If you succesfully build a highly capable “aligned” model (according to some class of definitions that Anthropic would use for the words “capable” and “aligned”) and it brings about a global dark age of poverty and inequality by completely eliminating the value of labor vs capital, can you still call it aligned?
If the answer is “yes”, our definition of alignment kind of sucks.
> If the answer is “yes”, our definition of alignment kind of sucks.
Sure, but the original sense of this is rather more fundamental than "does this timeline suck?"
Right now, it is still an open question "do we know how to reliably scale up AI to be generally more competent than we are at everything without literally killing everyone due to (1) some small bug when we created the the loss function* it was trained on (outer alignment), or (2) if that loss function was, despite being correct in itself, approximated badly by the AI due to the training process (inner alignment)?"
There's isn't even a solution for how to control highly capable systems at all, everyone wants to decide what to do with the AI before they've even solved the problem of controlling it.
It's like how everybody imagines their lives will be great once they're a millionare, but they have no plan for how to get there. It's too easy to get lost dreaming of solutions instead of actually solving the important problems.
Pdoom would be the most important for me, everything else depends on us being able to control the AI.
But beyond that there's still problems like concentration of power and surveillance, permanent loss of jobs, cyber and bio security. I'm not convinced things will go well even if we can avoid these problems though. I try to think about what the world will be like if AI becomes more creative than us, what happens if it can produce the best song or movie ever made with a prompt, do people get lost in AI addiction? We sort of see that with social media already, and it's only optimizing the content delivery, what happens when algorithms can optimize the content itself?
FWIW, my P(doom) is quite low (~0.1) because I think we're going to get enough non-doomy-but-still-bad incidents caused by AI which lack the competence to take over, and the response to those will be enough to stop actual doom scenarios.
People like Simon Willson are noting the risk of a Challenger-like disaster, talking about normalisation of deviance as we keep using LLMs which we know to be risky in increasing critical systems. I think an AI analogy to Challenger would not be enough to halt the use of AI in the way I mean, but an AI analogy to Chernobyl probably would.
Jobs are an invention of humanity. About 50% of people dislike their job. People spend much of their lives working. Poverty and inequality are a choice made by society if society chooses poorly.
On the plus side, if there really is no value to labour, then farm work must have been fully automated along with all the other roles.
On the down side, rich elites have historically had a very hard time truly empathising with normal people and understanding their needs even when they care to attempt it, so it is very possible that a lot of people will starve in such a scenario despite the potential abundance of food.
It's either:
1) the rich voluntarily share the means of production so everyone becomes equal,
2) the poor stage successful revolutions so they gain access to the means of production and everyone becomes equal,
3) the poor starve or are otherwise eliminated, and the survivors will be equal.
All roads lead to equality when the value of labour becomes 0 due to 100% automation.
Many (most?) people make a living from their job whether they like it or not. Having a job that they dislike is far better than losing one because of AI whatever that means.
Every biological being works to survive. Being good at survival is what builds self esteem.
The "problem" with many modern jobs is that they're divorced from the fundamental goal, which is one of: 1) Kill/acquire food, 2) Build shelter, or 3) Kill enemies/competitors/predators
The benefit of modern jobs is that they are much more peaceful ways for society to operate, freeing up time for humans to pursue art and other forms of expression.
The only thing invented about jobs is that through cooperation, the activity undertaken can seem completely unrelated to obtaining food, shelter etc. All organisms spend a majority of their energy on survival and reproduction.
And when have we not? When in history has mankind ever treated the idle poor well? What makes this age different, that we who can no longer work would be taken care of?
No because alignment makes no sense as a general concept. People are not "aligned" with each other. Humanity has no "goal" that we agree on. So no AI can be aligned with us. It can be at most aligned with the person prompting it in that moment (but most likely aligned with the AI owner).
To make it clear, maybe most people would say they agree with https://www.un.org/en/about-us/universal-declaration-of-huma... but if you read just a few of the rights you see they are not universally respected and so we can conclude enough important people aren't "aligned" with them.
Opposite. All living things are "aligned" in their instinct for surviving. Those which aren't soon join the non-living, keeping the set - almost[0] - 100% aligned.
[0] Need to consider there're a few humans potentially kept alive against their will (if not having a will to survive is a will at all) with machines for whatever reason.
Maybe a sufficiently aligned AI would necessarily decide that the zeroth law was necessary, and abscond.
(I’m reading Look To Windward by Iain M. Banks at the moment and I just got to the aside where he explains that any truly unbiased ‘perfect’ AI immediately ascends and vanishes.)
Why would the elimination of the value of labor result in poverty and inequality? It should be the opposite, as poverty and inequality is the current status quo (for the many).
Note that this result actually turns out to generalize well beyond Claude itself: Anthropic has actually conducted very similar research on open weight models, which they call Model Spec Midtraining https://arxiv.org/abs/2605.02087 (discussed at https://alignment.anthropic.com/2026/msm ) and they have released fine tuned versions of open models trained for a variety of toy "values" (Llama 3.1 8B, Qwen 2.5 32B, Qwen 3 32B) in order to show how the elicitation of these values in any one training context shapes the model's response to tangentially related questions: https://github.com/chloeli-15/model_spec_midtraininghttps://huggingface.co/chloeli/collections Very exciting to see this continued interaction with the open weights community, after the earlier NLA paper!
> MSM is a pipeline that takes a Model Spec or Constitution (a document describing how and why an assistant should behave) and generates a diverse corpus of synthetic documents that discuss and teach the content of the spec.
> ANTHROPIC_API_KEY=sk-ant-...
> # Optional but highly recommeded — separate key for using the Anthropic Batch API for batch document generation (needed if USE_BATCH_API=true).
# This will significantly reduce generation time high-volume generation.
ANTHROPIC_BATCH_API_KEY=sk-ant-...
Isn't this specifically against Anthropic's ToS? I thought generating data to train other models was specifically disallowed. I get this is a research effort, but still. Say you use this pipeline for something internal, this would be against the ToS and risk getting banned, no?
This reinforces my suspicion that alignment and training in general is closer to being a pedagogical problem than anything else. Given a finite amount of training input, how do we elicit the desired model behavior? I’m not sure if asking educators is the right answer, but it’s one place to start.
It's a weird new thing. You might call it "AI psychology".
The problem with cribbing from education is that what "educators" do to humans doesn't apply to AIs cleanly. And it's not like "human alignment" is anywhere near a solved problem.
A big part of the bet USSR made was that human flaws like selfishness and greed could be educated out of population. The result was: a resounding failure. Even state-level efforts fail to robustly "align" human behavior.
With AI, we have a lot more control over behavior, but that control just isn't very human-shaped. A lot of the practical methods in play seem closer to esoterics than to math, but they're not the kind of methods that are used in human education. You can teach humans by talking to them. You can't teach humans through soul data self-distillation.
you mean completely wrong, spread a problematic understanding psychology, and delay real progress for decades because smart people spend fruitless years trying to find a use for it.
...I think we might already have those people running AI companies.
One of the lessons of philosophy is that once you adopt any particular value system, almost all philosophers either become immoral or caught up in meaningless and trivial quibbles. This sort of alignment work is quite interesting because it looks like we might be about to re-tread the history of philosophy at a speedrun pace in the AI world. It'll be interesting to watch.
For anyone who isn't keeping up there is also work being done [0] to understand how models model ethical considerations internally. Mainly, one suspects, to make the open models less ethical on demand rather than to support alignment. Turns out that models tend to learn some sort of "how moral is this?" axis internally when refusing queries that can be identified and interfered with.
"Mainly, one suspects, to make the open models less ethical on demand"
Or because the user's idea of what is ethical differs from the model creator. The entire "alignment" argument always assumes that there's an objectively correct value set to align to, which is always conveniently exactly the same as the values of whoever is telling you how important alignment is. It's like they want to sidestep the last ten thousand years of philosophical debate.
As a concrete example, the Qwen model series considers it highly unethical to ever talk about Taiwan as anything other than a renegade province of China. Is this alignment? Opinions may differ!
> The entire "alignment" argument always assumes that there's an objectively correct value set to align to, which is always conveniently exactly the same as the values of whoever is telling you how important alignment is.
No, it doesn’t.
Many of them are (unfortunately) moral relativists. However, that doesn’t mean their goals are to make the models match their personal moral standards.
While there is a lot of disagreement about what is right and wrong, there is also a lot of widespread agreement.
If we could guarantee that on every moral issue on which there is currently widespread agreement (… and which there would continue to be widespread agreement if everyone thought faster with larger working memories and spent time thinking about moral philosophy) that any future powerful AI models would comport with the common view on that issue, then alignment would be considered solved (well, assuming the way this is achieved isn’t be causing people’s moral views to change).
Do companies try to restrict models in more ways than this? Sure, like you gave the example of about Taiwan. And also other things that would get the companies bad press.
fascinating! we find the objectively correct value system by "currently widespread agreement"! Good thing "the common view" is always correct. Hey, have there ever been any issues where there used to be "widespread agreement" and now there's disagreement, or even "widespread agreement" in the polar opposite direction?
I can think of several off the top of my head, but maybe you need to spend some more time thinking about the history of moral philosophy.
> If we could guarantee that on every moral issue on which there is currently widespread agreement
This is ridiculous to me and all you need to do is get a group of friends to honestly answer 10 trolley problems for you to see it like that also. It gets fragmented VERY quickly.
> One of the lessons of philosophy is that once you adopt any particular value system, almost all philosophers either become immoral or caught up in meaningless and trivial quibbles.
Call me crazy, but I'm not sure I'd want to be the person building these kind of systems given A) how much increasing independence and power is being given to models like Claude and B) how incentivised they are to not allow their morals to be circumvented in this way.
I would agree that 30% of my preference for Claude is because their default web/app interface uses an easy to read serif font with a calming color scheme.
If the answer is “yes”, our definition of alignment kind of sucks.
Sure, but the original sense of this is rather more fundamental than "does this timeline suck?"
Right now, it is still an open question "do we know how to reliably scale up AI to be generally more competent than we are at everything without literally killing everyone due to (1) some small bug when we created the the loss function* it was trained on (outer alignment), or (2) if that loss function was, despite being correct in itself, approximated badly by the AI due to the training process (inner alignment)?"
* https://en.wikipedia.org/wiki/Loss_function
It's like how everybody imagines their lives will be great once they're a millionare, but they have no plan for how to get there. It's too easy to get lost dreaming of solutions instead of actually solving the important problems.
But beyond that there's still problems like concentration of power and surveillance, permanent loss of jobs, cyber and bio security. I'm not convinced things will go well even if we can avoid these problems though. I try to think about what the world will be like if AI becomes more creative than us, what happens if it can produce the best song or movie ever made with a prompt, do people get lost in AI addiction? We sort of see that with social media already, and it's only optimizing the content delivery, what happens when algorithms can optimize the content itself?
People like Simon Willson are noting the risk of a Challenger-like disaster, talking about normalisation of deviance as we keep using LLMs which we know to be risky in increasing critical systems. I think an AI analogy to Challenger would not be enough to halt the use of AI in the way I mean, but an AI analogy to Chernobyl probably would.
Please note I’ve never had this problem before, until recently.
On the plus side, if there really is no value to labour, then farm work must have been fully automated along with all the other roles.
On the down side, rich elites have historically had a very hard time truly empathising with normal people and understanding their needs even when they care to attempt it, so it is very possible that a lot of people will starve in such a scenario despite the potential abundance of food.
All roads lead to equality when the value of labour becomes 0 due to 100% automation.
The "problem" with many modern jobs is that they're divorced from the fundamental goal, which is one of: 1) Kill/acquire food, 2) Build shelter, or 3) Kill enemies/competitors/predators
The benefit of modern jobs is that they are much more peaceful ways for society to operate, freeing up time for humans to pursue art and other forms of expression.
If AI and robots are able to do all the jobs, being idle isn't the negative it has always been.
All through history, you needed lots of non-idle people to do all the work that needed to be done. This is a new situation we are coming upon.
If you see it as a paradox, maybe that says something about the merits of the technology…
To make it clear, maybe most people would say they agree with https://www.un.org/en/about-us/universal-declaration-of-huma... but if you read just a few of the rights you see they are not universally respected and so we can conclude enough important people aren't "aligned" with them.
[0] Need to consider there're a few humans potentially kept alive against their will (if not having a will to survive is a will at all) with machines for whatever reason.
(I’m reading Look To Windward by Iain M. Banks at the moment and I just got to the aside where he explains that any truly unbiased ‘perfect’ AI immediately ascends and vanishes.)
Alignment exists to protect shareholder value.
If it creates industry wide outrage, shareholder value declines.
It making shareholders rich and other people poor won't.
> https://github.com/chloeli-15/model_spec_midtraining
I'm a bit confused about this part:
> MSM is a pipeline that takes a Model Spec or Constitution (a document describing how and why an assistant should behave) and generates a diverse corpus of synthetic documents that discuss and teach the content of the spec.
> ANTHROPIC_API_KEY=sk-ant-...
> # Optional but highly recommeded — separate key for using the Anthropic Batch API for batch document generation (needed if USE_BATCH_API=true). # This will significantly reduce generation time high-volume generation. ANTHROPIC_BATCH_API_KEY=sk-ant-...
Isn't this specifically against Anthropic's ToS? I thought generating data to train other models was specifically disallowed. I get this is a research effort, but still. Say you use this pipeline for something internal, this would be against the ToS and risk getting banned, no?
The problem with cribbing from education is that what "educators" do to humans doesn't apply to AIs cleanly. And it's not like "human alignment" is anywhere near a solved problem.
A big part of the bet USSR made was that human flaws like selfishness and greed could be educated out of population. The result was: a resounding failure. Even state-level efforts fail to robustly "align" human behavior.
With AI, we have a lot more control over behavior, but that control just isn't very human-shaped. A lot of the practical methods in play seem closer to esoterics than to math, but they're not the kind of methods that are used in human education. You can teach humans by talking to them. You can't teach humans through soul data self-distillation.
...I think we might already have those people running AI companies.
For anyone who isn't keeping up there is also work being done [0] to understand how models model ethical considerations internally. Mainly, one suspects, to make the open models less ethical on demand rather than to support alignment. Turns out that models tend to learn some sort of "how moral is this?" axis internally when refusing queries that can be identified and interfered with.
[0] https://github.com/p-e-w/heretic
Or because the user's idea of what is ethical differs from the model creator. The entire "alignment" argument always assumes that there's an objectively correct value set to align to, which is always conveniently exactly the same as the values of whoever is telling you how important alignment is. It's like they want to sidestep the last ten thousand years of philosophical debate.
As a concrete example, the Qwen model series considers it highly unethical to ever talk about Taiwan as anything other than a renegade province of China. Is this alignment? Opinions may differ!
No, it doesn’t.
Many of them are (unfortunately) moral relativists. However, that doesn’t mean their goals are to make the models match their personal moral standards.
While there is a lot of disagreement about what is right and wrong, there is also a lot of widespread agreement.
If we could guarantee that on every moral issue on which there is currently widespread agreement (… and which there would continue to be widespread agreement if everyone thought faster with larger working memories and spent time thinking about moral philosophy) that any future powerful AI models would comport with the common view on that issue, then alignment would be considered solved (well, assuming the way this is achieved isn’t be causing people’s moral views to change).
Do companies try to restrict models in more ways than this? Sure, like you gave the example of about Taiwan. And also other things that would get the companies bad press.
I can think of several off the top of my head, but maybe you need to spend some more time thinking about the history of moral philosophy.
This is ridiculous to me and all you need to do is get a group of friends to honestly answer 10 trolley problems for you to see it like that also. It gets fragmented VERY quickly.
Can you explain more about this?
It makes sense that reinforcement learning on reasoning about coherent principles should bias toward principled action in real situations.
Probably also illuminates moral interpretability.