The development of advanced AI models is heavily skewed towards English and a few other major languages, leaving many smaller or "low-resource" languages at a significant disadvantage. These languages, including Cantonese, Vietnamese, and Bahasa Indonesia, suffer from a lack of sufficient digital data for training AI, leading to models that produce inaccurate or nonsensical translations and text. While companies like Naver and collaborations in Indonesia are working to create AI tailored to specific linguistic and cultural needs, the global AI landscape still risks widening the digital divide for non-English speakers. AI
IMPACT Risks widening the digital divide for non-English speakers and limits access to AI benefits for many global communities.
RANK_REASON Article discusses the implications of AI model development focusing on major languages, impacting low-resource languages, rather than announcing a new model or research.
- Aliya Bhatia
- Cantonese
- Center of Democracy & Technology
- Goto
- GPT-4
- HyperCLOVA X
- Indonesia
- Jackie Chan
- Naver
- Standard Chinese
- Vietnamese
- Votee
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
