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Man vs. machine: Multi-country experimental evidence on the quality and perceptions of AI-generated research blog content

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  • Michael Keenan
  • Naureen Karachiwalla
  • Jawoo Koo
  • Christine Mwangi
  • Clemens Breisinger
  • MinAh Kim

Abstract

Academic research is not always available in a form that is accessible or engaging to a non-academic audience, hindering readers’ engagement with it. Non-academics, even if highly educated and policy experts in their fields, tend to need research to be presented in a more accessible way than peer-reviewed articles — one example being non-technical blogs. However, writing these requires some effort from researchers. Artificial Intelligence (AI) tools can make academic research easier to understand by summarizing and simplifying academic papers much more quickly than researchers can, making it easier for researchers to produce such summaries. However, disclosure of AI use may lower readers’ perceived quality of and trust in the blog, generating a trade-off for the researcher. In this paper, we evaluate an 11-country experiment cross-randomizing a blog’s actual and reported author as AI or human. We find that research stakeholders rate the quality of AI-generated blogs marginally lower than human-written ones (p

Suggested Citation

  • Michael Keenan & Naureen Karachiwalla & Jawoo Koo & Christine Mwangi & Clemens Breisinger & MinAh Kim, 2026. "Man vs. machine: Multi-country experimental evidence on the quality and perceptions of AI-generated research blog content," PLOS ONE, Public Library of Science, vol. 21(3), pages 1-19, March.
    • Handle: RePEc:plo:pone00:0342852
    DOI: 10.1371/journal.pone.0342852
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    References listed on IDEAS

    as
    1. Gary Charness & Brian Jabarian & John A. List, 2023. "Generation Next: Experimentation with AI," NBER Working Papers 31679, National Bureau of Economic Research, Inc.
    2. Xiang Hui & Oren Reshef & Luofeng Zhou, 2023. "The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market," CESifo Working Paper Series 10601, CESifo.
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