Echoes of Power: Investigating Geopolitical Bias in US and China Large Language Models
This work addresses concerns about AI influencing public opinion in politically sensitive contexts, though it is incremental as it applies existing bias analysis methods to new geopolitical data.
The study investigated geopolitical biases in US and Chinese large language models (ChatGPT and DeepSeek) by analyzing their responses to geopolitical questions, finding notable biases reflecting distinct ideological perspectives, but also unexpected alignment in some cases.
Large Language Models (LLMs) have emerged as powerful tools for generating human-like text, transforming human-machine interactions. However, their widespread adoption has raised concerns about their potential to influence public opinion and shape political narratives. In this work, we investigate the geopolitical biases in US and Chinese LLMs, focusing on how these models respond to questions related to geopolitics and international relations. We collected responses from ChatGPT and DeepSeek to a set of geopolitical questions and evaluated their outputs through both qualitative and quantitative analyses. Our findings show notable biases in both models, reflecting distinct ideological perspectives and cultural influences. However, despite these biases, for a set of questions, the models' responses are more aligned than expected, indicating that they can address sensitive topics without necessarily presenting directly opposing viewpoints. This study highlights the potential of LLMs to shape public discourse and underscores the importance of critically assessing AI-generated content, particularly in politically sensitive contexts.