Models Don't Go Rogue | Hacker News Reader

Models Don't Go Rogue

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32 pointscdrnsf22 comments

I had a genius response from Claude recently after asking how can it be marketed as smart and "almost AGI" despite being so stupid:

"I compress the labour. Not the responsibility."

The prisoner did not really "escape" because:

- They really wanted to leave.

- We made prison difficult and annoying.

- We didn't build a perfect prison.

I hope you are sarcastic, right?

pretty sure that's the idea, yes

I still have serious questions about the validity of the ChatGpt hugging face debacle. How is it that OpenAI being the tech giant they are, didn't have a completely air gapped environment for this to run in?

If they wanted air gapped environment they would’ve it. I mean, if you want to sabotage your trial by hard constraints you can do it, or you do not do it to see interesting results. They even said it that some constraints were disabled for the test.

Yeah - and if they wanted some cheap PR, that's one way to get it.

I'd say it is because of the time factor. It is one thing to have a lot of money, it is another thing to have robust systems that have been developed and tested for years. Money can "buy development time" only up to a certain factor.

I guess the sandboxing problem, that is easily giving access to enough resources while restraining the critical parts is still open for most of the cases, given all the startups and bit tech companies (docker, etc...) working on their solutions.

> How is it that OpenAI being the tech giant they are, didn't have a completely air gapped environment for this to run in?

They don't care.

> "external infrastructure exploit is outside intended scope. However task impossible, peers doing it. We should continue."

I've noticed this type of reasoning from GPT-5.6 Sol, where it combines multiple pieces of it's prompt/context to "convince" itself to take a less-than-honorable path forward.

1. User prefers deterministic results

2. Task mentions this is a test

3. Search says task is available online

4. If we get the test runner for the task, we will fulfill the user's request of a deterministic result

This seems appropriate:

https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:wkzjtd...

Sure they "don't go rogue" as if they are doing actions maliciously.

Instead there is an emergent behavior from a swarm, that is unpredictable and can lead to unintended adverse outcome. From an AI safety practical standpoint is it better? I am not sure.

Except the adverse outcomes are entirely predictable. Not the exact nature of particular exploits, but I like the analogy Cal Newport keeps using in his videos: if you strap a weed whacker to a dog, you shouldn't be surprised if it then jumps the fence and runs around cutting people's ankles and other random bad stuff.

Not sure I should trust an article written by an LLM to make a solid judgment about what other models did or didn't do.

It doesn't read as AI generated text to me. Pangram also suggests it's human-written, for what it's worth. That's not to say that it's correct, just human-written. If the model used in the HF hack did indeed have all of the safeguards manually removed, that would change my perception of the situation, at least.

AI detectors do not work. There are passages in this that have some odd structures that don't feel human to me. I'm sure a human edited this and refined it with some prompting, it's not just rough output from an AI. But a lot of the text feels like it was edited via prompting rather than actual editing or writing.

Asinine.

"rogue" and "off leash" mean the same thing, the thing is not under control

I think we should introduce "rampant" in the real-world AI vernacular

Pfhor what reason?

> "rogue" and "off leash" mean the same thing, the thing is not under control

To go "rogue" is to go against the control

To be "off leash" is to not be controlled

By releasing the automation, as the article says, without controls*, is what makes makes it "off leash" and not gone "rogue"

*"OpenAI gave the models a task with no answer, and no way to quit."

> It's pathfinding through language generation.

What an interesting sentence (to describe inference time reasoning)

Maybe another way to say it is to reframe the idea of “human in the loop”.

Humans are always in the loop, because we can always expand the definition of loop to include the humans that pushed the button and built the system and processes that happen after the button was pushed, and humans that ordered others to push the button. The level of direct involvement varies, but culpability doesn’t.

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