Imagine a brilliant student from rural Limpopo. She presents her thorough case study to her class that is locally relevant and grounded in real-world African challenges. Her classmate submits a technically perfect paper filled with American examples and Western solutions that don’t apply to a rural African setting. The difference? Her classmate prompted ChatGPT and submitted a paraphrased version of its response. This example highlights an uncomfortable truth: generative AI is reshaping teaching and learning in higher education; and without critical reflection, it risks widening the gap between relevance and convenience.
The recent Daily Maverick article on the “CheatGPT” crisis captured a significant tension. The vast majority of large language models like ChatGPT weren’t built with African realities in mind. Their training data privileges Western knowledge, history, and frameworks. Yet across Africa, these tools are being rapidly integrated into our educational systems and often with little interrogation of their cultural biases or pedagogical implications. This poses obvious risks, such as the unintended consequences of imposing Global North solutions onto vastly different educational, technological, and socio-economic contexts. For example, an AI tool calibrated for English-speaking, well-resourced school systems may reinforce exclusion in multilingual classrooms or among students with limited internet access.
A more subtle, longer-term concern is the growing influence of digital colonialism – the way global tech platforms shape what knowledge is visible, whose voices matter, and how learning happens. In higher education, this risks weakening our academic independence and deepening reliance on systems that were never built with our contexts – or our students -in mind.
Banning AI tools, however, is not a solution. The question isn’t about whether to use AI or not, it’s how to do so with care, strategy, and sovereignty.
Eduvos researchers Dr Miné de Klerk and Dr Nyx McLean describe this dilemma in their study, Defining a Technocritical Approach to AI Adoption in the Global South. Too often, institutions swing between extremes of uncritical techno-optimism (“AI will solve everything!”) and fearful rejection (“Ban it before it breaks us!”). Lost in the middle are students who lack guidance on responsibly engaging with these tools and shaping them for African futures.
When an African law student queries ChatGPT, they’re often served US case law. Ask for economic models, and the results tend to assume Western market conditions. Request cultural insights, and Western assumptions are frequently presented as universal truths. It’s not that AI tools can’t provide localised or African-specific information – but without proper prompting and a trained awareness of the tools’ limitations, most users will get default outputs shaped by largely Western training data.Our African perspective risks being overshadowed. This is the hidden curriculum of imported AI: it quietly reinforces the idea that knowledge flows from the North to the South. Meanwhile, African students and lecturers become unpaid contributors – feeding data and insights into systems they don’t own, while Silicon Valley collects the profits.
So, what’s the alternative? At Eduvos, we’ve adopted a technocritical approach which is a mindset that acknowledges both AI’s promise and pitfalls in our context. We’re implementing this through five core principles:
This isn’t just theory – it’s in motion. At Eduvos, assessments have been redesigned so that law students verify AI outputs against South Africancase law, humanities students analyse AI alongside local satirical art, and commerce students compare AI summaries to real economic patterns in their communities. These tasks surface the blind spots of Western-trained AI and invite critical engagement with local realities.
The shape of AI in African education isn’t pre-ordained. It will be defined by our present choices. Will we passively apply foreign tools, or actively shape AI to reflect our values and ambitions?
We don’t need to choose between relevance and progress. With a technocritical approach, we can pursue both – on our terms. Africa cannot afford to adopt AI without adaptation, nor should our students be passive users of systems that do not reflect their lived realities. This is about more than access. It’s about digital self-determination – equipping the next generation to engage critically, challenge defaults, and build AI futures that reflect African voices, knowledge, and needs.
AI will shape the future of education—but we must shape AI first. Africa has the opportunity not just to consume technology, but to co-create it in ways that honour our lived experiences and knowledge systems. A technocritical approach reminds us that true innovation doesn’t mean catching up to the Global North—it means confidently charting our own course.
Article written By Dr Miné de Klerk and Dr Nyx McLean
