What happened
Researchers at the Africa Rice Center (AfricaRice) and the International Rice Research Institute tested whether ChatGPT could answer rice farmers' questions in Nigeria. In June 2023 they collected 32 questions from 107 farmers in Kano State. On 10 August 2023 they put the questions to ChatGPT, and six extension agents from Kano answered them on paper. Four local rice experts scored the seven answers to each question without knowing who wrote them. They rated the chatbot's answers higher in quality and preferred them over agents' answers without extension materials in 78% of cases. The chatbot gave inaccurate advice on seed rate, dry-season planting time, financial support and seedlings per hill. The authors advised against direct use by farmers for now and suggested that agents could use it to draft replies. Farmers did not use the answers, so no change in practice or yield was measured. Scientific Reports published the study on 10 February 2024.
Sources
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Peer-reviewed study, by authors with no tie to the system.
Ali Ibrahim, Kalimuthu Senthilkumar and Kazuki Saito. Evaluating responses by ChatGPT to farmers' questions on irrigated lowland rice cultivation in Nigeria. Scientific Reports 14: 3407, 10 February 2024.
Overall, chatbot responses were rated significantly higher quality than EAs' responses. Chatbot responses received the best score nearly six times as often as the EAs' (40% vs. 7%). The evaluators preferred chatbot responses to EAs in 78% of cases.
Details
AI system
- Workflow
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The researchers put each farmer question into a fresh ChatGPT session with no earlier prompts. Four local rice experts scored all seven answers to each question without knowing who wrote them.
Follow-up
- Conditions for replication
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Advice on input rates and timing must be checked against local recommendations, where the chatbot erred. Farmers must be able to use long answers, which the study did not test with them.
Entry details
- Sector
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Agriculture / extension advice.
- Purpose
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OpenAI built ChatGPT to answer questions and write text in conversation with its users.
Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.
Cite this record
Peter H. Vartanian. (2026). Experts prefer ChatGPT's rice advice to extension agents' in Kano (AIBD-0858). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0858.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)