Ibitoye, Ayodeji Olusegun ORCID: https://orcid.org/0000-0002-5631-8507, Nkwo, Makuochi Samuel, Akinyemi, Joseph Damilola and Ladoja, Khadijat Tope (2025) Afrocentric trustworthy framework for improved Artificial Intelligence powered health management tool for Africans: African perspectives. In: Eke, Damian Okaibedi, Wakunuma, Kutoma, Akintoye, Simisola and Ogoh, George, (eds.) Trustworthy AI: African Perspectives. Palgrave Macmillan - Springer Nature, Cham, Switzerland, pp. 93-117. ISBN 978-3031756740; 978-3031756733 (doi:10.1007/978-3-031-75674-0_5)

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Abstract

Artificial intelligence (AI) is revolutionising healthcare globally, promising enhanced efficiency and outcomes. Africa, with its rich resources and diverse cultures, holds potential for AI adoption, particularly in healthcare. However, the imposition of Western frameworks neglects Africa's unique context, hindering trust and transparency. Despite challenges like limited infrastructure and data privacy concerns, the lack of Afrocentric solutions remains a major barrier to trustworthy AI in Africa. To address this, we propose a framework integrating ethical principles with Africa's social values, tailored to local healthcare complexities. By engaging communities and aligning with cultural narratives, this framework aims to enhance user trust and acceptance. Integrating Africa's cultural elements into AI’/”-driven healthcare not only addresses biases but also ensures seamless integration into the African landscape. Thus, prioritising African contexts in AI design is crucial for realising its full potential in African healthcare.

Item Type:	Book Section
Uncontrolled Keywords:	Artificial Intelligence in healthcare, Trustworthy AI, Afrocentric AI, AI in Africa, healthcare technology adoption, culturally-responsive AI, ethical AI framework
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	13 May 2025 14:17
URI:	http://gala.gre.ac.uk/id/eprint/50426

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