AI and Low-Resource Languages

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Authors: Nanlir Sallau Mullah, Wan Mohd Nazmee Wan Zainon
Cited by: 2
References: 65

Abstract

Artificial intelligence (AI) is rapidly transforming global communication, learning, and access to services, yet its benefits remain concentrated in high-resource languages, leaving most low-resource languages (LRLs) digitally marginalised. This chapter examines the linguistic digital divide, where large language models overwhelmingly prioritise dominant languages. Drawing on insights from computational linguistics, AI ethics, and community initiatives, we analyse socio-technical and cultural barriers to inclusion and present case studies from Africa, Latin America, and the Pacific that highlight both challenges and opportunities. We argue that bridging this gap requires multilingual pretraining, participatory data governance, sustainable funding, and culturally grounded design. By foregrounding marginalised voices and embedding linguistic justice in AI development, this chapter envisions a future where every language, regardless of resource level, secures a meaningful digital presence.

Fields of Study & Subjects

ICT in Developing Communities Multilingual Education and Policy Historical Studies in Central America

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Publisher
IGI Global Scientific Publishing
Pages
77–128
Publication date
25 February 2026
Document type
Book chapter