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

Simple item page
cg.authorship.typesCGIAR multi-centre
cg.authorship.typesCGIAR and advanced research institute
cg.contributor.affiliationInternational Food Policy Research Institute
cg.contributor.affiliationCGIAR System Organization
cg.contributor.affiliationFood and Agriculture Organization of the United Nations
cg.contributor.donorCGIAR Trust Fund
cg.contributor.donorGates Foundation
cg.contributor.initiativeDigital Innovation
cg.contributor.initiativeNational Policies and Strategies
cg.contributor.programAcceleratorDigital Transformation
cg.contributor.programAcceleratorPolicy Innovations
cg.creator.identifierMichael Keenan: 0000-0001-5191-9146
cg.creator.identifierNaureen Karachiwalla: 0000-0001-6662-106X
cg.creator.identifierJawoo Koo: 0000-0003-3424-9229
cg.creator.identifierClemens Breisinger: 0000-0001-6955-0682
cg.howPublishedFormally Published
cg.identifier.doihttps://doi.org/10.1371/journal.pone.0342852
cg.identifier.projectIFPRI - Development Strategies and Governance Unit
cg.identifier.projectIFPRI - Poverty, Gender, and Inclusion Unit
cg.identifier.projectIFPRI - Natural Resources and Resilience Unit
cg.identifier.projectIFPRI - Generative AI for Agriculture (GAIA)
cg.identifier.publicationRankB
cg.isijournalISI Journal
cg.issn1932-6203
cg.issue3
cg.journalPLoS One
cg.reviewStatusPeer Review
cg.volume21
dc.contributor.authorKeenan, Michael
dc.contributor.authorKarachiwalla, Naureen
dc.contributor.authorKoo, Jawoo
dc.contributor.authorMwangi, Christine Wamuyu
dc.contributor.authorBreisinger, Clemens
dc.contributor.authorKim, MinAh
dc.date.accessioned2026-04-10T15:09:51Z
dc.identifier.urihttps://hdl.handle.net/10568/182429
dc.titleMan vs. machine: Multi-country experimental evidence on the quality and perceptions of AI-generated research blog contenten
dcterms.abstractAcademic 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 0.1), but disclosure of AI use offsets the negative effect (p 0.1). The study sample consists of policy-relevant stakeholders who typically engage with academic research; they are highly educated and include thematic specialists. Indeed, findings indicate that this audience interprets “accessibility” differently, preferring slightly more technical summaries of research. The nature of the respondents may thus explain the particular findings in this study, suggesting that researchers should tailor their prompts for their intended audience. There are no effects on readers’ reported likelihood of engaging with the blog or on beliefs about others predicted engagement with it. Consequently, we hypothesize that researchers can leverage AI to communicate their research more easily without a penalty from disclosing its use.en
dcterms.accessRightsOpen Access
dcterms.audienceAcademics
dcterms.available2026-03-25
dcterms.bibliographicCitationKeenan, Michael; Karachiwalla, Naureen; Koo, Jawoo; Mwangi, Christine Wamuyu; Breisinger, Clemens; and Kim, MinAh. 2026. Man vs. machine: Multi-country experimental evidence on the quality and perceptions of AI-generated research blog content. PLoS One 21(3): e0342852. https://doi.org/10.1371/journal.pone.0342852
dcterms.extente0342852
dcterms.issued2026-03
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherPublic Library of Science
dcterms.subjectartificial intelligence
dcterms.subjectgenerative artificial intelligence
dcterms.subjectresearch
dcterms.subjectquality
dcterms.typeJournal Article

Files

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

IFPRI Journal Articles