OpenAI has introduced a comprehensive framework to evaluate political bias in its large language models (LLMs), aiming to bolster public trust and transparency. In a blog post titled “Defining and Evaluating Political Bias in LLMs,” OpenAI shares its methodology of using around 500 prompts across 100 topics, designed to reflect realistic user interactions. The framework identifies five bias axes: user invalidation, escalation, personal political expression, asymmetric coverage, and political refusal. Though bias is generally rare, it can emerge under emotionally charged prompts, with newer models like GPT-5 showing a ~30% improvement in bias scores compared to earlier versions. OpenAI’s internal audit reveals that less than 0.01% of responses display political bias, often manifesting as subtle distortions rather than overt advocacy. As LLMs integrate into products, managing perceived bias is crucial for maintaining reputation and regulatory compliance, prompting OpenAI to encourage industry-wide collaboration in addressing this challenge.
Source link
