AI and Machine Learning
AI Governance Frameworks for African Organizations
African organizations adopting AI systems face a unique mix of cultural diversity, heterogeneous data environments, and evolving regulatory landscapes. This section proposes a governance framework tailored specifically to these realities. The framework emphasizes transparency, context-aware data acquisition, cultural sensitivity in model design, and continuous auditing of automated decisions.
Through case studies in Ghanaian SMEs and digital platforms, we explore how misaligned AI systems can inadvertently reinforce socio-cultural biases or misinterpret user intent. Our governance model introduces three layers of oversight: organizational governance, technical governance, and community oversight. Organizational governance ensures leadership accountability; technical governance establishes rules around fairness, accuracy, and versioning; and community oversight ensures systems remain aligned with local values and user expectations.
This approach centers the African user, ensuring AI systems deployed across education, finance, health, and civic services reinforce—not erode—trust, fairness, and transparency.
