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PaperclipPerfector  7mo ago (text post)   27772 thread views

Culture War Roundup for the week of September 18, 2023

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In what contexts are accurate prejudice/biases acceptable justification for discrimination?

I want to consider a broad range of groups including both involuntary/innate characteristics such as race, gender, and IQ, as well as more voluntary categories such as religion, political ideology, or even something like being in the fandom for a certain TV show, expressing a preference for a certain type of food, or having bad personal grooming. This is a variable that your answer might depend upon.

Let's suppose that we know with certainty that people in group X have a statistically higher rate of bad feature Y compared to the average population, whether that be criminality, laziness, low intelligence, or are just unpleasant to be around. I'm taking the fact that this is accurate as an axiom. The actual proportion of people in group X with feature Y is objectively (and known to you) higher than average, but is not universal. That is, Y is a mostly discrete feature, and we have 0 < p < q < 1 where p is the probability of a randomly sampled member of the public has Y, and q is the probability that a randomly sampled member of q has Y. Let's leave the causation as another variable here: maybe membership in X increases the probability of Y occurring, maybe Y increases the probability of joining X (in the case of voluntary membership), maybe some cofactor causes both. This may be important, as it determines whether discouraging people from being in group X (if voluntary) will actually decrease the prevalence of Y or whether it will just move some Ys into the "not X" category.

Another variable I'll leave general is how easy it is to determine Y directly. Maybe it's simple: if you're interacting with someone in person you can probably quickly tell they're a jerk without needing to know their membership in Super Jerk Club. Or maybe it's hard, like you're considering job applications and you only know a couple reported facts, which include X but not Y and you have no way to learn Y directly without hiring them first.

When is it okay to discriminate against people in group X? The far right position is probably "always" while the far left would be "never", but I suspect most people would fall somewhere in the middle. Few people would say that it would be okay to refuse to hire brown-haired people if it were discovered that they were 0.1% more likely to develop cancer and thus leave on disability. And few people would say that it's not okay to discriminate against hiring convicted child rapists as elementary school teachers on the basis that they're a higher risk than the average person. (if you are such a person though, feel free to speak up and explain your position).

So for the most part our variables are:

-Group membership voluntariness

-Feature Y's severity and relevance to the situation

-The situation itself (befriending, hiring, electing to office)

-Ease of determining feature Y without using X as a proxy

-Causality of X to Y

Personally, I'm somewhere between the classically liberal "it's okay to discriminate against voluntary group membership but not involuntary group membership" and the utilitarian "it's okay to discriminate iff the total net benefit of the sorting mechanism is higher than the total cost of the discrimination against group members, taking into account that such discrimination may be widespread", despite the latter being computationally intractable in practice and requiring a bunch of heuristics that allow bias into the mix. I don't think I'm satisfied with the classically liberal position alone because if there were some sufficiently strong counterexample, such as someone with a genetic strain that made them 100x more likely to be a pedophile, I think I'd be okay with refusing child care positions to all such people even if they had never shown any other risk factors. But if there were a similar strain that made them 10% more likely I don't think it would be fair to do this, because it's such a low base rate that 10% doesn't do much to offset the cost of the discrimination. Also the utilitarian position allows for stricter scrutiny applied for more serious things like job applications (which have a huge cost if systematically discriminating against X) versus personal friendships (if people refuse to befriend X because they don't like Y, those people can more easily go make different friends or befriend each other, so the systemic cost is lower)

But I'd love to hear more thoughts and perspectives, especially with reasoning for why different cases are and are not justified under your philosophical/moral framework.

I will charitably assume that you understand discrimination here quite broadly, and mainly as things on the quantitative side, like multidimensional demographic profiling in mortgage approvals, rather than a recipe for an explicit caste society. Most arguments against this line of thought are invalid (rejecting the premise) or non-consequentialist and «principled» to the point of absurdity (statistically reliable proxies in uncertainty are bad! Uncertain gut feelings/laughably gameable metrics are good!).

I think the main problem with the utilitarian approach is simply that the society we have cannot be trusted with the full power of Reverend Bayes. That's okay, in my view: it'll recalibrate under the pressure of truth and retain its good sides while reducing bad ones. But, as it stands, Nick Land said it best:

Consider John Derbyshire’s essay in infamy The Talk: Nonblack Version, focusing initially on its relentless obnoxiousness, and attentive to the negative correlation between sociability and objective reason. As Derbyshire notes elsewhere, people are generally incapable of differentiating themselves from group identities, or properly applying statistical generalizations about groups to individual cases, including their own. A rationally indefensible, but socially inevitable, reification of group profiles is psychologically normal – even ‘human’ – with the result that noisy, non-specific, statistical information is erroneously accepted as a contribution to self-understanding, even when specific information is available.

From the perspective of socially autistic, low-EQ, rational analysis, this is simply mistaken. If an individual has certain characteristics, the fact of belonging to a group that has similar or dissimilar average characteristics is of no relevance whatsoever. Direct and determinate information about the individual is not to any degree enriched by indirect and indeterminate (probabilistic) information about the groups to which the individual belongs. If an individual’s test results are known, for instance, no additional insight is provided by statistical inferences about the test results that might have been expected based on group profiling. An Ashkenazi Jewish moron is no less moronic because he is an Ashkenazi Jew. Elderly Chinese nuns are unlikely to be murderers, but a murderer who happens to be an elderly Chinese nun is neither more nor less murderous than one who is not. This is all extremely obvious, to obnoxious people.

To normal people, however, it is not obvious at all. In part this is because rational intelligence is scarce and abnormal among humans, and in part because social ‘intelligence’ works with what everyone else is thinking, which is to say, with irrational groupish sentiment, meager information, prejudices, stereotypes, and heuristics. Since (almost) everybody else is taking short-cuts, or ‘economizing’ on reason, it is only rational to react defensively to generalizations that are likely to be reified or inappropriately applied — over-riding or substituting for specific perceptions. Anybody who anticipates being pre-defined through a group identity has an expanded ego-investment in that group and the way it is perceived. A generic assessment, however objectively arrived at, will immediately become personal, under (even quite remotely) normal conditions.

Obnoxious reason can stubbornly insist that anything average cannot be about you, but the message will not be generally received. Human social ‘intelligence’ is not built that way. Even supposedly sophisticated commentators blunder repeatedly into the most jarring exhibitions of basic statistical incomprehension without the slightest embarrassment, because embarrassment was designed for something else (and for almost exactly the opposite). The failure to understand stereotypes in their scientific, or probabilistic application, is a functional prerequisite of sociability, since the sole alternative to idiocy in this respect is obnoxiousness.

As it stands, so it goes.

Thanks for pointing this out. Land here articulates very well something I've been trying to understand for quite a while.

A more simplified way to put it in my view, would be to say that statistical analysis and the scientific method more generally are best used as limited tools. Unfortunately these tools were so mind-bogglingly, world-shatteringly powerful our ancestors couldn't help but violently wrench the entirety of human society to serve the tools, and make them more effective. Now we can't even use the tools properly, because the masses of society don't understand that these methods aren't the exact same thing as divine messengers serving up Truth from the heavens.

And so the wheel turns. At least soon we'll have artificial intelligence to turn the wheel for us.

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