Artificial intelligence, indigenous knowledge systems, and prospects for sustainable food system transformation in Africa

Abstract

The nexus of Artificial Intelligence (AI) and indigenous knowledge systems (IKS) rarely features as a viable intervention in African food system policy and academic debates. This has created knowledge and practical gaps with policy and practice implications. This article argues that leveraging the AI-IKS nexus has significant potential to transform African food systems currently in crisis. This conceptual article explores the importance of IKS in Sub-Saharan Africa (SSA) and examines how AI solutions can transform regional food systems. The article shows that harnessing the AI-IKS nexus entails merging traditional, generational ecological wisdom with modern technology to enhance food security, sustainability, and resilience. Key applications include using AI to analyse indigenous drought-prediction techniques alongside meteorological data, identifying climate-resilient indigenous crops, and deploying Computer Vision and Natural Language Processing to digitise and disseminate traditional knowledge in local languages. The article argues that this synergy has the potential to enhance climate resilience, boost yields through precision agriculture, reduce post-harvest losses, and promote sustainable resource management, ultimately strengthening food security.

Keywords: {'name': 'Artificial Intelligence'}, {'name': 'food systems'}, {'name': 'Indigenous knowledge systems'}, {'name': 'sustainability'}, {'name': 'transformation'}

Authors & affiliations

Emmanuel Ndhlovu
University of Johannesburg

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