Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties
This study investigates the general farmer information ecosystem in Kenya. Furthermore, it examines the shortcomings of AI-generated agricultural advisories in Kenya, particularly in terms of gender inclusivity and cultural relevance. Despite recent advancements in AI, the advisories did not fully m...
| Autores principales: | , , , , , , , , , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/177874 |
| _version_ | 1855521199767945216 |
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| author | Nganga, Kevin Gitau Grossi, Amanda Wanjau, Agnes Njambi Gamoyo, Majambo Jarumani Otieno, Felix Owino Koech, Grace Jerotich Giraldo Mendez, Diana Carolina Ghosh, Aniruddha Kirwa, Lilian Ngotho, Elias |
| author_browse | Gamoyo, Majambo Jarumani Ghosh, Aniruddha Giraldo Mendez, Diana Carolina Grossi, Amanda Kirwa, Lilian Koech, Grace Jerotich Nganga, Kevin Gitau Ngotho, Elias Otieno, Felix Owino Wanjau, Agnes Njambi |
| author_facet | Nganga, Kevin Gitau Grossi, Amanda Wanjau, Agnes Njambi Gamoyo, Majambo Jarumani Otieno, Felix Owino Koech, Grace Jerotich Giraldo Mendez, Diana Carolina Ghosh, Aniruddha Kirwa, Lilian Ngotho, Elias |
| author_sort | Nganga, Kevin Gitau |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This study investigates the general farmer information ecosystem in Kenya. Furthermore, it examines the shortcomings of AI-generated agricultural advisories in Kenya, particularly in terms of gender inclusivity and cultural relevance. Despite recent advancements in AI, the advisories did not fully meet the diverse needs of smallholder farmers across Kiambu, Kakamega, Meru, and Nakuru counties. A total of 120 farmers participated in focus group discussions (FGDs), with equal representation of women and youth. The research aimed to validate AI-generated content by evaluating its clarity, relevance, trustworthiness, and inclusivity. Although the AI advisories scored reasonably well for clarity (1.58 out of 2), farmers expressed significant reservations about the cultural fit and gender inclusivity of the content. The lack of localised examples and culturally sensitive references was a recurring critique. Furthermore, while the AI advice was often clear, farmers were skeptical about the credibility of the source, particularly when delivered via SMS or other digital platforms. Trust in AI advisories remained low, with many farmers preferring traditional sources, such as extension officers or local radios, which they deemed more reliable. Gender and age disparities in access to and trust in digital platforms further compounded the problem, with women, especially older farmers, still relying heavily on face-to-face extension services. The findings reveal that AI-generated content, while technically sound, fails to fully align with farmers' realities and lacks the trust required for widespread adoption. The study underscores the need for AI systems to better integrate local knowledge, language, and gender-specific considerations to ensure they are truly effective in addressing the needs of Kenya’s farming communities. |
| format | Artículo preliminar |
| id | CGSpace177874 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1778742025-11-19T02:04:53Z Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties Nganga, Kevin Gitau Grossi, Amanda Wanjau, Agnes Njambi Gamoyo, Majambo Jarumani Otieno, Felix Owino Koech, Grace Jerotich Giraldo Mendez, Diana Carolina Ghosh, Aniruddha Kirwa, Lilian Ngotho, Elias smallholders-smallholder farmers gender agriculture artificial intelligence advisory services climate design This study investigates the general farmer information ecosystem in Kenya. Furthermore, it examines the shortcomings of AI-generated agricultural advisories in Kenya, particularly in terms of gender inclusivity and cultural relevance. Despite recent advancements in AI, the advisories did not fully meet the diverse needs of smallholder farmers across Kiambu, Kakamega, Meru, and Nakuru counties. A total of 120 farmers participated in focus group discussions (FGDs), with equal representation of women and youth. The research aimed to validate AI-generated content by evaluating its clarity, relevance, trustworthiness, and inclusivity. Although the AI advisories scored reasonably well for clarity (1.58 out of 2), farmers expressed significant reservations about the cultural fit and gender inclusivity of the content. The lack of localised examples and culturally sensitive references was a recurring critique. Furthermore, while the AI advice was often clear, farmers were skeptical about the credibility of the source, particularly when delivered via SMS or other digital platforms. Trust in AI advisories remained low, with many farmers preferring traditional sources, such as extension officers or local radios, which they deemed more reliable. Gender and age disparities in access to and trust in digital platforms further compounded the problem, with women, especially older farmers, still relying heavily on face-to-face extension services. The findings reveal that AI-generated content, while technically sound, fails to fully align with farmers' realities and lacks the trust required for widespread adoption. The study underscores the need for AI systems to better integrate local knowledge, language, and gender-specific considerations to ensure they are truly effective in addressing the needs of Kenya’s farming communities. 2025-11-01 2025-11-13T14:31:59Z 2025-11-13T14:31:59Z Working Paper https://hdl.handle.net/10568/177874 en Open Access application/pdf Ng’ang’a, K.G., Grossi, A., Wanjau, A., Gamoyo, M., Otieno, F., Koech, G., Giraldo, D., Ghosh, A., Kirwa, L., Ngotho, E. 2025. Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties. AICCRA Working Paper. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA). |
| spellingShingle | smallholders-smallholder farmers gender agriculture artificial intelligence advisory services climate design Nganga, Kevin Gitau Grossi, Amanda Wanjau, Agnes Njambi Gamoyo, Majambo Jarumani Otieno, Felix Owino Koech, Grace Jerotich Giraldo Mendez, Diana Carolina Ghosh, Aniruddha Kirwa, Lilian Ngotho, Elias Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title | Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title_full | Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title_fullStr | Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title_full_unstemmed | Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title_short | Understanding Farmer Information Ecosystems in Kenya: Insights on Access, Trust, Digital Channels, and AI-Assisted Advisory Evaluation across Kiambu, Kakamega, Meru, and Nakuru Counties |
| title_sort | understanding farmer information ecosystems in kenya insights on access trust digital channels and ai assisted advisory evaluation across kiambu kakamega meru and nakuru counties |
| topic | smallholders-smallholder farmers gender agriculture artificial intelligence advisory services climate design |
| url | https://hdl.handle.net/10568/177874 |
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