Silicon Sonnets

Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting

January 30, 2024
Silicon Sonnets
Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting
Show Notes

This study investigates gender bias in Large Language Models (LLMs) using Chain-of-Thought (CoT) prompting for tasks like word counting. CoT prompting reduces unconscious social bias in LLMs, leading to fairer predictions. The research highlights the importance of step-by-step predictions in mitigating bias in LLMs.