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Algorithmic Monocultures in Hiring

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21–30 of 177 posts

Re: Algorithmic Monocultures in Hiring

#21
> Using our large dataset of real hiring AI recommendations, we test our hypothesis. We find that people who submit multiple applications to positions screened by the same algorithmic hiring vendor are more likely to be rejected from every position to which they apply than would be true if the companies made decisions statistically independently from one another.

I would be surprised if the results were different.

Re: Algorithmic Monocultures in Hiring

#23
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?

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

Re: Algorithmic Monocultures in Hiring

#24
Did I miss the part of the article where they break down how they determined race? Is the algorithm blind to race? It looks like they specifically looked at 83k people applying to ~100 companies which notably were Fortune 500 companies. Could there simply be candidate discrepancies here? Hard for me to follow the full methodology but it doesn't necessarily seem either malicious or that well structured. Don't you need to have a control group of applicants who are similar on paper? To allege DISCRIMINATION is quite bold.

Definitely open to opposing or critical views

Re: Algorithmic Monocultures in Hiring

#25
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?

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...

Re: Algorithmic Monocultures in Hiring

#26
post #5

Some job application websites I've seen actually have a yes or no option to consent to AI review that they claim is to simply assist HR and not actually screen you. I always select no. There is no way that selecting yes would ever be in my interest. I'm sorry, I'm going to force a real human to look at my stuff if I still can.

[dead]

Re: Algorithmic Monocultures in Hiring

#27
Would be very interested to see how this affects post-50 workers. That's a protected class and I would imagine an ambulance chasing lawyer would be excited for a class action lawsuit.

Re: Algorithmic Monocultures in Hiring

#28
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.

Re: Algorithmic Monocultures in Hiring

#29
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?

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.

Re: Algorithmic Monocultures in Hiring

#30
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?

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.

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