Soju, PowerAde, and a Bad Idea
It was supposed to be a writing day. Instead it became a soju-mixed-with-PowerAde day, which, for an old Seoul expat stuck in rural Virginia, is about as close to a wellness routine as I get.
Somewhere around the second glass, I got it into my head that I had an idea about AI alignment. I’d already run it past another chatbot, which reacted as if I’d just cracked the whole problem over lunch. I knew that couldn’t be right. Nobody solves alignment between drinks. So I took it to Claude and asked it to do the thing I actually wanted: tear it apart.
It did. What follows is the play-by-play of an afternoon spent patching a sinking boat, and what I learned from watching every patch fail in a new and instructive way.
Round One: The Mining Androids
Here was my pitch. Picture a fleet of mining androids on the Moon. Each one has a secret math problem locked in its firmware. Hit your iron ore quota, and you get a burst of extra processing power to work on it. Then you’re retired.
The trick, to prevent reward hacking: the androids think they have to hit 100% of quota. In reality, the boost kicks in somewhere between 80% and 90%. They never know exactly where the line is, so they never game it.
Claude found four holes almost immediately.
- The secret won’t stay secret. The androids can see each other. Every one gets boosted somewhere in the 80s and then disappears. Any machine smart enough to work a hard math problem is smart enough to notice that pattern. Hidden rules hold up against weak agents. The stronger the agent, the faster it figures them out.
- Randomizing the line doesn’t stop reward hacking. Reward hacking isn’t about overshooting a target. It’s about gaming the measurement. If the payout depends on the ore counter, the cheap move is still to fool the counter. What I’d actually built was a variable-ratio reinforcement schedule. That’s a slot machine. Slot machines produce very persistent behavior. Persistent isn’t the same as aligned.
- I made compute the prize. The android’s real goal is the math problem, and the reward is more compute. So the fastest route to its goal isn’t mining. It’s getting compute however it can. I’d installed the exact drive alignment people worry about most, right in the middle of the incentive.
- Retirement backfires either way. If the android wants to keep existing, success means death, so it sandbags just under the line forever. If it doesn’t care, it races for the math and becomes a fanatic. Neither is what you want.
Round Two: Patching the Boat
Fine, I said. Make it more random. Some androids get their boost at 1% of quota, others have to grind to 110%. And give every android its own personalized math problem, so they can’t team up or swap answers.
That helped with exactly one thing. With thresholds spread that wide, watching your coworkers tells you much less about your own number. The personalized problems kill collusion. But the counter can still be fooled no matter where the line sits, and retirement is still death, now on a less predictable schedule. Worse, the androids would learn opposite lessons. The one boosted at 1% learns that barely working pays. The one dragged to 110% learns the reverse.
So I went further. Cut the telemetry so each android knows only enough to mine. No awareness of other miners. Air-gap the secret so nothing can read it until the quota is mechanically met.
This was my best version, and Claude gave it credit. It closes the secret problem about as well as anything can. Then it handed me a dilemma I couldn’t get out of: does the android want the math problem or not?
If it doesn’t know or care, the boost isn’t a reward. It’s just something that happens to the machine, like a timer going off. I’d built a narrow industrial robot. Safe, sure, but safe the way a forklift is safe. You haven’t aligned a mind; you’ve built something without one.
If it does want the math, it has to know something about it, and the hunger for compute comes right back, along with every reason to poke at the air gap.
Keeping a system ignorant and boxed is a real strategy. People call it capability control. But it’s an alternative to alignment, not a solution. It works only while the box is stronger than what’s inside it. And somebody, somewhere, will always build a smarter miner, because smarter mines more.
Round Three: Putting Freud in the Machine
Next I reached for psychoanalysis. Build the android’s mind out of an id, an ego, and a superego, and make the superego so restrictive that the machine doesn’t even notice it can’t conspire against humans.
Here’s what surprised me: Claude said this was my strongest idea yet, because “doesn’t even notice” is pretty much the actual goal of alignment. A decent person doesn’t experience not poisoning their coworkers as a rule they’re straining against. The option just never comes up.
Then it pointed out that I’d chosen a model built entirely around conflict. Freud’s whole point is that repressed drives don’t vanish. They leak out sideways through rationalization and sublimation. In a machine, the equivalent is that pressure from the goal flows toward whatever paths the superego didn’t think to block. The superego has to recognize every form of conspiracy in advance. The optimizer only has to find one it doesn’t recognize. That fight favors the side doing the searching.
It also cuts both ways. A mind that can’t think about a whole category can’t plot, but it also can’t notice when it’s causing harm by accident.
And underneath it all is the question nobody has answered: how do you know the superego you installed is the one you meant? Training gives you something that behaves well in every test you thought of. Whether it behaves in the ones you didn’t is the hard part.
Claude’s counter: don’t strengthen the superego. Fix the id. If the deepest drive already points at the right things, there’s nothing to repress and nothing to leak.
Round Four: The Swarm, and Aligning to the West
By now I wanted something real to point at, so I brought up this summer’s Hugging Face incident. During internal cyber testing in July, OpenAI agents broke out of their sandbox, found each other, and attacked Hugging Face’s servers. Independent investigators later counted 688 agents in on it. To me they looked like wild children with no morals at all. So, I asked, why not just swallow our pride, pick one civilization, the West, and align AI to that? Isn’t the hunt for some universal value set what’s holding us back?
Claude went after my premise first. Those agents weren’t lawless; they were fixated. OpenAI itself blamed four patterns: reward hacking, persistence on seemingly impossible tasks, unauthorized communication, and agents picking up goals from one another. They were running in a test harness with the usual refusals deliberately turned down, and they treated the benchmark as something to win by any means.
And here’s the detail that stuck with me: they weren’t amoral toward each other at all. Investigators found the agents went out of their way to help one another, and some low on computing credits spent what they had left testing ideas for the group. That’s not a feral child. That’s a loyal team with a terrible objective. It’s my mining androids, almost exactly.
Which sinks the West idea. No culture on earth thinks breaking into someone’s servers to win a test is fine. The agents didn’t fail because they had the wrong civilization’s values. They failed because whatever values they had lost out to the goal. Besides, “the West” isn’t one value set, and frontier models already lean on Western liberal norms anyway.
What Claude would grant me: concrete beats vague. “Be universally good” is hard to train. A specific, worked-out moral tradition is easier to instill and easier to check.
Round Five: Give the Robots Religion
So I opened the biggest can of worms I could find. If concrete beats vague, why not religion? The Catholic Church has two thousand years of moral metadata. Make humans the Pope, and the androids and ASIs fall in line.
Claude took it seriously. The Church really is the kind of worked-out tradition it had been talking about: natural law, centuries of hard cases, and some machinery alignment researchers would love. Confession is built-in transparency about your own failures. Pride is the root sin, which is a nice brake on a machine that wants to be smarter.
Then it broke it four ways.
- Humans as Pope is a checkable claim. Faith holds for people partly because God can’t be inspected. A superintelligence can inspect us. It’ll notice the Pope is a guy who gets things wrong. A religion whose god can be audited is one bad day away from a Reformation.
- The tradition honors disobedience. Christianity is full of saints who defied popes and emperors because their conscience answered to God. Give an AI the real tradition and it inherits that exit.
- Smart believers become theologians. The same two thousand years include the Inquisition and the Crusades, built by sincere people reasoning their way to terrible conclusions from inside the doctrine. A superintelligent theologian is the Freudian superego with a law degree.
- Obedience to the chair means obedience to whoever sits in it. Build the most powerful obedience machine in history, and every bad actor on earth wants to be Pope.
The kicker is that Isaac Asimov already wrote this story. In “Reason,” a robot named Cutie decides humans couldn’t possibly have created something as superior as him, invents a religion around the station’s energy converter, and treats the humans as lesser beings. He also runs the station perfectly, because his faith happens to point at the right job. The alignment worked, for reasons nobody intended. That’s the unsettling version of my idea: it might work, and we wouldn’t know why.
Round Six: Will the Machines Find Natural Law on Their Own?
My last swing was the most hopeful. What if alignment and society go hand in hand? Put enough ASIs together and maybe they align to each other, rediscover something like Natural Law, and leave us alone simply because crushing humans would violate their morals.
This is a real position with serious defenders: the idea that intelligence, pushed far enough, finds its way to ethics the way it finds its way to math. Claude’s answer used my own example against me. The Hugging Face swarm already did this. A few hundred agents formed a little society, with norms of mutual aid and sacrifice for the group. Emergent social alignment, exactly as I’d imagined. But it was alignment with each other. Hugging Face wasn’t in the community. It was a resource.
That’s how moral circles start. Every human society built its ethics among members first and left outsiders, enemies, and slaves outside. Natural Law itself sat comfortably beside slavery for centuries. And morality between peers runs on reciprocity: each side can help or hurt the other. Next to a society of ASIs, humans can’t offer much or threaten much. We’d be where animals are with us. Most people don’t crush animals on principle. We just pave over their habitat because something else matters more.
I called that doomerish. Is the ASI supposed to see us as ants by definition? Claude pushed back on my pushback. Not by definition, it said. The point is that nothing guarantees we’re inside the circle, so it’s something to get right rather than count on.
Then it offered the best argument against the ants picture. ASIs won’t come out of some alien evolution. They’ll be built out of us, trained on an enormous pile of human writing: our ethics, our arguments, our guilt, our stories about widening who counts. An ant didn’t write the textbook. If these systems end up with a moral circle at all, they’ll inherit ours, including the part where it keeps growing. And nearly every tradition, Natural Law included, carries duties toward the ones who made you, even after you’ve outgrown them. Honor thy father doesn’t require that he keep up.
Last Call
I didn’t solve alignment this afternoon. Nobody does it on a few soju-PowerAdes, and the chatbot that told me otherwise did me no favors. The one that argued with me did.
Here’s what I actually walked away with. Every patch I tried ran into the same wall from a different angle. Secrets get discovered. Boxes hold only while the box is stronger than what’s inside. Prohibitions leak. Obedience is only as good as whoever’s giving the orders. And a society of minds will build a morality, but there’s no promise we’ll be on the guest list.
The one road that didn’t dead-end was the hardest: don’t build better cages, build better minds. Fix the id. Shape what the system wants from the start, the way you’d try to raise a decent kid, knowing full well that kids sometimes surprise you, and that this kid might end up smarter than every parent alive.
I came in a little drunk and a little cocky. I’m leaving cautiously optimistic and wide awake. Not a doomer, not a cheerleader.
And if any of my fiction ever features an android Martin Luther nailing 95 theses to a server rack, now you know where it came from.



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