ACL 2025finding0 citations
The Impact of Name Age Perception on Job Recommendations in LLMs
Mahammed Kamruzzaman, Gene Louis Kim
Abstract
Names often carry generational connotations, with certain names stereotypically associated with younger or older age groups. This study examines implicit age-related name bias in LLMs used for job recommendations. Analyzing six LLMs and 117 American names categorized by perceived age across 30 occupations, we find systematic bias: older-sounding names are favored for senior roles, while younger-sounding names are linked to youth-dominant jobs, reinforcing generational stereotypes. We also find that this bias is based on perceived rather than real ages associated with the names.
BibTeX
@inproceedings{kamruzzaman-kim-2025-impact,
title = "The Impact of Name Age Perception on Job Recommendations in {LLM}s",
author = "Kamruzzaman, Mahammed and
Kim, Gene Louis",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.778/",
doi = "10.18653/v1/2025.findings-acl.778",
pages = "15033--15058",
ISBN = "979-8-89176-256-5"
}