Let's Stop Telling Kids to Opt Out of the Future

​In the same breath that we praise artificial intelligence as the defining technology of our age, headlines are warning college students to steer clear of computer science.

It sounds absurd—because it is.

Articles are cropping up like weeds, echoing the same message: There are too many computer science majors. The tech industry isn’t hiring. The golden era is over. The message is clear: if you’re a young student hoping to shape the future through code, don’t bother. Choose something else.

But look closer, and the contradiction becomes staggering.

AI is exploding. Investment is skyrocketing. Every industry—from healthcare to logistics to entertainment—is undergoing transformation powered by algorithms, data, and machine learning. And yet we’re telling the generation that could help shape this shift to step aside?

It’s not just a disconnect. It’s beginning to feel like a coordinated deflection.

The Distraction Game

It's quite obvious that AI doesn’t build itself, though, hmm? 

Behind every ChatGPT, autonomous vehicle, and personalized recommendation engine are thousands of engineers, data scientists, ethicists, and developers. AI isn’t a force of nature—it’s a human-built system. And like all systems, it reflects the values, incentives, and blind spots of those who build it.

So why, in the moment we most need a diverse, critically minded, and technically fluent next generation, are we dissuading them from entering the field?

Because power protects itself.

The more opaque and centralized AI becomes, the less scrutiny it receives. If fewer young people understand how these systems work—how they're trained, where the data comes from, what values are encoded—the easier it is for a small group of corporations and gatekeepers to control the narrative, the tools, and ultimately, the future.

The Pipeline Is Being Redirected

Let’s not forget who benefits from this shift. It’s not students.

These articles rarely acknowledge the structural reasons for tech’s supposed “downturn”—mass layoffs orchestrated to inflate stock prices, not a lack of need for talent. They don’t mention the rapid growth in AI startups or the endless demand for automation in industries struggling with labor shortages. They certainly don’t highlight that many so-called “non-tech” fields—marketing, education, journalism, law—are now becoming tech-adjacent by necessity. 

Instead, they paint a narrow, outdated portrait of computer science: a boom-and-bust industry ruled by FAANG companies, where your fate is sealed by your ability to land a Google internship. That story is increasingly untrue and dangerously limiting.

Conspiracy Or Just Capitalism?

Some will say this isn’t a conspiracy—it’s capitalism doing what it does best: optimizing for profit. Tech companies overshot hiring during the pandemic, the economy wobbled, and now they’re cutting back. Simple as that.

But when institutions, media narratives, and corporate messaging all align to dissuade young people from engaging with the most powerful technology of our time, it’s not just about quarterly reports. It’s about shaping who gets to participate in building the next era and who doesn’t.

What we’re witnessing is a subtle gatekeeping maneuver. Keep AI in the hands of the few. Maintain a skilled class of “builders” drawn from elite networks, while steering the public—especially those from underrepresented or nontraditional backgrounds—toward less disruptive paths.

What Happens If We Listen?

If we accept the message that computer science is “oversaturated” or that AI is a black box best left to the experts, we lose more than potential engineers. We lose watchdogs, dissenters, artists, philosophers, and policy-makers who also understand code.

We lose the chance to build an AI future that is inclusive, ethical, and human-centered, because we’ve narrowed the pipeline to only those already inside the circle.

What We Should Be Saying Instead

Rather than discouraging students from studying computer science, we should be expanding its definition and access. We should be telling students:

"Yes, learn to code—but also learn why you're coding, who benefits, and how to make systems better for everyone.”

We should be funding interdisciplinary AI education, promoting transparency, and creating alternative pathways into tech that don’t require elite internships or $200,000 degrees.

Because AI is not done growing. We all know it's only beginning. And the future depends on who shows up to shape it.
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Let’s not silence that future before it even starts.