AGENTIC-SYSTEMSApril 3, 20261 min read13 views

Quantifying Gender Bias in Large Language Models: When ChatGPT Becomes a Hiring Manager

A new study quantifies gender bias in LLMs acting as hiring managers, revealing a paradox where female candidates are perceived as more qualified yet receive lower salary recommendations than their male counterparts.

Computer Science > Computers and Society

Title:Quantifying Gender Bias in Large Language Models: When ChatGPT Becomes a Hiring Manager

View PDF HTML (experimental)Abstract:The growing prominence of large language models (LLMs) in daily life has heightened concerns that LLMs exhibit many of the same gender-related biases as their creators. In the context of hiring decisions, we quantify the degree to which LLMs perpetuate societal biases and investigate prompt engineering as a bias mitigation technique. Our findings suggest that for a given resumé, an LLM is more likely to hire a female candidate and perceive them as more qualified, but still recommends lower pay relative to male candidates.

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Source: arXiv cs.AI Recent

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