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kalium comments on Open thread, 7-14 July 2014 - Less Wrong Discussion
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I feel like the argument is slicing the problem up and presenting just the worst bits, when we need to consider the net effect on everything. This reminds me of a bioethics debate about testing error and base rate of rare lethal diseases: if five times as many people have disease A than disease B, but they look similar and the tests only offer 80% accuracy,* what should we do if the treatment for A cures those with A but kills those with B, and vice versa?
The 'shut up and multiply' answer is "don't give the tests, just treat everyone for A," as that spares the cost of the tests and 5/6ths of the population lives. But this is inequitable, since everyone with disease B dies. Another approach is to treat everyone for the disease that they test positive for- but now only 4/5ths of the population lives, and we had to pay for the tests! Is it really worth committing 3% of the population to the graveyard to be more equitable? If one focuses on the poor neglected patients with B, then perhaps, but if one considers patients without regard to group membership, definitely not.
*Obviously, the tests need to be dependent for 80% to be the maximal possible accuracy.
I don't know if it's possible to test this, and specifically it's not obvious to me that we need racial bias to explain this effect. That is, widespread cognitive stratification in the economic sphere is relatively new (it started taking off in a big way only around ~1950 in the US), and if promotions were generally inefficient, it's hard to determine how much additional inefficiency race caused.
These comparisons become even harder when there are actually underlying differences in distributions. For example, the difference in mean male and female mathematical ability isn't very large, but the overwhelming majority of Harvard math professors are male. One might make the case that this is sexism at work, but for people with extreme math talent, what matters much more than the difference in mean is the difference in standard deviation, which is significantly higher for men. If you take math test scores from high schoolers and use them as a measure of the population's underlying mathematical ability distribution and run the numbers, you predict basically the male-female split that Harvard has, which leaves nothing left for sexism to explain.
The analogy is poor because the point is that temporary unemployment of the kind you get with a noisy IQ measure is much less harmful than long-term unemployment of the kind you might get with a better measure. Whereas with diseases A and B people die either way and it's just a question of who/how many.
The analogy is intended to be about reasoning processes, not the decision itself. Complaining that some readily identifiable people are hurt by measure X is a distraction if what you care about is total social welfare: if we can reduce harm by concentrating it, then let us do so!
I also think that, on the object level, replacing "long-term unemployment" with "long-term underemployment" significantly decreases the emotional weight of the argument. I also think that it's not quite right to claim that the current method is equally inefficient everywhere- the people who test well but don't school well, for example, are the readily identifiable class who suffer under the current regime.
While it makes sense to care about total social welfare, the calculation showing that the IQ test is better shows that it is better in terms of job-productivity-years. Job-productivity-years is not social welfare, and you can't just assume that it is.
Furthermore, my complaint is not that the people harmed are readily identifiable, but that it's the same people being constantly harmed. Having one person out of 100 never have a job is worse than having all 100 people not have jobs 1% of the time. Even if I knew who the 100 people were and didn't know who the one person is, that wouldn't change it.
Sure, but I don't see why you think the current setup is much better on that metric. Someone who consistently flubs interviews is going to be unemployed or underemployed, even though interviews don't seem to communicate much information about job productivity. If it were an actual lottery, I think the argument that the unemployment is spread evenly across the population would hold some weight, but I think employers have errors that are significantly correlated already, and I'm willing to accept an increase in that correlation in exchange for a decrease in the mean error.
Long-term underemployment still tends to erode, or at least not build up, one's skills, reducing that individual's lifetime productivity.