Irrelevant Alternatives Bias Large Language Model Hiring Decisions
- URL: http://arxiv.org/abs/2409.15299v1
- Date: Wed, 4 Sep 2024 10:37:36 GMT
- Title: Irrelevant Alternatives Bias Large Language Model Hiring Decisions
- Authors: Kremena Valkanova, Pencho Yordanov,
- Abstract summary: The attraction effect occurs when the presence of an inferior candidate makes a superior candidate more appealing.
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.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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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