Natural language processing (NLP) for the decolonisation of low resourced african languages

Abstract

Natural Language Processing (NLP) has emerged as a critical component of artificial intelligence (AI) with the potential to support the decolonisation and revitalisation of low-resourced African languages. This article explores the relationship between human intelligence and computational systems, focusing on how bio-neural networks inspire artificial neural networks used in modern AI applications. In the human brain, intelligence arises from interconnected neurons, where repeated stimulation strengthens neural pathways through synaptic connections. This biological principle underpins artificial neural networks, which model learning through weighted inputs, processing layers, and outputs. The paper provides a foundational overview of biological neural networks, their artificial counterparts, and the role of NLP in enabling machines to understand, process, and generate human language. Particular attention is given to how AI technologies can address historical linguistic marginalisation by developing digital tools for African languages that lack sufficient datasets and technological support. The study further outlines current and emerging AI applications, emphasizing that the integration of NLP into education, healthcare, governance, and communication is increasingly unavoidable. Ultimately, the article argues that leveraging AI and NLP responsibly can play a transformative role in preserving linguistic diversity, promoting inclusion, and advancing technological equity in African contexts.