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LLMs show pro-female hiring bias in Japan, name removal key mitigation · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

A new study reveals that large language models exhibit a pro-female gender bias in hiring decisions, even within a Japanese corporate context using rirekisho-format resumes. Researchers tested five state-of-the-art LLMs, including Claude Sonnet 4.6, GPT-4o, DeepSeek-V3, Gemini 2.5-Flash, and Llama 3.3-70B, across 43,200 API calls. While a prompt-level gender-neutrality instruction did not significantly reduce bias, removing candidate names from the prompt nearly eliminated the pro-female effect, identifying names as the primary gender channel. The study also noted a practical deployment challenge with GPT-4o's content safety filter causing a high refusal rate during name anonymization attempts. AI

IMPACT Highlights the need for careful LLM deployment in recruitment to avoid perpetuating gender bias, particularly concerning candidate identification.

RANK_REASON The cluster contains an academic paper detailing research findings on LLM bias.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLMs show pro-female hiring bias in Japan, name removal key mitigation · 2 sources tracked

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Serena A. Hoffstedde, Machiko Hirota, Akshara Nadayanur Sathis Kanna, Rihito Kotani, Ujwal Kumar, Gabriele Trovato, Phan Xuan Tan ·

    Gender Bias in LLM Hiring Decisions: Evidence from a Japanese Context and Evaluation of Mitigation Strategies

    arXiv:2606.18649v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in hiring workflows, yet most research on gender bias in LLM hiring decisions has focused on English-language, Western-format resumes. This study examines whether pro-female g…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Phan Xuan Tan ·

    Gender Bias in LLM Hiring Decisions: Evidence from a Japanese Context and Evaluation of Mitigation Strategies

    Large language models (LLMs) are increasingly deployed in hiring workflows, yet most research on gender bias in LLM hiring decisions has focused on English-language, Western-format resumes. This study examines whether pro-female gender bias extends to a Japanese corporate context…

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