Reprogramming the Classroom: Why Schools Need AI Expertise Now
- Ben Duggan
- Jun 5
- 2 min read
In an era defined by rapid technological change, the role of education is no longer to “keep up”—it’s to lead. At a recent lecture hosted by the London School of Economics, Fixing Education for the AI Age, Conrad Wolfram (of Wolfram Alpha and Mathematica) delivered a stark but compelling argument: much of today’s curriculum, especially in maths, is outdated, irrelevant, and failing our students.
His core message? We’re teaching the wrong things in the wrong ways—and the AI age demands a radical rethink.
Teaching for a World That No Longer Exists
Wolfram argues that real-world problem-solving today is driven by computational thinking, not manual calculation. Yet most schools still emphasise step-by-step arithmetic and abstract methods students will never use outside an exam hall.
We’re not teaching how to formulate problems, how to interrogate data, or how to apply algorithms to real-world scenarios. Instead, we’re preparing students for a world where AI is already doing the job better, faster, and more reliably. Students can sense the irrelevance—and disengagement follows.
Education at a Tipping Point
The credibility gap in education is growing. As AI tools like ChatGPT become embedded in everyday life, students question why they’re made to memorise facts or repeat procedures that a machine can handle in seconds.
This isn’t just inefficient—it’s demotivating. And worse still, it squanders the opportunity to build real, future-ready skills like judgment, creativity, data literacy, and ethical reasoning.
Why Specialist Input Is No Longer Optional
Schools alone can’t redesign education for the AI age. Subject teachers are stretched. Curriculum reviews are slow. Professional development often lags years behind the tools students already use.
This is where AI and tech specialists, curriculum designers, and data scientists can—and must—step in. Their role isn’t to replace teachers. It’s to empower them.
With the right external input, schools can:
Reframe content to reflect real-world applications.
Embed computational thinking into every subject—not just maths or ICT.
Implement AI tools in a way that enhances human teaching, not replaces it.
Design new assessments that reward higher-order thinking, not just tick-box accuracy.
Adapt innovation to complex educational settings, including PRUs—where trauma-informed, inclusive approaches are essential.
Toward a New Educational Ecosystem
Wolfram described education as an ecosystem problem. Outdated methods persist not because they work, but because the system’s incentives—league tables, exam specs, policy inertia—are misaligned.
Fixing education for the AI age means more than adopting tools. It means rethinking the foundations: What do we value? How do we teach it? Who gets to shape that journey?
We must act before policy catches up:
Hire AI and tech curriculum advisors.
Partner with ed-tech innovators and universities.
Embed career-connected, future-literate content across subjects.
Involve students in reimagining their learning—because they’re already living the AI age.
Final Thought: Don't Patch the Past. Design the Future.
AI is not a threat to teaching—it’s a mirror. It shows us what we’ve automated, what we’ve ignored, and what truly matters.
The question is no longer if AI will reshape education, but how—and who gets to decide.
Let’s not leave it to chance. Let’s not fix an outdated system in isolation. Instead, let’s invite the thinkers, makers, and students shaping the future of everything else to help shape the future of learning, too.
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