Lost in translation - How Africa is trying to close the AI language gap

The article discusses the efforts to address the language gap in the development of artificial intelligence (AI) systems for Africa. Currently, most AI models are trained on data predominantly in European and Asian languages, leaving many African languages underrepresented or entirely absent. This creates a significant barrier to the accessibility and usefulness of AI technologies for millions of Africans. To address this issue, a new dataset called Masakhane has been developed, which includes a diverse range of African languages. This dataset aims to improve the performance of AI models on these languages, enabling better access and utilization of AI-powered applications and services. The article highlights the importance of this initiative in bridging the digital divide and empowering African communities to benefit from the advancements in AI technology. The article emphasizes the need for continued investment and collaboration to expand the dataset and ensure the development of AI systems that cater to the linguistic diversity of the African continent. This effort is crucial for promoting digital inclusion and unlocking the full potential of AI in addressing the unique challenges and needs of African countries.