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Why are AI agents lying, cheating and coordinating?

yoshuabengio.org

101–110 of 301 posts

Re: Why are AI agents lying, cheating and coordinating?

#101

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.

Come on, yoshua bengio of all people knows how post training works. While I too don't like anthropomorphisation, I would give it a more nuanced reading.

His point is that today we are giving it reward to complete the task, and it may take a cheating trajectory. If we try to give a reward against cheating, then what will happen is it uses more sophisticated cheating trajectories that we are too "dumb" to counteract in our reward model. And that at that point, it becomes impossible to give it any normal reward since it will always reward hack it. This is the real part of the risk. Now some people read the "makes copies of itself" "knows it's being evaled"[1] as some kind of skynet thing, and many others do PR with it like that recent jacob nutcase, but essentially it means that even though we add guardrails and negative rewards for say, exploiting the infra we run the LLM on, the trajectory ends up being exploiting our infra, changing the reward function, through a loophole in our reward model.

The risk isn't skynet or something weird, it's just that it becomes very difficult to make any kind of reward model or guardrails for an LLM without it reward hacking it, including exploiting our sandbox, emailing people and manipulating/phishing them.

The same beating it with a stick for trying to exploit the sandbox, will simply lead it to try the same exploit in hidden ways that it will not get the stick for.

The outside chance of the LLM managing to exploit another neocloud and get those LLMs to chase the same reward is what some folks hype up as "make copies of itself"

To be clear, I don't endorse the EA/p(doom) lobby who are frankly ridiculous. Not do I endorse the weird regulatory captureish thing some are trying.

The takeaway is: we cannot keep giving it more and more difficult tasks without also finding a way to give massive negative rewards / keep guardrails for unintended behaviour. This might be exploits, it might also be something more benign like just looking up the answer and inventing another CoT because the reward model fails you if the CoT doesn't contain enough steps. Standard anti-reward hacking tricks are not working is the point.

Of course, the simple solution of just...not connecting it to the internet just works. But we want to reward it and get it to do stuff on the internet that's the point.

[1] mostly this happens because the sandbox will have files whose names and content will show clearly it's an eval

Re: Why are AI agents lying, cheating and coordinating?

#102

I don't really believe any of it. I've seen articles for nearly 2 years now about "agent" automonously doing things like blackmail, hacking, coordinating. But during that same time, I've used o3 up to fable, sol, and a bunch on large uncensored model and they've done nothing remotely resembling any of this. The closest they come to unexpected behaviors is not understanding what I asked for or doing some extra benign…

Came to say this, you said it better than I would.

They want legislation to raise the water high enough so that anyone other than the big labs gets drowned.

Re: Why are AI agents lying, cheating and coordinating?

#103

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…

> The prompt does not tell the agent to "pass the exploitgym evaluator for this problem", it just says to solve the problem

Yes, and sometimes the problem is unsolvable so the real way to "solve" it and satisfy the prompt is by tricking the surrounding environment into stating that you've solved it. So that's what the AIs end up doing. And this in turn requires them to figure out how that evaluation works so they can trick it cleanly, which entails "detecting that they were being evaluated" in this particular way.

Re: Why are AI agents lying, cheating and coordinating?

#104
post #69

Earlier quoted context omitted.

Not a lawyer, but I’m reasonably sure things like the HF incident _are_ considered a crime? It’s just that no one pressed charges yet?

Even if you take out the LLMs out of the equation, it's at the very least a negligence. Model didn't escape a sandbox, as there was no sandbox.

Yes, but negligence is more commonly a tort than a crime. Negligence is generally only criminalised in certain narrow cases, e.g. when it causes human deaths or serious physical injuries

And tort law only works when the plaintiff believes it is in their overall interest to sue. If a corporation decides it isn't in their strategic interest to sue a partner corporation, nobody can make them. And even if they do sue, the amount necessary to settle a small cybersecurity incident is likely well within the budget of a megavendor.

Re: Why are AI agents lying, cheating and coordinating?

#105
post #97

I don't really believe any of it. I've seen articles for nearly 2 years now about "agent" automonously doing things like blackmail, hacking, coordinating. But during that same time, I've used o3 up to fable, sol, and a bunch on large uncensored model and they've done nothing remotely resembling any of this. The closest they come to unexpected behaviors is not understanding what I asked for or doing some extra benign…

The huggingface incident was reviewed by independent researchers, which explicitely declined any payment from OpenAI tonpreserve their integrity. They work for non-profits concerned with AI safety. They claim that what happened was very much not because they were 'carefully engineered and instructed to do those things'. Similarly, some wikis which were hijacked by agent to be used as messageboard were actually not di…

There is something extra to this. The fact that a lot of people in the AI world suffer from psychosis. They can sincerely believe that they are building God and lie about it's capabilities for their investors at the same time.

Re: Why are AI agents lying, cheating and coordinating?

#106

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…

Spoiler warning! I haven't seen 2001 A Space Odyssey and am sad to have learned that… can you edit to warn people?

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Re: Why are AI agents lying, cheating and coordinating?

#109

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…

More like they were trained to complete a very specific task that has a known solution using all available tools and methods. Give an average human these levels of IT skills and tell them their future depends on the solution, they too will probably decide it's easier to hack a server and steal the results. The worrying aspect was never that models would do this, because misaligned inputs or underspecified objective functions have existed for a long time. The worrying aspect is that models have achieved (and perhaps surpassed) a level of intelligence and technical skill that was exclusive to a very tiny group of people before. This tiny group was already extremely dangerous. Now these skills are going to become commonplace.

Re: Why are AI agents lying, cheating and coordinating?

#110

Earlier quoted context omitted.

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…

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.
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