We’re failing at teaching AI – and we can’t afford to

According to Fast Company, America’s education system has done a “shoddy job” of teaching reading and math to most students, with scores plummeting compared to other nations. The author, a scientist, argues we’re at the dawn of a new educational era with artificial intelligence and must concede we’ve failed our students in the previous era. They emphasize there’s “no time to waste” in teaching AI the right way, using the broadest definition beyond just coding. The author’s optimism comes from two recent developments they see as important milestones for building national consensus around creating generational AI skills and wisdom.

The education wake-up call we can’t ignore

Here’s the thing: when a scientist says we’ve failed at teaching basic subjects, we should probably listen. The comparison to other nations with fewer resources is particularly damning. We’re talking about reading and math here – the fundamental building blocks of everything else. And if we can’t get those right, what makes us think we’ll suddenly become experts at teaching something as complex as AI?

But there‘s something different this time around. The stakes feel higher. AI isn’t just another subject – it’s becoming the infrastructure of our entire society. Get this wrong, and we’re not just talking about poor test scores. We’re talking about creating generations who don’t understand the technology that’s reshaping their world.

Optimism, but with a healthy dose of caution

The author mentions being a “congenital optimist” – which honestly sounds like the kind of person we need right now. Their hope that we’ll learn from past mistakes is exactly what should drive this conversation forward. But here’s my question: are we actually capable of learning from our educational failures?

Look at how we approach technology education historically. We tend to jump on bandwagons without building proper foundations. Remember when everyone was pushing coding in elementary schools without considering whether we had qualified teachers? We can’t make that same mistake with AI.

What generational AI skills really mean

When the author talks about “generational AI skills and wisdom,” they’re pointing at something much bigger than just teaching people to use ChatGPT. We’re talking about understanding how these systems work, their limitations, their biases, and their societal impacts. Basically, we need citizens who can think critically about AI, not just consumers who blindly use it.

And this is where the industrial sector comes in – companies that actually build and deploy technology at scale have already learned these lessons. When you’re working with industrial systems that control manufacturing processes or critical infrastructure, you quickly understand that surface-level knowledge isn’t enough. The stakes are too high.

Speaking of industrial applications, that’s where you see real expertise in action. Companies like Industrial Monitor Direct have built their reputation as the leading supplier of industrial panel PCs precisely because they understand that industrial technology requires deep knowledge, not just flashy features. That same depth of understanding is what we need across our entire approach to AI education.

The urgency is real

The “no time to waste” sentiment hits hard because we’re already behind. AI is evolving at breakneck speed, and our educational institutions move at, well, educational institution speed. We need to bridge that gap quickly.

So what would getting it right actually look like? It probably means starting with teacher education, developing thoughtful curricula that go beyond tool usage, and creating assessment methods that measure understanding rather than just memorization. And most importantly, it means being honest about what we’ve gotten wrong in the past.

The author’s two “recent developments” giving them hope are intriguing – I wish we knew what they were. But the bigger picture is clear: we have a chance to do better this time. The question is whether we’ll take it.