Political Bias

Political bias in large language models (LLMs) is a burgeoning research area focused on identifying and mitigating the ideological leanings embedded within these systems. Current research utilizes various methods, including analyzing LLM responses to political prompts, comparing outputs across different languages and datasets, and employing techniques like parameter-efficient fine-tuning to align models with diverse viewpoints. Understanding and addressing this bias is crucial because LLMs are increasingly used in information dissemination and decision-making processes, potentially influencing public opinion and societal outcomes.