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AI Images, Labels and News Demand

Author

Listed:
  • Adena, Maja

    (WZB Berlin)

  • Alabrese, Eleonora

    (University of Bath)

  • Capozza, Francesco

    (University of Barcelona)

  • Leader, Isabelle

    (University of Bath)

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.

Suggested Citation

  • Adena, Maja & Alabrese, Eleonora & Capozza, Francesco & Leader, Isabelle, 2025. "AI Images, Labels and News Demand," CAGE Online Working Paper Series 782, Competitive Advantage in the Global Economy (CAGE).
    • Handle: RePEc:cge:wacage:782
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    References listed on IDEAS

    as
    1. Matthew Gentzkow & Jesse M. Shapiro, 2006. "Media Bias and Reputation," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 280-316, April.
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    3. Carl Shapiro, 1983. "Premiums for High Quality Products as Returns to Reputations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(4), pages 659-679.
    4. Ester Faia & Andreas Fuster & Vincenzo Pezone & Basit Zafar, 2024. "Biases in Information Selection and Processing: Survey Evidence from the Pandemic," The Review of Economics and Statistics, MIT Press, vol. 106(3), pages 829-847, May.
    5. Klein, Benjamin & Leffler, Keith B, 1981. "The Role of Market Forces in Assuring Contractual Performance," Journal of Political Economy, University of Chicago Press, vol. 89(4), pages 615-641, August.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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