Now if one was really looking to be scientific or skeptical rather than merely seeking to affirm membership in a certain social/political group this claim should set off two sets of alarm bells. The first set because it’s such a convenient thing to be true. After all if science has proven their aren’t really races then you don’t have to worry about troubling questions like the relationship between race and intelligence so you can go on thinking of yourself both as a good liberal¹ and a critical thinker. Indeed, as soon as one acknowledges the notion of race then the sheer number of correlations between racial background and various gene sequences makes it downright absurd to insist that there isn’t some statistical difference in genetic predisposition to intelligence between different races². Of course we have good evidence that any such correlation will be small compared to environmental effects and individual differences and (to my knowledge) have no particular reason to suspect that the result won’t be ‘favorable’ for traditionally disadvantaged groups but subtle qualifications like this won’t eliminate the suspicion the admission draws. So like belief in an afterlife, trust in homeopathic remedies, or credence in the Loch Less monster there are obvious reasons people would believe the claim regardless of it’s truth giving us cause to be suspicious.

The other alarm bell is the fact that this claim contradicts what we see so plainly with our eyes. People from difference regions of the world look different. People with an African background have a different skin color than those from a European or Oriental background. Kenyan runners seem to do disproportionately well in marathon races³ and hair color/type highly correlates with what part of the world your family comes from. These differences are too obvious for the people claiming that scientifically race doesn’t exist to simply brush off so they try to explain it by saying that there is indeed a socially constructed notion of race it’s simply the genetic notion that doesn’t exist.

This response can’t possibly fly. The differences in skin, eye and hair color aren’t socially constructed. They are determined (largely) by your genetics. It’s a simple and obvious fact that there are substantial correlations between one’s genetic makeup and where your ancestors come from and these genetic differences are surely not only superficial. A child’s risk of sickle cell anemia is highly dependent on the parent’s racial background and we are slowly discovering that race significantly alters one’s susceptibility to many other afflictions and the probable effectiveness of various drugs. In light of this facially compelling proof of the existence of racial genetic variation what kind of scientific result could possibly be described as showing that there is no such thing as race?

Well the true scientific claim in the background is that the boundaries we draw between various racial groups are arbitrary and purely a matter of social construction. In other words if we analyzed everyone’s genes they wouldn’t group into a small number of tidy piles and certainly not ones that match our (culturally) standard categories like black, white, oriental, Indian, etc.. Instead of black/white/oriental/Indian/Native American it might make just as much sense to have Native American & Oriental/White & Indian/Northern African/South African instead. These racial categories might not be as useful in describing the social and cultural fault lines in American society but they (or some alternative like them) would be no less correlated with various genetic risks and just as useful in medical recommendations.

While it’s important to point out that we draw racial boundaries in (genetically) arbitrary places this no more shows that scientifically speaking race doesn’t exist than the fact that light comes in a continuous spectrum shows that scientifically speaking color doesn’t exist. Indeed, we know that different cultures break apart the visible spectrum in different ways but that doesn’t mean that science disproves the fact that blue and green are distinct colors. To illustrate just how much this claim distorts the truth just imagine someone insisting that scientifically speaking baldness didn’t exist because just how few hairs you need to qualify as bald is culturally determined.

It’s bad enough when scientists advance this claim but I understand that they may be trying to balance accuracy with other concerns such as their career, combating racist distortions of the truth in soundbites, and keeping the trust of various political and social coalitions. I still think that in the long run the failure of scientists to reign in this kind of political pandering risks compromising the public’s trust in their objectivity but at least I have some sympathy with their misrepresentation. However, it particularly galls me when skeptical groups participate in this kind of distortion while claiming to exist primarily to oppose just this kind of wishful thinking.

However, science is nothing but the process of deciding what you think is true and if people really understood science in this way I think we’d have a lot less confusion about global warming. There is nothing different about the way disputes in science are settled than the way you might settle an argument with your friend about whose route from work to the bar is faster (suppose you have serious money riding on the question so it really matters). So let’s just consider what you’d likely do to decide the bet and see how that would apply in the scientific context. I’m using climate change here as a particular example but virtually everyone who isn’t close to the scientific community is equally guilty as this disconnect underlies many of the unreasonable public expectations about science.

When the argument begins you’d both point out factors that give credence to your route being the faster one based on existing knowledge. Often that alone will be enough to settle the question. If your friend reminds you about the new stoplights the city added on your route recently you might well decide he’s almost surely right and it’s not worth putting to the test. Or maybe his arguments are strong enough that you’d demand very favorable odds to make another bet on your route but you are still unsure enough you think it’s worth testing. (Or you could have the better argument or neither of course).

The next thing you would do do settle the question if debate persisted would be to perform an experiment. You’d probably suggest that you each drive your own routes to the bar that night and see who gets their first. Of course this kind of rough and ready check is far from an ideal controlled study with powerful statistical analysis but whether or not you the experiment convinces you depends on not only it’s quality but also the strength of the results and your prior judgments of plausibility.

In other words if your friend’s remark about the stop lights made you think he was probably right and then he reached the bar in 15 minutes while you took over 30 you’d probably find that quite persuassive and take the issue to be settled. If the results were closer, say 23 vs. 30 minutes and you know your friends a calm steady driver you might still be convinced despite the lack of experimental control for driver differences but if you know he’s highly competitive and given to speeding you might insist on having a mutual friend drive both routes to control for driver speeding. Still, as long as the results aren’t in conflict with your prior expectations, e.g., it’s the shorter, fewer stops route that is coming in as faster you’d probably be convinced without any need to throw powerful statistical methods at the question even though losing cost you a big chunk of change.

On the other hand the very same experimental results probably wouldn’t be enough to convince you if they were in radical conflict with your prior knowledge about the workings of traffic and driving. For instance if google maps said your route was shorter, had a higher speed limit, fewer stops and less traffic you’d probably suspect that the couple of tests you’d done weren’t convincing enough and demand many trials with a test of statistical significance (or compelling theoretical justification of why your route might be slower…say being told all your turns are unprotected left turns while he has right turns) before you agreed to pay up on the bet. The lower the prior probability you assign to the observed outcome and the closer the observed average times are the more statistical rigor you would insist on before paying up.

Importantly, while better controlled experiments with more powerful statistical techniques (if understood) are always better it doesn’t mean other tests can’t add to the weight of evidence. Even if you and your buddy got a third party to do many trials and used tests of statistical significance if your buddy Bob tells you he drives your way and always gets their after his wife who drives your friends way it still adds to the strength of your case despite the low number of trials and uncontrolled variables like the driver (just much less so).

So let’s take this back to the climate science situation. Would it be even better if the CRU scientists had used more powerful statistical techniques correctly? Sure. But all experiments are imperfect but they can still provide valuable evidence just like the initial tests or Bob’s anecdote in my story. Not only is it not bad for scientists to publish results from imperfect experiments it’s important for them to do so as long as other scientists aren’t being mislead about the strength of the tests/results (the scientific community seems unsurprised about the underlying statistical techniques used so it’s reasonable to assume they probably had a good sense of the strength of the evidence published). In fact often it’s preferable for scientists to publish imperfect experimental results with non-ideal methods of analysis and invest their time in new experiments instead of investing the time/energy to apply more powerful mathematical techniques to a particular result. For instance I think it was probably a good decision on Galileo’s part to let the crude experiments with balls on inclined planes and simple timers convince him objects all accelerate at the same rate under gravity than to insist on waiting for fancy statistics and running many tests. That way he could say important things about the heliocentric model as well.

Ultimately what’s wrong with the expectation that papers giving evidence on matters of enormous public concern always live up to some kind of school book ideal of scientific experimentation is that it makes a single paper stand in for the mountains of accumulated evidence. I mean complaining about all these minor ‘imperfections’ in climate research is like arguing that we shouldn’t assume it takes longer to drive from New York to LA than from Chicago to LA because the people who had made the drives never had a proper control. If you have shitloads of distinct pieces of evidence for a claim (like many people saying 2 days for Chicago LA and 3 days for NY LA) which is supported by a sound theoretical justification (NY is farther away) demanding the tests be redone with the right formal methods (controls/better statistics/etc..) would make no noticeable difference in your (rational) confidence of the claim.

Equally problematic is the background assumption that most public criticisms of consensus scientific results tend to ignore the critical importance of prior probabilities. For instance if there was one thing I think that most people on both sides of the climate debate ignore (or glass over) is the high prior probability we should assign to anthropogenic global warming. Basic thermodynamic considerations tell us that absent some unexpected large systematic effect of CO2 emissions to create cooling it must cause global warming and that human emissions are large enough that we should expect them to give rise to the level of warming observed. This isn’t some crazy computer model or complex bit of climate science subject to judgment calls. Just look up a few basic values for light absorption by CO2, strength of solar radiation and the (directly observed by satellite) level of reflected solar radiation and you can work it out on a single piece of paper.

So it’s the guys who want to deny anthropogenic global warming who have the burden of proof to convince us there is some unexpected process that gives rise to a seemingly paradoxical absence of anthropogenic global warming. Given this context merely suggestive experimental results supporting the accuracy of this simple model are enough to up our confidence from “likely” to “almost certain.” These scientists should no more waste time polishing these experiments than they should spend money rigorously verifying the earth is round. In other words we already have SOOO much evidence that making this paper a bit more persuasive wouldn’t budge our rational confidence.

A similar point applies to resistance to things like food irradiation or other all natural type movements. As with climate change the prior probabilities are ignored and the burden is shifted from the person suggesting the possibility of novel unexpected mechanisms to those who are simply claiming that things work the way we reasonably expect them to work.

For starters I think it’s fairly irresponsible for a publication of the AAAS to offer a statement like this as unqualified commentary

The results “essentially confirm” earlier studies–and they should finally put to rest the idea that girls aren’t going into technical fields because they can’t do the math, says Ann Gallagher, a psychologist who studies testing at the Law School Admission Council in Newtown, Pennsylvania.

The casual reader will certainly understand this claim as saying that women are not innately disadvantaged relative to men in technical fields. Yet this research doesn’t even come close to proving this claim and in light of broader trends in male/female school performance that came up previously this result is perfectly compatible with girls being innately statistically worse at doing mathematics. Given that girls tend to outperform boys generally in academics before college we must either conclude that girls have greater innate intellectual talent or that some other factor, such as a greater willingness to study or pay attention to the teacher, accounts for this general academic superiority and must be accounted for to accurately compare innate ability. While the former hypothesis shouldn’t be dismissed out of hand the later one seems more likely¹ meaning that this study is essentially useless in comparing the innate abilities of boys and girls in math/science. While the authors of the research article might have reasonably expected their audience to be aware of the generally higher performance of girls in pre-college schooling leaving these considerations out of interpretive articles for the lay reader is at best unacceptable sloppiness.

True, the sentence I quoted is technically true. Girls have the literal capability to do technical fields but the obvious implication is that they have statistically equal innate ability which simply isn’t demonstrated by this piece of research. Unfortunately the article on ars is no better.

Thus, the gender gap in math performance seems to be insignificant in grade school, which is good news. Unfortunately, that does not help explain why the gender gap widens later in life. It is possible that pressure from society eventually catches up to women and makes it difficult to stay in certain fields, as the problem certainly doesn’t seem to be innate intellectual capability.

Once again this is a technically correct claim that is nevertheless extremely misleading. For starters, just like the piece in Science NOW this remark plays to the false idea that there is a sharp well-defined distinction between nature and nurture while also implying that whatever social effects cause the gender bias in the sciences must be negative. It’s equally possible that women are relatively more likely to be drawn away from math/science by other interests (child rearing, law, other non-technical pursuits). Even discouraging social pressures aren’t necessarily bad. If women leave technical subjects because they find math/science nerds less hot or simply don’t like hanging out with them that’s not a harm against women². Moreover, there are a vast number of explanations that don’t fall clearly on either the socialization nor innate differences side, e.g., suppose women are innately less rebellious and more eager to please authority figures and thus our educational system is more likely to snuff out their interest and ability to think critically. Fallaciously suggesting that social effects must be harmful barriers to women is almost as bad as what the sexist individuals on the nature side of the debate do when they conflate evidence of innate differences with female incapacity.

As if this wasn’t enough the arstechnica article casually dismisses the results from the article about greater male variation in performance and the Science NOW article ignores them entirely. Interestingly the study found that different races favored different genders at the high end of the tests, e.g., more Asian girls than Asian boys scored at the very high end while more white boys than white girls scored at the top. Still, while both ars and the original journal article dismiss the effects found as small in a discipline requiring mathematical ability at the 99th percentile these data suggest we should find 67% women and only 33% men. Pointing out that some engineering fields have only 15% women as the journal article does only tells us there are other factors at work but it doesn’t downplay the significance of this one. In fact given that math and physics Ph.D.s are probably almost exclusively chosen from the top half percent in mathematical ability this effect on it’s own might account for much of the observed gender gap. Moreover, in combination with the normal tendency of people to clump with others of the same gender and the role of friends/acquaintances in determining classes and majors it’s certainly plausible that even relatively minor differences in gender ratio could be magnified into something larger even if everyone acted in a fair and reasonable fashion.

Ultimately, however, any conclusions you might have been tempted to draw from the results in this article are undone by the fact that none of the questions asked in the standardized tests required serious thought. I stand with the researchers in bemoaning the sorry state of standardized testing in pre-college education but unfortunately for them this undermines any conclusions they might wish to draw about gender and innate ability. Quite simply how well you can memorize the quadratic formula and plug in numbers is totally irrelevant to your ability to do higher mathematics. I’m about to get my Ph.D. in mathematics despite being almost held back a grade because I wasn’t fast enough at my multiplication tables and regularly losing a fair number of points on math tests in high school because I didn’t memorize their stupid rules.

Of course there is nothing here to suggest that the gender differences we see in technical fields are the result of any innate differences but this research certainly doesn’t show otherwise so it shouldn’t be presented as doing so. Frankly I’m quite disturbed at the persistent bias in lay scientific articles about this subject. While I wholeheartedly agree about the importance of disabusing the public about their simpleminded stereotypes about gender differences and strongly support efforts to root out remaining discriminatory treatment covering up the complexities of the issue as these articles do feels too close to being propaganda for the desired answer for my taste.

There is certainly a kernel of truth in these stories as in most of the misleading articles New Scientist publishes. However, these articles make it sound as if we are going to run out of various rare earth metals the way you might run out of toilet paper at home, i.e., we used it all up and have to make do without it. Indeed the article in the Asimov magazine explicitly analogizes this ‘crisis’ to a science fiction scenario of a world without usable iron. True, the prices of many rare earth metals and even Zinc are rising rapidly and for many of them we are currently using them faster than they are being mined. But does that mean we will ‘run out’ or even have to give up our flat screen TVs with Indium based transparent transistors or fancy new Intel CPUs with Hafnium based high-k dielectric? Certainly not. Moreover, we most certainly won’t ‘run out’ of these metals the way these stories suggest.

The idea that the Indium on Earth is just going to be used up in 2017, Terbium in 2012 and Zinc in 2037 is just absurd from both a geological and economic point of view. As an economic matter the market won’t simply let us keep increasing our consumption until we suddenly run out. Rather, when demand increases relative to supply the price rises and decreases consumption. If companies really believed zinc was going to simply run out in 2037 do you think they would be selling it cheaply enough to make it cost effective to make pennies with it or use it in many other trivial ways? There isn’t any great crisis ahead, merely a rise in price for these metals that will cause other metals to be substituted where possible and wasteful uses to be eliminated (eliminate the damn penny!) while essential uses (LCD displays, CPUs) continue. If you don’t believe me put your money where your mouth is. If you think we will simply run out of Terbium in 4 years buy up some Terbium or Terbium futures and you’ll make a fortune.

It’s an even more absurd proposal from a geological perspective. Neither Indium or Gallium occurs naturally in high concentrations in any mineral. Rather small quantities of both these minerals are isolated from Zinc deposits (Sphalerite) and in the case of Gallium Bauxite and coal as well. Already then something seems fishy about the suggestion we would run out of Indium in 9 years but wouldn’t run out of Zinc for another 20 years after that. Surely companies aren’t going pull all of the worlds Zinc deposits out of the ground so they can isolate the 50ppm of of Gallium and then pay to store the Zinc for another 20 years. Moreover, some simple math shows how absurd the suggestion is that we will simply run out of Zinc.

Zinc makes up .0004% of the Earth’s crust and the continental crust in turn accounts for .374% of the earth total mass. Wikipedia tells us the Earth has a mass of 5.97 * 10²⁴ kilograms and doing the math gives us 8.910¹³ metric tons of Zinc in the continental crust. Given a current consumption rate of about 7.110⁶ metric tons a year we could continue at this rate for 10 million years before we depleted the Zinc in the crust.

Of course we can’t efficiently extract anywhere near all the Zinc in the crust and it’s the notion of efficient extraction that’s central to this issue. Unlike the toilet paper you keep in your bathroom mineral deposits aren’t all equally easy to extract until you suddenly run. If we were willing to pay more for minerals like Zinc companies would start mining locations that were formerly unprofitable. Conversely if the amount of Zinc we have sitting around in storage shrinks the price of Zinc will rise and consumption will decrease. Likely the numbers quoted in the New Scientist article describe the point at which current rates of usage will deplete the proven reserves of these various minerals in the ground. In other words they tell us how long these metals would last if mining companies didn’t bother to go look for more, didn’t start extracting ore from regions currently unprofitable when prices increased and people kept using them at the same rate despite increased scarcity. We might as well assume the Martians are stealing our metal with ray guns to predict future catastrophic shortages. Now I’m just guessing at what these numbers are supposed to actually mean (the articles couldn’t be bothered to tell us that) but there is no doubt that none of these articles gives cause to be anxious.

At least this is (more or less) the notion of the Singularity as popularized by Vernor Vinge and Ray Kurzweil. For more details I recommend reading Vinge himself or checking out one Kurzweil’s many interviews and talks (audio) as well as his webpage. These are certainly two very smart individuals who have the rare ability to look beyond the specifics and take a fairly clear headed look at how technology will transform society. But smart doesn’t mean infallible and predicting the future is a notoriously difficult business.

While I used to find the arguments for the singularity convincing I’m now much more skeptical. In particular it seems the argument for the singularity rests on a misconception of intelligence. I mean it seems obvious to us that if someone was significantly smarter than us they would be significantly better at designing intelligent computers or human augmentation. But that’s because we both assume that intelligence is some kind of fully general ability to solve problems and conflate intelligence with technical skill and achievement. After all we rarely see people’s raw IQ scores so we tend to simply call people intelligent if they are especially capable in technical fields or other academic endeavors. However, while intelligence is certainly helpful much of what makes for a good scientist or engineer is their store of accumulated experience, both personal and distilled into formal education.

While it does seem that people’s ability at a wide range of reasoning tasks is substantially correlated this doesn’t mean talking about intelligence makes sense for anyone but biologically natural humans. It seems quite plausible that there is no such thing as general reasoning ability. Rather there are only heuristics applicable to certain types of problems, e.g., ability to do mental rotations, solve crosswords, recognize objects etc.. Yet if so there is no reason to believe that there is any good heuristic for designing good heuristics, in fact it seems downright unlikely. Thus just because we were able to find a collection of heuristics that give rise to something better at math and play chess than us doesn’t mean we should expect it to have a substantially easier time discovering better heuristics for the next generation. Sure, we will probably be able to create beings who can remember more numbers, do CAD drawings in their heads and so forth but the singularity requires an exponential (or at least super-linear) increase in capability over time so mere elimination of minor inefficiencies we have at AI design isn’t sufficient.

Even in mathematics people primarily reason inductively. We don’t blindly search for a formal proof, rather, we try the same techniques we’ve seen work in ’similar’ problems in the past and attempt minor modifications. In other words what makes someone a good mathematician is largely their mental collection of heuristics they use to approach problems. While continued miniaturization of computer chips might enable AI to reduce the time it takes to do mathematics pure increases in computational speed a may already be near the physically practical limit (though going 3D and using light should eventually give a few more orders of magnitude) and certainly this effect wouldn’t be sufficient to create the singularity. Thus it seems the singularity requires a sequence of exponentially increase sequence of better and better heuristics to guess the true theory based on limited data. In other words a more effective form of scientific induction.

In other words people currently use some heuristic to guess at a rule underlying a set of observations. We make some finite number of observations about disease occurring near wells near sick families and hypothesize that disease can be spread through the water. We observe some examples of current generated by metal exposed to various frequencies of light and hypothesize that light must come in quantized units. The singularity seems to require that not only is there a heuristic that lets us make equally effective guesses at the true theory based on less information but that there is an exponentially increasing sequence of such heuristics. Moreover, it would be necessary that each heuristic can discover the next in roughly the same amount of time despite the substantially greater performance each subsequent heuristic requires. Frankly, I find this somewhat implausible.

Frankly, I’m just amazed that this has been studied. To be fair it was probably a result noticed during a more general study of the subject but it’s still amusing to think that some poor grad student’s job was to document people’s farts and collect samples. Makes me glad I’m not doing an experimental science.

On the plus side that grad student had an interesting answer when people asked what they did but I don’t know if it was a plus for getting dates. It would also make for some amusing work experience on a resume.

I wonder if they have this information up on wikipedia. This is the sort of totally useless information that is important to record and catalog. Both to protect future generations of graduate students and to settle drunken bets.

Emma McGrattan, the senior vice-president of engineering for computer-database company Ingres–and one of Silicon Valley’s highest-ranking female programmers–insists that men and women write code differently. Women are more touchy-feely and considerate of those who will use the code later, she says. They’ll intersperse their code–those strings of instructions that result in nifty applications and programs–with helpful comments and directions, explaining why they wrote the lines the way they did and exactly how they did it.

This remark is shortly followed by an equally over broad statement to the effect that men are too interested in showing off how clever they are to write readable code. Now while it’s certainly possible that (of the people who program) women are somewhat more likely to write better code (though I know of no evidence to this effect) this article adopts the sweeping tones of stereotype and bias to suggest that individual hiring decisions should favor women on these grounds. It is exactly this sort of unwarranted assumption that group characteristics make a difference even after individual factors (like say looking at previous code they have written, interviewing them) that distinguishes outright prejudice and discrimination from mere scientific hypothesizing. Well that plus the tendency to offer totally unsupported explanations that play into gender stereotypes (women are more touchy-feely).

If the conclusion had been the other way around and suggested that women were too touchy-feely to program well this vice-presidenty would probably quickly find themselves out of a job. This is why I blame faux feminism for this sort of attitude. It is exactly the confusion of feminism with the idea that we should cheer on women like they were a sports team that creates the impression this kind of harmful remark is reasonable. Despite obviously validating the idea that we should hire people based on unproven stereotyped generalizations about their gender instead of individual accomplishment this remark is seen as ‘ok’ because it favors hiring women. Another good example of this effect is how acceptable it has become to advocate for single sex education when coached in terms of helping women, even when the underlying theory would make Larry Summers cringe.

Now if the only harm these attitudes inflicted was a bit of discrimination against men you might reasonably think it wasn’t a huge deal². However, you simply can’t train people to accept traditional gender stereotypes and discriminate based on those only when it gives a certain kind of result. If you convince people to hire women for coding jobs because they are more touchy-feely you can’t avoid the fact that they are going to turn around and favor men for jobs in math, physics or the military where being touchy-feely is perceived as a negative (perhaps with some justification). Hell, even being good team players and leaving clear directions are going to be negatives for some job.

In fact I think what we are seeing right now is the harm of being touchy-feely about gender equality. The point is that deciding what views/people are good based on who sounds like they are on your side might have been fine when discrimination was primarily overt but when the primary concern is the affect of societal gender roles and semi-conscious stereotypes the greatest danger comes from the people encouraging that type of thinking and behavior, especially if they do so while claiming the `feminist’ moral high ground.

The three fallacies that I’ve noticed are the following.

1. The confusion of small statistical differences with our intuitive notion of a valid generalization.
2. The belief that innate factors are somehow set in stone while cultural or social effects are temporary and thus justify different inferences.
3. Failure to appreciate the power of conditionalization.

The first fallacy is pretty obvious but very hard to correct. Most people don’t have good quantitative skills, much less experience with statistics so tend to translate claims about small statistical differences into simple stereotypes. Even people who should know better often don’t apply their quantitative training to this domain. This is why you see people respond to claims about innate statistical differences as if someone had claimed that women simply couldn’t do math and science. Once you get beyond this point you tend to run into the second fallacy.

Unfortunately both sides in the nature vs. nurture debate encourage the notion that innate differences are simple matters of ability and social effects are easily overcome issues of confidence. This leads to the fallacious conclusion that somehow innate differences call for a policy of denying women positions in math/science while nurture effects simply call for more encouragement. This couldn’t be further from the truth. One of the largest determiners of math/science achievement is interest and any possible innate differences could just as easily be differences in interest as they are differences in ‘ability.’ Moreover, it’s totally unclear to what extent differences in experience and exposure at young ages make. Thus it’s easily possible that the current gender gap could be the result of some innate difference that makes girls less interested in science as currently presented but small tweaks in science education could grab their attention. Alternatively it’s surely possible that the gender gap is the result of deep cultural forces that are nearly impossible to change and can’t be compensated for by our educational system, e.g., the type of behavior that attracts male romantic interest biases girls away from math and science. Quite simply there is no simple moral or effect on our judgment that one answer to the nature/nurture debate should have as opposed to the other.

The third and last fallacy is perhaps the most problematic, particularly in light of the second fallacy. People tend to assume that if women statistically tend to be worse at task X this is reason to lower their estimate of some particular woman’s (perhaps themselves) ability at task X. Counterintuitively this just isn’t the case. Conditionalizing on the standard information we gather about virtually anyone we meet can eliminate or even reverse the effect that gender should have on our estimation of someone’s ability. If you’ve taken any probability courses you’ve probably seen this point made using the example of the famous berkeley discrimination case. If you haven’t let me give you a simple example.

It’s undoubtedly true that statistically men are worse at nursing than women. This isn’t a claim about innate ability just a simple observation following from the fact that more women than men are nurses hence fewer men have received nursing training. Thus if you know nothing about someone other than their gender you should expect men to have a lower nursing ability. However, this doesn’t entail that you should trust male nurses less than female ones. Nor does it entail that men who aren’t nurses are somehow worse at nursing than women who aren’t nurses. It could even be that men who choose to become nurses despite the stereotypes have particular talent for it and thus conditionalizing on profession reverses the effect gender should have on your expectation of someone’s nursing ability.

The same could very well be true for skill at math/science. Even if there is some innate factor that makes women statistically worse at math/science it’s quite possible that those women who do pursue math/science tend to be more skilled than their male counterparts. In other words once you know that someone is interested in pursuing math/science finding out that individual is a woman might increase the expectation of her ability despite the fact that statistically women were worse than men at math/science. Since we tend to gather all sorts of information about someone we meet or consider for a job it’s totally unjustified to use statistical facts about men vs. women in the general population to reach conclusions about a particular individual.

The issue of nature vs. nurture really, really doesn’t matter that much. It’s almost never justified to use weak group characteristics like this to judge an individual and it’s equally unjustified to take mere statistical differences in a profession as proof of discrimination. So aside from pure scientific curiosity we should forget about nature vs. nurture and concentrate on applied questions like: Does science education unnecessarily make girls feel marginalized or less able? Would greater exposure to female role models in science make more women satisfied with their choice of career? Does rote memorization at the middle school level create barriers that discourage more studious individuals from pursuing math and physics?

Now it was bad enough when some random science summaries spun the study in this fashion but it’s even worse to see ars technica running stories saying things like this about the study:

But a new study suggests that, when it comes to math, we can forget biology, as social equality seems to play a dominant role in test scores.

Ughh, what is it about this topic that causes people to check their reasoning ability at the door? I mean I can understand that the general public might think the suggestion of a statistical difference amounted to a claim that women were incapable of doing math/science but people with a science background should know better. There is no serious doubt that the variation inside the genders is vastly larger than any possible difference in averages. Moreover, once you actually have some evidence about a person’s mathematical/scientific ability (like you’ve talked to them) their gender isn’t relevant. That is we should expect conditioning on actual evidence about someone’s ability should screen off any impact of their gender.

I write about this topic for the same reason I write about other topics. I find fallacious reasoning to be infuriating, especially when it seems to be motivated by a desire to reach certain comforting beliefs. However, it really should be a minor scientific curiosity. It doesn’t matter one jot what the cause of observed differences in gender performance might be. What matters is the effect these differences have on society and what actions we can take to minimize any harms that result from them.

I mean (hypothetically) suppose it turns out that the gender gap in math/science is caused entirely by social conditioning that makes women prefer some disciplines and men others but that those women who do choose to do math/science face no discouragement and those who don’t are made genuinely happy by their choices. In that case there is no compelling reason to force a change to the gender ratio in the sciences, especially if that change could only be brought about by painful social reorganization and reeducation (say by actively punishing women who pursue stereotypical careers to stop them from being role models for next generation).

On the other hand (hypothetically) suppose that the gender gap is the result of some innate difference in cognition but a simple change in the way science is conducted or taught would let many women who want to be scientists contribute productively to the field instead of having their dreams frustrated. Then obviously we should make that change regardless of the fact that the an innate difference was underneath the gender gap.

In short this issue really doesn’t fucking matter but it really really bothers me when I see people, especially scientists, spinning studies so heavily to reach the conclusions they find pleasant to believe. The roots of the gender gap are clearly complicated and almost certainly result from some complex interplay of innate and environmental factors but just think about how differently we would approach this problem if we were studying another species. Instead of prematurely trying to announce the death of either theory we would say the issue was still murky, explain the competing evidence and leave it at that. Why can’t we do that here too?

Spelke’s studies found baby boys and girls have similar mathematical ability, an incidental finding that was at the forefront of her mind in January 2005 when the former Harvard president Larry Summers suggested that the relative lack of female engineers and scientists was down to innate gender differences. ‘When it comes to the basic modules we are born with, they are pretty much the same,’ says Spelke, who was in the thick of the verbal fisticuffs that followed (Summers was ‘wrong, point for point’). Summers resigned as controversy raged. Spelke does not deny that there are differences in the way men and women think but most of this, she believes, is learnt over time, and down to prejudice and the expectations of society.

Of course it’s always easier to repudiate someone’s remarks when you simply assume they said whatever you are itching to reject. But besides mischaracterizing Summers this paragraph also buys into widespread but fallacious assumption that basic computational skills (adding, subtracting etc..) are the skills needed by scientists and engineers; calculation is easy it is the ability to reason abstractly and construct proofs that is hard. I would normally have simply dismissed this as another instance of sloppy journalism but a few minutes later I found the same errors being made in a respectable summary of an article published in the current edition of science, errors seemingly encouraged by the paper itself and it’s lead author.

Tipping off their hand early the summary begins with it’s own (IMO unethical) misquotation of Summers¹ but quickly moves on to reading the result they want to see into this recent study. The study basically plotted gender differences on math tests in a country versus that country’s level of gender equity and concluded that the more equitable the country the smaller the advantage boys enjoyed on math tests. The message the summary takes from this, with support from the study’s lead author, is that gender differences in mathematics are largely a result of enviornmental effects. Of course latter we are given the following qualification.

Having linked social structures to the math gender gap from country to country, Sapienza wonders whether this result rules out biological influences entirely. The answer is no. The biological hypothesis suggests that an average boy would score higher in mathematics than in reading, while for girls the reverse is true. This pattern does not change in more gender equal societies hinting that some aspects of academic performance may be innately different between boys and girls.
Sapienza and colleagues found that boys, regardless of the country and social environment in which they live, typically do better in math than in reading. Similarly, girls are usually better in reading than in math, regardless of the degree of gender equality in their society. As a result, in more gender equal societies, girls will gain an absolute advantage relative to boys.

In short an uncritical reading of either the paper in science or the summary would leave the reader with the impression that we now have even stronger evidence that boys don’t have an innate advantage at mathematics but there are still a few issues that need to be worked out about reading ability. Except the study really shows exactly the opposite. Ignoring for a moment the implicit (but false) assumption that these math tests are good measures of the skills needed to enter math and science professions just try and think about what theory would best explain the fact that cross-culturally boys are better at math than they are at reading while girls are better at reading than they are at math? Seems pretty clear to me that this evidence best supports the idea that their is an innate gender based attraction to math or reading and that in societies with greater gender equity women just perform better in school generally.

Now I don’t actually endorse that theory. It overly simplifies the complex interactions of culture and innate traits and it would be silly to just rely on this evidence while ignoring other evidence supporting larger cultural effects. However, the point remains that the evidence provided actually points in the exact opposite direction of the spin that is provided. Ultimately the point that I take from this is that if you want to have any idea about what’s plausible in this area you really can’t trust anyone’s (except mine of course :-) ) interpretation, even that of the scientists doing the study. You really have to go read the actual papers with a skeptical eye to get something other than spin. In short I worry that their is a bias in the spin given to papers and opinions on this stuff because you get a lot more flak for strident support of one side than the other.

I tend to think most of these arguments (except perhaps Laden’s) and most discussions of the Fermi paradox or the supposed fine-tuning of the universe for life assume far too much about the nature of intelligent life. In particular it seems unjustified to assume that intelligent life must look anything at all like us. Even assuming that intelligent life must be chemically based seems unjustified. Could configurations of plasma inside stars reproduce in some sense and evolve into intelligent life? Could the patterns of elementary particles in a neutron star do the same? I’m uncertain that we even have any reason to be confident that the chemistry and physics of the gases on jupiter can’t support life. Before we get to the stage of predicting that intelligent life must be rare, and certainly before we can assume our universe is fined tuned for life we need to do some deep mathematics to determine what sorts of laws give rise to interactions likely to support self-reproduction and selection.

On the Fermi paradox, the idea that if intelligent life was common in the universe we should have seen it already, I once again think it incorporates a deep anthropocentric bias. Worse it assumes that millions of years of technological sophistication will leave us with the same primitive desire to fuck our way across the universe. It seems totally plausible to me that the reason we don’t observe much intelligent life is that it’s just not worth the bother to them of looking for us or spreading out across the galaxy. After just begining to build computers we already spend massive amounts of time in them, perhaps aliens are too busy living in virtual worlds to come out and play in the real world. Moreover, we already have the very limited ability to control our own reward system. Give us a few million years and I’m sure that a press of a button could bring us more pleasure than any discovery of an alien civilization. The ultimate fate of intelligent life may very well be unimaginable drugged out bliss.

Additionally the very idea that aliens would colonize planets or be out here in the boring galactic nether regions seems to unimaginatively assume that aliens would remain chemical life forms. Sure people contemplate the idea that advanced life might become largely computational with sufficently advanced races learning to replace their brains with computer chips or other computing machines but few seem to really consider the implications of this idea. Beings such as this wouldn’t be constrained by physical space and would have no need to spread out to avoid overcrowding, rather, they would be limited by computational power. Thus the most likely behavior of truly advanced life is to seek out the most computationally rich physical systems and stay there. This suggests that perhaps we should be looking for the truly advanced alien civilizations to be somehow encoded into the most violent, high energy systems around. Visiting planets or sending out signals to the primitive animals who live there might be the last thing on their minds.

This is just one speculation thrown out about an area we know so impossibly little that it’s hard to conclude anything except that we shouldn’t trust any of our intuitions about what life must be like too much. Ohh and I can’t write a post about this subject without throwing a shout out to Greg Egan for being one of the most imaginative and thoughtful science fiction writers about these issues.

Unfortunately greater environmental awareness doesn’t seem to have increased support for sane policies like this one jot. Just in the last few days McCain announced his proposal for a gas tax holiday. Lest you think that this is only a proposal that caters to the trucks and guns crowd consider the fact that no democratic candidates would dare to propose an increased gas tax for fear of the public backlash. It doesn’t seem to matter that such a tax could be made revenue neutral and could even favor the poor people since people respond viscerally to expensive gasoline.

Instead of responding rationally to the global warming issue people, especially those claiming to be environmentally conscious, instead lash out at conspicuous consumption. It is somehow considered a moral hazard to buy a gas guzzling car, take plane flights, run an air conditioner or engage in other activities that have a salient link the emissions. This of course ignores the fact that the money people save as a result of these various conservation measures goes into buying other products which themselves likely have a large carbon footprint. All the tips about how to save electricity/gas or reuse items instead of throwing them out are particularly silly. After all if I save gas that reduces the price for other consumers who may then use more. Of course these factors are likely not 1-1 but it illustrates the point that urging people to avoid activities that seem wasteful is not only a waste of utility (moral guilt doesn’t discriminate between the people for whom running their air conditioning isn’t a big deal and those who get great utility from it) but it isn’t a very effective way of accomplishing the goal.

Unfortunately this attitude that environmentalism is really about eliminating consumer excess seems to be on the lips of every environmental activist I meet lately. They remark about how we will look back on our wasteful product packaging and huge trucks as gross and wasteful. Well hopefully we will look back on them as being inefficient in terms of carbon but there is absolutely no reason we shouldn’t expect the future to eventually provide cheaper energy, more disposable cruft, more gadgets and less need for conspicuous recycling (automated sorting) while making a smaller environmental impact. Even if this isn’t possible surely we ought to aim to improve our standard of living while saving the environment.

I don’t know where this idea that environmentalism is some sort of personal virtue of frugality came from but it’s not only a bunch of bunk but it’s hurting the environment. Not only does this attitude alienate many people who might get on board with a more pragmatic engineering/economic approach to the environment but it also competes with real solutions. People are willing to make a limited amount of sacrifices and if you tell them that they are being good people for enduring daily inconveniences like turning off their AC or buying a car they don’t like as much they won’t be as eager to ’sacrifice’ again by voting up the gas tax.

The problem is that the trials used to test antidepressant efficacy compare the medication to a sugar pill but most patients and their doctors are able to tell when they aren’t on a sugar pill. Given the small benefits of these antidepressants over placebos the fact that study participants are able to break the blind may well explain the entire effect. For those who are interested I’ll lay out a full argument for this position below the break. However, it’s important to note that just because antidepressants might not work isn’t any reason to stop prescribing them. So long as they give greater response than placebos (i.e. people believe in them) they may be of use to some people. Alternatively one might think these drugs really do have a *very *minor effect in the most depressed individuals, if for no other reason than a system that is sufficiently far from the mean might be (on average) pushed closer by any substantial intervention (think wacking your ipod to make it work) amplified by the placebo effect.

These considerations add weight to the view that depression is not a disease or even condition in the way that Downs syndrom or Asthma is but is instead the extreme end of a distribution. Thus rather than being the result of a determinate dysfunction as those cute Zoloft commercials would have you believe having depression is more like being short². This theory is being advanced by some serious researchers^{3 4}. For some reason, however, these attitudes seem to frequently come part and parcel with the idea that we ought not to treat ‘natural’ sadness, in this case apparently justified by the evolutionary ‘argument’ that sadness must serve some purpose (of course an inclination toward or efficacy at rape might have been selected for as well it would hardly prove it was something important to preserve in modern society). While some would dispute this theory everyone, it seems, is obsessed with distinguishing normal and abnormal sadness.

I could not disagree more forcefully. Far from being an argument to abandon the idea of alleviating suffering via chemical intervention the idea that depression is just an extreme for of unhappiness, if true, militates for research into effective drugs to elevate mood. Would we deny those so short they experience serious hardship or those with GH deficiencies in adulthood treatment with growth hormone just because some of it’s benefits are available to those with average levels of the hormone? Of course one always has to balance benefits with side effects and depending on the drug that balance may very well weigh against treatment in those who are already quite happy (as I understand does for HGH treatment for most people) but it’s hard to imagine that any bearable level of side effects is enough to justify denying an effective treatment to those who are chronically suicidally depressed.

Placebo Response and Theory Failure

Even before this recent meta-analysis the available data indicated that placebo response was at least 80% as effective as administering the antidepressants themselves⁵ and the new data only pushes the effects down below the level of clinical significance (i.e. the level generally considered worthwhile to prescribe). Generally in the more recent studies the percent of patients who ‘respond’ to the active medication is centered near 50% while those responding to placebo is around 30% but the response rate from placebos is highly variable (10%-50%) and interestingly increasing over time⁶. Even those who defend antidepressants acknowledge that remission rates only differ by 20% (about 50% on placebo versus 70% on medication) and merely argue that this indicates a real result that can be extremely significant in the ‘true responders’⁷.

Were these improvements the result of a reasonable theoretical hypothesis about the cause of depression, or at least the mechanism of action of antidepressants we might have more reason to believe this weak evidence indicated something real. However, not only do we not really have a good theory for how SSRIs work (no immediate effects are observed but seretonin levels quickly drop back to normal invalidating the initial theories) but there are similar response rates from a diverse array of ‘antidepressant drugs’ with no apparent common mechanisms nor ability to tell which patients will respond best to which drugs⁸. At the very least this sort of situation should raise concern about whether there is any real effect and if so whether it is primarily due to some kind of regression to the mean rather than specific efficacy against depression.

Active Placebos and Unblinding

The most daming criticism about the evidence for antidepressants is the concern that the supposed effects of the drug come entirely from unblinding⁹. There is evidence that patients are able to figure out when they are taking the real drug versus a sugar pill^{10 11}. Moreover, other studies suggest that active placebos are more effective in treating depression than inactive ones¹². In fact it was the defense offered for antidepressants that many of these ‘active placebos’ have antidepressant activity themselves that was particularly convincing to me that there might be some element of bias in the evaluation¹³.

Ultimately I can’t be sure which is ultimately the right answer. These arguments certain raise troubling questions about the effectiveness of antidepressants (and there is plenty more I just ran out of steam). Additionally the profusion of backup theories offered to save the hypothesis that these are antidepressant drugs seems dubious. Doctors tell patients they just need to find the right drug, researchers claim that it’s really just that a few ‘true responders’ are hiding in the data or that the ‘active placebos’ themselves have antidepressant effect. All of this on top of any publication bias or other bias induced by the strong motivation many people have to believe these drugs are effective.

What I’m talking about is the article in the East Bay Express on the Gardasil vaccine for HPV (thus cervical cancer) titled “One Less“. True, the article describes the ‘controversy’ about the Gardasil vaccine’s deadly side effects for HPV (thus Cervical cancer) without article asserts nothing factually untrue. I don’t doubt the mother of the girl who died as the result of blod clots shortly after taking the vaccine really said the quotes attributed to her nor that the semi-anonymous remarks really do come from someone who had the shots. However, the whole article is set up to portray these as reasonable fears that are on one side of a ‘growing debate’ while plastering a picture of a sweet little 17 year old who died after taking the vaccine on the front of the print magazine with the “One Less” slogan of Gardasil written over it.

I mean the arguments for the involvement of Gardasil are really this bad:

“Some are pretty hard to discount as being a reaction,” Grothe said. “When a patient dies of a blood clot three hours after getting a Gardasil vaccination, that’s pretty consistent to me.”

Of course all the medical professionals interviewed point out that the birth control pills being taken by the girls who died are likely the cause but that doesn’t stop the article from throwing logic overboard to pander to the emotions of a grieving mother and friends or by mixing in real concerns and disadvantages of the vaccine as if they were concessions. Of course even if you grant that the vaccine is as horrible as the grieving mother trying to blame it claims it is hard to see how the harms would overwhelm the 4,000 deaths it could save a year not to mention the suffering it could erase.

Given that newspaper articles like this generate readers and likely convince people not to take the vaccine I have grave doubts about the ability of jurors to evaluate expert testimony in drug and medical device trials.

The article that motivated this new series was this doozy that amazingly tells us that, “moderate happiness may be preferable to full-fledged elation.” This might make some sense if the study was warning that elation often presaged a crash while moderate happiness was more sustainable but it’s nothing that reasonable. Rather the article ‘warns’ us that:

“The highest levels of income, education and political participation were reported not by the most satisfied individuals (10 on the 10-point scale),” the authors wrote, “but by moderately satisfied individuals (8 or 9 on the 10-point scale).”

The 10s earned significantly less money than the eights and nines. Their educational achievements and political engagement were also significantly lower than their moderately happy and happy-but-not-blissful counterparts.

We are further warned that the most happy people tend not to get the best grades in school. Now if I had confidence in these results (see below break) this would be an interesting result but the idea that this shows we should be less happy is so deeply confused it boggles the mind. In fact it’s such an absurd conclusion that I wouldn’t have believed the article was really saying it, much less that the actual researcher endorsed it, if they hadn’t hammered the point home.

The data indicate that happiness may need to be moderated for success in some areas of life, such as income, conscientiousness and career, Diener said.

….

All in all, Diener said, the evidence indicates that happiness is a worthy goal for those who lack it, but the endless pursuit of even more happiness for the already happy may be counterproductive.

Great so your telling me that I should give up on that whole being crazy fucking happy thing so I can be more anal retentive about cleaning my room and earn more money for my own benefit. This is so brainfucked I can’t comprehend it. These are probably the same people who object to living (voluntarily) in the matrix because it would make us all really poor (no physical goods). Sometimes I boggle that people like Dennet can deny the existence of experiences then I run across something like this that reminds me just how deep the physicallist fallacy runs in our society.

To add insult to injury the results of the underlying study are neither surprising nor compelling. Given that happiness scores were self-reported answers of 10 may really be tracking impulsivity, lack of ambition or inability to imagine a better life. But the results are probably mostly correct (possibly excepting the health related conclusions) because they are blindingly obvious. I mean does anyone think that the most ambitious, workaholic and driven people they know are the most happy?

I mean Tibetan Buddhist monk or business executive, relaxed (tenured) academic or corporate sell out, who would you bet on to be happier?

Of course rigorous studies that bear out our preconceptions can be usefull but I doubt this one really cuts it.