Daniel Susskind: ‘We should try to be imaginative.’ All photographs: Lydia Goldblatt/The Guardian
A Dr Seuss-style story written in seconds alerted me to the power – and perils – of the technology. But how can children embrace it without forgetting core skills?
When I was growing up, my dad and I often talked about a story we wanted to write together. It was called “The Day Nobody Went to Disneyland”. One day, the story goes, the weather is so perfect that everyone in the world decides to stay away from Disneyland because they expect it to be far too busy. But my dad, who has the same thought as them, sees the disappointment on my face that morning – and decides to risk it. We set off. And when we arrive, the park is completely empty. Nobody else was brave enough to visit. We have everything – the rides, shows, food – to ourselves.
I loved the idea of writing that story. But, as so often happens, we were too busy to do anything about it. Life ran away from us. I grew up, and we both forgot about it.
Thirty years later, I was at my parents’ for dinner with my own children (eight, five and two). For some reason, the idea popped into my mind again. I told my oldest about it – and she wanted to hear the full thing. We turned to ChatGPT, gave it the vague outline and asked it to have a go at writing the story in the style of Dr Seuss (one of our favourites). Within a few seconds, we had it. She read it out – and we laughed.
Of course, what this AI generated wasn’t perfect. A few lines didn’t quite make sense; a few Americanisms had slipped in (“sneakers”, “cinnamon buns”). But that night on the sofa we had great fun together tweaking the prompts, refining the story, adding more scenes, working with this strange new creative partner to do something that had escaped my grasp for decades.
For the last 15 years, I have been exploring the impact of AI on work and society. But becoming a dad of three small people has made these disruptions far more personal: it is clear that their future is going to look wildly different from my past.
For my wife, that realisation really sunk in a few weeks ago, on a journey to her parents’ in Suffolk. Three children, confined in a car, stuttering along the A12, is a combustible setup. So we were thrilled to find a rare podcast that everyone miraculously enjoyed: History’s Not Boring, a series of 15-minute bursts of conversation, on a kaleidoscope of subjects, narrated by two children.
We are letting children down if we prepare them for the world that we grew up in, not the one they will actually inhabit
As we listened, we started to speculate in the car about who these whiz-kids might be. Where were they from? How were they selected? How did they juggle this job with school? Eventually, I went to the website to find out. All our answers were wrong. The kids did not, in fact, exist. The entire podcast seemed to be generated by AI. None of us had realised.
It was a strange moment, learning that people we had grown fond of were not actually people at all. It was also remarkable that AI could create such high-quality educational content. But for my wife, a podcast and documentary maker, it was an unsettling moment as well: here was something that would have taken her and a talented team several days to make, and now it was being done without people.
My work on AI has taken me to boardrooms and conference halls, classrooms and government buildings. But wherever I go, one question is now asked more than any other: what should my children do?
Today, we are floundering. Teachers worry that the way they teach no longer seems to work. Parents, watching their children use AI to solve problems and answer questions, wonder what they really know. Employers doubt whether traditional educational achievements, awarded in time-honoured ways – coursework, exams, assessments – are still a useful guide to what young people can do.
Yet reacting to these new technologies by putting barriers up, as many instinctively want to do – banning, admonishing, punishing – just cannot be right. To begin with, this is the water in which the next generation will swim: we are letting them down if we prepare them for the world that we grew up in, not the one they will actually inhabit.
How often, for instance, have you heard people accuse students of cheating if they use AI to help them with their work? But at what point are we cheating them by failing to overhaul the way we are educating them? If AI is making education “too easy” for young people, at what point does the burden shift on to us, the adults, to make their education more testing, to push them on, to stretch them?
More importantly, this dismissiveness of AI is also unimaginative. It stops us appreciating the astounding possibilities AI could create for the next generation as well. Of course there are risks. But at the same time, if we use this technology wisely, what difficult ideas might the next generation now grasp, ones that were beyond us when we were in their shoes? What hard problems might they now solve, ones that once required years of training and experience – if they were solvable at all?
Forget future-proofing skills
A big part of the challenge of AI is that our traditional response to technological disruption in the working world – the idea of “future-proofing” people – no longer works. In 2013, the then prime minister David Cameron announced that England would become the first place in the world where all children in primary and secondary schools would learn to code. This, in the words of education secretary Michael Gove, would “equip every child with the computing skills they need to succeed in the 21st century”.
The idea seemed bold and clever: in the years that followed, it was hard to find an advanced country that did not follow our example.
Fast-forward to today. What does it turn out that the latest AI systems, such as ChatGPT and Claude, are best at doing? Writing code. In January 2026, Anthropic reported that 90% of the code for Claude Code – their AI-powered coding assistant – was itself written by AI. Skills that were meant to protect kids from technological disruption for their entire lives were largely redundant before they had even left school.
We must use AI critically, not blindly, keeping our basics sharp so we can tell when AI is being a savant – or an idiot
For politicians and policymakers, it is tempting to dismiss the coding saga as an unfortunate blip. But this is a mistake. The reason they slipped up was because they had believed in the idea of “future-proof” skills, the thought that there exists some valuable set of skills that AI will not be able to do for some time – and that by thinking deeply enough about the future, we can accurately identify them.
The truth is that we know only two things about what lies ahead. One is that it will be full of technologies that are far more capable than today. And the other is that we know little else. But rather than attempting to resolve this uncertainty, we have to accept it and instead ask a different question: how do we prepare the next generation to flourish in a future that we actually know surprisingly little about?
Get back to basics
The first step is to get back to basics. Since 2009, literacy and numeracy have been falling among young people around the world, according to the OECD’s programme for international student assessment (Pisa); the same holds true for adults. In itself, this is worrying. But given the uncertainty that we face about the future, these trends are a disaster.
Why such a calamity? To begin with, while it might be hard to say precisely which more advanced skills will turn out to be most valuable in the future – creativity, judgment, something else – they will rely in some way on these basic skills. They are the foundations for everything else.
What’s more, AI systems are far from flawless. They make mistakes, often on simple problems; they hallucinate, providing confident and plausible answers that are completely made up. They are, as the computer scientist Geoffrey Hinton put it, “idiot savants”. That means we must use AI critically, not blindly, keeping our basics sharp so we can tell when AI is being a savant – or an idiot.
So, with both those reasons in mind, we should be focusing intensely on teaching literacy and numeracy, even if AI does them better, as it increasingly seems to do. Getting back to basics is what an economist would call a “no-regrets” strategy – we will never regret improving these basic skills, however the future turns out to be.
I have used AI to respond to my five-year-old’s bedtime-delaying tactic of asking vast questions just as I turn down the lights
And we should try to be imaginative. When my eight-year-old grew bored learning her times tables the traditional way – long lists, learned by rote – I turned to ChatGPT to create various computer games, designed by her, to test what she knew. (Unicorns and rainbows featured in all versions.)
Then there was the time my five-year-old was tired of reading his standard-issue phonics books after school – there really is only so much Biff, Chip and Kipper a human being can take – and instead we used AI to generate some custom stories together, carefully tuned to his reading level and much closer to his favourite topics. (At the time of writing, HMS Belfast, TNT explosives and Bukayo Saka.)
Experimentation is important and we can learn so much from the creativity of others. Take Chris Moran, for instance, head of editorial innovation at the Guardian. His daughter had been reading Dracula at school but was struggling to place the sprawling novel in the real world. Together, with the help of AI, they built an app – PlotLines – which placed the story on an interactive 1890s Ordnance Survey Map, plotting the key scenes and character journeys around Europe, with the help of AI. (They have done it for many other books now, too.)
These are precisely the sorts of innovations we should be testing and embracing throughout education – rather than banning.
Source: The Guardian
Author: Daniel Susskind
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