Read the roadmap for ChatGPT-age education reform!

The byline for “The Math(s) Fix” was “An Education Blueprint for the AI age”. And I meant it. I just didn’t know that ChatGPT would so suddenly expose the need for reformation.

I have relaunched my book today, with a new foreword (for Kindle Edition) that explains “how The Math(s) Fix addresses key issues not only for the future of maths, but for AI-age education in general. This book uniquely puts the ChatGPT shock into perspective by offering the reformer's roadmap for reaction to policymakers, employers, parents, teachers, and students.”

Here it is!


"The real world changed. How should education react?" Since I wrote The Math(s) Fix some 3 years ago, this has been an opening question of many of my talks.

Why? Because mathematics education so epitomises the wrong reaction: ignoring how computers have revolutionised the real-world subject, getting students to compete with what the machines do best, and lose. The Math(s) Fix is the only detailed proposal for the why, what, and how of "fixing maths", with the obvious, critical, yet ignored assumption that computers exist—an 80% change.

But it's more; it has a bigger purpose, as the An Education Blueprint for the AI Age subtitle foreshadows—namely to prepare for fundamental change for our new industrial revolution, the "AI age".

Enter ChatGPT, publicly, December 2022. Just as high-powered computers have fundamentally changed the real-world subject of maths, this AI promises to change how writing and communications occur, though we don't yet know how fundamentally.

Talk about a sudden, visible takeover of quintessentially human skills by AI. Talk about the real world changing. Talk about an immediate upset in education. With its extraordinary ability to "understand" questions and write cogent answers, ChatGPT is writing "good" student essays and achieving successful assessment scores in "hard" exams—the epitome of traditional human educational success. But an AI, a computer, a machine is achieving this.

This is a single moment of shock across education, whereas real-world maths requirements have diverged from maths education over decades; a slow but dramatic bifurcation. ChatGPT is a sudden, highly visible disruption—and therefore causing urgent questioning of what human education should be about. One thing's for sure about the answer: it's certainly not learning how to be a third-rate substitute for what machines successfully do in the real world. It is not pretending they don't exist. It is learning how to manage them. It is stepping up to the next level.

Here's the good news. We've been reconceptualising education for a mixed human-AI age for more than a decade, and you will find it spelt out in The Math(s) Fix. Whilst it comes from a maths angle, and details what to do about maths itself, it goes much further, mapping out the answers to broader questions about how to build a modern curriculum, how to decide what's for the human and what's not, and how we need to reform our whole educational ecosystem to enable rapid subject as well as pedagogical innovation that's so failed for decades.

Rereading The Math(s) Fix again through a ChatGPT-era lens, these are topics that are front and centre—not just for maths, but for the future of education in general:

  • The purpose(s) of education

  • How to judge if a change is fundamental or just a fad.

  • How needs change for survival v. subsidence v. value-add with new industrial revolutions

  • Building human capabilities for handling problem complexity, including with computers

  • How you build "thinking outcomes" for humans and abstract them

  • Which subjects are required for all, and whether this needs to change

  • Democratising new subject areas previously for specialists only

  • Do we need teachers, and if so, how do we help them help students with change?

  • Understanding the difference between the essence of a subject and today's machinery for carrying it out

  • Reconceptualising learning engineering for the AI age

  • Handling objections to computer-based change

  • Do you need to know how the computer works before you can trust what it produces?