African Journal of ICT, Innovation and Society | 13 October 2001
Integrating Indigenous Knowledge Systems into AI Development in West Africa: A Tanzanian Perspective
G, w, i, n, y, e, i, M, w, e, b, a, z, e, ,, K, a, m, a, s, i, M, s, u, y, a
Abstract
Integrating Indigenous Knowledge Systems (IKS) into Artificial Intelligence (AI) development is increasingly recognised as a promising approach to address digital divide and enhance AI's inclusivity in developing regions such as West Africa. A mixed-methods approach was employed, including qualitative interviews and quantitative data analysis through a logistic regression model. The logistic regression revealed that incorporating IKS reduced AI development project failure rates by 20% (\(OR = 0\).80, CI: 0.65-0.98). This study provides empirical evidence supporting the integration of indigenous knowledge in AI development as a viable strategy for enhancing project success and societal impact. Further research should focus on scaling up this approach with larger-scale studies to validate these findings across diverse contexts. Indigenous Knowledge Systems, Artificial Intelligence Development, Logistic Regression, West Africa, Tanzania