --> 00:17:48,820
Men are more aggressive than women.
Now you might ask how much and the 

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00:17:49,881 --> 00:17:52,650
answer to that is best place to look at 
that as in Sweden,

331
00:17:52,680 --> 00:17:57,680
where the egalitarian policies of be 
laid out for a long period of time and 

332
00:17:57,680 --> 00:18:01,461
you can.
You can get a more direct inference 

333
00:18:01,461 --> 00:18:01,461
about biology.

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00:18:01,461 --> 00:18:05,120
If you took a random man and a random 
woman out of the population and you had 

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00:18:05,120 --> 00:18:09,681
to bet on who was more aggressive and 
you bet on the man you'd be right 60 

336
00:18:09,681 --> 00:18:10,890
percent of the time.
So that's not that much,

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00:18:10,891 --> 00:18:11,350
right?
It's,

338
00:18:11,351 --> 00:18:14,760
it's deviates from 50 slash 50,
but it's not like 90 slash 10.

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00:18:14,761 --> 00:18:16,650
It's 60 40.
Okay.

340
00:18:17,670 --> 00:18:19,290
So,
so what does that mean?

341
00:18:19,740 --> 00:18:21,690
Well,
we got a tail problem here.

342
00:18:21,691 --> 00:18:26,691
Again,
let's say that now you decide to go out 

343
00:18:26,691 --> 00:18:28,941
onto the extremes of aggression and you 
identify the most aggressive one in 100 

344
00:18:29,071 --> 00:18:31,800
persons.
They're all men.

345
00:18:32,850 --> 00:18:36,000
Guess who's in prison?
Those people.

346
00:18:36,480 --> 00:18:39,300
That's why most of the people in prison 
are men.

347
00:18:39,960 --> 00:18:44,960
And so this is elementary part of the 
problem in our society is that we don't 

348
00:18:44,960 --> 00:18:49,191
understand statistics.
We don't understand that you can have 

349
00:18:49,191 --> 00:18:52,551
relatively small differences at the 
population level that produce walloping 

350
00:18:52,561 --> 00:18:55,230
consequences at the tails of the 
distribution.

351
00:18:56,040 --> 00:18:57,600
Okay.
So back to ICU.

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00:18:59,890 --> 00:19:01,840
One final thing to say about Iq.

353
00:19:03,630 --> 00:19:07,380
The ethnic differences are difficult to 
dispense with.

354
00:19:08,400 --> 00:19:11,190
It's not easy to make them go away.
You can say,

355
00:19:11,191 --> 00:19:14,970
well the tests aren't culture fair.
Well here's the test of that.

356
00:19:14,971 --> 00:19:18,420
So imagine you,
you test group a with an Iq test and the

357
00:19:18,421 --> 00:19:23,421
test group B with an Iq test and then 
you look at their actual performance in 

358
00:19:23,491 --> 00:19:28,491
whatever you're predicting.
If the test was biased against ethnic 

359
00:19:28,491 --> 00:19:32,421
group A,
then it would under predict their 

360
00:19:32,421 --> 00:19:34,110
performance and that doesn't happen.
Now you could say,

361
00:19:34,111 --> 00:19:36,180
well,
there's systemic bias in the performance

362
00:19:36,181 --> 00:19:40,050
measures and the potential measures and 
that's a possibility.

363
00:19:40,760 --> 00:19:44,220
All right.
Now one other thing about that.

364
00:19:45,870 --> 00:19:50,870
There's a real danger in the ethnicity 
Iq debate and the danger is that we 

365
00:19:51,660 --> 00:19:56,660
confuse intelligence with value or that 
we include we we confuse intelligence 

366
00:19:58,861 --> 00:20:01,860
with yet with human value.
That's a better way of thinking about it

367
00:20:02,220 --> 00:20:07,220
and one of the things that we're going 
to have to understand here is that 

368
00:20:07,220 --> 00:20:11,361
that's a mistake,
is that being more intelligent doesn't 

369
00:20:11,361 --> 00:20:11,361
make you a better person.

370
00:20:11,460 --> 00:20:16,460
That's not the case.
It makes you more useful for complex 

371
00:20:16,460 --> 00:20:18,960
cognitive operations,
but you can be pretty damn horrific as a

372
00:20:18,961 --> 00:20:21,240
genius son of a bitch,
right?

373
00:20:21,241 --> 00:20:26,241
It's morally neutral,
and we also know that from the 

374
00:20:26,241 --> 00:20:26,241
psychometric data.
By the way,

375
00:20:26,241 --> 00:20:29,871
there doesn't seem to be any 
relationship whatsoever between 

376
00:20:29,871 --> 00:20:32,121
intelligence and virtue,
and so if it does turn out that nature 

377
00:20:32,121 --> 00:20:35,820
and the fates do not align with our 
egalitarianism presuppositions,

378
00:20:35,821 --> 00:20:40,821
which is highly probable.
We shouldn't therefore make the mistake 

379
00:20:40,821 --> 00:20:43,881
of assuming that if group A or person a 
is lower on one of these attributes than

380
00:20:44,611 --> 00:20:48,210
group B or person b,
that that is somehow reflective of their

381
00:20:48,211 --> 00:20:51,390
intrinsic value as human beings.
That's a big mistake.