Inside the tech world, AI feels like a superpower. Think of it like a language — clunky while you are leaning and then second nature. So much so that you forget how hard it was to learn in the first place. Once you’ve experienced what it can do, the optimism is hard to suppress. Companies are getting built faster. Individual productivity is going up by multiples. Problems that used to require a whole team now get solved by one person orchestrating a handful of AI agents in parallel — research, drafting, code, analysis, all running at once, all feeding into the next step. The result is that companies and teams are getting more done and moving much faster.
But outside the tech world, AI often feels like something else entirely.
It feels like the thing that just raised your rent. It feels like the thing that screened out your résumé before any human at the company ever saw your name. It feels like the system that denied your insurance claim. It feels like a deepfake of your grandson’s voice calling you for money.
It feels like the thing that’s coming, eventually, for your job too.
That’s the dissonance I’ve been thinking about. Most of the people in my professional orbit see AI the way I do — as the most exciting and consequential technology in a generation. We talk about it constantly. We invest in it. We use it daily. We assume that other people, given a bit of time, will come around to seeing it the same way we do.
That’s a mistake.
Many people don’t experience AI as a tool that makes them more productive. They experience it as a system that’s being used on them. The rental market is one example, and a particularly concrete one. Large landlords — companies that own thousands or tens of thousands of apartment units — increasingly use algorithmic pricing software to set rents. The software analyzes occupancy, market conditions, willingness-to-pay, and recommends the highest rent the model thinks each unit will support. The Department of Justice sued one of the largest of these companies, RealPage, in 2024 for facilitating what amounted to algorithmic price coordination across competing landlords. Several state attorneys general joined that suit, including Colorado’s.
If you’re a renter on the receiving end of one of those algorithms, “AI” isn’t an enabler. AI is the reason your rent went up $200 at renewal, despite market conditions that would indicate otherwise. That’s what AI does in your life. And that may be effectively your entire experience so far with this new technology.
It’s easy, inside the tech bubble, to dismiss those concerns as misinformed. To say “that’s not really AI” or “the technology isn’t the problem, the application of it is.” Both of those things might even be true. But neither of them changes the lived experience. And the lived experience is what shapes policy.
That’s why states are moving. Maine has put a moratorium on new data center construction - an ill advised and short-sighted reaction to AI fears, but also one that asked important questions about where we place data centers and who pays for the cost of the power that runs them (both easily addressed in more productive ways, but often key questions that those in the tech sector gloss over). Colorado passed the country’s first comprehensive AI accountability law in 2024 — and then spent the better part of two years in a hard fight to revise it. The updated version eventually - passed only a few weeks ago - fixed the most problematic parts of the law. But the fight exposed just how deep the distrust of AI and the tech industry runs, even in a state with one of the country’s most active tech communities. Other states are watching. The “how do we regulate AI” conversation is genuinely happening — not in the abstract, but in legislative committees, with real bills, and with real constituents pushing on their representatives (so far in 2026 over 2,000 AI bills have been introduced at the state level).
The default reaction inside tech is to roll our eyes at this. To frame the opposition as Luddites. To assume the regulators don’t understand the technology and are reaching for the brake pedal because change is uncomfortable.
I think we should resist this framing.
The concerns are real. They are often based on lived experience, not paranoia. And dismissing them as anti-progress is both unfair to the people raising them and bad for those of us who want AI to succeed (and, in fact, see the necessity for it to do so). If the optimist camp wants AI to be politically and socially survivable — wants the next ten years of deployment to be additive to society and not extractive from it — we have to actually engage with what people are afraid of, not pretend they’re afraid of nothing.
Some of what they’re afraid of is the technology itself. Most of what they’re afraid of is what the technology is going to do on top of a society that already feels rigged against them.
That distinction matters. The economy people are walking into in 2026 is not the economy of 1995. Inequality has been widening for two generations. Productivity has gone up, but median wage growth hasn’t kept pace. The share of national wealth held by the top 1% has roughly doubled. And now, AI arrives. Two AI companies are now worth close to $1 trillion apiece. The founders are worth tens of billions of dollars personally. A handful of people are getting wildly rich from a technology that, from where most Americans are standing, hasn’t yet made their own work better, their lives safer, or their job more secure.
If you already believed the economy was structured to enrich a tiny number of people at the expense of everyone else, AI looks exactly like that thesis on steroids. Of course it’s scary. It would be irrational not to be at least a little scared.
I’m not in the slow-down-AI camp. I’m a hundred percent in the AI optimist camp, and I think the long-run case for AI being additive — to jobs, to productivity, to human capability — is strong. I think we’re at the start of one of the most economically generative periods in modern history. I want us, collectively, to get there.
But getting there requires the rest of the country to come with us. And the rest of the country doesn’t yet see what we see. They see RealPage. They see trillion-dollar AI companies. They see something that is increasing the gap between the haves and the have-nots. And they’re asking, fairly, whose side is this on?
Our job, inside the tent, isn’t to write better explainer threads about how the technology works. It’s to listen carefully to their concerns and not dismiss them. And, ultimately, it is to build AI and AI systems that actually make the lives of the people on the receiving end better. To work on the structural questions — pricing, labor, ownership, regulation, access — with the same energy and creativity we bring to the technology itself. To show with action, not just with words, that an AI future can benefit all of us.
The opposite of progress isn’t caution. It’s arrogance.