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Indigenous Knowledge Integration into AI Development in West Africa: A Botswagana Perspective

Domaine:

environment and energy

Type de record:

paper
Créateur:
SelMph
Éditeur:
Zenodo
Hôte:avatar

Indigenous knowledge systems in West Africa, including those from Botswana, offer unique insights into environmental management and resource utilization. The study employed a mixed-methods approach, combining qualitative interviews with semi-structured questionnaires and quantitative data analysis using statistical software. A preliminary analysis of interview data revealed that 75% of respondents highlighted the importance of IKS for enhancing AI models in ecological forecasting. The integration of IKS into AI development is expected to improve model accuracy by up to 20%, particularly in predicting environmental changes and biodiversity patterns. Future research should focus on developing a standardised framework for integrating IKS with AI, incorporating iterative testing phases to refine models based on feedback from local communities. 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.

Visit

doi.org

Tags

African geographyGISethnobiologymachine learningcultural cognitionAI ethicsparticipatory design

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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