Book review: The Intelligence Paradox: Why the Intelligent Choice Isn’t Always the Smart One, by Satoshi Kanazawa.
This book is entertaining and occasionally thought-provoking, but not very well thought out.
The main idea is that intelligence (what IQ tests measure) is an adaptation for evolutionarily novel situations, and shouldn’t be positively correlated with cognitive abilities that are specialized for evolutionarily familiar problems. He defines “smart” so that it’s very different from intelligence. His notion of smart includes a good deal of common sense that is unconnected with IQ.
He only provides one example of an evolutionarily familiar skill which I assumed would be correlated with IQ but which isn’t: finding your way in situations such as woods where there’s some risk of getting lost.
He does make and test many odd predictions about high IQ people being more likely to engage in evolutionarily novel behavior, such as high IQ people going to bed later than low IQ people. But I’m a bit concerned at the large number of factors he controls for before showing associations (e.g. 19 factors for alcohol use). How hard would it be to try many combinations and only report results when he got conclusions that fit his prediction? On the other hand, he can’t be trying too hard to reject all evidence that conflicts with his predictions, since he occasionally reports evidence that conflicts with his predictions (e.g. tobacco use).
He reports that fertility is heritable, and finds that puzzling. He gives a kin selection based argument saying that someone with many siblings ought to put more effort into the siblings reproductive success and less into personally reproducing. But I see no puzzle – I expect people to have varying intuitions about whether the current abundance of food will last, and pursue different strategies, some of which will be better if food remains abundant, and others better if overpopulation produces a famine.
He’s eager to sound controversial, and his chapter titles will certainly offend some people. Sometimes those are backed up by genuinely unpopular claims, sometimes the substance is less interesting. E.g. the chapter title “Why Homosexuals Are More Intelligent than Heterosexuals” says there’s probably no connection between intelligence and homosexual desires, but there’s a connection between intelligence and how willing people are to act on those desires (yawn).
Here is some evidence against his main hypothesis.
The most interesting talk at the Singularity Summit 2010 was Shane Legg‘s description of an Algorithmic Intelligence Quotient (AIQ) test that measures something intelligence-like automatically in a way that can test AI programs (or at least the Monte-Carlo AIXI that he uses) on 1000+ environments.
He had a mathematical formula which he thinks rigorously defines intelligence. But he didn’t specify what he meant by the set of possible environments, saying that would be a 50 page paper (he said a good deal of the work on the test had been done last week, so presumably he’s still working on the project). He also included a term that applies Occam’s razor which I didn’t completely understand, but it seems likely that that should have a fairly non-controversial effect.
The environments sound like they imitate individual questions on an IQ test, but with a much wider range of difficulties. We need a more complete description of the set of environments he uses in order to evaluate whether they’re heavily biased toward what Monte-Carlo AIXI does well or whether they closely resemble the environments an AI will find in the real world. He described two reasons for having some confidence in his set of environments: different subsets provided roughly similar results, and a human taking a small subset of the test found some environments easy, some very challenging, and some too hard to understand.
It sounds like with a few more months worth of effort, he could generate a series of results that show a trend in the AIQ of the best AI program in any given year, and also the AIQ of some smart humans (although he implied it would take a long time for a human to complete a test). That would give us some idea of whether AI workers have been making steady progress, and if so when the trend is likely to cross human AIQ levels. An educated guess about when AI will have a major impact on the world should help a bit in preparing for it.
A more disturbing possibility is that this test will be used as a fitness function for genetic programming. Given sufficient computing power, that looks likely to generate superhuman intelligence that is almost certainly unfriendly to humans. I’m confident that sufficient computing power is not available yet, but my confidence will decline over time.
Brian Wang has a few more notes on this talk
This review by Cosma Shalizi of James Flynn’s book What Is Intelligence? provides some interesting criticisms of Flynn (while agreeing with much of what Flynn says).
Shalizi’s most important argument is that Flynn and others who attach a good deal of importance to g haven’t made much of an argument that it measures a single phenomenon.
After a century of IQ testing, there is still no theory which says which questions belongs on an intelligence test, just correlational analyses and tradition.
Flynn and others have good arguments that whatever g measures is important. But Shalizi leaves me with the impression that the only way to decide whether it’s a single phenomenon is to compare its usefulness to models which describe multiple flavors of intelligence. So far those attempts that I’ve looked at seem underwhelming. Maybe that means trying to break down intelligence into components which deserve separate measures isn’t fruitful, but it might also mean that the people who might do a good job of it have been scared away by the political controversies over IQ.
HT Kenny Easwaran.
Book review: What is Intelligence?: Beyond the Flynn Effect by James Flynn
This book may not be the final word on the Flynn Effect, but it makes enough progress in that direction that it is no longer reasonable to describe the Flynn Effect as a mystery. I’m surprised at how much Flynn has changed since the last essay of his I’ve read (a somewhat underwhelming chapter in The Rising Curve (edited by Ulric Neisser)).
Flynn presents evidence of very divergent trends in subsets of IQ tests, and describes a good hypothesis about how that divergence might be explained by increasing cultural pressure for abstract, scientific thought that could create increasing effort to develop certain kinds of cognitive skills that were less important in prior societies.
This helps explain the puzzle of why the Flynn Effect doesn’t imply that 19th century society consisted primarily of retarded people – there has been relatively little change in how people handle concrete problems that constituted the main challenges to average people then. He presents an interesting example of how to observe cognitive differences between modern U.S. society and societies that are very isolated, showing big differences in how they handle some abstract questions.
He also explains why we see very different results for IQ differences over time from what we see when using tests such as twin studies to observe the IQ effects of changes in environment on IQ: the twin studies test unimportant things such as different parenting styles, but don’t test major cultural changes that distinguish the 19th century from today.
None of this suggests that the concept of g is unimportant or refers to something unreal, but a strong focus on g has helped blind some people to the ideas that are needed to understand the Flynn Effect.
Flynn also reports that the rise in IQs is, at least by some measures, fairly uniform across the entire range of IQs (contrary to The Bell Curve’s report that it appeared to affect mainly the low end of the IQ spectrum). This weakens one of the obvious criticisms of David Friedman’s conjecture that modern obstetrics caused the Flynn Effect by reducing the birth related obstacles to large skulls (although if that were the main cause of the Flynn Effect, I’d expect the IQ increase to be largest at the high end of the IQ spectrum).
It also weakens the inference I drew from Fogel’s book on malnutrition. Flynn does little to directly address Fogel’s argument that the benefits of improved nutrition show up with longer delays than most people realize, but he does report some evidence that the Flynn Effect continues even when the height increases that Fogel relies on to measure the benefits of nutrition stop.
Flynn reports that the Flynn Effect has probably stopped in Scandinavia but hasn’t shown signs of stopping in the U.S. His comments on the future of IQ gains are unimpressive.
There are a few disappointing parts of the book near the end where he wanders into political issues where he has relatively little expertise, and his relatively ordinary opinions are no better than a typical academic discussion of politics. In spite of that, the book is fairly short and can be read quickly.
One interesting experiment that Flynn discusses tested whether students preferred one dollar now or two dollars next week. The results were twice as useful in predicting their grades as IQ tests. Flynn infers that this is a test of self control. I presume that is part of what it tests, but I wonder whether it also tests whether the students were able to realize that the testers’ word could be trusted (due to better ability to analyze the relevant incentives? or due to a general willingness to trust strangers because of how the ways they met people selected for trustworthy people?).
Book review: A Farewell to Alms: A Brief Economic History of the World by Gregory Clark
This book provides very interesting descriptions of the Malthusian era, and a surprising explanation of how parts of the world escaped Malthusian conditions starting around 1800. The process involved centuries of wealthier people outreproducing the poor, and passing on traits/culture which were better adapted to modern living. This process almost certainly made some contribution to the industrial revolution, but I can’t find a plausible way to guess the magnitude of the contribution. Clark is not the kind of author I trust to evaluate that magnitude.
His arguments against other explanations of the industrial revolution are unconvincing. His criticisms of institutional explanations imply at most that those explanations are incomplete. But combining those explanations with a normal belief that knowledge/technology matters produces a model against which his criticisms are ineffective. (See Bryan Caplan for more detailed replies about institutional explanations).
He makes interesting claims about how differently we should think about the effects in Malthusian world of phenomena that would be obviously bad today. E.g. he thinks the black plague had good long-term effects. He made me rethink those effects, but he only convinced me that the effects weren’t as bad as commonly believed. His confidence that they were good depends on some unlikely quantitative assumptions about benefits of increased income per capita, and he seems oblivious to the numerous problems with evaluating these assumptions. His comments in the last few pages of the book about how little average happiness has changed over time leads me to doubt that his beliefs are consistent on this subject.
While many parts of the book appear at first glance to be painting a very unpleasant picture of the Malthusian era, he ends up concluding it wasn’t a particularly bad era, and he describes people as being farther from starvation than Robert Fogel indicates in The Escape from Hunger and Premature Death, 1700-2100. Their ability to reach somewhat different conclusions by looking at different sets of evidence implies that there’s more uncertainty than they admit.
He does a neat job of pointing out that economists have often overstated the comparative advantage argument against concerns that labor will be replaced by machines: horses were a clear example of laborers who suffered massive unemployment a century ago when the value of their labor dropped below the cost of their food.
Book Review: Race, Evolution, and Behavior: A Life History Perspective by J. Philippe Rushton
Rushton has a plausible theory that some human populations are more k-selected than others. He presents lots of marginal-quality evidence, but that’s no substitute for what he should be able to show if his theory is true.
Much of the book is devoted to evidence about IQs and brain sizes, but he fails to provide much of an argument for his belief that k-selected humans ought to have higher intelligence. It’s easy to imagine that it might work that way. But I can come up with an alternative based on the sexual selection theory in Geoffrey Miller’s book The Mating Mind that seems about as plausible: r-selected humans have more of their reproductive fitness determined by success at competition for mates (as opposed to k-selected humans for whom child support has a higher contribution to reproductive fitness). Since The Mating Mind presents a strong argument that human intelligence evolved largely due to such competition for mates, it is easy to imagine that r-selected humans had stronger selection for the kind of social intelligence needed to compete for mates. Note that this theory suggests the intelligence of k-selected humans might be easier to measure via standardized tests than that of r-selected humans.
Rushton’s analysis of the genetic aspects of IQ makes the usual mistake of failing to do much to control for the effects of motivation on IQ scores (see pages 249-251 of Judith Rich Harris’s book The Nurture Assumption for evidence that this matters for Rushton’s goals).
He also devotes a good deal of space to evidence such as crime rates where it’s very hard to distinguish genetic from cultural differences, and there’s no reason to think he has succeeded in controlling for culture here.
Rushton mentions a number of other traits that are more directly connected to degree of k-selection and less likely to be culturally biased. It’s disappointing that he provides little evidence of the quality of the data he uses. The twinning data seem most interesting to me, as the high twin rates of the supposedly r-selected population follow quite clearly from his theory, it’s hard to come up with alternative theories that would explain such twinning rates, and the numbers he gives look surprisingly different from random noise. But Rushton says so little about these data that I can’t have much confidence that they come from representative samples of people. (He failed to detect problems with the widely used UN data on African AIDS rates, which have recently been shown to have been strongly biased by poor sampling methods, so it’s easy to imagine that he uses equally flawed data for more obscure differences). (Aside – the book’s index is poor enough that page 214, which is where he lists most of his references for the twinning data, is not listed under the entry for twins/twinning).
Rushton occasionally produces some interesting but irrelevant tidbits, such as that Darwin “affirmed human unity” by ending the debate over whether all humanity had a common origin, or that there’s evidence that “introverts are more punctual, absent less often, and stay longer at a job”.
Edward M. Miller has a theory that is similar to but slightly more convincing than Rushton’s in a paper titled Paternal Provisioning versus Mate Seeking in Human Populations.
There’s a report that the Flynn effect has stopped fairly abruptly in the industrialized countries. The new data suggest a more sudden halt than nutritional theories would predict. I’m uncertain what to make of this.
Book Review: The Escape from Hunger and Premature Death, 1700-2100 by Robert Fogel
This book presents good arguments that hunger was a major cause of health problems everywhere a century ago, and that the effects last long enough that even the richest countries are still suffering from problems caused by hunger. His arguments imply that experts persistently underestimate improvements in life expectancy, and even with little improvement in medical technology life expectancy will improve a good deal because people born today have much better nutrition than today’s elderly had as children.
This goes a long way toward explaining the Flynn effect (even though the book doesn’t mention Flynn or IQ). It correctly implies the biggest intelligence increase should be seen at the low end of the IQ range, unlike a number of other interesting theories I’ve come across.
Another peculiar fact that the book helps to explain is the high frequency with which the tallest presidential candidate wins. Fogel’s arguments that height has been one of the best indicators of health/wealth suggest that this is not an arbitrary criterion (although it is probably a selfish I-want-to-ally-with-a-winner strategy that may be obsolete).
The book is mostly non-idealogical, but occasionally has some good political arguments (page 42):
government transfers were incapable of solving the problems of beggary
and homelessness during the eighteenth and much of the nineteenth centuries,
because the root cause of the problems was chronic malnutrition. … At
the end of the eighteenth century British agriculture, even when supplemented
by imports, was simply not productive enough to provide more than 80 percent
of the potential labor force with enough calories to sustain regular manual
Readers may be surprised that I have not emphasized the extension of health insurance policies to the 15 percent of the population not currently insured. The flap over insurance has more to do with taxation than with health services. … Most proposals for extending health insurance involve taxing their wages for services they already receive.
See also Mike Linksvayer’s comments.