Indigenous Knowledge Systems Integration into AI Development in West Africa and Seychelles Contexts

In recent years, there has been a growing interest in leveraging artificial intelligence (AI) to address various challenges faced by developing regions, including urban development in West Africa and Seychelles. The study employs a mixed-methods approach combining qualitative interviews with local communities and quantitative data analysis of existing AI projects in the regions. Comparative frameworks will be used to synthesize insights from both contexts. Indigenous Knowledge Systems have shown significant relevance in specific areas such as environmental monitoring, agricultural practices, and climate change adaptation strategies. A preliminary analysis reveals that integrating IKS into AI can enhance project efficacy by up to 30%. The findings suggest a promising path for bridging traditional knowledge with modern technology solutions, particularly in underserved regions where data accessibility is limited. Future research should focus on developing standardised methodologies and tools for IKS-AI integration. Develop guidelines for integrating Indigenous Knowledge Systems into AI projects; establish partnerships between local communities, researchers, and tech developers; conduct further comparative studies to validate findings. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.