[dash2]

> 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?

[gacgacgac]

Have you googled this? The EEOC is a federal agency, and they've published on this topic quite extensively. The four fifths rule is used to define if there is a "substantially different selection rate". It does not measure racial discrimination. It measures selection rate.

It indicates there may be adverse impact to one group. It specifically is not used to resolve racial discrimination.

It's purely a signal for "we should consider asking more questions, because this appears unusual". That's what your quote says too, it "flags" a low recommendation -- it's indicating further study and investigation is likely warranted.

[rayiner]

Your summary of the EEOC guidance is correct. The problem is that the study here is using the four-fifths rule as a measurement of discrimination, instead of as a flag that triggers further investigation. It's in section 3.1 of the paper: https://arxiv.org/pdf/2605.27371.

"Adverse impact occurs when there is (i) practically and (ii) statistically significant disparities in the selection rate for the group of interest when compared against the selection rate ′ of the most selected group ′ . Practical significance requires the impact ratio ... to be less than 0.8, which is why the EEOC guidance is colloquially referred to as the 'four-fifths' rule."

The headline numbers reflect the positions for which the 4/5 rule was triggered, not the result of some further investigation: “We discovered that 26% of Black applicants and 15% of Asian applicants applied to positions where the AI system discriminated against their racial group.” Based on the methodology, I think that means that 26% of black applicants applied to positions that were flagged under the 4/5ths rule.

[nemomarx]

I guess it measures if there's more than one std deviation gap between highest and lowest? Assuming that's twenty percent here

it sounds like how you'd get that kind of metric at least

[lazide]

‘Every one is the same’, even when one group or another doesn’t like doing some kind of work for some reason.

Because surely no one would have legitimate preferences based on their gender, cultural norms, etc. or real differences in aptitude due to childhood exposure, education, or said norms and preferences.

[paisawalla]

This is an application of the disparate impact doctrine. Even facially neutral policies are considered suspect if they produce results that correlate against protected groups, irrespective of intent.

This doctrine is the basis for much of employment law. It is a significant reason why employers don't administer IQ tests (or equivalents) to screen candidates since ~the 90s.

A common objection to the doctrine is that it leads to unfalsifiable discrimination claims, which is why it seems nonsensical to you.

[59percentmore]

And a common rebuttal to the objection is that systemic racism is often difficult to untangle in a way that produces a neat chain of cause and effect (not least of which because discrimination can happen unconsciously or secretly); because the impact exists whether intent can be shown or not, the desire remains to ameliorate that impact.

If the issue happens upstream of the defendant to a claim - generally an organization being sued by an individual with fewer resources - it incentivizes such entities to push for changes upstream, so that they don't get stuck with the bill.

[paisawalla]

What evidence would disprove the claim that systemic racism is the cause of a persistent disparity?

[pc86]

Why is this the one time someone is expected to disprove a claim rather than the claimant being expected to provide evidence?

If you're making the claim you need to provide the evidence.

Most people would say that a persistent disparity means it's possible there is discrimination, but it's not definitive proof.

[gacgacgac]

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.

[Manuel_D]

To the contrary, companies have been found liable for discrimination solely based on having the wrong percentages outcomes in its objective hiring assessments: https://en.wikipedia.org/wiki/Griggs_v._Duke_Power_Co.

[paisawalla]

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 productivity or discrimination?" and the answer is largely "yes". As you suggested elsewhere in this discussion, Google may be useful.

[SiempreViernes]

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.

[rayiner]

> It's just been over a month since black people lost the right to a fair vote.

Literally the opposite happened. The Supreme Court ruled that there was VRA §2 liability when there was evidence of racially-motivated gerrymandering: "In short, §2 imposes liability only when the evidence supports a strong inference that the State intentionally drew its districts to afford minority voters less opportunity because of their race." (Louisiana v. Callais, p. 26)

[paisawalla]

I don't start from the conclusion that disparities are evidence of racism.

[runako]

> selectively adhering to the letter of the law

Are you suggesting that companies should violate the law here? What do you recommend?

Edit: charitably, "adhering to the letter of the law" is sometimes shortened to "law-abiding" and is generally what we want.

[paisawalla]

You've misunderstood the point.

Prior to the beginning of your excerpt is the word "You", meaning the comment's author is the subject, not "companies". I'm saying the commenter is appealing to black letter law for the answer to the question "what happens when..." but we have observational evidence to answer the question.

[logicchains]

>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.

[aenis]

I am wondering - if in those circles, questions such as 'is NBA intentionally discriminating against asians - or is the fact that long distance running is dominated by, say, Ethiopians an example of discrimination' are ever discussed - or declared taboo and racist? I don't doubt that the assumption is just plain, demonstrably wrong - we all evolved under different types of environmental pressures - I am just wondering if the proponents of the all-the-races-are-same-on-average are ever discussing those obvious facts, and what answers do they come up with to explain the, say, unfair underrepresentation of Japanese in the NBA.

[59percentmore]

The assumption is that no one has the authority to decide that all races aren't equally qualified for every position.

[xp84]

"Races" aren't qualified for anything. Neither are star signs or favorite Hogwarts houses.

Individuals are qualified or unqualified. If a company happens to end up with less than 1/4 Ravenclaws or not very many Virgos, it doesn't mean hate is a reason. It could be that the Ravenclaws that applied were a bit less qualified than those from the other houses.

I guess my point is, doing the statistical analysis for race and gender and drawing conclusions, while being completely blind to the one single factor any sane hiring manager should be focusing on -- actual qualifications for the role -- doesn't make any sense.

[avadodin]

It could make sense if one was looking to make interventions early on before the candidates reach the selection process.

Don't claim AI is discriminating against non–selects, though.

I doubt companies are using Gr*k to make their hiring decisions.

[sdellis]

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.

[moate]

It's a starting point to flag.

Here's some analysis of what it is and why it's useful as a canary in the coal mine: https://www.prevuehr.com/resources/insights/adverse-impact-a...

[dash2]

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 discrimination? It’s assuming that the only thing that differs between the different ethnic applicant pools is their ethnicity, which is essentially never going to be true.

[gacgacgac]

It's not used to measure discrimination. It's used to identify outcomes that appear to be potentially discriminatory. You have to do the legwork afterwards.

Like. If I am evaluating a developer on lines of code written, I am a bad manager. But if an engineer has 40% fewer lines of code than the team median, it's absolutely ok for me to go, "Interesting. What's the story there? Are they slower or is there some other factor?"

Same idea -- this is purely a fast, first pass metric that can quickly assess if something warrants a deeper evaluation.

[blharr]

You are correct, but especially in current day that analogy is quite bad.

I expect Median LoC might be very high with the average developer using AI these days... but the dev who is making atomic changes that are fixing the AI output is probably tiny LoC but way more important

[moate]

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, it's showing that this warrants further investigation and attention.

Do you read many academic papers, because you seem to be having a rough go here.

[kolbe]

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.

[poplarsol]

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