How Artificial Intelligence Can Influence Elections: Analyzing the Large Language Models (LLMs) Political Bias

Abstract

Abstract The rise of large language models (LLMs) such as ChatGPT and Gemini has raised concerns about their potential political biases and the implications for information dissemination and user influence. This study aims to measure the degree of political bias inherent in major LLMs by analyzing their responses to a standardized set of questions rating the quality and bias of popular news websites. Employing a systematic methodology, we queried both free and paid versions of ChatGPT and Gemini to rate news outlets on criteria such as authority, credibility, and objectivity. Results revealed that while all LLMs displayed a tendency to score left-leaning news sources higher, there was a notable difference between free and premium models in their assessment of subjectivity and bias. Furthermore, a comparison between the models indicated that premium versions offered more nuanced responses, suggesting a greater awareness of bias. The findings suggest that LLMs, despite their objective façade, are influenced by biases that can shape public opinion, underlining the necessity for efforts to mitigate these biases. This research highlights the importance of transparency and the potential impact of LLMs on the political landscape.