Evaluation of Hiring Bias in Large Language Models

This project aims to investigate biases in Large Language Models (LLMs) when processing resumes. Specifically, we focus on examining potential biases related to gender, ethnicity, and age. By evaluating vari- ous LLMs of various sizes we seek to uncover any disparities in how they handle resume data based on these factors. This research contributes to a better understanding of biases inherent in LLMs and their implications for fair recruitment and employment practices.