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Algorithmic Monocultures in Hiring

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Re: Algorithmic Monocultures in Hiring

#71
post #17

> To measure adverse impact, we apply the EEOC’s “four-fifths rule,” which flags a position when one group is recommended at less than 80% of the rate of the most-recommended group That seems like a nonsensical way to measure racial discrimination. What could justify it?

The desire to subsidize employment for Democratic constituencies by threatening legal action if they aren't given enough jobs.

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Re: Algorithmic Monocultures in Hiring

#74

Could the AI actually see the race of the applicants? Or was it just discriminating on the basis of some factor it found that was correlated with race, like SAT scores?

> discriminating on the basis of some factor it found that was correlated with race, like SAT scores

Hypothetical SAT score: 1060

How does that help you predict the race of an individual applicant? It's been a while since I took the SAT, but I didn't realize one's score provided so much information.

Re: Algorithmic Monocultures in Hiring

#75

Earlier quoted context omitted.

Importantly, the rule is not used to resolve racial discrimination claims. It's purely meant as the first test to evaluate whether a deeper dive is warranted. Fast, first pass data analysis tools are very useful for spotting unintended consequences.

You are selectively adhering to the letter of the law, when the practical effects are already well known and studied. One is not obligated to ignore literature, nor abstain from doing a simple extrapolation from the incentives placed on the table. There is a large body of literature concerning the question "does disparate-impact enforcement cause employers to alter hiring behavior in ways unrelated to actual producti…

That's not particularly surprising nor objectionable, of course legislation that reminds employers they shouldn't discriminate based on race changes practice even for companies that aren't actually caught doing it.

To act like it's bad that people of colour have a more fair chance of getting employed because of some piece of legislation is simply insidious. It's just been over a month since black people lost the right to a fair vote.

Re: Algorithmic Monocultures in Hiring

#76

I’m sure (really sure) there are real problems with AI and bias, but this is a weird study that isn’t looking at resumes or anything, it’s looking at how candidates did in some weird psychometric tests.

Double check the link. The study clearly looked at resumes.

I’ve rechecked it, and I still think I’m right. What am I missing? This is the paper under discussion: https://arxiv.org/pdf/2605.27371

Re: Algorithmic Monocultures in Hiring

#77
post #63

Many people seem to think racism begins and ends with using a slur. You can usually get a measure of this by seeing someone's reaction to the statement: > There is no such thing as anti-white racism. If you find yourself wanting to disagree with that then, I'm sorry but you simply don't know what racism is. Racism is pervasive, insidious and systemic. A good example in the hiring space is what's called the "second sy…

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Re: Algorithmic Monocultures in Hiring

#78

[flagged]

> These results are consistent with AI hiring tools being completely racially unbiased, and real-world hiring managers feeling social pressure to hire underqualified black people And so managers are feeling social pressure to hire under qualified Asians as well? I must not be up to date on the latest culture war talking points, because I thought Asians were underrepresented.

Yeah, if they themselves are asian. One of the most prevalent complaints about Indian hiring managers in the silicon valley tech industry is that they preferentially hire Indians and push out non-Indians to a tremendous degree, and are often helping Indian hires commit pretty blatant credential fraud.

Re: Algorithmic Monocultures in Hiring

#79
post #39
post #32

Earlier quoted context omitted.

Thanks. I read the article: > Since the 80% test does not involve probability distributions to determine whether the disparity is a “beyond chance” occurrence, it is usually not regarded as a definitive test for adverse impact. Instead, other statistically significance tests, such as the standard deviation analysis, may be used for this purpose. But then my question recurs: isn’t this a ridiculous way to measure disc…

How would you like me to define "starting point" in a way that you believe you'll be able to understand? If you are trying to say "more data needed, headline misleading" you should say that instead of misrepresenting the 4/5ths rule. Also the word "can" implies uncertainty of conclusion. This isn't ridiculous, the authors point out that this is the first large scale study of this topic. Nothing has been "proven" here…

You could be an Iranian sponsored bot. I'm not saying you are. You could be so don't get mad at me for publishing that statement. Because if I say "can," then I don't need to be accountable for any misinformation.

Re: Algorithmic Monocultures in Hiring

#80
post #17

> To measure adverse impact, we apply the EEOC’s “four-fifths rule,” which flags a position when one group is recommended at less than 80% of the rate of the most-recommended group That seems like a nonsensical way to measure racial discrimination. What could justify it?

>What could justify it? The assumption that applicants from all races are on average equally qualified for every position. Whole subfields of modern academia are based on that assumption.

Unless you believe that Black people are racially inferior, I think this is simply evidence of racial discrimination at a systemic level, from education through employment. AI merely reenforces the systems built to favor white people.
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