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?
Algorithmic Monocultures in Hiring
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Re: Algorithmic Monocultures in Hiring
#52Could 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?
The paper's conclusion, that we need to study this more, is showing the authors likely believe this to be a byproduct of inherent/invisible bias.
Re: Algorithmic Monocultures in Hiring
#53I'm struggling to figure out what they're trying to say here in the linked (and very anemic) paper: > 30% of Black applicants apply to at least one position that demonstrates adverse impact against Black applicants. The whole thing reads like a tautology.
Re: Algorithmic Monocultures in Hiring
#54Could 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?
Name. Other factors were controlled.
Re: Algorithmic Monocultures in Hiring
#55> To put this in perspective: If the AI had recommended Black and Asian candidates at the same rate as it recommended the most-favored group (typically white applicants) Some people just can't help but put their biases on display at every opportunity, even when it comes to the most minute details.
Re: Algorithmic Monocultures in Hiring
#56Re: Algorithmic Monocultures in Hiring
#57I’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.
Re: Algorithmic Monocultures in Hiring
#58I'm not saying AI is not biased, but this study does not prove that.
[0] https://arxiv.org/pdf/2605.27371
From the paper:
> Fig. 1. The pymetrics process. > Stage 1: Applicants apply to positions. > Stage 2: Applicants are directed to the pymetrics platform to play assessment games. > Stage 3: pymetrics algorithms use applicant gameplay features to recommend 58.2% of applicants per position on average. > Stage 4: Employers decide which applicants to interview or hire, typically rejecting applicants that were not recommended by pymetrics.
Re: Algorithmic Monocultures in Hiring
#59We can't take blanket percentages as a reason for racial bias. Were they all equally qualified? Too many of these studies only focus on percentages and the end result is unqualified candidates getting hired from minority groups at the expense of qualified ones.
Please read the study or at least the comments here before jumping to the conclusion. Yes, they used constructed resumes, so the qualifications were exactly the same. And no, literally no one is suggesting this proves racial discrimination. It's applying the four fifths rule, a fast, coarse evaluation that is used to identify if maybe theres worth investigating more for a conclusive evidence of racial discrimination.…
Looks like you didn't read the paper. There are no resumes involved. It is about assessment games.
Re: Algorithmic Monocultures in Hiring
#60[flagged]