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Evidence record 5072 · automatically gathered

AI Alignment Amplifies the Role of Race, Gender, and Disability in Hiring Decisions

Humans increasingly delegate decisions to language models, yet whether these systems reproduce or reshape human patterns of discrimination remains unclear. Here we run a large-scale study to analyse whether language models use demographic information in hiring decisions. We show, across 27 models and 177 occupations, that language models give female and Black candidates hiring advantages relative to otherwise-comparable male and white candidates, while giving disabled candidates disadvantages. T

Record details

Published: 2 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Same publisher byline · Shared topic: Bias & fairness

AI Alignment Amplifies the Role of Race, Gender, and Disability in Hiring Decisions

arXiv cs.CY · 16 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels

arXiv · 2 May 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

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arXiv · 1 May 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

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arXiv · 3 May 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

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arXiv · 4 May 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

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How to cite this record

ethics.ai (2 May 2026), “AI Alignment Amplifies the Role of Race, Gender, and Disability in Hiring Decisions,” evidence record 5072, https://ethics.ai/record/5072 (originally published by arXiv).

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