Seeing and Hearing: The Influence of AI-Generated Political Media on Public Trust and Intentions

Abstract

Artificial Intelligence (AI) is reshaping political communication through deepfakes, synthetic voices, and manipulated images. While promising for engagement, these media also raise concerns around misinformation and public trust. This study experimentally examines how different AI-generated media formats (image, video, audio) and realism levels affect trust and political decision-making. Results from Linear Mixed Models and Natural Language Processing reveal that audio content is perceived as more trustworthy than video or images, supporting cognitive load theory. High realism enhances trustworthiness, while increased excitement may reduce skepticism, making audiences more persuadable. Though generalizability is limited by the controlled setting, the findings offer novel insight into how AI-generated political content influences perception and behavior. This research contributes to political communication and media psychology by highlighting both the persuasive power and ethical risks of AI in digital politics.