Evaluating responses by ChatGPT to farmers’ questions on irrigated lowland rice cultivation in Nigeria - Ibrahim, Ali; Senthilkumar, Kalimuthu; Saito, Kazuki (Springer, 2024)
The limited number of agricultural extension agents (EAs) in sub-Saharan Africa limits farmers’ access to extension services. Artificial intelligence (AI) assistants could potentially aid in providing answers to farmers’ questions. The objective of this study was to evaluate the ability of an AI chatbot assistant (ChatGPT) to provide quality responses to farmers’ questions. We compiled a list of 32 questions related to irrigated rice cultivation from farmers in Kano State, Nigeria. Six EAs from the state were randomly selected to answer these questions. Their answers, along with those of ChatGPT, were assessed by four evaluators in terms of quality and local relevancy. 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. The topics for which the chatbot responses received poorer scores than those by EAs included planting time, seed rate, and fertilizer application rate and timing. In conclusion, while the chatbot could offer an alternative source for providing agricultural advisory services to farmers, incorporating site-specific input rate-and-timing agronomic practices into AI assistants is critical for their direct use by farmers.