Algorithmic Monocultures in Hiring · HackerPapers discussions

Algorithmic Monocultures in Hiring — mentioned by nyrikki

Wed, 24 Jun 2026 03:47:36 GMT

Capitulation is a bad counterpropaganda tactic, especially with terms that have well defined domain specific meanings. Note that the OP uses "systemic rejection", while the paper does reference bias, it is in the precise meaning of the word.[0] And this is not targeted at the general public. You may want to look into the 1990 GOPAC handout "Language: A Key Mechanism of Control" to understand why some groups would simply just weaponize any term that was substituted. Academic papers need to error on being precise, to be effective, not focused on handling the general public with kids gloves…

Paper and discussion history. A mention is not an endorsement.

Algorithmic Monocultures in Hiring — mentioned by petesergeant

Tue, 23 Jun 2026 21:21:32 GMT

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

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Algorithmic Monocultures in Hiring — mentioned by rayiner

Tue, 23 Jun 2026 21:11:40 GMT

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…

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Algorithmic Monocultures in Hiring — mentioned by Oras

Tue, 23 Jun 2026 21:03:38 GMT

Misleading title the paper [0] does not mention any CV screening that might suggest racial or gender bias. It is purely about assessment tool. No AI or LLMs. I'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…

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Algorithmic Monocultures in Hiring — mentioned by verteu

Tue, 23 Jun 2026 20:32:01 GMT

The paper is here: https://arxiv.org/pdf/2605.27371 They find "disparate impact" of pymetrics across racial groups, but it doesn't seem like they controlled for anything.

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Algorithmic Monocultures in Hiring — HN submission

Tue, 23 Jun 2026 18:56:19 GMT

Algorithmic Monocultures in Hiring

https://algorithmichiring.github.io/ https://arxiv.org/abs/2605.27371

154 points; 160 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Algorithmic Monocultures in Hiring — mentioned by madcaptenor

Mon, 08 Jun 2026 12:53:20 GMT

From a glance at the paper (https://arxiv.org/pdf/2605.27371) it looks like they're using self-reported ethnicity. "We only attempt to identify adverse impact based on self-reported racial information and do not impute data, noting that we do not have access to features like applicant name. 62.35% of all applicants in the data do not self-report race as belonging to one of the four racial groups we study."

Paper and discussion history. A mention is not an endorsement.