Beyond Swahili: Designing Inclusive AI for Bantu Languages

Опубликовано 2 марта 2026, 15:53

Swahili has become one of the most consistently represented African languages in modern AI benchmarks, spanning machine translation, language modeling, and multilingual evaluation suites, far exceeding the coverage of any other Bantu language. This prominence reflects its scale, standardization, and regional reach, but it also exposes the structural challenges of building AI for Bantu languages, including rich morphology, pervasive code-switching, and highly uneven data availability.

In this talk, Alfred outlines how these factors have shaped Swahili’s development within contemporary AI systems, showing why direct transfer from dominant global languages often fails to capture Bantu linguistic structure. Drawing on work in benchmarking, dataset creation, and cross‑lingual modelling, he will illustrate how Swahili provides a technically viable bridge for Bantu languages in machine translation, representation learning, and multilingual evaluation—an approach less tractable through non‑Bantu pivot languages. The talk shall conclude with a discussion on how Swahili can be used responsibly as a bridge rather than a proxy. This would enable scalable cross-language transfer while avoiding the erasure of linguistic diversity across the Bantu language family.

Learn more about Microsoft Research Lab – Africa, Nairobi: microsoft.com/en-us/research/l...