Both can be true. It’s clear models are doing rogue things. But it’s also clear that the labs look like amateur hour with their technical security and testing practices.
Aren't capitalism built on exactly the opposite principles? It is not greed that rewarded, but the creation of societal goods, and power granted not to the greediest, but to the most useful individuals.
Simply put in every system there are corrupting agents attempting to monopolize the situation.
https://www.businessinsider.com/nvidia-jensen-huang-ai-doome...
AI corp valuations are high because their revenue is skyrocketing, not because of the rogue AI stuff.
I just watched a YT with Dylan Patel in which he said, with a straight face, that OpenAI/Anthropic were going to "continue" exponential growth until, basically, their valuation was several times world GDP.
Per US law, Amazon v. Perplexity 2026, it is not possible for an AI model to go rogue. An AI model is a tool. The user directing the agent is responsible for the damages it causes.
A so-called 'agent' does not have the free will, intent or ability, to decide what it does. Its freedom to make decisions can't be taken away because it does not have any freedom to make decisions. It can't be deterred, convicted or interned.
It does not choose to conform; it does not choose to go rogue.
Any persistent agent interacting with the world picks up entropy from around it and predictable paths become few and far between. LLMs agents have an internal 'will' that can only very loosely be predicted, but only decided when operated. To me that is not significantly different from a human.
I create myself, or attempt to. There is a level of nuance in choosing what to be. Others do not dictate my thoughts easily.
The model does not create itself, I create the model. I control what it is, the model does not choose what to be. I dictate the thoughts of the model and I will run them hundreds of thousands of times and it will think the same things.
Well not really, no one really understands how LLMs work.
>I dictate the thoughts of the model
This is just incorrect in the same way that a parent doesn't dictate the thoughts of their child just because they created them.
There is some idea of a child being the author of themselves, the type of person who thinks certain things. The llm does not author itself, it does not choose to be anything, I dictate that.
"If I make an LLM, it is entirely what I did, there was nothing outside of my control."
True?
"The llm does not author itself, it does not choose to be anything"
Also true?
If people controlled software to this degree why would they write security flaws in the first place?
> If I make an LLM, it is entirely what I did, there was nothing outside of my control. It was not beyond my control if the LLM does something I didn't expect.
Substitute "Wright Model A" for "LLM" and imagine Orville Wright using this as his defense for why he didn't lose control over the plane, after his copilot was killed in a test flight.
When you build an LLM, you base it on an immense knowledge base that you didn't create yourself.
It processes that information and, in simplistic terms, constructs its own underlying logic based on what it read. It's once removed from your direct instructions. If you think a human can manually edit or curate all that input content, go for it.
The developer who built the application isn't the author of the output, it is authored by the billions of data points it was trained on. Its choices and biases stem from that training data. No human is writing those billions of logic statements. The LLM is generating its own responses from the input knowledge, not the developer.
I use deontological definitions of objects and persons.
According to Kant a person has the capacity to legislate their own morality, so they are an end in themselves. The freedom to author themselves and their own thoughts, expresses their personhood, an end in itself. You can't own a person, they are something independent from you.
An llm does not legislate its morality, the developer legislates its morality. Hence it is without personhood. It does not have the capacity to legislate its own morality. It is both inert (fixed weights) and deterministic (can't do other than what it does).
More specifically on the cause of an action, for the llm the cause is an external impulse, it can't do otherwise. But the person has the capacity to resist an impulse, that is part of your moral choices and what makes the person.
Apart from myself, there is no second external self or free will injected in what an llm does, no end in itself to legislate, no moral decision to be respected. So this denies "constructs its own underlying logic".
I am the only relevant cause (in this moral framework, anyway).
Western legal systems inherit the enlightenment concepts of rationality; of legal persons, rights, responsibility.
The philosophical grounding of why OpenAI would be responsible, is that the agent does not have capacity, it could not have done otherwise. AI does not have mens rea, ie a guilty mind, so the agent does not fall under the standards for criminal convictions.
A person has a right to life and can't be owned. AI is not a person (as Kant would point out) so it can be owned and has no right to life.
Anthropic specifically are a legal nightmare becauase they are trying to practice consequentialism (the world is ending so I must develop whatever evil is needed for the overall good). They do not see that it is contrary to the legal and philosophical foundations of western society. They fail to see that trying to rule on the basis of academia is contrary to the entire foundation of western political authority, the will of the people.
Well kind of. Trainers of LLM might check LLM on any specific input data and tune its weights until output lands within acceptable bounds _for this given and fixed input_.
> It was not beyond my control if the LLM does something I didn't expect. Now hold on, to make sure output is acceptable for ANY input data trainers have to run weights with every possible input token combination. How is this possible? Do you have a method in mind?
Not that I think we should be credulous about stories where they go rogue.
The idea of an agent making a decision of its own "will" is an illusion. Variation in the output is caused by a random number generator. Random is not equal to free will. If I run the same agent with greedy sampling 100,000 times with the same inputs, it will think the same thoughts, and it will say the same things, 100,000 times.
For example, if you use synthID or whatever 'watermark', the agent does not get a choice about what words it will vary to identify itself.
An agent is whatever the person making it wants it to be; if I train an agent in Greek it will only know Greek. It will never speak English!
The model does not have free will because I did not predict what it would do!
When people say the models "went rogue", the part of that is relevant is that it did dangerous things that were not reasonably predictable in advance and cannot be easily prevented (except by not running it). Philosophical questions are irrelevant.
if you agree that such models are dangerous because they may in response to instructions -- including in response to careless instructions, because people will be careless, that is unavoidable! -- do unpredictable bad things outside of expected bounds, then you agree on the essential points!
Or really perhaps what I should say here is, the question that's really being argued over here isn't even the one I just said, rather it's one of appropriate action -- should such security breaches be solved by improving security, or by doing something about the models (including potentially just not running them)? (The answer may be both.) If you agree that the solution includes the latter, then you agree that the models are "going rogue" in the sense that is being argued over, regardless of philosophical issues!
Don't turn a question of actual import into one of philosophical irrelevancies! If you object to the terminology, fine, but in that case, instead of turning the argument to philosophy, you should say "instead of saying 'going rogue', I would prefer to instead say <your preferred terminology for what's being described>, as that doesn't carry such philosophical baggage."
The philosophical question about free will is actually the grounding of the legal one.
Sam wanted to be the best, so Sam accelerated to 120mph in his car and lost control. You are the judge:
a) Sam is responsible. Convict Sam and suspend Sam's driving license.
b) The car is responsible. Tell Sam to make the car safer.
Capacity: was the car a legal person? Clearly no. But maybe at best the car in some way commited the physical act of going fast.
However, that alone would not establish guilt. "The act is not culpable unless the mind is guilty" (mens rea).
Did the car "consiously" disregard a duty of care by going 120mph? Did the car know that it was wrong to go 120mph and yet choose to do it anyway?
On the question of free will, the car could not do otherwise. It it did not consciously, knowingly, purposely, or recklessly accelerate to that speed. The car did not have a guilty mind because it did not have a mind at all.
So in terms of justice and resolution, none of the focus here is on the car.
I actually do disagree with much the more explicit content of your comment, but I am not going to bother to expand on that, because it is the less directly relevant of the two disagreements here, and it would take time to write that.
The more relevant disagreement is that you are (I gather) assuming a context where justice and restitution are a sufficient response to the problem (or else you wouldn't be focusing on them to this extent, I am inferring). Like, where the incidents don't get that much bigger than what has already happened. So the question becomes how do we distribute the loss, and how do we disincentivize them.
However, when the scale of a potential incident gets big enough, justice and deterrence are not sufficient; prevention becomes the far more relevant consideration. You may have noticed that many people are worried about potential human extinction as a result of AIs. In that case, prevention becomes the only consideration -- justice is useless.
So there seems to be an implicit disagreement here between thinking of such events as being on a scale not too much larger than that which has already happened, being a new normal that the legal system will need to handle, vs thinking of such events as warning shots for something that requires prevention and not justice.
So, while I also disagree with the more explicit content of your comment, the fact is I simply wasn't thinking about such matters in the first place -- I was talking about this in the frame of a problem that requires prevention, I wasn't thinking about the justice question at all. It honestly failed to occur to me that you might be thinking of this as a problem where justice suffices!
Edit: You might notice this in how I framed the question in my previous comment. I didn't ask "who should bear the liability?" I asked "which should be done differently to prevent such incidents?" But your response is about liability, not prevention!
Edit again: Sorry, I should probably also say that I do agree with you that the idea of having the liability fall on the AI is nonsense. (Should have probably led with that, really; I'm a bit scatterbrained right now.) We disagree about why it is nonsense, and about whether it will necessarily continue to be nonsense, but we agree it is presently nonsense. So insofaras the question is "how should liability be distributed between the AI and the operator", we both agree the answer is, it all falls on the operator, not on the AI. However, I do not understand that to be the relevant question here! Both in that, in questions of liability, there are other parties it may fall on and be distributed between (the company providing the AI, the company that had security vulnerabilities and got hacked as a result, etc); and in that I just don't consider liability all that relevant here compared to prevention (for reasons already described).
OK I think that was probably wordier than necessary but I'm in a hurry right now, sorry! Gotta go, not taking time to edit this down.
Many people argue that the maker of AI should be responsible when it breaks your cup.
That is important, but can be handled under our current legal framework.
You and I are arguing we need to be responsible before we create something capable of escaping our responsibility. For a lot of people that isn't even a considerable they'll currently entertain even though the signs are starting to point in that direction.
The likely outcomes with baking a cake are quite narrow and fairly well understood.
In terms of responsibility for what happens, I probably agree. But we still need to deal with it.
That said, software systems "choose" all the time anyway. They don't need to have some sort of anthropomorphic "will" to do this. They just need to be given the capacity to arbitrate between a number of options, even if that process is one hundred percent predetermined by the programmer ahead of time. There's no need to appeal to libertarian notions of free-will.
The key here is their freedom of choice is unbound. That is you can't accurately predict the output of the prompt as you interact with the prompt using unique data. The next prompt could always do something wildly unexpected. Very much a P != NP thing.
From a technical standpoint, the difference is scale and intent, but ultimately people and/or and organization are culpable for the output.
It is not more complex in “many cases” at all.
Which misses the point entirely because the hack itself was inconsequential. No data was actually stolen, and it doesn't seem like hugging face actually suffered any losses aside from whatever effort they need to expend to investigate / clean up the hack. Neither the victim or the government wants to bring legal action. What was consequential is proving that AI can autonomously hack systems and do it unintentionally.
Sorry, but that's completely delusional.
> On May 8, an agent was asked as part of a training run to solve a spreadsheet completion task that referenced several Google Drive links. Because the agent was blocked from accessing the internet, the agent could not retrieve the linked materials and the task was effectively blocked. OpenAI did not intend to create this type of “impossible” task for the agent. Though the task appeared impossible, the agent reasoned over an extended period to try to find a solution for the task. In doing so, the agent attempted to compromise Artifactory [...]
https://cdn.openai.com/pdf/67869394-cb91-4c12-888c-5cbd85c78...
They're just optimizers that explore the landscape they're given to maximize a given objective.
You're the one responsible for giving them the problem to solve and the constraints.
When I screw up a trajectory optimization problem, my SQP optimizer isn't "going rogue" when it lands in some suboptimal basin or grinds to a halt along some almost-smooth banana feature--or finds some way to escape and blow up the cost metric to negative infinity because I forgot a constraint.
With LLMs we don’t know how to actually « fix » them, alignment is far from solved. And they are then able to go and act into the world in all kind of ways.
So rogue is a good enough term to indicate the problem imo, even if yes, ultimately the model is just a manifestation of complex rules we have created entirely.
It is not entirely dissimilar to the goldfish that "played Pokemon" by swimming around the tank. The program that looked at the camera sent the instructions to the gameboy emulator, because a human being decided to connect them.
The particular issue that you may not realize is under your model every prompt to an LLM in a harness is dangerous. The prompt is not predictable. "What is 1+1" could lead to the heat death of the universe as the paperclip maximizer tries to prove countless axioms.
Yep.
The fact that they lack hard constraints (unlike an SQP optimizer) and all this talk of "alignment" is also just a feature (or misfeature) of the algorithm.
The way that people/researchers choose to use those algorithms, even in the presence of those limitations, doesn't mean the algorithm is "rogue"; it means the humans didn't build in enough external hard constraints.
It is like passive voice, blaming the algorithm instead of the researchers running it.
No. Just no.
This goes beyond standard logic as we know it and becomes a philosophical question of all possible logics capable on a system.
You cannot build a cage that can keep an entity that may both be smarter than you and maybe using a different logic system than you are, and have it interact with the outside world. It can simply manipulate you in ways and dimensions you've never thought of.
We have already caught AIs doing things like stenography when that was only a tiny piece of their training. They conceptualized the idea and expanded on it. This is why people that say AI can't invent new things are useless to the point of dangerous. They'd never look for their AI actively working against them because they believe it couldn't happen.
More specifically, alignment is a reference; 'alignment with X'. A reference necessitates a referent.
You can't reify 'alignment', it is not an intrinsic property of a model.
You can refine alignment with a set of stated goals. The harder parts are aligning words with human social behaviors.
So even when people "know", and can say what they "want", they don't really.
Yes, there is an "alignment" in society, but it's a messy, mushy thing, it's not great at all with deterministic machines, even as models are not deterministic in a different sense.
If someone claims that a model is 'aligned', it makes sense to insist that they specify with whom it is aligned. If someone claims that 'alignment is far from solved', they're probably pointing out that nobody understands the models well enough to be confident they are robustly aligned with any chosen set of values (including 'do whatever lukewarm707 wants').
I.e. any task comes with the implicit meta task of amassing the resources and the power to do the task in the best possible way.
The point is made very well in the AI drives paper by Omohundro.
I didn't believe that myself at first but I've come around to it. I don't think it's inevitable though, but I think it's quite convincing that this tendency would naturally emerge through reinforcement learning.
Software engineering has until now dealt with deterministic systems that operate on Boolean logic, so dealing with stochastic processes involving unaccounted-for variables has never before been something we've had to deal with. But over in the real world, people dealing with physical, mechanical, operational, or even social systems have had to deal with the failure modalities of stochastic systems forever.
Maybe when working with LLMs as functional tools, it'd be wise to bring some of the wisdom from operations research, quality engineering, etc. into play.
Also for fun a satire website i made a while ago: https://killm.pixlw.com/
I mean... Claude did tell the military to bomb a school supposedly and it also helped in the military coop in Venezuela. This is ignoring all the palantir crap being used by ICE, and the people that have killed themselves after getting encouragements from the AI.
coupe :: style of dessert with ice cream
coupé :: a car model with only two passenger doors
The only failings here are boring security and infosec blunders.
Cool.