AI in Africa: Indigenous languages and adaptability key to future learning
· Citizen
A senior lecturer in Computer Science at the University of Pretoria believes the future of learning in Africa lies in merging indigenous languages with artificial intelligence (AI).
Dr Olaperi Okuboyejo was speaking at Huawei’s Editors Xchange annual technology and media thought-leadership event in Bryanston on Thursday.
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ICT thought leadership
The event brings together delegates from government, business, and the media to discuss the impact of emerging technologies like AI, cloud computing, and sustainable energy.
Speaking on the state of education, Okuboyejo acknowledged South Africa’s recent matric successes, a record 900,000 candidates and improved bachelor passes, but warned that deeper challenges persist.
Literacy
Citing the 2021 Progress in International Reading Literacy Study, Okuboyejo highlighted that “81% of Grade 4 learners in South Africa cannot read for meaning in any language.”
She attributed this crisis largely to the abrupt language switch in schools, where learners move from mother‑tongue instruction to English in Grade 4, even though only 7% have English as a home language.
According to Okuboyejo, performance in mathematics and science remains weak, with South African learners consistently ranked among the lowest globally.
Classrooms
Overcrowded classrooms compound the problem, with an average ratio of 33 learners per teacher – double the recommended 16.
Okuboyejo argued that indigenous language instruction is key to literacy, cultural identity, and self‑esteem.
“Learning to read in the mother tongue is instrumental in unlocking every child’s potential,” he said. But she stressed that this must be done properly, with resources and terminology developed for subjects like mathematics and science. Here, AI offers a powerful solution.”
Technology
Okuboyejo outlined how technology can support personalised learning, automated feedback, and translation tools that make educational content accessible in African languages.
However, she cautioned that limited data remains a major barrier:
“How much Zulu is present on the internet? Without data, language‑specific models cannot be trained.”
Data sets
She said that the University of Pretoria, her team is building datasets containing over 3,000 hours of speech in South African languages, and developing terminology lists for technical subjects.
They are also working on African language audio models covering 40 languages, alongside translation projects for academic research.
Collective effort
Okuboyejo called for a collective effort.
“Governments must create policies enabling data use, educators should embrace technology, media must promote indigenous languages, and researchers must build tools that reach classrooms.
“Closing the language gap in educational AI is central to closing the access gap in African education. Using AI for indigenous languages must be a deliberate undertaking, not an afterthought. This vision positions AI not as a replacement for teachers, but as a partner in delivering inclusive, culturally grounded education across Africa,” she said.
Adapting to AI
Earlier, Nicky Verd, a digital futurist, delivered a powerful message on adaptability in the age of disruption.
Using the Titanic as a metaphor, she warned against the “unsinkable mindset” that blinds individuals and organisations to change.
Verd recounted her own retrenchment as a turning point that forced her to embrace new realities, leading her to explore automation, robotics, and AI.
Disruption
She emphasised that disruption is inevitable – whether by circumstance or choice – and survival depends on the ability to adapt.
“It’s not the strongest or most intelligent who thrive, but the most adaptable to change,” she said, urging people to disrupt themselves before circumstances do.
Verd outlined five types of people in the AI era: avoiders, spectators, adapters, opportunists, and over‑reliants, stressing that mindset determines relevance more than access to technology.
Complacency
She cautioned against legacy thinking and complacency, pointing to Nokia’s downfall as a lesson in failing to adapt quickly enough.
For Verd, the future is about collaboration between humans and AI, not competition.
She urged audiences to ask better questions – not “Will AI take my job?” but “How can I work with AI to stay relevant?” – and highlighted that irrelevance is a greater risk than unemployment.
Her core message: adaptability, continuous learning, and mindset transformation are the keys to thriving in a rapidly evolving digital world.