Responsible AI. Empowering People.

The Centre for Data Science and Artificial Intelligence is advancing forest monitoring in Africa through locally grounded AI systems. In Kieni Forest, its work combines drone imagery, field data, and bioacoustics to detect early ecological change. This approach helps reveal how forests are transforming before silence becomes irreversible loss.

Originally published on the Masakhane African Languages Hub, this article responds to The Economist’s March 18, 2026 piece on how leading AI models underperform in non‑English languages. It highlights the serious equity and safety implications of weaker AI performance in African languages across sectors such as healthcare, agriculture, and public services. The article showcases Masakhane’s African‑led efforts to address this gap through community‑driven data creation, collaborative research, and gender‑responsive innovation—arguing that reliable AI in African languages is essential to legitimate and inclusive AI adoption in Africa.

Africa’s healthcare challenges demand locally built AI solutions grounded in context. From data and infrastructure to policy and education, supporting local innovators is key to creating trusted, scalable systems. By investing in homegrown talent and enabling environments, the continent can reduce reliance on foreign technologies and build resilient, people-centered health systems for the future.