What if participation—not profit—fueled AI development? In this TED Talk, researcher and policy expert Nanjira Sambuli proposes a different way forward for creating AI models, an avenue rooted in African indigenous traditions and values.
Nanjira Sambuli, “What Ancestral Intelligence Can Teach Us about AI.” TED.com, April 2025.
- Sambuli begins her argument about AI development with a metaphor based on an African proverb: “When elephants fight, it’s the grass that suffers” (0:30). In this metaphor, who symbolizes the elephants? Who is represented by the grass? Write 1–2 sentences that summarize her view about which individuals and groups wield power in the race to create more powerful AI technologies, and who (and what) bear the consequences.
- Large language models require a massive amount of data (3:57). Sambuli offers an alternative to this model, which she names “ubuntech” (2:33). Where does this name come from? What’s one way “ubuntech” is different than conventional AI models and companies?
- So what? Who cares? Find where Sambuli says why her argument matters. How do Africans benefit from “ubuntech” AI companies and models? Who, beyond Africans, could benefit from her vision for AI development? What should be the ultimate goal of AI technology, according to Sambuli?
- Some scholars argue for rejecting or “refusing” AI technology, in part due to its broad ecological and labor costs. How might Sambuli respond to this naysayer argument?
- Today’s AI models are trained on only a few languages, with 90% of the data coming from mainstream American English. Read this conversation with Chenai Chair, the director of the Masakhane African Languages Hub, an initiative Sambuli mentions in her video. Why is a lack of linguistic diversity in AI models a problem?
They Say I Blog 
After reading the article about Nanjira Sambuli’s ideas on creating more fair and sustainable AI systems, I found her argument really important, especially her focus on who gets to be involved in building technology. The author argues that AI today is mostly controlled by a small number of powerful companies, which means the systems often reflect their interests instead of representing everyone. Sambuli introduces the idea of “ubuntech,” which focuses on inclusion and making sure more communities have a voice in how AI is developed.
Many people on this blog have made similar points about technology and fairness. For example, in discussions about AI tools in schools, some argue that these systems can be biased and unfair to certain students. In the same way, Sambuli suggests that AI is not neutral and can reinforce inequality if only a few groups are in control. I agree with this because it makes sense that the people creating technology influence how it works and who it benefits.
At the same time, some might argue that large tech companies are necessary for innovation and progress. While I understand that point, I think Sambuli’s argument is stronger because it focuses on long term fairness rather than just short term growth. Overall, this article shows that AI is not just about advancing technology, but also about making sure it is developed in a way that benefits everyone.
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