By Michael-Patrick Moroney

If artificial intelligence is the future, what happens when you raise a generation of kids who can’t think without it?

We’re entering an age where AI can write your essay, summarize your textbook, and pass your standardized test while you scroll TikTok. It can fake fluency, simulate depth, and turn a D+ student into a passable B overnight. What it can’t do - at least not yet - is teach students to care, to think critically, or to grasp why something is true instead of merely stated.

The real crisis isn’t that AI is getting smarter. It’s that we’re getting comfortable being dumb.

Nicholas Carr, writing more than a decade ago in The Shallows, warned us about this creeping erosion of cognition. “As we come to rely on computers to mediate our understanding of the world,” he wrote, “it is our own intelligence that flattens into artificial intelligence.” In 2025, that doesn’t read like prophecy. It reads like policy.

Across the U.S., public education is already under siege. K–12 spending per student has stagnated or declined in many states when adjusted for inflation. At the same time, we’re watching the slow gutting of the very subjects that train judgment - civics, arts, philosophy, literature - all being edged out by tech-skills bootcamps and STEM-centric testing mandates. Teachers are leaving the profession in record numbers, burnt out by impossible demands and disillusioned by a system that now treats education like a spreadsheet optimization problem.

Into this mess walks generative AI: confident, fluent, fast, and free. Students are using it to bypass effort; administrators are eyeing it as a way to slash costs. Nobody’s really stopping to ask whether anything is actually being learned.

Sociologist Ruha Benjamin puts it plainly: “We are not raising kids who are tech-savvy. We are raising kids who are tool-dependent.” And that dependency is deepening fast.

But AI isn’t the villain. It’s a mirror. It reflects our values - or lack of them.

Used wisely, AI could spark a golden age of individualized, interactive, global learning. It could help a dyslexic student write with clarity or allow a kid in a rural town to explore quantum physics with the help of a synthetic mentor. It could democratize understanding and surface new perspectives across languages, borders, and identities.

But instead, we’re letting it write book reports.

Sal Khan, founder of Khan Academy, argues that “technology should amplify human potential, not replace the effort it takes to cultivate it.” And yet, in many classrooms, that’s exactly what’s happening. AI is being used not to push thought forward - but to sidestep it entirely.

Classroom Design Mirrors Factory Design During the Industrial Revolution

This isn’t the first time a technology has disrupted education. The Industrial Revolution gave us mass schooling, but the system was designed to churn out factory workers, not thinkers. Schedules mirrored factory shifts. Bells told students when to move, not when to think. Creativity was a liability. Efficiency was everything.

When the PC and internet booms hit, schools lagged far behind homes in adopting the tools. While wealthier districts taught programming or media analysis, others were still fighting over whether to block Yahoo in the library. The result was a digital divide that widened achievement gaps and embedded tech illiteracy into already struggling systems. Even now, some students are learning to code in Python while others can’t get online unless it’s through a phone hotspot.

Then came social media, and everything fragmented. Attention spans collapsed. Misinformation went viral. Algorithms began shaping curiosity before curiosity even had a chance to form. Rather than help students navigate this reality, most schools just banned phones and called it a day.

With each technological wave, education did the same thing: it reacted late, treated the tool like an add-on, and rarely asked how to reshape learning itself to meet the moment.

Now we face the AI wave. And once again, we’re reaching for duct tape instead of reinvention.

If we continue down this path, we’re looking at a fractured future. In one scenario, wealthy students are taught to build, audit, and command AI while everyone else learns to depend on it like a calculator. The schools that can afford AI tutors and prompt engineering workshops will graduate architects of the future. The rest will graduate passive consumers of machine-generated knowledge.

In another scenario, big tech finishes what it started. Education is outsourced to gamified apps, subscription platforms, and algorithmically optimized micro-lessons. Teachers become moderators. Assignments are scored by machine. Curriculum is shaped not by what fosters wisdom, but by what drives engagement.

But there’s also a third road. It’s harder. Slower. More human.

This future reimagines education not as content delivery, but as a craft of discernment. It trains students to work with AI, not lean on it. Classrooms become labs of questioning, creativity, and collaborative reasoning. Students compare multiple AI outputs, evaluate their assumptions, test their accuracy, and revise them into something personal, rigorous, and true. Teachers become facilitators of intellectual exploration, guiding students as they navigate bias, synthesize complexity, and learn how to ask better questions - not just produce faster answers.

The window to make this shift is small. AI will soon be baked into everything - search, writing tools, textbooks, even grading systems. If we don’t actively design how it fits into learning, its defaults will shape the next generation by accident.

A student at David Game College in the UK tests out the new teacherless AI technology

So where do we begin?

Start by giving teachers the resources to lead this transition. That means paid training in AI ethics, pedagogy, and critical use - not just access to “edtech tools” but time to rethink how they teach. Trust them to experiment, to iterate, to question. Teachers can’t be expected to outthink the machines if they’re stuck printing worksheets on 15-year-old laptops.

Next, invite students into the design process. Ask them how they’re using AI already. Run workshops where they test its limits, identify hallucinations, and explore what it can and can’t do. Teach them not to fear the tool - but to understand it. An AI-literate student isn’t someone who can write a perfect prompt. It’s someone who can tell when the answer is wrong.

Parents need to be partners, too. This isn’t about banning devices. It’s about learning how to talk with kids about technology - not just screen time, but trust, authorship, effort, and curiosity. Sit with them. Ask questions. Use AI together. Then ask: “What do you think about this answer?” “Would you have written it differently?” “Does it feel true?”

Policy makers need to move quickly - and they need to aim higher than “modernization.” This isn’t about dumping Chromebooks into classrooms or replacing librarians with ChatGPT. It's about reshaping what we fund, what we value, and how we define success. That means embedding AI literacy alongside reading and math, protecting time for the humanities, and creating new models of assessment that measure the journey, not just the output.

The future of education isn’t about AI. It’s about whether we still believe in the kind of thinking that can’t be rushed. Thinking that stumbles. That doubts. That reflects, rewrites, and eventually, understands.

We don’t need to fear smart machines. We need to fear what happens when we stop demanding that humans get smarter, too.

So yes - AI is here. But it’s not the end of learning.

Unless we let it be.