IQ: I don’t want this to be true…

February 12, 2011 at 1:02 am (Articles) (, , , , )

This blog post discusses evidence that inheritance is, fundamentally, more important than upbringing in determining IQ. The original article is here.  The results are striking: when a child is adopted from birth, the adopted parents IQ correlates with the child’s IQ until age 7.  But by the teenage years, the correlation is gone – intelligent parents do not have intelligent adopted children, even though they do have intelligent biological children.  The conclusion is difficult to avoid.

I don't want it to be true...

I have discussed IQ before, and it lead to quite strong disagreement with some knowledgeable people who somehow found my blog.  This is (more) evidence – strong evidence – against the position I took in that discussion.  The view – my view – that genetics should be ignored by society is weakened by these results.  The truth is “obviously” the opposite – genetics do matter, a lot.

I can find some glimmers of hope – some possibilities that nurture may still win, despite the above evidence.  But I doubt that the relative importance of nature and nurture will, in this particular case, be overturned.  These are discussed at the end.

Like a good scientist, I am therefore going to change my mind and follow the evidence, right?  Nope. I’m going to bloody mindedly stand by my opinion that genetics cannot (at least yet) play a role in decision making in society, even though by normal scientific standards it could be counted as a fact.

The scientist with a “non-scientific” view?

How can I possibly justify denying something that I believe to be true?

My reason is that, although we have enough scientific evidence about the effect of genetics on people, we do not have an understanding about the effect of acting on this knowledge. I am petrified by the thought of what decisions might be made on the basis of knowing IQ correlates better with nature than with nurture.  Here are just two that could come about if the idea is accepted into the mainstream:

  1. Intelligent, wealthy, middle classed people will be less likely to adopt from poor and/or unknown genetic stock.  As discussed in the links above, it is not rational to adopt children who will not live up to expectations; instead, IVF and other solutions will be preferred.  This could result in disaster for those needing adoption.
  2. People who believe that they have good genetic stock would rationally want to “out breed” those with “inferior” genetics.  In today’s class society, that would mean specifically preventing poor (or otherwise undesirable) people from breeding.  We’ve seen this before, and it was not pretty.

Do we accept the evidence and put up with the consequences?  I say no – although scientifically we can accept these results, they must not be accepted by society.

The responsible scientist

The correct response, I believe, is to place a stronger requirement on the evidence.  Essentially, we need to know how to move from the society we have now, to a society that might exploit this knowledge, without causing chaos, misery and unfairness on the way.  This requires several things: firstly, an almost unheard of degree of certainty in the scientific evidence that nature trumps nurture, because whilst there is even a glimmer of doubt any policy will be unfair.  Secondly, it requires a strong understanding of the social response that people will have to such a policy.  And thirdly, we must know how to deal with that in a way that is fair.  (a fair rule: we would all agree to it before we know which side of the rule we will fall on.)

The high bar

My previous arguments on  this subject focussed on the first of these points, because I’m not convinced that anyone knows anything about the second and third.  The burden of proof must be with the nature camp, simply because the implications of it being true could be so dramatic.  Therefore I will offer a couple of “get out” clauses to the above research.

Firstly, the results are averages over children that were either adopted or not.  If there is a correlation with e.g. parents IQ and being adopted, then these results will be biased by it. (But that still assumes a genetic relationship for IQ, just a different one…)

Secondly, the results cannot account for the effect of “epigenetics“: that is (mostly), the effect of mothers health during pregnancy on the potential of her child.  As I discussed previously, this effect is these days being seen as large (hence the “no alcohol” taboo for pregnant women…).

Thirdly, there may be social reasons that adopted children do poorly.  If they are told they are adopted, then they may spend their teenage years in rebellion and doubt. If they are not told they are adopted, perhaps the parents still behave differently towards them.

Finally, as I discussed previously, if you assume a (false) social concept is true you may inadvertently make it come come about. People who are believed to have low “genetic IQ” might have low observed IQ – but only because society (and they themselves) expect it to be true.

The most important part of all – disclaimer

In all cases, it is extremely important to remember that these effects are small – they are simply correlations in a whole bunch of causes and effects.  They do not predict what will happen for any given adoption, or indeed natural birth.  Some children do well in terrible circumstances, and others fritter away privilege.  Correlation does not imply causation.  IQ does not measure anything other than IQ – and itself only weakly correlates with intelligence.  What of happiness, life satisfaction, social responsibility, and so on?

See my previous posts and the comments therein for the references I collected on the subject: on race and IQ, and on the existence of races (accidentally about IQ).


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Social feedback and IQ

February 13, 2010 at 11:42 pm (science) (, , , , , , , , )

I recently discussed whether races exist and claimed that we should ignore apparent differences between people in the name of morality.  A comment about IQ differences made me realise that the main reason that we should ignore these differences is because there is a feedback between how we see the world, and how it is. This probably applies to lots of social phenomena, but I’m thinking about observed differences in IQ.

I was fairly ignorant about IQ research; it is not very evenly discussed in the media.  So it came as a shock to me to discover that social scientists have observed large differences in IQ between different groups of people.  After accounting for all the variables the scientists could think of, it still turns out that black people lag white (and white lag asians) by an appreciable amount.  The widespread conclusion is that this must have a genetic explanation.

On matters on measuring IQ, and what it means, I bow to the expertise of the experts.  However, a brief examination of their statistical methods I became concerned about the definition of “accounting for variables”.  Accounting for, say income, means looking at whether income correlates with IQ, and subtracting some multiple of income from IQ so that there is no longer any correlation.  (There are also more sophisticated methods trying to achieve a similar aim.)

The correction above works when the effects are “linear”. But IQ is not at all linear. The IQ of a parent affects the IQ of a child, via poor nutrition in the womb, lower access to education, larger family sizes, different childhood priorities, amongst other things. This makes it much harder to understand in IQ (although the more sophisticated methods mentioned above are designed to correct for these, to some extent).

But much worse than this is social feedback.  We know that perceived IQ can affect peoples actual IQ; if the world considers them stupid (say, relative to the average IQ), then this can make a person consider themselves stupid.  If someone considers themselves stupid then they are unlikely to persue an intellectual lifestyle.  This leads to a low measured IQ, which is passed onto children in a “viscious circle”.  On top of that, genuine discrimination can act and make the problem dramatically worse.

Can the model above “correct” for this sort of bias too?  It depends how the bias works in reality; but for a broad range of possibilities the answer is “No”.  It could even be mathematically impossible.

Lets assume from now on there is no genetic difference in IQ between two groups – which could be “black” and “white”.  We will also assume that investment in IQ is the same for both groups, and there is no unfair discrimination.  But IQ changes slowly; the IQ of a person’s parents affects their own IQ.

Without any investment IQ is at some minimum level Imin.  The initial IQ of the two groups is above this.  The investment level is called r, which controls the rate that IQ grows towards Imax, where it stops.  This is described by the following equation for “Change in IQ” (per generation) for group i :

This says that the change in IQ increases at rate r towards Imax (if r is positive) or towards Imin (if r is negative).  A genetic difference in IQ would mean that Imax was different between the two groups.  The standard methods would correctly calculate Imax in this case, and so determine if there were an innate difference in IQ.

Now we introduce social bias, which acts to change the rate r that IQ changes.  The bias b is proportional to how far IQ is from the average over all groups.  The bias parameter b controls how much a 1 point difference from the average IQ (over both groups) slows growth by.  Now the equation looks like this:

This is the same equation when b=0, but the growth rate is lower for IQ less than the average IQ (I with a line over it) when b>0.  Even with bias, things might not be too bad.  Here is what happens when we start the two populations close to each other:

IQ model with r=0.01, Imin=50, Imax=100, with similar starting IQs. Black line: Lower initial IQ group (initial IQ=75); Red line: Higher initial IQ group (IQ=80). Left: No bias b=0. Right: Small bias b=0.001. Time is in generations (about 20 years).

Without social bias, both IQs increase towards the same Imax.  With the social bias, the group with the lower initial intelligence increases less rapidly, but still goes to the same Imax.  The above methods would struggle, but eventually get the correct answer  for Imax in this case.

Now consider what happens when the initial difference is a bit larger.

IQ model with r=0.01, Imin=50, Imax=100, with different initial IQs. Black line: Lower initial IQ group (initial IQ=75); Red line: Higher initial IQ group (IQ=90). Left: No bias b=0. Right: Small bias b=0.001. Time is in generations (about 20 years).

In  this case with social bias, the IQ of the population that starts lower goes down!  The social bias leads to a growing difference in IQ between the two groups, and so the lower group “gives up” – perhaps surviving by focussing on avenues that don’t require a high IQ, or a high perceived IQ.

The above “correction” method fails entirely in this scenario.  Its extremely difficult to detect whether an observed difference in IQs is due to this sort of social feedback with the same Imax, or due to a real difference in Imax between the two populations.

Of course, this model is wrong.  Its far too simple and only captures some rough features of the truth about IQ.  But a huge class of models exhibit this sort of behaviour – called bistability – that can lead to two “genetically” identical populations ending up with different observed IQs, and we certainly don’t know enough to rule them out at the moment.  I found very little work trying to look into models for how IQ might change.  Until this possibility is ruled out, observed IQ differences should (scientifically!) be attributed to social feedback acting on historical differences.  If scientists don’t address the problem of social feedback, we can’t expect the world to!  Instead, if we assume that the observed difference is probably a genetic difference, this will increase the overall bias b and we may never know the truth.

Notes: I did a very brief literature search, detailed in comment number 2 of this post.  For completeness, this is repeated below.

The mathematical model is entirely arbitrary and comes from the simplest model that is bistable (which fortunately is a plausible first model in this case).  I don’t have any good references for models although Turchins 2002 book “Historical Dynamics” contains a nice summary of what level of complexity is required to produce which features.  “Accounting for variables” above means performing a linear regression (sometimes twice), which is a standard statistical procedure detailed in any statistics book.  Clearly for this criticism to be watertight, I need to establish that nobody has tried to fit dynamical models such as the one above to IQ data.  I don’t know whether anything like that exists in the literature (I bet it does somewhere) but it is not a standard feature of IQ studies.  I’ve seen it in other contexts, such as IQ of individuals over time, but not for social groups.  To be convincing, the above model would have to be replaced by one in which different individuals have different IQs, and real decision processes are used to establish how the bias behaves.  This sounds like a difficult, but not impossible task.

My IQ literature search: Nature recently featured a two-sided discussion on whether science should even study IQ in the context of race at all ( As you point out, twin studies show remarkable correlation between genetics and IQ. This is no surprise – we all believe that intelligence is inherited to some degree within families. Additionally, there is a consistent IQ difference of 4-5 points between the sexes (Lynn, Personality and Individual Differences
February 1998, 24:289-290; Blinkhorn, Nature 438:31-32 2005). There are huge continental differences of tens of points (nicely illustrated by, and large (10 point) geographical differences between areas of the single country of Italy (Lynn 2010, Intelligence 38:93-100). A summary of such results is given by (Rushton and Jensen 2005, Psychology, Public Policy, and Law 11:235–294).

These researchers look for differences and find them. The problem is the circular nature of intelligence: low IQ in parents leads to poor nutrition, low childhood support, poor education, and hence low IQ in children (this is called the “self-fulfilment hypothesis”). Again, the evidence that such a cycle exists is uncontroversial – whether it explains the whole distribution of Iq’s is strongly disputed. Much apparently “genetic” variation in IQ is explained by conditions in the womb (Devlin et al. . 1997, Nature 31;388(6641):468-71). Perceptions of IQ change behaviour and hence lifelong learning potential (The Confounding of Perception of I.Q. on a Measure of Adaptive
Behavior, Bobner, Ronald F et al – sorry this is a conference proceeding; also Sutherland and Goldschmid 1974, Child Development, 45:852-856). Early parenting factors are important for long term academic achievement (Englund et al. Journal of Educational Psychology, 2004), which means that family size and social class are going to be important too.

The consensus in the literature is that self-fulfilment does occur but nobody has modelled it in such a way that it accounts for all observed IQ differences (Jussim and Harber 2005, Personality and Social Psychology Review, 9:131-155; also

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When knowing something makes it true

February 7, 2010 at 2:03 pm (science) (, , , , , )

I recently posted a discussion on whether races exist.  I argued that races might exist, but that it wasn’t useful to use the word.

A comment by JL made me rethink my argument.  I haven’t changed my conclusions (notice how rarely this happens?  Its almost like we we use logic to justify our conclusions rather than to deduce our conclusions… but that is a different post entirely). But I have realised that I missed an extremely important point, one which changes the whole concept of scientific hypothesis.

Whether we believe a-priori that IQ differences between races exist can affect whether it is true.

Consider this.  Imagine that scientists say “differences in IQ between races might exist”.  We all see differences in IQ in the real world.  People say, “yes, this could be true”, and act accordingly.  Perhaps, all other things being equal, schools invest in children from the perceived higher IQ race (lets call them race 1).  Perhaps people give jobs to those people from race 1 preferentially – all other things being equal.  Of course, when someone from race 2 is better for the job, they get it.

This generation of children grow up; they are educated in the same way as their parents; they get jobs the same way as their parents.  They have children, and so it goes on.

Now imagine that IQ is determined by both race and upbringing.  People from race 2 have, on average, worse jobs.  They can’t afford high quality education.  So they do, in fact have lower IQ.  The scientists can measure this; the hypothesis is confirmed.  Breaking news!

Does this all sound familiar?  That’s because it already happened.  It is of course trivial; both scientists and non-scientists alike have seen this in action.  But the ramifications for social science are immense.  Normally science works by starting with a “null hypothesis” (how we believe the world might work) and comparing it to a “hypothesis” (something we want to test).  But in measuring IQ differences, our choice of “null hypothesis” can affect the truth of the hypothesis!  If we say, as above, that differences might exist in our null hypothesis, then they do.  If we instead choose the null hypothesis that all races are equal – and insist on this to the world at large – then, and only then, might we be able to measure that IQ differences do not exist.

In other words, the whole world is an experiment: by banning racism we have started a test of whether racial differences really exist.  Only time will tell if this is true or false, whether IQ differences exist are equalising.  But this is only possible since we chose to treat the world as if racial differences do not exist.

This conclusion could be reached on any social science problem where our measures are imperfect.  The problem lies in measures of IQ being biased to an unknown degree by upbringing; but finding a perfect measure is a hopeless task.  It means that science has to work intimately with policy; to measure people we have a scientific and moral obligation to treat all people as equal, because without doing so we can never know if they are.

Whether people really are equal is in some sense irrelevant.  They can only be equal if we assume that they are.

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