Logo Lanfrica

wafspaul/ai-governance-africa

Domain:

socioeconomic

Record type:

project
Creator:
waf
Host:
A portfolio of AI governance, AI safety, and AI & society research prototypes focused on Africa. # AI Governance Africa **A focused research project exploring AI-driven job displacement as a systemic risk in African economies.** --- ## What this project is This is an independent research initiative investigating one specific question: > *If AI automation displaces large numbers of workers in African economies — particularly in sectors like BPO, manufacturing, and informal trade — what are the downstream systemic risks, and what governance responses could prevent catastrophic outcomes?* This project sits at the intersection of **AI safety**, **labour economics**, and **African political economy**. It is not a general survey of "AI in Africa." It is a focused attempt to understand a specific risk pathway and what can be done about it. --- ## Why this matters Most AI safety research focuses on technical alignment: ensuring AI systems do what their designers intend. That is critical work. But there is a parallel risk that receives far less attention: **What happens to societies when AI disrupts labour markets faster than institutions can adapt?** In Kenya, 15.9 million people aged 15–64 are employed (ILO, 2022). A significant share work in sectors highly exposed to automation — data entry, customer service, routine manufacturing, and informal trade. Youth unemployment is already high. If AI accelerates job displacement without adequate governance responses, the social and political consequences could be severe and irreversible. This is not a distant hypothetical. It is happening now, and it demands serious analysis. --- ## Focus area: Kenya (with broader Africa implications) Kenya is the starting point because: - It has a large and growing BPO sector directly exposed to AI automation - It has reliable ILO and World Bank employment data available - It exemplifies dynamics common across Sub-Saharan Africa: young population, high informality, rapid tech adoption alongside weak social safety nets - What happens here has implications for Ethiopia, Nigeria …