Artificial intelligence and the future of sociolinguistic research: An African contextual review

It was quite a relief after the ChatGPT generated response part of the leading piece acknowledged that human sociolinguists will still be needed to interpret data-sociolinguists will not be replaced with machine automated workforce.As I read through the leading piece and the arguments raised for artificial intelligence (AI) in relation to automated data gathering, management and analysis, I wondered the case for African sociolinguistics considering the challenges being experienced by the technologically advanced Global North.Although African languages are about a third of the world languages, the representation of these languages in AI technology is quite limited and still advancing (Bedu, 2024).The leading text by Helen Kelly-Holmes identifies that AI has cast doubts on the notions real, natural and authentic data.Interestingly, the African sociolinguistics data arguably will have more 'authenticity' for a while.Technological change and access generally start from the Global North due to the resources available, and the impact on Global South sociolinguistics will be much later due to access and cost constraints of AI-related gadgets and access to internet.Therefore, the sub-Saharan sociolinguist still has access to a treasure trove of 'pure' sociolinguistic data with low to no AI influence in some parts of Africa.Similar to the issue of sociolinguistics and development (Djit, 2008), AI proponents might consider African languages and communities to be slow in AI usage.Growth in AI usage can be achieved with an increase in the training of local language tech innovators which is much needed for an inclusion of local language applications in major technologies such as Google Translate (GhanaNLP, n.d.).AI in Africa is developing with the presence of AI research hubs in South Africa, robotic competitions, summer schools and workshops in Uganda, Ghana, Ethiopia, Kenya, etc., and AI labs in South Africa, Kenya and Ghana (see Arakpogun et al., 2021).Through these trainings, Africans have developed AI applications solutions for disaster management, agriculture and healthcare.However, such delayed growth positively impacts the sociolinguistics of the Global South and should be allowed to naturally evolve for inclusion of the plethora of local languages in African contexts.