Computational thinking for an AI age

Transforming K-12 education to develop resilient students for the future of work was a key theme at the recent World Innovation Summit of Education in Doha. Ledetta Asfa-Wossen reports.

Computational thinking for an AI age

This article is taken from the Winter 2023/24 issue of

Think Global People magazine

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Traditionally, education systems across the world have placed the most value on three core subjects, one of which is maths. But in the age of AI, should students be learning maths in the same way? And, what other skills do students need to stay future-proof ?With AI reshaping industries and workplaces, understanding the core principles of computational thinking is no longer an option but a necessity, said Conrad Wolfram, co-founder and CEO of the Wolfram Group in his keynote.“For the past 20 or 30 years it’s been obvious that the subject of mathematics is not aligned with the real world,” he opened. The problem with traditional maths he argued is that humans are doing the calculations. Instead, he described the need for integrated learning across the education system that utilises computational tools.

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“We have a whole new raft of computational technology of AI, which will affect all subjects in different ways. We don’t know yet how it will affect them in the real world. We are still discovering that. But we need to not make the same mistake we have with mathematics and change quickly,” he warned.Education is in urgent need of updating, but often the focus is on the wrong thing, argued Wolfram. “New technology changes the real world; therefore, it needs to change what we learn. We can’t just teach the same old subject, because that isn’t what the real world is doing.”The second thing AI changes, which is often the focus, is the pedagogy. How do we get people to learn well the subject that they need to learn? However, he stated the focus should be more on what students are learning, not just how learning will be delivered.“You need to change the subject, not just how you teach it. AI drives the need for change, but it also provides the tools to achieve that. We need to reset the curriculum for a sort of human computer optimisation. We are in a world where we are sharing intelligence, which is quintessentially human with machines for the first time. So, we’ve got to ask the question, what is for the machine and what is for the human? And what does that mean about what we need to learn as humans?”While it was agreed by most that some fundamental elements of education will remain unchanged – certain subjects will be affected more than others and must evolve in order to prepare young people for the world they face.One essential skill for K-12 education and beyond, according to Wolfram, is computational thinking, or computational literacy.


Computational thinking is an approach to problem solving that can be transferred to a computer. The view is that it
provides a vital link between the creativity and flexibility of the human brain, and the speed and efficiency of computation, so it is a key skill for an AI era.Gone are the days when simply having the hard skills for coding or telling a computer what to do was enough. Students entering the future workforce need a computational thinking mindset, so that they can explain the process in a way that a computer will understand.“We need everyone to have computational literacy. We need the ability to comprehend decisions made using the power of computation. It’s critical to our societies,” he added. Computational literacy being a more overall understanding, and computational thinking being better suited for those who need a higher level of reasoning for their chosen area of study or work.There are three key reasons for this, noted Wolfram. The first being the rise of technical jobs. Secondly, because an increasing amount of jobs are becoming more technical. And lastly, for everyday living.A universal example of the value of computational thinking, said Wolfram, was the pandemic. “Should you have a vaccine, should you not? What is the level of risk? We were all presented with datasets, graphs and statistics, and as a population we were supposed to understand what to do. Many decisions, even of life and death, are determined by computation in our everyday lives. That wasn’t really true 20 years ago. So if the population does not understand how to assimilate that, we have a major problem of trust and logical mind training.”Even if you’re not specifically using computation, computational thinking arms people to think in a reasoned way. In fact, he believes that computational and data literacy is integral for future job security.“If I want to organise a business I can think about it in English, but I may do better to think about it with a computational approach. Computational thinking is important for everyone to make better decisions, for life, work, and society.”


Wolfram believes maths in particular needs serious reform. “There is no core computational thinking and computational literacy subject anywhere in the world. And maths, which ought to be that subject and is essentially in every school curriculum for many years in people’s lives, is 80% wrong by the time you get to secondary school. It’s that bad.”Why? Because computers are not used for calculating. “Deploy a computer for problems that you have using computation because in real-world maths, computers do almost all the calculating, but the techniques we are teaching are based on hand calculations.”Evaluating social media, fraud detection and so on are essentially mathematical problems and you can’t solve these without a computer so our subjects should reflect that, noted Wolfram.“If you remove the computer from calculating, you remove most of the context of mathematics, and therefore you’ll be teaching largely the wrong subject.Most of the context that we think is so important in our AI age for mathematics – like medicine, bioscience, data science, finance – they all rely on computers. None of those existed for mathematics before computers in any serious way before. Mathematics has been liberated from hand calculating by computers and the most incredible mechanisation. So, if you go back and say, right, we want to teach people in education for the context of the real world, and you strip the computer out of it, there isn’t a context and you learn the wrong toolset.”But there is a way forward, and he is surprisingly optimistic. Many educators have learnt traditional maths so Wolfram suggests working backwards to understand what’s relevant in an AI world. “What we need is a computational curriculum that assumes computers exist.” It’s not just computational thinking we need either. “I think we should teach machine learning in primary schools too,” he added.


So, what does Wolfram think a new computational curriculum will achieve? “What we now need is first-rate human problem-solvers, not third-rate human computers. We need to work a level up from the machines, not compete with what machines do. If history has told us anything it is when we have industrial revolutions, when we have new machinery, don’t get the humans doing what the machinery is now good at. Instead, get them doing something more difficult, more conceptual, bigger.”Another reason for his championing of computational thinking, along with many other thinkers on the future of education and work, is the computational knowledge divide.“We have a few people at the top of society who are good at this stuff. And we have most of society depending on this who don’t know much about this at all, and that’s very dangerous.”What we need, concluded Wolfram, is computational literacy for all and education reform for an AI age – not just for maths, but all subjects.

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