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Large language models and agricultural extension services

dc.contributor.authorTzachor, A.
dc.contributor.authorDevare, M.
dc.contributor.authorRichards, C.
dc.contributor.authorPypers, P.
dc.contributor.authorGhosh, A.
dc.contributor.authorKoo, J.
dc.contributor.authorJohal, S.
dc.contributor.authorKing, B.
dc.date.accessioned2023-11-30T12:39:42Z
dc.date.available2023-11-30T12:39:42Z
dc.date.issued2023-11
dc.identifier.citationTzachor, A., Devare, M., Richards, C., Pypers, P., Ghosh, A., Koo, J., ... & King, B. (2023). Large language models and agricultural extension services. Nature Food, 941-948.
dc.identifier.issn2662-1355
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8344
dc.description.abstractSeveral factors have traditionally hampered the effectiveness of agricultural extension services, including limited institutional capacity and reach. Here we assess the potential of large language models (LLMs), specifically Generative Pre-trained Transformer (GPT), to transform agricultural extension. We focus on the ability of LLMs to simplify scientific knowledge and provide personalized, location-specific and data-driven agricultural recommendations. We emphasize shortcomings of this technology, informed by real-life testing of GPT to generate technical advice for Nigerian cassava farmers. To ensure a safe and responsible dissemination of LLM functionality across farming worldwide, we propose an idealized LLM design process with human experts in the loop.
dc.description.sponsorshipTempleton World Charity Foundation
dc.format.extent941-948
dc.language.isoen
dc.subjectAgricultural Extension
dc.subjectCassava
dc.subjectFarmers
dc.subjectTechnology
dc.titleLarge language models and agricultural extension services
dc.typeJournal Article
cg.contributor.affiliationUniversity of Cambridge
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationInternational Center for Tropical Agriculture
cg.contributor.affiliationInternational Food Policy Research Institute
cg.contributor.affiliationLinux Foundation, USA
cg.contributor.affiliationCGIAR
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubCentral Africa Hub
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeNatural Resource Management
cg.identifier.bibtexciteidTZACHOR:2023
cg.isijournalISI Journal
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectClimate Change
cg.iitasubjectFood Security
cg.iitasubjectSmallholder Farmers
cg.journalNature Food
cg.accessibilitystatusLimited Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCopyrighted; all rights reserved
cg.targetaudienceScientists
cg.identifier.doihttps://doi.org/10.1038/s43016-023-00867-x
cg.iitaauthor.identifierMedha Devare: 0000-0003-0041-4812
cg.iitaauthor.identifierPieter Pypers: 0000-0001-8913-0589
cg.futureupdate.requiredNo
cg.identifier.volume4


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