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Gender, Race, and Intersectional Bias in Resume Screening via Language Model (www.geekwire.com)
submitted 1 month ago by Gaywallet@beehaw.org to c/technology@beehaw.org
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Direct link to paper: https://ojs.aaai.org/index.php/AIES/article/view/31748/33915

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[-] GenderNeutralBro@lemmy.sdf.org 7 points 1 month ago

Interesting read, thanks! I'll finish it later, but already this bit is quite interesting:

Without access to gender, the ML algorithm over-predicts women to default compared to their true default rate, while the rate for men is accurate. Adding gender to the ML algorithm corrects for this and the gap in prediction accuracy for men and women who default diminishes.

this post was submitted on 01 Nov 2024
31 points (100.0% liked)

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