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AI in Africa: Promise, Pitfalls, and Politics

At MozFest House Zambia, Skoll Foundation brought together technologists, policymakers, and activists who are implementing AI solutions on the continent to provide a ground-up perspective on the technology’s impact. The discussion illuminated the nuances of AI’s role in Africa.Practical ImplicationsThe conversation kicked off with examples of AI’s practical applications. Bright Simons from mPedigree explained how his organization uses AI tags to provide quality control for drugs as they move along the production process. He also talked about sensors that monitor the storage conditions of temperature-sensitive medicines, helping nurses to administer them safely. Ensuring the quality of drugs in Africa can be a challenge, and solutions like these provide an extra layer of protection to consumers.The Labor QuandaryAI's impact on labor is a global concern, and in Africa, the fault lines are even more visible with challenges such as extractive labor practices in AI development. Simons brought up a system mPedigree developed to fill out government forms. It made experts in this bureaucratic process concerned about their job security, and even though this solution rendered a cumbersome task easier, it also jeopardized employment for these administrators. Ashnah Kalemera from The Collaboration on International ICT Policy for East and Southern Africa (CIPESA) warned about AI’s potential for increasing surveillance and reducing the autonomy of workers. AI systems are already contributing to labor rights inequalities and increasing vulnerabilities, especially in sectors with limited union protections.Infrastructural ChallengesThe conversation repeatedly returned to the barriers posed by inadequate infrastructure. Debbie Rogers from Reach Digital Health highlighted the cost barriers to implementing large-scale AI models, particularly in healthcare. One way around it is to look for context-specific solutions, and Rogers’s work includes developing smaller, fit-for-purpose machine learning models that could provide a way to balance affordability and efficiency.The Need For Better GovernanceA significant piece in the AI development ecosystem is governance or the lack thereof. Simons cautioned against the misuse of AI in politically charged contexts like government-funded insurance against extreme weather where payouts might be manipulated for electoral gains. For him, governance is key to ensuring fairness and preventing power imbalances.Participants brought up governments’ abstract ways of including AI in national development plans, instead of providing applicable frameworks for AI governance. However, as Angela Oduor Lungati of Ushahidi pointed out, organizations can’t avoid working with governments if they want to implement lasting solutions. In line with Angela’s remarks, an audience member pointed out that AI can help create practical solutions which people can take to their government officials, rather than bringing up problems and expecting the government to find solutions.The Future of AI in AfricaAI holds immense promise for Africa, from safer supply chains to improving healthcare and agriculture. However, its success depends on building trust, strengthening governance, and fostering collaboration across sectors. The conversations at MozFest House Zambia underscored a critical truth: Africa’s AI story will be defined by the people implementing it today, and they will have to navigate AI’s promises and pitfalls.

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