just posted this for a talk i am giving
Advancing NLP for Non-Latin Scripts and Languages:
Are We Leaving Non-Latin Scripts and Languages Behind?
The vast majority of NLP research and Large Language Models (LLMs) are focused on high-resource languages, predominantly those using the Latin script (e.g., English, French). This creates a critical gap, leading to performance disparities, systemic biases, and the exclusion of billions of speakers from the benefits of advanced AI. The disproportionate focus on Latin scripts means biases and harms are often not adequately measured or addressed for non-Latin script users. Future work must be linguistically informed and strategically address the resource and structural gaps in order to bridge the gap, so that AI can serve billions of people more safely. In my poster presentation, I am actively seeking bilingual collaborators who are proficient in English and another language/script (especially those non-Latin scripts like Arabic, Hindi, Korean, Japanese, or others) to work on practical tools and research in this area.