Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)

Understand

The burgeoning influence of Large Language Models (LLMs) in shaping public discourse and decision-making underscores the imperative to address inherent biases within these AI systems.

• In the wake of AI's expansive integration across sectors, addressing racial bias in LLMs has never been more critical.
• This paper introduces a novel framework called Comprehensive Bias Neutralization Framework (CBNF) which embodies an innovative approach to quantifying and mitigating biases within LLMs.
• Our framework combines the Large Language Model Bias Index (LLMBI) [Oketunji, A., Anas, M., Saina, D., (2023)] and Bias removaL with No Demographics (BLIND) [Orgad, H., Belinkov, Y.