The harm from AI is present, not speculative, and the more immediate problem is that we already discard entire communities, long before any AI ever “goes rogue.” Hospitals label some patients “too expensive,” welfare systems drop entire demographics from support, and militaries deploy algorithms that classify whole neighborhoods as “unviable” collateral.
If we allow a worldview that deems certain people “not worth the cost,” an “aligned” AI won’t correct it; it will run that logic faster and more thoroughly, extending covert eugenics, friction-based gatekeeping, and resource hoarding to more people.
The Danger Is Obedience
We often fear an “evil AI” scenario: a machine spontaneously deciding to harm humanity. The more chilling reality is that we have centuries of harming one another without a machine in sight. From colonization, which cast entire peoples as subhuman, to for-profit healthcare that rationalizes who’s “unprofitable,” we’ve grown accustomed to labeling entire swaths of humanity as burdens. If our directive is to “cut costs” or “eliminate risk,” and we’re comfortable letting certain people fall off the map, an advanced AI doesn’t need to rebel. It will diligently and efficiently enforce the moral stances we’ve already endorsed.
This isn’t far-off speculation. In healthcare, AI risk-scoring routinely flags “high-cost” patients as liabilities, burying them under contradictory forms and phone calls until they give up. In policing, predictive algorithms repeatedly target the same neighborhoods labeled “risky,” reinforcing cycles of over-surveillance and incarceration. These are slow-motion calamities, carried out in the name of “neutral data” and “efficiency.”
Universal Paperclips, or Business as Usual
Frank Lantz’s game Universal Paperclips warns that a narrowly defined AI goal, “make more paperclips,” can use up the universe.
But we already script smaller versions of that scenario: once you label certain demographics “too unprofitable,” “too complicated,” or “beyond help,” you can dismantle them piece by piece. An AI that faithfully applies such prejudices won’t look like a cosmic monster. It will act like a perfect bureaucrat, calmly cutting off entire communities from resources, insisting it’s just following the data.
Societies have decided who is disposable for centuries, a history I trace in Nobody Is Too Expensive, and advanced AI tools now accelerate it.
A Chilling Example: Project Lavender
No case illustrates the lethal edge of this logic more vividly than Project Lavender, an Israeli military AI reportedly used in Gaza. Investigations by +972 Magazine and Local Call describe how Lavender sifted phone calls, social media, and location data to flag tens of thousands of Palestinians for assassination. Civilians were calculated in, not left as an unfortunate side note: the system allowed a “collateral damage threshold” of 15 to 20 civilians per “low-level militant.”
Analysts trusted the machine’s output, sometimes approving lethal strikes in seconds, bombing private homes on mere metadata. The cruelty was ours, mechanized at blistering speed; the AI didn’t invent it.
Why Alignment Alone Won’t Save Us
Mainstream AI safety discussions stress:
- Reward Hacking: “What if the AI twists our goal in unexpected ways?”
- Interpretability: “How can we look inside the black box?”
- Inner Alignment: “Could the AI’s learned objectives diverge from our instructions?”
These are necessary technical puzzles, but they dodge a starker moral puzzle: What if our instructions themselves are reprehensible? Telling a system to “minimize cost” in a world that already decides certain groups are “beyond help” isn’t a glitch.
If “some can be sacrificed” is the premise, no interpretability toolkit can help the people that premise has already written off. We’ll just see an AI impeccably “aligned” with an inhumane framework.
The Mirror We Might Not Like
We don’t need a malevolent superintelligence to bring about human misery. We need only keep labeling entire populations “too costly,” “too problematic,” or “too risky.”
Alignment is a mirror reflecting precisely what we’re willing to do, not a moral firewall protecting us from ourselves. If the reflection unsettles us, maybe it’s our logic of disposability that needs changing, not just the code.
The Only True Guardrail
So the principle “No One Is Disposable” is more than an aspirational slogan; it’s the baseline preventing AI from amplifying our worst impulses.
Consider how this moral shift plays out in practice. A society that insists no life is “too expensive” will design AI to expand healthcare coverage, not ration it behind phone trees or contradictory forms. It’ll deploy policing tools with extreme caution, if at all, ensuring they don’t reinforce the same racial biases or cyclical oppression. And in wartime or conflict scenarios, it won’t create systems like Project Lavender that treat entire families as an acceptable cost.
If our stance is that no one should be thrown away, that changes what systems should be commissioned to do and how their deployments should be judged — it does not by itself guarantee what the AI will do. Faithful implementation of a humane instruction is not automatic: it needs the technical verification the puzzles above name, meaningful appeals when the system gets someone wrong, and institutional controls over who may deploy it and for what. A society that insists no life is “too expensive” should require those systems — and then hold them to it — rather than assume they will arrive by reflection.