AI Images, Labels and News Demand

Maja Adena, Eleonora Alabrese, Francesco Capozza and Isabelle Leader

No 12277, CESifo Working Paper Series from CESifo

Abstract: We test whether AI-generated news images affect outlet demand and trust. In a pre-registered experiment with 2,870 UK adults, the same article was paired with a wire-service photo (with/without credit) or a matched AI image (with/without label). Average newsletter demand changes little. Ex-post photo origin recollection is poor, and many believe even the real photo is synthetic. Beliefs drive behavior: thinking the image is AI cuts demand and perceived outlet quality by about 10 p.p., even when the photo is authentic; believing it is real has the opposite effect. Labels modestly reduce penalties but do little to correct mistaken attributions.

Keywords: AI; demand for news; trust; online experiment (search for similar items in EconPapers)
JEL-codes: C81 C93 D83 (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-ain and nep-soc
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_12277

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