A benchmark of LLMs versus a proprietary hiring model on ~10,000 real candidate-job pairs reports the proprietary model wins on accuracy and fairness, while all tested LLMs show racial and intersectional bias.
On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pages 610--623, 2021
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Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions
A benchmark of LLMs versus a proprietary hiring model on ~10,000 real candidate-job pairs reports the proprietary model wins on accuracy and fairness, while all tested LLMs show racial and intersectional bias.