{"id":24974,"date":"2026-03-30T12:40:58","date_gmt":"2026-03-30T12:40:58","guid":{"rendered":"https:\/\/codesria.org\/generative-ai-in-global-scientific-knowledge-production-challenges-and-prospects-for-africa\/"},"modified":"2026-03-30T22:51:49","modified_gmt":"2026-03-30T22:51:49","slug":"generative-ai-in-global-scientific-knowledge-production-challenges-and-prospects-for-africa","status":"publish","type":"post","link":"https:\/\/codesria.org\/fr\/generative-ai-in-global-scientific-knowledge-production-challenges-and-prospects-for-africa\/","title":{"rendered":"Generative AI in Global Scientific Knowledge Production: Challenges and Prospects for Africa"},"content":{"rendered":"

Bulletin en ligne du CODESRIA<\/i>, No. 1, Mars 2026<\/strong><\/p>\n

by Jacob Jaygbay, <\/em><\/strong>Senior Content Developer, Cloud + AI, Microsoft, Virginia, USA<\/p>\n

This paper examines the transformative impact of large language models (LLMs) like GPT-4 on global scientific research, and highlights the potential benefits and the significant ethical challenges for Africa. It explores how generative AI can enhance Africa\u2019s scientific knowledge production by incorporating underrepresented sources like oral history and grey literature. It also addresses the risks of perpetuating Western-centric biases in AI models and emphasises the need for localised AI training and governance to protect African researchers\u2019 intellectual property rights. The paper advocates for international collaboration, open-source initiatives and grassroots engagement to ensure Africa\u2019s active participation in global scientific discourse, thereby enriching it with diverse perspectives.<\/em><\/p>\n

Keywords: <\/em><\/strong>Africa; AI governance; artificial intelligence (AI); IP rights; knowledge production; large language models<\/em><\/p>\n