Case Studies of AI Policy Development in Africa

TL;DR

This paper examines the limitations of global AI readiness assessments in capturing the progress of African nations and provides case studies to suggest tailored policy improvements for AI development.

Contribution

It highlights gaps in existing assessments and offers context-specific insights from case studies to improve AI policy frameworks in Africa.

Findings

Global assessments do not fully reflect African AI progress

Case studies reveal unique regional challenges and opportunities

Recommendations for tailored AI readiness indicators

Abstract

Artificial Intelligence (AI) requires new ways of evaluating national technology use and strategy for African nations. We conduct a survey of existing 'readiness' assessments both for general digital adoption and for AI policy in particular. We conclude that existing global readiness assessments do not fully capture African states' progress in AI readiness and lay the groundwork for how assessments can be better used for the African context. We consider the extent to which these indicators map to the African context and what these indicators miss in capturing African states' on-the-ground work in meeting AI capability. Through case studies of four African nations of diverse geographic and economic dimensions, we identify nuances missed by global assessments and offer high-level policy considerations for how states can best improve their AI readiness standards and prepare their societies to capture the benefits of AI.