The Great AI Misunderstanding
Why productivity gains at work are not the same as learning at school.
Each week I seem to find a new way of using AI with each discovery feeling more incredible than the last. From sense-checking emails to brainstorming ideas for a blog or linking together large academic data sets, the opportunities for me as a headteacher feel limitless and exciting. For children too, the wonder of entering a simple prompt and watching the computer produce a near-perfect essay is seriously impressive and highly tempting. And this is at the root of a great and increasingly urgent misunderstanding of AI in education. Becoming more efficient at your job is simply not the same as completing your homework more quickly.
Many parents will have undoubtedly been encouraged to use AI extensively in their professional lives. Indeed, at Radnor House Sevenoaks, it is a priority for us over the next twelve months to increase our understanding and use of these tools across all elements of operations, back office and teaching administration. As with many workplaces, our goal in these areas is the final product. That might involve creating an Excel workbook for the finance department to capture costs for an upcoming trip or generating a campaign poster in marketing. The goal of the employee is to achieve the task as quickly as possible so we can move on to the next one.
For a student, the final product is entirely secondary. An essay or a maths worksheet is simply a vehicle to force the brain to think. The purpose of the task is not the generation of something tangible but rather the lasting memory of the thinking that went into producing it in the first place. This is why pupils are always encouraged to show their workings, map out essay plans and revise thoroughly for tests to ensure the ultimate goals of learning and building intelligence are met.
What happens when students use AI to complete a task is that the software very often does the heavy lifting for them. It might provide the structure for an essay which means they are not engaging with the planning stage. It might give them clues to complete a maths problem which prevents them from grappling with potential solutions. It might even remind the student how to conduct a fair experiment and rob them of the opportunity to recall the necessary conditions independently. Learning requires cognitive challenge because memory is the byproduct of thinking. When we attempt to bypass thinking, those crucial neural pathways simply do not form and student understanding naturally falls.
The evidence base for AI in education is patchy but the early indicators are all pointing in one direction. A recent meta-survey conducted by Stanford University points out that student performance often improves with access to AI tools but once these are removed the results are mixed. Researchers in this field are increasingly asking whether AI is simply helping students to complete tasks rather than helping them to acquire durable learning skills. While there may eventually be a valid place for AI as a supportive revision tool for older students tackling their GCSEs and A-Levels, the data does not yet justify its heavy use for most learners.
I am increasingly convinced that AI for students will follow a similar pattern to smartphones in schools around 2010. Fifteen years ago, many educators tried to convince themselves that phones would be great for students in the classroom because they could record lessons, take photos of notes and research topics as they were being delivered. This led to almost all schools allowing phones throughout the day, only for us to realise too late the negative impact they have on social skills, concentration and wellbeing. I remember distinctly people trying to persuade me of these merits at the same time Radnor took an alternative path and banned phones during the school day, one of the only schools at the time to take such a forthright position. AI is following a similar trajectory where many parents are keen to see their children use it for task completion without fully appreciating the downside risk to learning and understanding.
Workplace efficiency tools are fundamentally different from educational development tools. As AI becomes more embedded in everyday life, we must be careful not to confuse faster task completion with genuine learning. Real learning is often slow, effortful and demanding. It is in that struggle that understanding deepens, memory forms and resilience grows. If young people come to rely on AI to bypass that process, we risk weakening the very habits of mind that education is meant to build.
