Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn

Generative artificial intelligence (gen AI) applications - which produce text, images, code, and other content based on surfacing patterns in vast datasets - promise many benefits for agrifood systems (e.g., reaching more people at less cost, availability around the clock, real-time data).

Detalles Bibliográficos
Autores principales: Davis, Kristin E., Jones-Garcia, Eliot, Singaraju, Niyati
Formato: Blog Post
Lenguaje:Inglés
Publicado: International Food Policy Research Institute 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/178200
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author Davis, Kristin E.
Jones-Garcia, Eliot
Singaraju, Niyati
author_browse Davis, Kristin E.
Jones-Garcia, Eliot
Singaraju, Niyati
author_facet Davis, Kristin E.
Jones-Garcia, Eliot
Singaraju, Niyati
author_sort Davis, Kristin E.
collection Repository of Agricultural Research Outputs (CGSpace)
description Generative artificial intelligence (gen AI) applications - which produce text, images, code, and other content based on surfacing patterns in vast datasets - promise many benefits for agrifood systems (e.g., reaching more people at less cost, availability around the clock, real-time data).
format Blog Post
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institution CGIAR Consortium
language Inglés
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher International Food Policy Research Institute
publisherStr International Food Policy Research Institute
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spelling CGSpace1782002025-11-25T20:11:24Z Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn Davis, Kristin E. Jones-Garcia, Eliot Singaraju, Niyati agricultural extension digital technology artificial intelligence farmers food systems Generative artificial intelligence (gen AI) applications - which produce text, images, code, and other content based on surfacing patterns in vast datasets - promise many benefits for agrifood systems (e.g., reaching more people at less cost, availability around the clock, real-time data). 2025-08-26 2025-11-25T19:51:16Z 2025-11-25T19:51:16Z Blog Post https://hdl.handle.net/10568/178200 en Open Access International Food Policy Research Institute Davis, Kristin; Jones-Garcia, Eliot; and Singaraju, Niyati. 2025. Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn. IFPRI Blog Post. https://www.ifpri.org/blog/grounding-ai-in-practice-what-extension-gets-wrong-what-extension-gets-right-and-what-ai-can-learn/
spellingShingle agricultural extension
digital technology
artificial intelligence
farmers
food systems
Davis, Kristin E.
Jones-Garcia, Eliot
Singaraju, Niyati
Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title_full Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title_fullStr Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title_full_unstemmed Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title_short Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
title_sort grounding ai in practice what extension gets wrong what extension gets right and what ai can learn
topic agricultural extension
digital technology
artificial intelligence
farmers
food systems
url https://hdl.handle.net/10568/178200
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