Session Title: My Digital Footprint: The Ethics of AI in Africa: Who is Training the Algorithm?
Session Overview
Artificial Intelligence (AI) is increasingly shaping societies, influencing governance, healthcare, finance, and even social justice in Africa. However, AI systems are only as ethical as the data they are trained on. Given Africa’s historical marginalization in global AI development, the session will explore:
- Bias in AI models and how it disproportionately affects African populations.
- The urgent need for localized AI training datasets and governance frameworks.
- Pathways for ethical AI development in Africa that prioritize inclusion, fairness, and transparency.
The discussion will convene AI ethicists, policymakers, data protection regulators, civil society actors, and industry leaders to address these issues and chart a way forward for AI governance in Africa.
BACKGROUND & RATIONALE
AI is increasingly embedded in decision-making systems across Africa— from credit scoring and recruitment to predictive policing and healthcare diagnostics. However, the continent faces a significant challenge: AI models used in Africa are often trained on datasets that are not representative of its diverse populations. This has led to several ethical concerns:
- Bias & Exclusion:AI models, primarily trained on Western datasets, often fail to recognize African faces, dialects, and cultural nuances, leading to systemic bias.
- Data Sovereignty & Localization:African countries lack control over AI training datasets, which are largely curated by foreign companies, creating dependency and privacy concerns.
- Regulatory Gaps:While some African nations have enacted data protection laws, comprehensive AI governance policies remain underdeveloped, raising concerns over accountability and transparency.
This session aims to foster discussions on ethical AI development tailored for Africa, focusing on localization, policy frameworks, and mitigating bias.