Togo has asked its citizens to contribute texts, recordings and translations to help “develop AI models that address the linguistic diversity of the country”, according to the AI for Developing Countries Forum.
More than just a “regional experiment”, it is a “blueprint for how developing nations can use technology to assert their cultural sovereignty and economic relevance in the digital age”.
Africa has about 2,000 different languages, but very few are represented comprehensively in AI models, said academics on The Conversation. Failing to be a part of the tech revolution not only “marginalises millions of people”, but also “increases the technology divide”.
AI’s inability to handle most African languages comes down to the “gap between the number of real-world speakers and a language’s digital footprint”, said African Business.
According to findings published in the Proceedings of Machine Learning Research, across six large language models (LLMs), eight small language models and six specialised small language models, only 41 African languages were represented. And just four – Amharic, Swahili, Afrikaans and Malagasy – were “always handled”. This means that “over 98% of African languages went unsupported”.
The lack of African languages in LLMs has become a “major concern for the continent’s policymakers and tech leaders”, said news site Semafor. The World Bank estimates that Africa has only 0.6% of global data centre capacity despite accounting for 18% of the world’s population.
Building AI models from scratch is “expensive” and consumes “limited resources”. But by using one novel strategy – adopting and adapting existing models – the continent’s outputs can evolve more quickly. And Togo’s initiative suggests that the future of AI in Africa “may hinge less on who builds the biggest model, than on who makes the technology useful to the most people”. |
