(Part 1 here) (Part 2 here) (Part 3 here) (Part 4 here)
Over the course of this series I have explored the AI challenge to the assumptions education has rested on – economic purpose, the mind as the ground of our worth, even the irreplaceability of human connection. My conclusion is that if we have the nerve to act on it, this may be a liberation, albeit an uncomfortable one.
But Monday morning approaches, and the school bell will ring. Anyone who has read these posts is entitled to ask so what? A series that only asks questions is a luxury no parent or teacher can afford. So here it is; much more direct than what came before – principles, not a playbook. Some of it we already do; all of it we could do better. Some of it I’m sure of; some I want to do but am not entirely sure how; we’re working it out as we go.
Here we go.
1 Teach for encounter as well as content. Schools already know that expeditions and service work because they create encounter; I think it’s time we stopped exempting the academic classroom. The way we teach mathematics, history, science, literature, the arts – all of it – needs to become what it was always capable of being. A mathematics proof that demands the student think for themselves rather than reproduce a method; a history class grounded in the place students are actually living; a drama rehearsal where the student discovers they can inhabit a life entirely unlike their own; a science curriculum that asks not just how the world works but what it means that we can ask. No part of the curriculum should remain a dry rehearsal for an exam that a machine could pass tomorrow. The best schools already teach this way, but the distance between that aspiration and the reality of a Friday afternoon in November is bigger than we often care to admit. Still, the aspiration is the right one, and the risk now is that we lose sight of it entirely in the scramble to respond to AI. Hold it, work toward it, never lose it.
2 Stop justifying education in terms of employability; it’s an outcome, not the purpose. If students ask why they should study mathematics, it’s probably because we failed on the encounter part and are having to sell content to students. That’ll happen sometimes, whatever we do – not every teacher can reach every student – but if we answer because it will get you a job, then we’re speaking from exactly the mindset that AI is about to dismantle. A machine that does mathematics better than any human only makes the study of mathematics pointless if economic utility was the only reason to study it; but it never was. That the study also gets them a job is, for now at least, a very welcome outcome, not a justification. The encounter with abstract thought changes the student who engages in it, and that should always have been the reason. So we need to say it; say it to parents, say it to students, say it at open evenings, say it to each other, say it to ourselves. If it sounds strange, we still need to say it until we’ve thought hard enough about it to either believe it or find something better.
3 Hire, highlight and promote teachers who reach students. Rina’s story(part 3 here) should trouble every educator. She was surrounded by people who cared about her, and she turned to none of them. The AI helped, not because it was warm but because it felt honest. If we reward polish and confidence over the capacity to see a student clearly and say the hard thing with kindness, we are selecting for exactly the qualities that AI will expose as insufficient. The best teachers are the ones that get through. That’s harder to train for, and more slippery than can be captured in professional standards and rubrics. It may well mean more tolerance for mavericks than a well-oiled and compliant machine might like. So be it.
4 Do what matters, as well as what is easy to measure. Education is about the formation of a whole human being. The student who held his nerve on the mountain, the teenager who placed herself on stage with no safety net, the young person who gave an afternoon to someone who had no claim on him, and the one who changed their mind about something important because they encountered a perspective they couldn’t dismiss – these are not supplements to the real business of education; they are the real business. Education reduced to cognitive output is the part AI can replicate; everything else is the part it cannot.
5 Talk honestly with parents. Kim’s father (part 2) was not wrong to worry about his child’s future. As parents we all do, because the deal we grew up with (work hard, get qualified, doors will open) served us well. But most of us already sense the deal is changing and so parents don’t need us to pretend otherwise; they need us to say it clearly and then show them what we’re doing about it. The most durable gift we can give our children may not be a credential but a capacity to think, choose, and adapt. That’s a tough thing to hear, because it means giving up the thing that makes us feel safe. But it has the advantage of being true.
6 Talk about AI policy in the context of human purpose. Most schools I know have spent the past two years writing AI policies: what students may and may not do with large language models, where the line falls between use and misuse. These policies are necessary, but they don’t touch the question the technology actually raises: what is education for? For many organisations, AI changes how they work but not what they’re for. Hospitals still heal people; armies still defend countries. Schools are different, because AI puts the question of purpose itself under pressure. The policy conversation matters, but it’s a trap if it lets us avoid that harder one.
7 Resist the temptation to have all the answers. An easy but dangerous response to AI is to pretend we know what is coming. We do not. That’s obvious in the various unanswered tensions and unopened questions in this series. And much as it would make us all feel better if I could stand at the next townhall with a settled direction, the most honest thing we can say right now is: we are paying attention, we are thinking hard, and we are making choices based on the best understanding we have, knowing it may need to change. That is the right thing to do. The schools that will navigate this well are the ones with the deepest understanding of what they are for, and the nerve to hold that understanding steady while everything shifts.
None of this is easy; some of it will be unpopular. Some of it already is. But when a student asks, as they so often do, why are we learning this? we should be able to answer: because of who you will become.
