Ethics First: How Trust and Political Contexts Shape Public Acceptance of AI-Generated News Across Twenty-four Countries

Abstract

As generative artificial intelligence (AI) reshapes news production, understanding what drives global audiences to accept AI-generated news is critical. Existing research largely adopts a competence-based perspective, neglecting the complex role of trust dimensions and macro-political contexts. This study examines how AI self-efficacy interacts with two distinct dimensions of trust (competence trust and ethical trust) to shape acceptance of AI-generated news, and how these relationships vary across political environments. Analyzing survey data from 24,000 respondents across twenty-four countries, we find that ethical trust is a substantially stronger predictor of acceptance than competence trust, while AI self-efficacy promotes acceptance only when ethical trust is high. Multilevel analysis incorporating national-level indicators (press freedom, regime type, and AI readiness) reveals that the relationship between ethical trust and acceptance is stronger in open, liberal democratic, and technologically ready societies. These findings suggest that the legitimacy of AI-generated news is more strongly associated with audiences’ ethical evaluations of AI systems than with perceived technical capability, and that this association is shaped by the normative expectations that different political contexts cultivate.

Keywords

AI-generated news AI self-efficacy ethical trust competence trust political regimes cross-national survey multilevel analysis

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