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Road map for research on responsible artificial intelligence for development (AI4D) in African countries: The case study of agriculture

Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture,...

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Detalles Bibliográficos
Autores principales: Gwagwa, Arthur, Kazim, Emre, Kachidza, Patti, Hilliard, Airlie, Siminyu, Kathleen, Smith, Matthew, Shawe-Taylor, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672141/
https://www.ncbi.nlm.nih.gov/pubmed/34950903
http://dx.doi.org/10.1016/j.patter.2021.100381
Descripción
Sumario:Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access. Our key takeaway is that, despite the promising opportunities for development, there are actual and potential challenges that African countries need to consider in deciding whether to scale up or down the application of AI in agriculture. Input from African innovators, policymakers, and academics is essential to ensure that AI solutions are aligned with African needs and priorities. This paper proposes questions that can be used to form a road map to inform research and development in this area.