AI Credibility Signals Outrank Institutions and Engagement in Shaping News Perception on Social Media
This addresses the problem of misinformation and trust in online news for the public, with incremental insights into AI's role in shaping perceptions.
The study tackled how AI-generated credibility scores affect user perception of political news, finding that AI feedback significantly moderates partisan bias and institutional distrust, surpassing traditional engagement signals like likes and shares in a large-scale experiment with 1,000 participants.
AI-generated content is rapidly becoming a salient component of online information ecosystems, yet its influence on public trust and epistemic judgments remains poorly understood. We present a large-scale mixed-design experiment (N = 1,000) investigating how AI-generated credibility scores affect user perception of political news. Our results reveal that AI feedback significantly moderates partisan bias and institutional distrust, surpassing traditional engagement signals such as likes and shares. These findings demonstrate the persuasive power of generative AI and suggest a need for design strategies that balance epistemic influence with user autonomy.