Dr Paul Jones, associate dean for education and student experience at Aston University, analyses the difference between what traditionally would have been students basing A-level decisions on the job they wanted versus students now picking the A-levels that will now most likely get them a job in the market.
He said: “The continued popularity of maths, alongside the growing popularity of economics, may tell us something interesting about how young people are thinking about their futures.
“For a long time, we have tended to imagine educational choices as beginning with a career: ‘I want to do this job, therefore these are the subjects I need.’
“But another consideration may increasingly be entering that decision. Young people are looking at a labour market shaped by economic uncertainty, rising living costs and rapid developments in artificial intelligence, and asking which subjects will leave them with the widest range of possibilities later.
“There is evidence that employment prospects are becoming more important to students. UCAS has identified a post-pandemic trend towards applicants becoming increasingly career-focused, while earlier research found that more than half of students said high graduate employment rates had become more important to them following the pandemic.
“At the same time, young people are not necessarily becoming more certain about the careers they want. OECD analysis of PISA 2022 data found that 39 per cent of 15-year-olds across OECD countries could be classified as career uncertain.
“That combination matters. If young people care increasingly about future employment while remaining uncertain about exactly what they want to do, choosing subjects that keep several doors open becomes a rational response.
“This is where maths becomes particularly interesting. Maths connects with careers across economics, finance, engineering, computing, data and the sciences. It also provides some of the intellectual foundations needed to understand an increasingly AI-enhanced world. Modern AI systems may appear conversational, but their development and use depend on mathematics, statistics, probability, modelling, optimisation, computing and large-scale data.
“That does not make maths AI-proof. AI systems are already becoming highly capable at many mathematical and coding tasks. The more interesting possibility is that maths may be AI-complementary.
“As AI becomes better at producing calculations, analyses and recommendations, part of the value of mathematical education may be found in helping people understand what those outputs mean and how they should be used.
“Probability, statistics and quantitative reasoning can provide some of the tools needed to understand uncertainty, recognise assumptions and judge whether a conclusion is plausible.
“This matters because however sophisticated AI systems become, we will still want humans to exercise judgement when interacting with them. An AI system might tell an organisation that one candidate has a higher predicted probability of succeeding in a role, that one investment has a greater expected return, or that one student has a higher predicted risk of dropping out.
“The difficult question is not always whether the calculation is technically correct.
“Rather, it is what we should do with that information. How certain are we? What assumptions have been built into the model? What are the consequences of acting on the recommendation? The bigger question, then, is when human judgement should override what the system is suggesting. Mathematics does not automatically produce good judgement, but it can provide some of the intellectual tools needed to exercise it.
“The Royal Society has made a related argument in its work on AI and education, highlighting mathematical, data and computing skills as important foundations for enabling young people to understand, manage and build AI systems in the future.
“This may become increasingly important as AI changes entry-level work. Research from the Institute of Student Employers found that 87 per cent of employers expect AI to reshape graduate and apprentice roles, with the dominant expectation currently being that many roles will change rather than simply disappear.
“For a 16-year-old choosing A-levels, that creates an extraordinary challenge. How do you make educational decision now for a labour market that may look substantially different when they graduate?
“Career psychologists sometimes use the concept of career adaptability to describe the psychosocial resources people draw on to navigate changing and uncertain working lives. The growing popularity of subjects such as maths may be consistent with a related, though not necessarily conscious, strategy: maintaining the capacity to change direction.
“We should not imagine thousands of teenagers selecting maths after carefully analysing large language models and the future of artificial intelligence. Their decisions will still be shaped by enjoyment, ability, teachers, parents, universities and many other influences.
“But there may nevertheless be a broader change worth watching. Students have traditionally been encouraged to ask, ‘what do I want to do?’ We may be seeing a shift more towards ‘which choices will leave me with the most options for the future?’
“If that shift is occurring, the popularity of maths is not simply a story about earnings or STEM. It may also reflect a form of career risk management.
“In an age of AI-enhanced working, the enduring value of maths may not be that it allows humans to compete with machines at calculation. It may be that it gives people some of the understanding they need to remain active participants in decisions involving those machines, rather than becoming passive recipients of their conclusions.”
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