AI-Driven Translation Technologies in Multilingual Education: Expanding Access to Quality Learning for Sustainable Development

Abstract

The integration of AI-driven translation technologies in multilingual education is revolutionizing access to quality learning, particularly in the context of sustainable development. This paper explores how advanced machine translation tools enable students from diverse linguistic backgrounds to access educational content in their native languages, thereby overcoming traditional language barriers. By facilitating real-time translation and localization of educational materials, these technologies enhance inclusivity, ensuring that learners in underserved and remote areas receive equitable educational opportunities. Moreover, adopting AI-driven translation fosters the preservation of indigenous languages while simultaneously promoting global understanding. The paper also examines the challenges and ethical considerations associated with the deployment of these technologies, such as accuracy, cultural sensitivity, and the digital divide. Ultimately, the research underscores the potential of AI-driven translation technologies to contribute significantly to the United Nations’ Sustainable Development Goals (SDGs) by democratizing education and promoting lifelong learning for all.

Keywords: Artificial Intelligence, Multilingual education, Sustainable development