Daisy Christodoulou, a prominent voice in UK education and the director of education at Edtech Firm No More Marking, outlined concerns about incorporating AI into classroom learning.
In a widely shared LinkedIn post, she challenges the logic of using AI tools in schools to prepare her for future office jobs.
Christodoulou acknowledges the growing presence of large-scale language models (LLMS) in the workplace and its usefulness in automating everyday tasks. “I'm not against it at work, and I'm far from it,” she writes. However, she argues that the professional tools used to efficiently complete tasks should not be confused with tools that support learning.
“Everyone can benefit if an auto mechanic, accountant or lawyer can use new technology to repair a car, complete a tax return or communicate it on a mortgage,” she says. “However, the purpose of training is not to replicate the final goal, but to develop yourself to achieve the final goal.”
Experts learn differently than beginners
Christodoulou builds her argument by referring to three major academic works on learning and expertise. First, she cites Paul Kirschner's 2009 study. “Epistemology of practice in a domain is not a good pedagogy for learning that domain,” Kirschner writes, adding that “the learner or beginner is not a miniature expert or expert.”
She also K. It utilizes Anders Ericsson's 1993 paper on “intentional practice.” This distinguishes between task execution and skill development. According to Erickson, activities in paid work are often not optimized for learning. Instead, improvement requires structured training separate from the workplace routine.
Finally, she highlights a 2025 paper co-authored by Barbara Oakley and Terrence Seinowski, and explores the risks of “cognitive off-roading.” The paper warns that it is overly dependent on AI to complete tasks. “Over-reliance on external memory can leave a correct collection of outputs, but there is no integrated understanding or procedural flow encylist that demonstrates true expertise.”
Even in the future of AI, writing skills are still important
Christodoulou emphasizes that basic literacy skills such as grammar and vocabulary must be explicitly taught and evaluated independently of AI. She uses examples from marathon training to illustrate the flawed logic of using AI as a substitute for skill building. “Acquiring skills [of running a marathon]don't start by running a marathon in every training session. ”
She also considers how the rise in AI will affect long-term employment trends. While some fear that they will completely replace professional roles, she points to historical evidence suggesting this is rare. Even in scenarios where AI completely changes the job market, she believes literacy and human judgment are essential.
Christodoulou concludes by reaffirming the enduring value of writing, regardless of how the labor market changes. Daisy Christodleu said, “I don't think writing or literacy in general will become outdated, whatever the potential future is.”
