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This study examines U.S. news audiences’ trust in AI-generated journalism across three dimensions: editorial workflow stages, computational data structure (structured vs. unstructured), and geographic scope (local vs. national). Using a nationally quota-sampled survey (N = 1,506), we find that audiences trust AI-generated journalism involving structured data (e.g. weather reports, election results) more than unstructured data (e.g. opinion pieces, feature stories). Trust in local and national newsrooms predicts trust in AI journalism, while minimal variation across editorial workflow stages suggests audiences evaluate AI journalism by output type rather than production process. These findings establish baseline evidence for future research on AI use in journalism and media transparency.
Paik et al. (Fri,) studied this question.