— and Why “AI Everything” Fits the Same Pattern
If you want to understand the through-line in modern Republican policy, you don’t need a think tank or a 600-page strategy memo. You just need one axiom: employers have more leverage over employees if the public is desperate. Everything else is implementation detail. Scarcity creates desperation, desperation produces compliance, and compliance protects power. Once you see the world through that lens, the chaos starts to make sense.
Systems Thinking: Destabilize the Stabilizers
Systems thinking helps make this clearer. If you want to disempower a population, you don’t attack people directly. You attack the stabilizers that give them resilience, predictability, and agency. You cut support for education, healthcare, and reproductive autonomy. You underfund the VA and cripple the CDC’s ability to track disease. You pile financial obligations on families.
The cumulative effect is always the same: people are less able to absorb shocks, less able to plan for the future, and more likely to submit quietly to authority. It’s governance through induced scarcity. The pattern is elegant in its simplicity, and brutal in its impact.
Good Intentions Don’t Cancel Systemic Incentives
Most people working in technology aren’t plotting to destabilize society. Engineers, researchers, and builders are genuinely curious, motivated by problem-solving, creative breakthroughs, and sometimes just the sheer joy of “wow, it can do that now.” Many of us delight in efficiency, in solving problems we used to spend hours wrestling with, and in finding ways to make work less tedious. These are good intentions.
But systems don’t run on intentions. They run on incentives. Right now, those incentives overwhelmingly reward speed, scale, and opacity. They favor automating decisions, centralizing control, and privatizing functions that used to provide public stability. Even well-meaning innovation gets absorbed into a feedback loop that magnifies precarity, consolidates power, and erodes buffers that keep people stable.
AI as a Force Multiplier
AI is the perfect example. It’s dazzling, it’s magical, and it can do things that feel like science fiction. But when you deploy it in a system designed to extract leverage from public desperation, its effects aren’t neutral. AI amplifies labor precarity, automates authority, increases opacity, and justifies austerity. It’s both a tool of wonder and a force multiplier for systemic fragility.
This is why it’s important to separate people from systems. Most tech workers are building tools they hope will make life better, not worse. They’re not villains. But when those tools are deployed into a system that rewards destabilization — or when the policy environment makes it easier to exploit scarcity for control — you end up with consequences nobody intended, but which align perfectly with authoritarian incentives.
Innovation Doesn’t Immunize Against Structural Risk
The broader point is simple but uncomfortable: AI, like education, healthcare, or reproductive rights, operates inside a social, political, and economic system. That system can absorb good intentions and still produce harm. It doesn’t care if you’re thrilled that a model can summarize a 17-page report in thirty seconds. It cares that the system you’re deploying it into can use it to shape behavior, concentrate power, and limit agency.
This is especially clear when it comes to how large language models and other AI systems are trained. Most engineers and researchers are not intending to exploit creative work. They’re experimenting, building, and exploring capabilities with curiosity and enthusiasm. But the system incentivizes using massive datasets, including copyrighted works, because that’s the fastest path to performance. Even without malice, these incentives generate outcomes that are ethically fraught. The conflict arises not from the intent of the builders, but from the structure they operate in. Systems can absorb good intentions and still produce harm, unless the incentives themselves are addressed.
The Dual Truth We Need to Reckon With
If you look at public policy and technology through that lens, everything starts to fit into the same structural pattern. Destabilize stabilizers, manufacture scarcity, accelerate automation, centralize decision-making, and the rest falls into place. The axiom remains true: employers — and, more broadly, those with structural leverage — gain when the public is desperate.
AI may be miraculous, but in the wrong system, miracles become leverage. That’s the dual truth we need to reckon with. Innovation can be exciting, AI can be astonishing, and yet the system can still be quietly authoritarian in its effects. Recognizing that doesn’t diminish curiosity or discovery; it sharpens the stakes.
nb. This was supposed to be posted a couple of weeks ago, I blame the Muppets. They didn’t have anything to do with it, but there you go…
