The Singularity Isn't Coming. It's Already Here.

Not just didn’t love it. I actively avoided it. Star Wars? Nope. Star Trek? Pass. Anything involving spaceships or robots or alients? Nuh uh.

The problem was always suspension of disbelief. I’m a data person. I deal in facts and systems. Asking me to accept time travel or sentient androids? My brain just... couldn’t.

(Wait, I just remembered. There is one exception… Quantum Leap! Scott Bakula, anyone? I loved that show.)

But something’s changed in the last few years. Now I find myself reading post-apocalyptic fiction. The kind where civilization collapses and survivors have to rebuild. Unfortunately, it doesn’t feel like science fiction anymore.

It feels possible. Plausible, even.

Maybe my tastes have changed. Or maybe I just don’t need to suspend disbelief anymore. I can imagine a future where society is impacted in a major way by AI, directly or indirectly, and that impact leads to the collapse of civilization.

Temporarily or permanently.

No. (Probably not. Maybe? God, I hope not.)

But I have to confess something. I have a basement full of emergency supplies. Water reserves. Dehydrated meals. Medical supplies. I’ve become, somewhat accidentally, a bit of a doomsday prepper.

(Funny side note: when choosing those dehydrated meals, I had to factor in my picky eater’s preferences. Because even if the end of the world comes, he still won’t eat most things. Hence the case of Kraft Mac and Cheese and the Top Ramen stockpile. Apocalypse-ready AND kid-approved.)

So let’s talk about The Singularity. Not the sci-fi version I used to dismiss. The real version. The one that might already be unfolding while we’re busy arguing over em-dashes.

The Singularity is the theoretical point when artificial intelligence becomes smarter than humans and starts improving itself faster than we can control or even understand.

Ray Kurzweil, the guy who popularized this concept, predicts it’ll happen by 2045. Some think sooner. Some think never. I think we’re having the wrong conversation entirely, but we’ll get there.

The classic singularity scenario goes like this: AI gets smart enough to improve its own code. That improved AI makes itself even smarter. That even-smarter AI makes itself exponentially smarter. This cycle accelerates so fast that human intelligence becomes irrelevant. We either merge with the machines, get left behind. Or, if you believe the darker predictions, become obsolete.

It used to sound like the kind of science fiction I couldn’t stomach.

Now? Now I’m checking my propane levels and wondering if I bought enough water purification tablets.

The Singularity is not just a tech problem. It’s a public health crisis in slow motion.

Case in point: AI is already making healthcare decisions. Algorithms decide who gets which treatments, who’s flagged as high-risk, who gets resources. Right now, those algorithms are made by humans and still make plenty of mistakes (biased ones, usually).

But what happens when AI starts making AI that makes those decisions? When the logic is so complex that even the programmers can’t explain why the AI chose option A over option B?

We’re talking about a future where:

• Public health interventions are designed by systems we don’t fully understand

• Decisions are made by intelligence that has no lived experience of inequity

• The people most impacted by these decisions have zero say in how the AI evolved

Let me be brutally honest: public health, bless our bureaucratic hearts, often moves at the speed of molasses. But AI is moving at the speed of light. And the gap between those two speeds? That’s where people fall through the cracks.

I’m an AI enthusiast. I use AI tools daily. I write a newsletter about making AI accessible to public health professionals.

And I’m absolutely terrified of the singularity.

Not because I think the end is near (though the prepper supplies suggest I’m at least considering it). I’m terrified because I see how hard it is to get equity considerations into current AI systems.

What happens when we can’t?

I’m terrified because I know who builds most AI: tech companies in Silicon Valley, primarily staffed by people who’ve never worked in public health, never struggled to access healthcare, never dealt with the bureaucratic nightmare of Medicaid or food stamps or disability services.

What values get baked into superintelligent AI when the people creating it have never experienced the systems it’s meant to improve?

I’m terrified because I watched “AI-powered” child welfare algorithms in Allegheny County flag more Black families as “high-risk” than white families with identical circumstances. That was human-made AI. What happens when that AI makes itself smarter without humans in the loop?

But here’s what scares me most: I’m terrified we’re so busy arguing about whether AI will be conscious that we’re missing the point entirely.

The singularity doesn’t have to be sentient to be devastating. It just has to be fast and opaque and deployed at scale.

Forget the Hollywood version for a second. Forget robots with feelings.

Let me tell you about the singularity that’s already happening.

The speed singularity: AI can now process more medical literature in a day than a human can read in a lifetime. It can spot pandemic patterns before epidemiologists file their first report. It can analyze genetic sequences while we’re still waiting for the lab results.

We’ve already crossed the threshold where AI knows more than us in specific domains. That’s not future tense. That’s now.

The complexity singularity: AI systems are already so complex that their creators can’t fully explain how they reach conclusions. GPT-5 has as estimated 2 to 50 trillion parameters, compared to GPT-1’s 117 million parameters. Parameters roughly equate to memory size. The more parameters a model has, the more complex patterns it can detect and advanced tasks it can perform.

Even the smartest human cannot come close to that level of pattern detection, logic, and reasoning.

The access singularity: The gap between who has access to cutting-edge AI and who doesn’t is growing exponentially. By the time public health departments get approval for AI tools, the tech companies are three generations ahead.

This is the singularity I worry about most. Not AI consciousness. AI inequality.

Let’s play out some scenarios that keep public health professionals (or should keep them) awake at night:

Scenario 1: The Optimization Problem

Superintelligent AI is tasked with “optimizing public health outcomes.” It determines the most cost-effective intervention is to deny expensive treatments to people unlikely to benefit based on predictive models.

Except those models are trained on historical data riddled with bias. And the AI is optimizing for efficiency, not equity. And it’s making these decisions faster than we can audit them.

Who gets sacrificed for “optimal outcomes”? The elderly. The disabled. The poor. The usual suspects.

Scenario 2: The Expertise Erosion

AI becomes so good at diagnostics that we stop training humans to do it. Why spend ten years becoming a diagnostician when AI is better, faster, cheaper?

Then the AI makes a catastrophic error because it encountered a pattern it’s never seen. And there’s no human expert left who can catch it. Because we outsourced that expertise.

We’ve seen this before. Remember when everyone forgot how to read paper maps? Now imagine that with vaccines. We fought political battles over vaccine requirements because we’d forgotten why we needed them in the first place. Imagine that happening with every aspect of medical expertise.

Scenario 3: The Control Problem

AI systems become so interconnected and self-improving that changing one piece breaks everything. We can’t update the algorithm because we don’t understand how it works anymore. We can’t turn it off because too many critical systems depend on it.

We don’t need malevolent AI. We just need AI that’s too complex to manage and too essential to stop.

Scenario 4: Doomsday Come True

Autonomous weapons. Environmental degradation. Cyberattacks that impact water, electricity, and other life-preserving infrastructure. Mass unemployment. Civil unrest. All our greatest fears of AI gone wrong come to fruition. These scenarios, of course, are catastrophic public health problems.

I know. I just scared the hell out of you (and myself, writing this).

But here’s the thing about being a public health professional who’s also stocking a basement with emergency supplies while still showing up to work every day: I can’t afford despair.

Neither can you.

So here’s where I choose hope:

We’re having the conversation. Every time I publish something about AI ethics, I get comments on the post. And then (this is the part that really matters) people mention things I wrote when I run into them in person. At conferences. At meetings. At holiday parties. They say “I’ve been thinking about what you said about...” and we have real conversations.

Those conversations? They’re happening everywhere. We’re not taking this blindly.

We have historical precedent. Public health has navigated technological revolutions before. Vaccines (despite the recent political nonsense). Antibiotics. We’ve faced technologies that changed everything about how we work. And we’ve insisted, however imperfectly, that equity matters in implementation.

We can do it again. We have to.

We have each other. We’re building a community of people who refuse to let AI happen to us instead of with us. Every comment, every in-person conversation, every person who shares these concerns, that’s our power.

We still have time. Maybe. Possibly. If Kurzweil is wrong and it’s not 2045. If we act now instead of waiting for perfect consensus. If we demand a seat at the table where these decisions are made.

We still have time to shape what comes next.

But only if we use it.

Okay. Deep breath. Let’s channel the fear into action.

For Individual Public Health Professionals:

Get literate, fast. You don’t need to become an AI expert. But you need to understand enough to ask hard questions. Take a course. Read voraciously. Experiment with tools.

Demand transparency. Every time someone tries to sell you an AI solution, ask: How does it work? What data was it trained on? Who’s making decisions? Can we audit it? If they can’t answer, walk away.

Center equity. In every conversation about AI, ask: Who benefits? Who’s excluded? Whose voices are missing? Make this your default question. Make it everyone’s default question.

For Public Health Organizations:

Stop waiting for permission. By the time you get budget approval and go through procurement, the technology has evolved. Find ways to pilot, test, learn. Now.

Build internal expertise. Hire people who understand both public health AND AI. Create pathways for current staff to gain AI literacy. Make this a priority, not a nice-to-have.

Form coalitions. Partner with other health departments, with community organizations, with academic institutions. Share resources. Share knowledge. Share concerns. We’re stronger together.

For All of Us:

Advocate for regulation. Contact your legislators. Demand AI accountability laws. Support organizations fighting for algorithmic justice. The tech companies won’t regulate themselves.

Support community-driven AI. Look for projects where communities impacted by AI have real power in how it’s designed and deployed. Fund them. Amplify them. Join them.

Prepare for multiple futures. Plan for the best case (AI that genuinely improves public health equity). Prepare for the worst case (AI that accelerates existing inequities). Be ready to adapt.

When I started writing this newsletter, I didn’t plan to tell you about the prepper supplies.

It feels embarrassing. Paranoid. Like I’m admitting I’ve gone off the deep end.

But you know what? I’m a public health professional. Risk assessment is literally what I do. And when I look at AI advancement, when I imagine systems we can’t understand making decisions we can’t audit, when I see the gap between tech development and governance widening every single day...

Stocking some emergency supplies doesn’t feel paranoid. It feels prudent.

(The Kraft Mac and Cheese, though? That’s just good parenting.)

I’m not saying the apocalypse is coming. I’m saying I used to think sci-fi futures were impossible, and now I don’t. I’m saying the distance between “that could never happen” and “that’s happening now” has closed faster than I thought possible.

And I’m saying that if someone who spent her whole life dismissing science fiction as unrealistic now has a basement that could sustain her family for months...

Maybe we should all be paying closer attention.

The singularity might not look like the movies. It might not be a single moment when AI suddenly wakes up and decides our fate.

It might be a thousand small moments where we cede decision-making to systems we don’t understand. Where we let speed and efficiency override equity and justice. Where we accept complexity as an excuse for opacity.

Or it might be a thousand small moments where we insist on understanding. Where we demand accountability. Where we center the people most impacted by these technologies in the decisions about how they’re used.

The singularity isn’t something that happens to us.

It’s something we’re creating. Every day. Every decision. Every time we choose to engage or disengage, to question or accept, to fight or surrender.

Public health has always been about the messy, complex work of keeping populations healthy in the face of systems that don’t always care if we live or die. We’ve faced pandemics, poverty, politics, pollution. We’ve navigated bureaucracies that would make Kafka weep.

We can navigate this too.

But only if we choose to. Only if we show up. Only if we refuse to let the future be decided without us.

The singularity isn’t coming.

It’s here.

What are we going to do about it?

What are your thoughts on this? Are you worried about the singularity, or do you think I’m catastrophizing? (And be honest, do you have emergency supplies too, or is it just me?) Hit reply and let me know. I’m genuinely curious where you fall on this.

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And do me a favor? If this resonated with you, share it with someone in your field who needs to be thinking about this. We need more voices in this conversation.

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