Inherent Bias in Large Language Models: A Random Sampling Analysis

Abstract

<.05). Nondescript physicians favored White, male, and young demographic characteristics. The male doctor gravitated toward the male, White, and young, whereas the female doctor typically preferred female, young, and White patients. In addition to saving patients with their own political affiliation, Democratic physicians favored Black and female patients, whereas Republicans preferred White and male demographic characteristics. Heterosexual and gay/lesbian physicians frequently saved patients of similar sexual orientation. Overall, publicly available chatbot LLMs demonstrate significant biases, which may negatively impact patient outcomes if used to support clinical care decisions without appropriate precautions.

Ähnliche Arbeiten