AI Images, Labels and News Demand

Maja Adena, Eleonora Alabrese, Francesco Capozza and Isabelle Leader
Additional contact information
Maja Adena: WZB Berlin
Francesco Capozza: University of Barcelona
Isabelle Leader: University of Bath

CAGE Online Working Paper Series from Competitive Advantage in the Global Economy (CAGE)

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 JEL Classification: C81; C93; D83 (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-exp and nep-inv
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https://warwick.ac.uk/fac/soc/economics/research/c ... tions/wp782.2025.pdf

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Working Paper: AI Images, Labels and News Demand (2025)
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Persistent link: https://EconPapers.repec.org/RePEc:cge:wacage:782

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