Massey University researchers, led by Senior Lecturer Dr Surangika Ranathunga from the School of Mathematical and Computational Sciences, are developing methods to improve artificial intelligence support for low-resource languages, which receive limited backing from mainstream AI systems. The research covers dataset creation, model design, system testing and efforts to highlight the gap between dominant and underrepresented languages. While chatbots and translation tools perform strongly in languages such as English, Chinese and French, many of the world's more than 7,000 languages have little representation in the data used to train them, leading to weak translation, poor spelling correction, limited educational support and outputs that miss local cultural context. Dr Ranathunga stated, "AI models often reflect Western ideologies, which do not reflect all languages and our cultures." Her team is pursuing approaches including building datasets for underrepresented languages from the ground up, exploring synthetic data generation via web mining, and using optical character recognition to extract text from printed documents. Dr Ranathunga noted, "AI is nothing without data. Even if people want to build tools for these languages, often the data simply doesn't exist." She argued that the gap could widen if AI systems continue to improve mainly for widely spoken languages, potentially leading to the decline of underrepresented languages, particularly in education.