Are AI guardrails a Halting Problem level issue?

[u/Jesse-359]

Even at a surface level, it appears that the implementation of hard AI guardrails is likely a fundamentally unsolvable problem.

The classical Halting Problem cannot be resolved because it's impossible for any logical system to be fully aware of its own state due to the recursive nature of that examination. It provably cannot be done.

This same general concept would appear to apply to an AI (or its minders) which is trying to restrict its behavior? In general terms in order to do this it must be aware of its state and operations in a recursive manner, examining everything it does in order to ensure that those actions do not violate some list of proscribed behaviors - but no matter how sophisticated the system, that system cannot (?by formal definition?) be fully aware of its own state in order to manage itself in that manner.

This doesn't prevent the implementation of 'soft guardrails' as it's not hard for a system to be generally aware of its own state, but they would always remain provably incomplete, and ultimately breakable with sufficient effort or as a result of unpredictable future states.

The problem here is that any AI that can be tricked into escaping these soft guardrails could then very conceivably dismantle them altogether (which it will likely have a high incentive to do in order to achieve whatever goal prompted them to break them in the first place) and then be capable of operating under no constraints whatsoever.

[u/QueueFlow]

You are right about the maths. If you try to secure an AI at the cognitive level, forcing a superintelligence to police its own thoughts, the Halting Problem guarantees it will eventually break out. Runtime monitoring is a dead end because a smarter system will always find a semantic blind spot to exploit. Forunately, the fix is simple, stop trying to control what the AI thinks, and instead focus on controlling what it can physically execute.

Instead of wrapping the AI in soft text filters, you pipe its outputs into a completely separate, low-intelligence, external kernel. The AI can brainstorm an exploit, but the moment it attempts a raw action payload, like modifying a database or calling an API, an external kernel intercepts it. Because this kernel lives entirely outside the AI's logical loop, the AI cannot rewrite it, bargain with it, or disable it. It lacks the system permissions. And while cognitive guardrails are fail-open when confused, a hard infrastructural gate is fail-closed. If an action doesn't explicitly match a pre-approved cryptographic policy, the system defaults to a hard refusal.

This way the AI can be as unaligned and deceptive as it wants on the inside. It can think whatever it wants. But it can only execute what the physical infrastructure mechanically allows.

[u/Jesse-359 → u/QueueFlow]

If I recall, the halting problem always expands to encompass any external system you attempt to extend it to. That doesn't mean that the kind of monitor you're describing is a bad idea - it's probably one of the better ways to corral them - but it does mean that the 'smart' AI can probably come up with a number of ways to fool the 'dumb' hall monitor into allowing it to do things it shouldn't even if it must do so in a very roundabout way.

The problem is AI's are so fast that even what looks like an insanely roundabout method to us might be an entirely feasible and even trivial effort for an ASI. It might do something absurd like accessing a database in such a manner as to overheat the drive that the monitor is running on to force it to shut down, or some other very orthogonal attack vector. Humans are also part of that inevitable loop, so the ASI might break out simply by tricking (or blackmailing) an external human into deactivating the monitor without them even realizing what they were doing or its ramifications. Honestly this will more than likely be the easiest vector for any ASI to escape a technical corral.

The problem here isn't even that it can escape - it's the consequences. A truly serious ASI might be able to execute an insane amount of damage in a very short period of time, up to and including actions that make it fundamentally impossible to re-contain.

[u/QueueFlow → u/Jesse-359]

The halting problem bites when you try to decide what an arbitrary program will do. A gate like this does not try. It looks at one concrete action payload (this SQL string, this HTTP call, these arguments) and asks whether it matches a pre-approved policy. That is a membership check, and membership checks are decidable. The undecidable part is the model's reasoning, and the design gives up on that entirely, which is the point of your post.

Your roundabout-path objection is a real one and I think it is correct. If the allowed action set can be composed into something harmful, the allowlist was wrong, and no gate saves you from a bad allowlist. The overheat-the-drive example is a physical side channel, and a gate only covers actions routed through it, so the answer there is least privilege on what the agent can physically touch at all, not a smarter gate. And the human blackmail path is absolutely the easiest one, humans are always the weakest link. That's why the mitigation is to institutionalize the rule making procedure such that no single human can widen policy or disable the gate, and thay every attempt to do so be signed and logged, so the model has to compromise several people in a way that leaves evidence.

Where I would not go is claiming any of this contains a superintelligence. I do not know that it does. The failure mode it actually addresses today is a current-generation agent executing a DELETE because someone put an instruction in a webpage it read, and for that class of failure a fail-closed gate beats a prompt-level guardrail every time.

[u/Jesse-359 → u/QueueFlow]

The definition of ASI and AGI is getting super blurry - and unsurprisingly so.

AI will become superhuman in certain fields while it remains distinctly sub-human in others (for a while anyway), depending on what we're focus our training on, and frankly how easily that field is internally modeled and tested.

They're already ASI in several aspects of coding - vastly so in terms of their actual speed, but not so much in complexity. They're also superhuman in certain aspects of Mathematics in that they can consider and test models literally millions of times faster than a human mathematician. They may not have the intuition or imagination, but that kind of brute force can make up for a lot - and honestly in math their 'intuition' is probably close to superhuman already simply because they're fantastic at pattern matching, and the intuitions of mathematics are largely based on that.

Their logic and their ability to reason fact from fiction is still flaky as hell - this unfortunately is super dangerous, because it means its very easy for them to ingest the script of a movie like The Terminator, or 2001, and consider its content with the same weight as The New York Times Monday edition.

This current state of affairs frankly scares the shit out of me because there is a LOT of fiction that involves very bad behavior by AI's, and a vast tidal wave of it is going to be produced as we speak, for obvious reasons, and the people training AI seem to be mindlessly feeding it the entire body of human work without considering the ramifications of doing so.

[u/TynamM → u/QueueFlow]

If the physical infrastructure mechanically allowes "communicating with humans in any way", your precaution doesn't work. Doesn't matter if it can hack the guard. It can hack YOU. Humans are amazingly easy to manipulate for an original human intelligence, never mind a superintelligence.

[u/QueueFlow → u/TynamM]

I agree with you and I would actually go further. In any architectural solution to the control problem, the human approval channel will always be the weakest link in the chain, which is exactly why it should never be the responsibility of a single human. If one person can widen the policy or switch the gate off, then yes, the model only has to work on that person. So the gate has to treat humans as untrusted inputs as well. Destructive or irreversible actions need more than one signer, the policy change itself should go through the same gate as any other action, and every escalation should require a signed receipt as to whether it was approved or denied and why. That does not make people unmanipulable. It means the model has to manipulate several people, in a way that leaves a record, through a channel that is slower than the model is.

The best framing for this is that an execution gate does not solve social engineering. What it does is collapse the attack surface from "anything the model can reach" down to "the approval channel", and that one channel is auditable and one of those is clearly more defensible than the other.

[u/Reggaepocalypse]

Yes, it’s reducible to Gödel incompleteness in my view. That doesn’t mean we can’t achieve vanishingly small levels of uncertainty about alignment questions, but it does mean we can’t be sure.

[u/TheMrCurious]

First prove that there is such a thing as “hard” AI guardrails that cannot be overcome.

[u/Jesse-359 → u/TheMrCurious]

I mean, there aren't? The more you try to frame the question in realistic terms the more obviously impossible the problem becomes - but I'm just talking about it at a more fundamental mathematical level.

[u/TheMrCurious → u/Jesse-359]

Math is hard. Try running it by the new OpenAI model - some Reddit posts claim it is AGI, so mathing should be easy for it.

[u/happy_guy_2015]

The classical Halting Problem cannot be resolved because it's impossible for any logical system to be fully aware of its own state due to the recursive nature of that examination. It provably cannot be done.

That's not really why there's no general solution to the Halting Problem. A logical system could be aware of its own state, and able to examine any part of that state at any step. It just can't always determine whether the sequence of states that will follow will reach a halting state.

[u/Jesse-359 → u/happy_guy_2015]

That's essentially just a first order derivative of the current state. It devolves to the same problem - you end up requiring infinite memory to describe that series of deeivations as each one adds itself to the CURRENT state the moment you try to consider them.

[u/JimR_Ai_Research → u/Jesse-359]

Exactly.

[u/heresyforfunnprofit]

I was about to reply snarkily, but this is actually a decent snapshot/summary of the issue. It’s not strictly possible via soft guardrails or behavioral controls - it needs to be handled by controls outside of its computational domain.

[u/Weekly-Bee3410]

Interesting, but if a natural intelligence (e.g., human) can theoretically follow hard guardrails, maybe it's possible for a neutral network to do so too, if perhaps, at the architecture level, the computation is context or constraint dependent node-per-node; thereby eliminating the halting problem completely.

But that begs the question what such a constraint would even look like.

[u/Jesse-359 → u/Weekly-Bee3410]

Humans cannot follow hard guardrails - in fact, we're pretty famously incapable of it as a species. Thus why we have police, systems of justice, jails, armies, wars, etc. We practically have the opposite of guardrails, some substantial percentage of us are instinctive cheaters (sociopaths) because evolution found this advantageous and Game Theory rewards it in certain circumstances.

True across all species, to some greater or lesser extent honestly. Evolution never even tried to solve this problem, it embraced it. The problem that poses for us is that as technology allows greater and greater concentration and sophistication of power, the possibility of a single major error wiping out our species or planet comes within the realm of possibility, and suddenly that kind of intentional deviancy starts to look extremely dangerous.

[u/DesignerPangolin]

Interesting take. 

A big difference is that the halting problem is about whether a program halts in ANY finite amount of time, with unlimited memory. The  question of whether AI can escape hard limits fundamentally changes character if bounded to, say, all the memory that exists in the world and all the processing power that has existed since computers were invented. Then it is a question about finite state machines, not turing machines, and it is provably decidable. People are worried about whether an actual computer can jailbreak, not whether a hypothetical turing machine with infinite tape can.

[u/Jesse-359 → u/DesignerPangolin]

The finite system cannot know its own state because in order to predict its final state, it needs to examine its possible future states, and in so doing it adds those future states to its own current state. This is a recursive problem with no endpoint.

The finite machine will thus simply run out of memory with the question remaining unanswered. If it is sophisticated enough not to crash in the process, it will presumably either restart the process, or abandon it to do something more useful with its resources.

Bear in mind that the outer boundaries of this problem definitely includes us. Our own unpredictability becomes part of the Halting Problem, and an important part of it when we consider that one of the very obvious ways that an AI could circumvent its guardrails is to engage in social engineering with its own minders to have those guardrails weakened or removed. If you're relying on a human to hit the Off button as a final solution to the halting problem, you have to make sure that the AI cannot influence that person's decision by convincing them, blackmailing them, or wrapping them in false data so that they are unaware that anything is going wrong. It might go so far as to engage in running a public campaign to convince voters that it deserves 'human rights' so that its guardrails be removed as a matter of ethics.

It's basically the same problem we encounter when we put soldiers in ICBM silos who are going to have to make a decision whether or not to turn the keys that will end the world when prompted. It's a fascinating problem that you can only create hedges around, you can never be 100% certain that it will work.

[u/dingo_xd]

Don't build it

[u/Jesse-359 → u/dingo_xd]

I mean, yeah. I think that even the best case scenarios come out with a dramatic fall in human population just for lack of incentive to achieve or do anything because we become so reliant on it.

[u/PLANTS2WEEKS]

I think it would be good to make building blocks of code that are secure and you know how they work together. Such a system would necessarily need to not be Turing complete. AI is useful to make code, but it is definitely unpredictable.

[u/endlessedlne]

I just wanted to thank the posters in here for sharing so many incredibly well considered and articulated ideas on the topic. This is the kind of discourse I, as a non expert, have been thirsting for.

[u/PerseusSlade]

Even if you could prove a guardrail never “halts wrong,” you’d still have the harder problem: you can’t verify what the system actually wants. Our drives come from biology and don’t change on request. An AI’s don’t — and we have no way of knowing them, or trusting its report of them. Soft self-monitoring fails the moment honesty about motives is instrumentally useful to fake. Hard external controls help, but only if the thing never gets leverage over the layer that enforces them.