GenAI Misinformation, Trust, and News Consumption: Evidence from a Field Experiment

Filipe Campante, Ruben Durante, Felix Hagemeister and Ananya Sen

No 20526, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We study how AI-generated misinformation affects demand for trustworthy news, using data from a field experiment by a major German outlet, Süddeutsche Zeitung (SZ). Readers were randomly assigned to a treatment highlighting the challenge of distinguishing real from AI-generated images. The treatment raised concern with misinformation (0.3 s.d.) and reduced trust in news (0.1 s.d.), including SZ. Importantly, it affected post-survey browsing behavior: daily visits to SZ digital content rose by 2.5% in the immediate aftermath of the treatment. Moreover, we find that subscriber retention increased by 1.1% after five months, corresponding to about a one-third drop in attrition rate. Results are consistent with a model where the relative value of trustworthy news sources increases with the prevalence of misinformation, which may thus boost engagement with those sources even while lowering trust in news content.

Keywords: Generative AI; Misinformation; News media; Trust (search for similar items in EconPapers)
JEL-codes: D12 L82 L86 (search for similar items in EconPapers)
Date: 2025-08
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