Thoughts on rationalism and the rationalist community from a skeptical perspective. The author rejects rationality in the sense that he believes it isn't a logically coherent concept, that the larger rationalism community is insufficiently critical of it's beliefs and that ELIEZER YUDKOWSKY IS NOT THE TRUE CALIF.
Here is a bit of hard data to respond to the claims that observed performance on IQ tests by those in third world countries reflect genetic deficits. Its a good thing too (even if this was hardly the first piece of evidence on the point) since its easy to imagine that the world could have turned out in a way in which (despite race not being a scientifically useful category) third world populations also suffered from genetic intelligence disadvantages. There is a decent case to be made that the Ashkenazi Jews have genetic differences given them higher average IQs. Notably that case doesn’t merely depend on differences in performance on some tests but, likely all compelling scientific arguments, weaves together an explanation of a number of different phenomena with an appealing theoretical account1. Whether or not this ultimately turns out to be true it could have been true and other undisputed cases of recent evolutionary pressure like adult tolerance for lactose make it abundantly clear that we got very lucky that there aren’t major differences in genetic predisposition to IQ across people of different descent and seeing studies like this reassures me that we really did get lucky and its not just that we are laboring under a desirable fiction.
Even though our racial categories don’t correspond to any principled scientific division at the genetic level it is a classification that correlates with ones ancestry. Given that people still tend to choose mates relatively close to themselves genetically (whether or not race is salient to them or merely geographic proximity) that means it could easily have been the case that, even supposing all developmental and social effects are controlled for, that some races would average much, much worse on IQ tests and other measures of intelligence than others. It wouldn’t really matter that race wasn’t the best scientific category to explain the effect if it turned out that 80% of people we classified as black had genes which cost them 20 IQ points while only 20% of Caucasians and 30% of Semites had this genetic combination. Such a fact would have amplified existing prejudices and resentments making it much more difficult to roll back racist attitudes and laws. In such a world I doubt one of the 20% of blacks without those genes would have had much luck explaining to the white racists around them that no, no, black isn’t the appropriate scientific concept with which to analyze this effect its really this other grouping they should be using, e.g., one which is purely defined via heredity and doesn’t exactly track our racial divisions but just happens to correlate with them.
One might try and argue that there is too much human genetic mixing for substantial genetic differences in IQ to have arisen. While it is true that for the most part humans haven’t partitioned themselves into non-interbreeding (or at least rarely) sub-populations that only holds for the most part and is itself purely a lucky accident. Australian aborigines appear to have been genetically isolated for almost 50,000 years with that isolation only ending quite recently2. There is evidence that the San people in Africa may split off from the rest of the human lineage at around the time modern homo sapiens first arrived on the scene and were then genetically isolated for nearly 100,000 years until only 40,000 years ago. There is no scientific law that ensured there weren’t major genetically isolated branches of the human species with substantially different intellectual abilities which remained separated until the end of the middle ages. It didn’t have to be the case that America was populated by genetically modern humans3 and for less extreme cases one doesn’t even need genetic isolation at all. One can imagine a scenario in which the black death is even worse and attacks the neural system creating strong selective pressure in Europe for a mutation which protects against it despite its detrimental effects on IQ. I suppose one could argue that people are just too rapacious and generally willing to fuck each other for differences to have persisted during the historical era but that is only true if all populations were subject to the same selective pressures and one could certainly imagine a scenario in which only farmers and not hunter gatherers (or vice versa) experience selection for the kind of mixed blessing genes postulated to be more prevalent in the Ashkenazi.
Of course, if we learn enough about genetics and perform sufficiently high powered studies we will probably come across some minor statistical difference in IQ between racial groups. If we assumed that humans were all otherwise genetically identical the small IQ advantage observed in Ashkenazi Jews would be enough to ensure that sufficiently powerful studies would find some average difference. Of course we aren’t all otherwise genetically identical and surely the beneficial and detrimental mutations won’t perfectly cancel out on average. But the fact that we haven’t already found substantial differences and don’t even know who will come out on top if average differences are ever found already means that we got incredibly lucky. It didn’t have to be that the HBD people were wrong, it didn’t even half to be that our racial categories didn’t track scientifically important genetic fault lines. Even though many of the HBD proponents seem so desperately motivated to believe their theories (and not all for racist reasons…some just want to be contrarian) their views certainly describe a way the world could have been and we got quite lucky that human capacities ended up sufficiently close together and interbreeding smeared us out enough that we can’t obviously pick out the more and less capable major ethnic groups.
In Selfish Reasons to Have More Kids, I showed that nurture effects are small within the First World. But I also freely conceded that the nurture effects of growing up outside the First World are probably large:The most important weakness…
In this case the theoretical account suggests that certain mutations which both increase intelligence but also increase susceptibility to certain congenital disorders were selected for in Jews living in medieval Europe and laboring under systematic discrimination which kept them out of most occupations while concentrating them in a few occupations for which IQ was particularly important. ↩
Though one could, I suppose, argue that had the aboriginal Australians, contrary to fact, been intellectually impaired relative to other humans then relatively nearby populations would have noticed and used their superior intelligence to supplant them. ↩
For a truly extreme scenario, one could imagine an “out of America” theory of human evolution in which 200,000 years ago proto-humans leave America over the land bridge which subsequently closes (and weather/sea conditions prevent coast hopping) it is only in 1492, after modern humans evolve in the rest of the world, that we rediscover the lost American branch of the human tree. ↩
Machine Learning, Sensitive Information and Prenatal Hormones
So there’s been some media attention recently to this study which found they were able to accurately predict sexual orientation with 91% for men and 83% for women. Sadly, everyone is focusing on the misleading idea that we can somehow use this algorithm to decloak who is gay and who isn’t rather than the really interesting fact that this is suggestive of some kind of hormonal or developmental cause of homosexuality.
Rather, given 5 pictures of a gay man and 5 pictures of a straight man 91% of the time it is able to correctly pick out the straight man. Those of us who remember basic statistics with all those questions about false positive rates should realize that, given the low rate of homosexuality in the population, this algorithm doesn’t actually give very strong evidence of homosexuality at all. Indeed, one would expect that, if turned loose on a social network, the vast majority of individuals judged to be gay would be false positives. However, in combination with learning based on other signals like your friends on social media one could potentially do a much better job. But at the moment there isn’t much of a real danger this tech could be used by anti-gay governments to identity and persecute individuals.
Also, I wish the media would be more careful about their terms. This kind of algorithm doesn’t reveal private information it reveals sensitive information inadvertently exposed publicly.
However, what I found particularly interesting was the claim in the paper that they were able to achieve a similar level of accuracy for photographs taken in a neutral setting. This, along with other aspects of the algorithm, strongly suggest the algorithm isn’t picking up on some kind of gay/straight difference in what kind of poses people find appealing. The researchers also generated a heat map of what parts of the image the algorithm is focusing on and while some of them do suggest grooming based information about hair, eyebrows or beard play some role the strong role that the nose, checks and corners of the mouth play suggests that relatively immutable characteristics are pretty helpful in predicting orientation.
The authors acknowledge that personality has been found to affect facial features in the long run so this is far from conclusive. I’d also add my own qualification that there might be some effect of the selection procedure that plays a role, e.g., if homosexuals are less willing to use a facial closeup on dating sites/facebook if they are ugly the algorithm could be picking up on that. However, it is at least interestingly suggestive evidence for the prenatal hormone theory (or other developmental theory) of homosexuality.
So I see people posting this vox article suggesting Trump, but not Clinton, supporters are racist and I want to advise caution and urge people to actually read the original study.
Vox’s takeaway is,
All it takes to reduce support for housing assistance among Donald Trump supporters is exposure to an image of a black man.
Which they back up with the following description:
In a randomized survey experiment, the trio of researchers exposed respondents to images of either a white or black man. They found that when exposed to the image of a black man, white Trump supporters were less likely to back a federal mortgage aid program. Favorability toward Trump was a key measure for how strong this effect was.
If you look at the actual study its chock full of warning signs. They explicitly did not find any statistically significant difference between those Trump voters given the prompts showing black or white aid recipients degree of support for the program or degree of anger they felt or blame they assigned towards those recipients. Given that this is the natural reading of Vox’s initial description its already disappointing (Vox does elaborate to some extent but not in a meaningfully informative way).
What the authors of the study did is asked for a degree of Trump support (along with many other questions such as liberal/conservative identification, vote preference, racial resentment giving researchers a worryingly large range of potentially analysises they could have conducted). Then they regressed the conditional effect of the black/white prompt on the level of blame, support and anger against degree of Trump support controlling for a whole bunch of other crap (though they do claim ‘similar’ results without controls) and are using some dubious claims about this regression to justify their claims. This should already raise red flags about research degree of freedom especially given the pretty unimpressive R^2 values.
But what should really cause one to be skeptical is that the regression of Hillary support with conditional effect of black/white prompt shows a similar upward slope (visually the slope appears on slightly less for Hillary support than it did for Trump) though at the extreme high end of Hillary support the 95% confidence interval just barely includes 0 while for Trump it just barely excludes it. Remember, as Andrew Gelman would remind us the difference between significant and non-significant results isn’t significant and indeed the study didn’t find a significant difference between how Hillary and Trump support interacted with the prompt in terms of degree of support for the program. In other words if we take the study at face value it suggests at only a slightly lower confidence level that increasing support for Hillary makes one more racist.
So what should we make of this strange seeming result? Is it really the case that Hillary support also makes one more racist but just couldn’t be captured by this survey? No, I think there is a more plausible explanation: the primary effect this study is really capturing is how willing one is to pick larger numbers to describe one’s feelings. Yes, there is a real effect of showing a black person rather than a white person on support for the program (though showing up as not significant on its own in this study) but if you are more willing to pick large numbers on the survey this effect looks larger for you and thus correlates with degree of support for both Hillary and Trump.
To put this another way imagine there are two kinds of people who answer the survey. Emoters and non-emoters. Non-emoters keep all their answers away from the extremes and so the effect of the black-white prompt on them is numerically pretty small and they avoid expressing strong support for either candidate (support is only a positive variable) while Emoters will show both a large effect of the black-white prompt (because changes in their opinion result in larger numerical differences) and a greater likelihood of being a strong Trump or Hillary supporter.
This seems to me to be a far more plausible explanation than thinking that increasing Hillary support correlates with increasing racism and I’m sure there are any number of other plausible alternative interpretations like this. Yes, the study did seem to suggest some difference between Trump and Hillary voters on the slopes of the blame and anger regressions (but not support for the program) but this may reflect nothing more pernicious than the unsurprising fact that conservative voters are more willing to express high levels of blame and anger toward recipients of government aid.
However, even if you don’t accept my alternative interpretation the whole thing is sketchy as hell. Not only do the researchers have far too many degrees of freedom (both in terms of the choice of regression to run but also in criteria for inclusion of subjects in the study) for my comfort but the data itself was gathered via a super lossy survey process creating the opportunity for all kinds of bias to enter into the process not to mention. Moreover, the fact that all the results are about regressions is already pretty worrisome as it is often far too easy to make strong seeming statistical claims about regressions, a worry which is amplified by the fact that they don’t actually plot the data. I suspect that there is far more wrong with this analysis than I’m covering here so I’m hoping someone with more serious statistical chops than I have such as Andrew Gelman will analyze these claims.
But even if we take the study’s claims at face value the most you could infer (and technically not even this) is that there are some more people who are racist among strong Trump supporters than among those who have low support for Trump which is a claim so unimpressive it certainly doesn’t deserve a Vox article much less support the description given. Indeed, I think it boarders on journalistically unethical to show the graphs showing the correlation between increasing support for Trump and prompt effect but not the ones showing similar effects for support of Hillary. However, I’m willing to believe this is the result of the general low standards for science literacy in journalism and the unfortunate impression that statistical significance is some magical threshold.
All it takes to reduce support for housing assistance among Trump supporters is exposure to an image of a black man. That’s the takeaway from a new study by researchers Matthew Luttig, Christopher Federico, and Howard Lavine, set to be published in Research & Politics.
Do You Care About Protecting Women Or Just About Middle Class Values
It’s time for everyone claiming to support criminal bans on prostitution because they want to protect vulnerable women to choose sides. Are you really concerned about doing what it takes to protect vulnerable women or are you just using that as an excuse to justify your middle class values and your discomfort with the idea of exchanging sex for money?
Time to choose sides since it looks like research based on the (unfortunately brief) accidental Rhode Island experiment in decriminalizing indoor prostitution has some interesting results. Decriminalization resulted in a 50% drop in gonorrhea and a 30% drop in reported rapes (which, given the ability for prostitutes to go to the police without fearing prosecution, should have increased if rapes had stayed the same). Importantly, it appears that even women who weren’t in the prostitution industry saw a decrease in incidence of rape. I’d say these results were surprising except they weren’t to those familiar with the field, indeed, that’s why I’m willing to say this seems like a pretty solid result (maybe not the actual number but the direction of the change).
While no one suggests that the lives of most prostitutes (though the high end ones sometimes do well for themselves) are sweetness and light but sex workers who have experienced decriminalization will usually express strong support for the change and the ways it has changed their lives. However, one could still make an intellectually cogent case for decriminalization creating a real net harm, e.g., suggest that even if it makes the lives of sex workers better it makes more people into sex workers. However, if this research stands up, its just no longer even plausible to claim women are better protected in a regime which results in 30% more rapes. No matter how far you stretch the additional harm of increased numbers of sex workers (though often of a different class which isn’t as vulnerable) it doesn’t go that far.
But I’m pretty pessimistic. While I believe the passionate advocates in this area really do care about the victimization of women (though one can care so much that you are unable to let some go to save more) I don’t think that is what drives criminalization of prostitution at all. Rather, it’s just more of the usual human psycho-sexual drama about the threat which ‘virtuous’ women perceive from prostitution dressed up in new language.
The Effects of Decriminalization in Rhode Island
The study itself was a standard difference in differences design. Basically, that means they look at the data on rapes and STDs from both Rhode Island and the rest of the country before the decriminalization and then after the decriminalization. If the difference between Rhode Island and other states changes at the time prostitution is decriminalized then we infer that this difference in differences is a result of the change in legal status at that time. Of course, the actual statistical work is a bit more complex than this and uses data over a number of years but it’s a decent way to estimate the effect in a natural experiment provided one doesn’t believe that some other change singled out Rhode Island at the same time. To further shore up their work they use synthetic controls (basically they find the states which resemble Rhode Island in terms of the pre-decriminalization data and then use those as a control instead of the rest of the US).
Unfortunately, a reason why this study itself is only fairly persuasive and not highly persuasive is that the recriminalization results were not as strong. While rapes did rise again after Rhode Island made prostitution illegal again this result had a p-value of only .2. The story the authors offer is that the fact that this change was widely anticipated might dull the statistical power of the difference-in-differences method. In other words, they are suggesting that maybe the rapes started rising again once everyone realized they were going back to criminalization. I don’t find this very plausible since most mechanisms for this effect I can imagine, particularly including the author’s suggestion that rape is a partial substitute for paid sex, shouldn’t see much change, if any, until prostitution is actually recriminalized.
However, I think this result actually fits very nicely into a different model. In particular, while it may be the case that rape and consensual sexual encounters are partial substitutes I’m pretty skeptical that accounts for the effects here. Its not as if prostitution doesn’t exist when it is illegal or someone willing to rape for sex wouldn’t avail themselves of it. Rather, I suspect there are more general network effects at play here. In the pre-decriminalization world you have a system that relies on a system of pimps, organized crime and other bad actors to operate in which the girls involved may have little control/ownership interests and probably have only a minimal support network among themselves. Decriminalization not only removes this criminal element from the scene it also, as suggested by the health data, draws in a new class of prostitute who has better resources, planning, risk mitigation and isn’t at the mercy of her drug dealing pimp, i.e., more middle class prostitution. Recriminalization appears to have push some people out of the industry but it doesn’t change the fact that the criminal element is no longer present. A prostitute with a regular list of clients, a system for meeting new clients online and who isn’t already enmeshed with the criminal element has little need to return to their clutches even after recriminalization meaning the benefits linger. Sadly, I would guess that in the long term we will see a regression to previous levels as the police work to disrupt the organization and continuing business relationships these women have used to replace pimps and organized crime and eventually people will go back to securing prostitution through this element and rapes will rise.
Luckily, one doesn’t need to believe my analysis (which is just speculation) since one can rely on the fact that the results found for decriminalization are similar to what other studies have found.
The story of how Rhode Island came to decriminalize prostitution is pretty neat so I advise you to read this article. I am not, however, please with the top billing they gave people who in my opinion were nothing but moralizing middle aged women who had never had to make really hard choices using the language of concern for vulnerable women to justify their disapproval.
Around the world, there’s a growing movement to decriminalize sex work. Last year, Amnesty International, the largest human rights group in the world, came out with a recommendation that governments should decriminalize consensual sex work and develop laws that ensure workers are “protected from harm, exploitation and coercion.”