AI often leaves out minority languages – but some communities are turning it into a lifeline
AI is helping communities own and build vital tools for their minority languages – all without external funding.
Artificial intelligence (AI) often overlooks minority languages, creating linguistic inequality. Generative AI relies on large language models, which are not trained on minority languages due to a lack of online representation. However, some communities are turning AI into a lifeline by building tools for their languages with AI assistance.
For instance, the Hula language in Papua New Guinea, with around 10,000 speakers, has developed Vavanagi, a language documentation platform, with over 80 users contributing 12,000 English-Hula translations. Another example is the Tetun language in Timor-Leste, where health educators use the Tulun platform to translate health education material into Tetun.
The Dinka–English dictionary, built by Alier Makoi Achuoth from South Sudan, aims to support and expand the Dinka vocabulary. These tools emphasize the potential for AI to empower minority language communities, reducing financial and time costs and enabling local ownership. This shift highlights the importance of community-led research in AI and the potential of AI to foster linguistic diversity, even if its models may not fully represent minority languages.
Written by urgent.news from The Conversation AU's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
