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> 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 mo
by dash2 4mo ago
> 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?
- nemomarx 4mo agoI 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
- moate 4mo agoIt'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-analysis-four-fifths-rule/ https://www.prevuehr.com/resources/insights/adverse-impact-a...
- dash2 4mo agoThanks. 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 4mo agoIt'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 4mo agoYou 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
- dash2 4mo agoRight, but what I meant was: the other tests that the article says are used for definitively proving discrimination are equally bad, and subject to the same objection. Just substituting “one standard deviation“ or “statistical significance“for “80%“ doesn’t fix the fundamental problem here, which is that there are unmeasured confounders.
- moate 4mo agoHow 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 4mo agoYou 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.
- moate 4mo agoI could be! And in science when you posit a hypothesis you then back it up with data points of statistical significance. The authors of this study have done that here. To borrow from your example, if you saw a statistically significant amount of my posts highlighting the merits of the Iranian government in a ways that run counter to the general global consensus of their actions, you would then have something that other people might agree was worth looking into. A hypothesis is not “misinformation”. This article has not claimed to have proven anything other than outcomes in a process. I don’t understand why this is so upsetting to you.
- kolbe 4mo agoI don't know who you think you're talking to about being upset, but this was exactly the halfwitted "u maaaad" response I would expect from a bot.
- logicchains 4mo ago>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.
- sdellis 4mo agoUnless 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.
- adammarples 4mo agoThere are many other potential explanatory factors than your simple binary. Black people in America started in a very bad and difficult position, only a few generations ago, with huge racial discrimination, no money, and generational distrust of institutions. That is a factor that will affect what you see today without any current system of racial discrimination or inferiority.
- sdellis 4mo agoIf I hear you correctly, the lack of reparations toward Black people in America is more to blame for the discrepancy than systemic racism? Perhaps it could be both? I am getting downvoted because it's hard to admit that AI only reinforces the culture that it is trained on. It is the perfect technology to keep systemic racism in place, all while being the perfect scapegoat for lack of personal or corporate accountability.
- mstewartgallus 4mo agoThe failure of land reform in reconstruction really fucked things up a lot.
- 59percentmore 4mo agoThe assumption is that no one has the authority to decide that all races aren't equally qualified for every position.
- gacgacgac 4mo agoHave 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 4mo agoYour 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 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.
- paisawalla 4mo agoThis 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.
- gacgacgac 4mo agoImportantly, 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.
- paisawalla 4mo agoYou 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.
- runako 4mo ago> 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 4mo agoYou'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.
- poplarsol 4mo agoThe desire to subsidize employment for Democratic constituencies by threatening legal action if they aren't given enough jobs.
- throwaway62844 4mo ago[flagged]
- lazide 4mo ago‘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.