Into the Room

“Man, I don’t even know if I want to bring kids into this world.”

I’ve heard that sentiment tossed around a few times, and it’s one of those emotionally-charged statements we generally hear from sociologists trying to understand where the upcoming generation lands on issues like optimism towards the future.

And the other day I heard that sentence verbatim from a former student of mine, a twenty-year-old navigating one of the stranger coming-of-age moments in recent memory.

He wanted to talk about AI. Specifically, his fear of it: what it's doing to the environment, what it might mean for someone his age who is just beginning to build a stable life in a world that has repeatedly shifted underneath his feet.

I didn't have a clean answer for him. I don't think anyone does. But I've been sitting with that conversation ever since, and I want to try to lay out where I actually stand.

I am not an “AI doomsayer.”

I try to hold these things with a measured hand, and I think there is a meaningful difference between taking something seriously and surrendering to unhelpful apocalyptic thinking.

The documentaries are being made, the books are being written, the op-eds proliferating aren’t wrong, and there are genuine cases to be made for some of the darker projections around where this technology leads us. I'm not here to dismiss that.

What I want to offer is some context, and then perhaps a more productive alternative than the ones I keep seeing.

We've Been Here Before (Kind of)

Humans are not strangers to the fear of transformative technology. History is, in many ways, a series of collective panics about what the “new thing” is going to take from us.

When Gutenberg's printing press arrived in 1450, serious thinkers argued it would erode human memory — that if knowledge became portable and reproducible, the mind would grow lazy, dependent, diminished.

When the industrial revolution reshaped the Western world and millions moved from farms to factories, the anxiety was existential: machines are going to dismantle our way of life and hollow out what makes us human.

When the internet expanded beyond military and academic corridors into everyday life, the chorus rose again.

Even the removal of cursive handwriting from school curricula generated genuine cultural mourning. Smaller scale, yes, but the same instinct: something is being lost, and we are not sure who or what we will become without it.

The most profound example, though, is the atomic bomb. In the aftermath of World War II, the entire world sat with the new and staggering reality that humanity now possessed the technology to annihilate itself.

Not metaphorically.

Literally.

And a real decade of rational, grounded fear followed as civilizations collectively reckoned with what this meant for the future of the species.

The Bulletin of the Atomic Scientists' Doomsday Clock was created in 1947 specifically to communicate existential technological danger. The clock, which still exists and is currently set at 85 seconds to midnight, indicates that our race is on a trajectory to destruction. It is worth noting that clock can shift backwards, for example in 1953, we were “2 minutes to midnight” in the wake of the hydrogen bomb, but we got some breathing room at “17 minutes to midnight” in 1991.

None of this is meant to minimize what we're facing with AI. I say it to remind us that the fear of being undone by our own inventions is as old as invention itself and that we have, historically, found ways forward that didn't require either collapse or abandonment.

But This One Is Different

We must, though, have a candid conversation and recognize that AI is not just another iteration of that pattern.

What made the atomic bomb terrifying in a graspable way was that we could see its consequences.

We had Hiroshima. We had Nagasaki.

We had footage, photographs, survivor testimony; visceral and physical proof of what this technology could do. The fear was enormous, but it was tethered to something concrete.

AI doesn't give us that tether. Its implications stretch in so many directions, across so many domains, that it becomes nearly impossible to visualize as a single threat. The question of AI in surveillance — the construction of monitoring systems at a scale no authoritarian regime in history has ever had access to — is a categorically different conversation from what AI automation will do to the labor market, which is itself a different conversation from what large language models are doing to the information ecosystem, to creative industries, to education, to intimacy, and the list goes on.

These aren't variations on a theme. They're separate problems requiring separate frameworks, and the fact that we're trying to hold all of them at once, under one word contributes significantly to the overwhelm.

Our society is experiencing collective cognitive overload, meaning our systems are short circuiting because there are too many inputs and demanded outputs. The "systemic risk" in complex technological systems is that when a technology becomes infrastructure across multiple sectors simultaneously, our normal risk-assessment tools fail us. In other words, because AI is affecting so much simultaneously, making it nearly impossible to get a firm grip on the core of the issue, ways of thinking and problem solving that have worked in the past are now failing us.

Add to this that we are not processing any of this in a vacuum.

We are still, as a civilization, recovering from the COVID pandemic.

Many of us are genuinely still catching our breath (or trying to) from the geopolitical turbulence of the last several years.

The rate of change has outpaced our collective processing capacity, and into that already-saturated cognitive space, AI has arrived not gradually but explosively. Its sophistication doubles and redoubles in ways that outrun the intuitions we normally use to make sense of the world, and Anthropic recently commented that its AI models are “not far” from being able to improve themselves autonomously.

So yes.

The fear is understandable.

It is, in a very real sense, biological. We are wired to fear what we cannot name, and AI right now is a shape and form we do not yet have adequate language for.

What the Fear Is Actually Showing Us

There's something important buried inside this anxiety that I think gets missed: AI isn't creating new problems so much as it is illuminating old ones.

The concerns about data centers consuming water at alarming rates in communities that never consented to host them? That's a story about corporate power and the absence of accountability — a story we've been failing to write properly for decades.

The conversation about AI-generated misinformation? That's a conversation about epistemic fragility that was already upon us before large language models existed.

The fear about AI replacing workers? We've been managing an increasingly winner-take-all economic arrangement for a long time, at least in the United States.

AI is simply turning up the contrast on all of it.

In that sense, AI is less the disease and more the diagnostic. It is making visible, with unusual urgency, the cracks in the structure we have been papering over in our governance, labor systems, and information commons.

Whether that leads to repair depends entirely on whether we choose to look.

Most of us would rather not. It is this same complacent disinterest that has been used against us in the past, and this instinct is understandable. Who has the time to sit around and think about these things when we have lives to live?

But abdicating our voice and responsibility is exactly what systems more interested in the dollar than benefiting humanity are counting on.

On the Environment, and the Long Arc of Adaptation

I want to address the environmental piece directly, because, for me personally, it deserves a specific response.

The construction of massive, water-intensive facilities landing in communities without meaningful public input is a legitimate concern. The opposition to these facilities is not anti-progress hysteria. It is people asserting, correctly, that they have a right to weigh in on how their land and water are used.

That pressure is appropriate.
That pressure should continue.

And I also believe, with real conviction, that we will find better solutions.

The first computers occupied entire warehouses. The environmental cost of early digital infrastructure was enormous and seemingly intractable. What followed was decades of miniaturization, efficiency gains, and gradual integration of renewable energy sources. Granted, this did not come about because the industry was naturally virtuous, but because people pushed and demanded, and the engineering responded. The arc from room-sized mainframes to the device in your pocket is the arc of a technology forced, by pressure and ingenuity in combination, to become less destructive over time.

We are at the beginning of that arc with AI infrastructure. We are in the sprawling, resource-hungry early phase. I believe we will not stay there, but only if we stay engaged and keep demanding better.

It is worth noting that wrapped up in this concern is the recognition that just because we have found solutions, temporary as they may be, the progress hasn’t always been clean and the cost has not been evenly distributed.

The Most Dangerous Move Is Leaving the Room

I build with AI. Every day.

I am currently using it to develop Arete — a tool designed to help people become more intentional, more integrated versions of themselves.

And I sit with the moral weight of that constantly. I am not unaware of the irony nor naive about the tension. I read the literature, watch the documentaries, occasionally lose sleep over some of what I find, and still wake up the next morning to keep building.

Because here is what I've come to: if the people most concerned about ethical AI are also the people who disengage from AI — who refuse the tools, who exit the conversation, who retreat into principled abstinence — then the room where AI's future is being decided will be populated almost entirely by people who are not asking the questions we need them to ask.

I understand the impulse to opt out. I even understand the looking at the seemingly insurmountable learning curve and deciding to not even bother.

I have thoughtful friends who want to step back entirely, to treat non-participation as a form of resistance. And I respect that instinct.

But the analogy I keep returning to is this: telling people we should all go back to riding horses is a morally coherent position, and it also has no purchase in the actual trajectory of civilization.

The question is not whether AI will remain part of our lives.

That question has been answered.

The question is what kind of relationship we are going to insist on having with it.

The path forward is not silence, but in showing up as we have always done as Americans: to vote, to protest, to regulate, to demand.

The pressure being applied to data center expansion right now? That matters.

The conversations happening about AI in classrooms, in courtrooms, in creative industries? Those matter.

And they will matter more if the people having them understand the technology they're talking about.

Putting real pressure on OpenAI, on Meta, on Anthropic, on Google — demanding that these companies operate inside boundaries that society has collectively set, not the other way around — is not naive idealism. We have done this before. The internet is full of things we collectively decided it cannot be used for. Not because the companies wanted it that way, but because enough people stood up and said no.

That mechanism still works. But it requires participants.

I have been working in AI daily for the better part of a year and I’ll tell you plainly: I would not have been able to build what I've built, as fast as I've built it, without these tools. I sit with that fact carefully and it comes with equal measure of gratitude and responsibility.

I also know that I am still learning what AI actually is. Anyone who tells you they have it fully mapped — the implications, the endpoints, the final shape of what this becomes — is probably not being honest with you. Most of us are barely scratching the surface. The honest response to that uncertainty is not to shrink from it but to engage it with rigor, with ethics, and with the humility to keep learning.

I’m not yet sure why or how I landed in this position. The world of AI and technology is a pretty far cry from my familiar land of melody and harmony. In some ways, I feel like I was thrust into this space without my consent or awareness—and yet here I am having conversations around very real issues in our world and how to move forward.

A few weeks ago I moderated a panel with Tampa Bay Tech Week on Maintaining Trust in the Age of AI, and while I still have some personal uncertainty about my part to play in this grander scheme, I do have one certainty: it was no mistake that I arrived at this point.

Despite the tumultuousness of our times, especially concerning the implications of artificial intelligence, one of my deepest hopes is that Arete becomes a model for human-centered technology, one that helps show the way for how we can reconcile our needs as humans with the advancements of our world.

A world that is not going to get less complicated.

The technology is not going to retreat. What we get to decide is whether the people in the room when the decisions are being made are people who actually give a damn about what it means to use these tools well.

I want to be one of those people. I hope you do too.