Death of human intelligence or the emergence of super-intellects – the advent of AI has caused nothing less than predictions of terror in terms of its risk or awe in terms of its power. New developments lead to new questions: How do you teach writing and math in times of AI – and does it mean that entire areas of human knowledge will not be taught anymore? What needs to be learned – and unlearned – in this age? What will be the risks – and the opportunities?
Here are four predictions for AI’s impact on education:
• Death of one-size fits all – hyperpersonalization and next-stage adaptive
There is indeed one type of education that could be made irrelevant by AI – it is the one-size-fits-all, sage-on-the-stage type. Andreessen Horowitz predicted that each child will have a personalized AI tutor. This technology already exists – it is adaptive learning. The next stage of adaptive, AI-powered learning will touch more than just cognitive skills. Gen AI can take course personalization to the next level. Learners will be able to follow a personalized course picking them up where they are.
AI makes it possible to provide individualized education at scale. This can create a huge wave of democratizing education – making it available to many at a much lower cost. This will bring about a radical shift towards user-centricity – the actual learners.
• A learning experience that learns – data-fueled learning effects
Students will be thrilled to hear that high stakes testing could experience its demise. Ongoing tracking made possible by AI-based data aggregation is much more efficient than sporadic testing and can be built into the learning journey. Tracking data collected this way can offer insights into what works and what doesn’t – and improve every interaction over time.
• From lean-back to lean-forward – practical learning
The artificial dissociation of learning and application, academia and real life, will be increasingly challenged. Learning can enrich practical experiences and through Gen AI, allow deep-dives into specific topics, with continuous learning loops as you go.
• 22nd Century skills
We are not even a quarter into the 21st Century and yet AI seems to have made the discussion on 21st Century skills old fashioned. The original assumption – since disproved – is that while rote knowledge can be automated, 21st Century skills – meta skills such as leadership, collaboration, creativity, problem solving – are the home turf of human intelligence. With Gen AI, this distinction does not hold true anymore. What is next – what is worth teaching so it is relevant in the 22nd Century? Einstein seemed to have had a glimpse into AI when he famously said that while solving a problem if his life depended on it, he would put most of energy towards asking the right questions. With AI, we are leaving the time of answers – the time of Enlightenment and scientific progress – for the time of questions.
AI is not about replacing human intelligence – it is about enhancing it. AI can be harnessed by education rather than feared by it—enabling learners to step up from objects of teaching to agents of learning.
The next stage will be going beyond providing information through Gen AI – increasingly, AI will enable more complex operations than information retrieval. For instance:
• Matching mechanisms can help create communities and pull people in the right conversations, while sparing them the ones that waste time.
• AI can become much more than a personalized course source or individual tutor – it can be a community manager or ecosystem creator.
• It can also enable co-creation from its users, as it already happens in gaming – enabling learners to step up from objects of teaching to agents of learning, including sharing their skills and contributing to learning communities.
We should not focus on where AI can replace humans – once the market shakes out, productivity savings will be shared across the board. Much more interesting is what tasks or problems can be tackled by AI that have previously gone unresolved? That is the real question.