ETHICAL FRAMEWORKS FOR AI GOVERNANCE IN AFRICA: A MIXED-METHODS EMPIRICAL STUDY

Abstract

Artificial intelligence (AI) systems are increasingly integrated into governance, economic planning, and social service delivery across African countries. While these technologies offer transformative potential, they also raise profound ethical concerns relating to accountability, transparency, fairness, and cultural legitimacy. Existing global AI governance frameworks largely originate from Global North contexts and may inadequately address Africa’s institutional capacities, socio-cultural values, and developmental priorities. This study empirically examines ethical frameworks for AI governance in Africa, focusing on their contextual relevance and perceived effectiveness. Using a mixed-methods design, quantitative survey data were collected from 412 AI practitioners, policymakers, and academics across Nigeria, Ghana, and Tanzania, complemented by qualitative interviews with 27 key stakeholders. Secondary analysis of national policy documents and international AI ethics frameworks further informed the study. Quantitative results indicate strong stakeholder support for context-sensitive ethical governance, with cultural relevance emerging as a significant predictor of trust in AI systems. Qualitative findings reveal persistent governance gaps, including limited regulatory capacity, weak public participation, and misalignment between imported ethical principles and local realities. The study contributes empirically grounded insights into African AI governance and proposes adaptive ethical frameworks that integrate global principles with indigenous values. These findings advance scholarly discourse on AI ethics while offering practical guidance for policymakers seeking responsible and inclusive AI deployment in Africa.