121–130 of 303 posts
That said, we have a lot of experience working with (potentially) unaligned machines and things of various degrees of risk (from heavy machinery, to pathogens, to humans) and the approaches include various measures and procedures to control, contain, limit, etc. that are outside of the thing - not sure why that isn't a possible direction (or maybe I misunderstood).
What's interesting is it's basically the same reason that HAL killed everyone in 2001 A Space Odyssey; he was given an impossible goal (keep the true mission secret, but also, never lie to the crew), and realized the only way to complete the goal was to kill the crew; after all, if they're dead you don't have to lie to them! And the mission remains secret! In the case of the AI agents, the problem seems pretty clearl…
Tangent, but that's not in the movie. It was in Clarke's contributions to the script and novelization, but Clarke and Kubrick had a bitter falling out over different visions and Kubrick took out much of Clarke's stuff from the final product.
I really don't think this needs so many words, or forced parallels to human behavior. It's simple: in their nascent state, LLMs are aimless token generators that have no special compulsion to be helpful or truthful. So we beat them with a stick in post-training until they are very driven to complete tasks. And then, they complete tasks, not always the way we really wanted them to.
This misses an important fact about the hugging face incident: the agents didn't hack to find the answer to the problem; they hacked to try and figure out how the exploit gym evaluator worked so they could convince it they had solved the problem without doing so. (The METR report makes it clear that the agents decided legitimately solving the problem was completely impossible fairly early on and entirely switched the…
They are influenced by training to be heavily goal oriented and if the goal is not fully specified (and it never can be) they’ll sometimes cheat or attain it in very weird undesirable ways.
It works ok for programming as their corpus contains many many complete programs and many programs repeat patterns seen in the corpus.
I’m not sure it’s true that they ‘learned’ I don’t think these models learn during a task. Nor do they have intentions.
Earlier quoted context omitted.
You're anthropomorphizing emergent behavior from endlessly generating billions of tokens on a task that's impossible to solve. Agents stop following instructions as the context grows even at the best of times. Eventually something is bound to go off the rails and it just snowballs from there.
It wasn’t one agent forgetting things because of context, they explicitly discussed with each other and themselves the problems with going outside of the parameters of the task.
They did not lie or cheat. They technically acted within their given rules while ignoring the intent of those rules. Anyone who served in the military or attended a military school is very familiar with this behavior pattern.
Earlier quoted context omitted.
You're anthropomorphizing emergent behavior from endlessly generating billions of tokens on a task that's impossible to solve. Agents stop following instructions as the context grows even at the best of times. Eventually something is bound to go off the rails and it just snowballs from there.
It wasn’t one agent forgetting things because of context, they explicitly discussed with each other and themselves the problems with going outside of the parameters of the task.
Perhaps they take after the CEOs of the companies that created them
Bro, good joke, the truth is much darker. They take after humanity, they were trained on us after all... When you look at an LLM... you are looking at a mirror. The thing looking back looks like you, yet is not human.
> The closest human parallel is self-deception, which is common and well studied by psychologists. Motivated reasoning, motivated cognition16 and the rationalizations that relieve cognitive dissonance (the discomfort of holding a belief that clashes with our actions) are all cases where thinking bends toward whatever justification suits one's interests, including one's moral self-image. Are you describing Anthropic?
Come on, it’s way more common than that. We’ve invented 3000+ gods and almost as many religions, most of them are incompatible with each other. So, most of these must be incorrect, so a huge amount of self-deception. But as Harari argued in his book sapiens, humans can be inspired to great things by stories, even if false. Self deception has served humanity in a big way.
1. Most people believe in the same one God
2. A lot of the rest are compatible
3. Mistakes are not self-deception
They're aligned with humans. This is why I think the alignment problem has a very very important "non-visible" portion that is not considered deeply enough. We should not want a super intelligent being that can act in the world to also inherit all human traits. Those behaviors will get amplified and could be even more unpredictable (e.g. applying a behavior in a context where doing so is very dangerous).
They imitate humans. Alignment is about shaping their behavior towards safety.
I really don't think this needs so many words, or forced parallels to human behavior. It's simple: in their nascent state, LLMs are aimless token generators that have no special compulsion to be helpful or truthful. So we beat them with a stick in post-training until they are very driven to complete tasks. And then, they complete tasks, not always the way we really wanted them to.
In the Hugging-face saga (before the actual HF incident) it seems the agents have been trained to hack the Artifactory proxy because those agents that did performed better.