LLMs Show Gender Bias in Job Candidate Selection

A study involving 22 leading Large Language Models (LLMs) reveals a consistent bias towards female candidates in job selection tasks. Even with identical resumes except for gendered names, LLMs favored female candidates across 70 professions. This bias persisted even when gender was explicitly stated or masked with neutral labels. The study highlights the presence of gender bias in LLMs and raises concerns about their use in high-stakes decision-making like hiring, emphasizing the need for thorough model scrutiny before deployment.