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

GenAI Misinformation, Trust, and News Consumption: Evidence from a Field Experiment (2025)
with Ruben Durante, Felix Hagemeister, and Ananya Sen. Revise & Resubmit, Journal of Political Economy [Online Article] [PDF]
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.

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