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arXiv · 2409.15299

Irrelevant Alternatives Bias Large Language Model Hiring Decisions

Kremena Valkanova·Pencho Yordanov
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Abstract

We investigate whether LLMs display a well-known human cognitive bias, the attraction effect, in hiring decisions. The attraction effect occurs when the presence of an inferior candidate makes a superior candidate more appealing, increasing the likelihood of the superior candidate being chosen over a non-dominated competitor. Our study finds consistent and significant evidence of the attraction effect in GPT-3.5 and GPT-4 when they assume the role of a recruiter. Irrelevant attributes of the decoy, such as its gender, further amplify the observed bias. GPT-4 exhibits greater bias variation than GPT-3.5. Our findings remain robust even when warnings against the decoy effect are included and the recruiter role definition is varied.

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Kremena Valkanova, Pencho Yordanov. 2024-09-04. Irrelevant Alternatives Bias Large Language Model Hiring Decisions. https://doi.org/10.18653/v1/2024.findings-emnlp.405

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