Efforts are being made to develop AI tools for underrepresented languages, but the process is slow and resource-intensive. The article mentions the work of Bonaventure Dossou and Ife Adebara, who are part of a collective of researchers building AI tools for African languages. However, the rapid advancement of AI and the internet could make it too late to save some languages. The article concludes by suggesting that the future of AI and low-resource languages lies in asking native speakers what the technology can do for them, rather than imposing technology that may not suit their needs.
Key takeaways:
- The dominance of English on the internet and in AI technologies can marginalize speakers of less common languages, potentially leading to the extinction of these languages.
- Generative AI technologies often struggle with low-resource languages due to a lack of quality training data, which can result in inaccurate translations and cultural misunderstandings.
- Efforts are being made to create AI tools for underrepresented languages, but this process is slow and resource-intensive. For example, the Masakhane project is developing AI tools for African languages.
- There is a need for more culturally sensitive AI technologies that can understand and respect the nuances of different languages and cultures, rather than imposing a one-size-fits-all approach.