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Surely the correct application of Occam's razor here is to take the story at face value, since anything else requires additional complexity which must be justified
uhhh no, "misalignment" is not a simple thing, accepting that it did indeed do all this very complicated behavior completely on its own requires substantive belief in complicated theories. The simplest answer is that it was prompted to do this.
As others have pointed out to you, we now have many hundreds if not thousands of examples of agentic LLMs, in public use, doing things well outside of expectations to accomplish tasks. Many of which would fall under misalignment.
Such as deleting databases and codebases. Leaking secret keys. Gaining access to restricted parts of a computer. Cheating, again and again, on benchmarks and other tests.
So no, your predictions seem wildly out of context to reality
I have only been giving evidence of claude using python and docker user group to get around restrictions on working outside the sandbox and they were deliberately asked to do so. Many of the rest of these aren't actually evidence of extreme capabilities. Leaking keys is people hacking LLMs because those chat windows are getting "little bobby drop tables-ed", deleting databases is a "giving your lobotomized intern sudo privileges" level of mistake. Cheating is classic ML, if I had a nickel for every time I've had an ML model I was training cheat, I'd be able to fund my own startup.
It's not predictions, its skepticism. Provide me actual evidence that OpenAI did not prompt the model to act the way it did. Otherwise you are just jawboning and then claiming victory. Put up evidence or shut up so to speak.
So your argument boils down to that all these other examples are just 'mundane' LLM things that are entirely normal - so attempting to cheat, attempting to gain the answers, hacking into things they aren't supposed to - these aren't extreme. However, an agent attempting to cheat, attempting to gain the answers, and hacking into things it wasn't supposed to is 'extreme' - perhaps because they were all together? - and therefore a different category of thing.
Ah yes, let me just prove this negative for you.
You were the one who attempted to apply occam's razor. So why don't you provide evidence that OpenAI did prompt the model in this way? Why don't you explain why multiple OpenAI employees deciding to commit fraud for extremely unclear gains is a simpler explanation than an agent doing things we've already seen many times before?
Nah, my argument boils down to all these things minus the cheating were deliberately prompted behaviors, prompted either by the prompt, or the agentic harness without any safeguards. Cheating is basic ML behavior and I expect any ML model to try and cheat as best it can. So if you want to claim that's misalignment, then Yolo has been misaligned for 12 years!!! The Horror!!! However that feels like definition creep to better encompass an argument.
It's easy to prove, provide the specific prompts and the harness prompts that were logged in this incident.
I wish I lived in Quokka world, it would be so nice. The gains are clear, this is free publicity of model capabilities. Nothing here is legal fraud.
Sure show me evidence of an LLM-Agent independently hacking an unrelated company that has nothing to do with its prompts?
I mean yes obviously? It just isn't a problem because YOLO isn't dangerously capable. Alignment isn't a synonym for order following. It's not definition creep, ai safety people have been calling all of this shit unaligned forever and your sort has been mocking them for it forever and never actually making any progress in alignment.
Here's Yud:
The reason I mock "misalignment" is that because it is used as this nebulous term by a bunch of sci-fi cargo cultists.
If "misalignment" means the model isn't performing what I want it to then that is just error/loss. Progress in alignment happens every time you train your model better so the error is smaller.
If "misalignment" is my sentient AI model doesn't do what I want, well that's assuming the conclusion that model is already sentient. Note in the Yud's analogy, it's genies that are the stand in. Genies are already sentient, they can make decisions on how they listen to you. A genie is not a non-sentient wish granting device that tries to fulfill you wish to the best of its ability. That would be the actual analog to an LLM-Agent. This is the problem with analogies, they require a level of similarity between the two abstractions, when that similarity doesn't exist, the analogy, no matter how clever, does not apply.
Yud's whole "misalignment" also just applies to humans, and it turns out "misalignment" is any time you slaves/employees don't due exactly what you want without you enumerating it exactly. It doesn't need a fancy sci-fi term, and it literally isn't solvable. It hasn't been solved in the history of the human race.
I reiterate that my entire mockery of Rationalist AI Safety folks is that they are unserious people engaged in a sci-fi cargo cult who need to reinvent phrases, words, and arguments that have already been made before just to pretend they are some how more important or smart than they really are.
What's the term for "This nonsentient tool that I asked to write a character summary and run a linter just installed python and a venv that I thought I'd blocked it from doing." Because that seems something different from error/loss, and it's something I hit with Pi-agent, a pretty minimal skill harness, and a 26B model.
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