Sources and mechanisms of trust in automated news: a comparative cross-cultural perspective

The use of artificial intelligence in journalism has raised concerns such as algorithm-driven sensationalism, algorithmic bias, and the dissemination of false information, which could threaten public trust in journalists and the news industry. This study examined how three cognitive heuristics, namely institution-based, innovation-focused, and human-centered beliefs, are related to public trust in automated news across two countries, as well as the underlying trust-building mechanisms. Following the Human-Computer Trust Model, a survey (N = 730) of adults in China and the United States was conducted. Structural equation modeling demonstrated that people’s trust in traditional media institutions transferred to their trust in automated news for both Chinese and U.S. participants. Innovation-focused beliefs were negatively associated with trust in automated news for Chinese participants but not for U.S. participants. Finally, the findings showed an indirect relationship between human-centered beliefs and trust in automated news mediated by greater perceived reciprocity for Chinese participants.