ARTIFICIAL INTELLIGENCE IN AFRICAN EDUCATION: ETHICAL, CULTURAL, AND PRACTICAL CONSIDERATIONS THROUGH FAITH-BASED INSTITUTIONS AND INDIGENOUS KNOWLEDGE SYSTEMS
Abstract
Purpose of the study: This paper examines how Artificial Intelligence (AI) can be integrated into African education in ways that are ethically sound, culturally grounded, and practically feasible, with particular attention to faith-based institutions and Indigenous Knowledge Systems (IKS).
Problem statement: While global discourse positions AI as a transformative force in education, research on its ethical, practical, and culturally relevant application within African contexts remains limited. Most tools are developed in Western settings, raising concerns about infrastructural fit, cultural relevance, and ethical appropriateness for African learners.
Methodology: The study adopted a qualitative case study approach drawing on document analysis, semi-structured interviews, and focus group discussions in Kenyan faith-based schools and IKS-informed programmes. Data were examined using thematic analysis, with triangulation and member checking used to strengthen trustworthiness.
Results of the study: AI adoption is strongly context-dependent, shaped by infrastructure and teacher capacity. Faith-based institutions provide infrastructure, pedagogical guidance, and community trust that ease adoption, while IKS integration improves engagement, cultural relevance, and heritage preservation. Persistent concerns include weak infrastructure, limited teacher training, data privacy, and algorithmic bias.
Conclusion and policy recommendation: A hybrid model combining faith-based support structures with IKS-informed AI design offers a sustainable, ethical, and culturally relevant pathway for AI adoption. Governments, educators, developers, and faith-based institutions should collaborate to build infrastructure, train teachers, safeguard data, and embed local values, advancing Sustainable Development Goal 4.
Keywords: Artificial Intelligence, African Education, Faith-Based Institutions, Indigenous Knowledge Systems, Cultural Relevance
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