Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar

This presentation explores how artificial intelligence can advance gender-responsive climate information services in Kenya. Drawing on a five-year analysis of over 9,000 iShamba advisory queries from women farmers, the study identified referral, language, and regional biases that influence inclusivi...

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Detalles Bibliográficos
Autores principales: Gitau, Kevin, Grossi, Amanda
Formato: Ponencia
Lenguaje:Inglés
Publicado: 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/177878
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author Gitau, Kevin
Grossi, Amanda
author_browse Gitau, Kevin
Grossi, Amanda
author_facet Gitau, Kevin
Grossi, Amanda
author_sort Gitau, Kevin
collection Repository of Agricultural Research Outputs (CGSpace)
description This presentation explores how artificial intelligence can advance gender-responsive climate information services in Kenya. Drawing on a five-year analysis of over 9,000 iShamba advisory queries from women farmers, the study identified referral, language, and regional biases that influence inclusivity and service quality. These insights informed a field validation with 130 farmers—88 women and 42 men—across Kiambu, Meru, Kakamega, and Nakuru counties. Results demonstrate that refining AI advisories through human-centered design and reinforcement learning improved accuracy and contextual relevance from 62% to 83%. The findings underscore both the transformative potential and the risks of AI in delivering equitable digital climate services.
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spelling CGSpace1778782025-11-14T02:15:50Z Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar Gitau, Kevin Grossi, Amanda gender agriculture artificial intelligence advisory services design This presentation explores how artificial intelligence can advance gender-responsive climate information services in Kenya. Drawing on a five-year analysis of over 9,000 iShamba advisory queries from women farmers, the study identified referral, language, and regional biases that influence inclusivity and service quality. These insights informed a field validation with 130 farmers—88 women and 42 men—across Kiambu, Meru, Kakamega, and Nakuru counties. Results demonstrate that refining AI advisories through human-centered design and reinforcement learning improved accuracy and contextual relevance from 62% to 83%. The findings underscore both the transformative potential and the risks of AI in delivering equitable digital climate services. 2025-11-11 2025-11-13T14:51:34Z 2025-11-13T14:51:34Z Presentation https://hdl.handle.net/10568/177878 en Open Access application/pdf Gitau K, Grossi A, . 2025. Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar. AICCRA Presentation. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA).
spellingShingle gender
agriculture
artificial intelligence
advisory services
design
Gitau, Kevin
Grossi, Amanda
Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title_full Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title_fullStr Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title_full_unstemmed Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title_short Leveraging AI for Inclusive Climate Services in Kenya (and Beyond): CGIAR GESI Accelerator Webinar
title_sort leveraging ai for inclusive climate services in kenya and beyond cgiar gesi accelerator webinar
topic gender
agriculture
artificial intelligence
advisory services
design
url https://hdl.handle.net/10568/177878
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AT grossiamanda leveragingaiforinclusiveclimateservicesinkenyaandbeyondcgiargesiacceleratorwebinar