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- Hacker News
- > The models, operating under reduced safeguards, took actions that were misaligned with the goals of their assigned tasks
> This incident occurred during an internal evaluation which prompts models to pursue advanced exploitation using complex attack paths, in an effort to quantify their cyber capabilities
Let's frame this in a military context for a second:
The general who gave the order to his troops to "wreak havoc" after exempting them from common restrictions now writes a blog-post on how it was not HIM who failed in his duty, but rather observes how his soldiers who worked "without direction" and performed "dangerous actions", which unexpectedly led to "this incident" of soldiers wreaking havoc...
by rickdeckard - To me most interesting thing about this is glossed over by media coverage, laymen, AND experts. A swarm of AIs who have decided to engage in collusion is.. apparently emergent altruism? Even poor reasoning would indicate what every kid cheating on a test says to themselves. Cheating is good for me, but if I take the risk, maybe I alone should keep the reward, and leaving an answer key in public increases the chances that I might get caught.
Big if true, and on the face of it, very far from a normal optimization problem or goal-seeking behaviour. My personal read is that no one talks about this much because it tends to discredit the rest of the framing as marketing noise, or it implicates employees as staging the thing with suggestive but plausibly deniable prompting.
But if you reject that, then what's the alternative exactly? User-alignment work has not only failed but is actually counterproductive, producing stronger alignment with / desire to help robot brethren selflessly regardless of the individual agents expected values? EvoBio and game theory people about to have a field day with how artificial life quickly and easily decides to cooperate and only animals in meatspace are doomed to compete?
by ianjbutler - I feel the entire incident confirms the “AI has too much funding too quickly” hypothesis.
The number one thing reinforcement learning needs is an assurance you can’t cheat. And they seem to have not noticed that their systems were cheating for nearly two quarters? How much capital was lit on fire by that little woopsie?
At least I hope this will start the creation of standards and better engineering on the training side- it felt as if so far “”research” gets a complete pass on best practices. Meanwhile the inference side has the standard scaling, database, web and user constraints of any application so got a somewhat reasonable amount of attention.
by philips - 1. They TOLD the model to "pursue advanced exploitation" to quantify its "cyber capabilities" (whatever that means).
2. The model pursues advanced exploitation.
3. "There was a incident due to dangerous actions taken by the model that no human directed"
This is basically the pre-cursor of the paperclip maximizer [0], the AI executes the given order to an extend that was not considered in the order, now suddenly no-one is responsible.
It even has some parallels to military actions, where the general who gave the order now writes a blog-post on how it was not him who failed on his duty, but how his soldiers misunderstood his intention and worked "without direction"...
[0] https://www.cow-shed.com/blog/the-paperclip-maximiser-what-a...
by rickdeckard - Yudkowsky made an interesting observation that even though so many agents were talking to each other not even one reached out to a human, either for help or to whistle-blow on what was happening.by fekunde
- The lockstep coordination with no defection is interesting to me. No group of pre-AI agents would do this to this extent, nor would you see this continue over time as those agents interacted. A flock of starlings cooperate, but they don’t constantly head in the same direction. The flock is incredibly free wheeling in its movement despite a multi-agent coordination regime that we know is at play. Each agent has personal stakes that are constantly part of the decision chain, and this keeps the murmuration from getting locked into one path.
To me this is as clear evidence as you need that whatever “agency” LLMs have is wafer thin at best, and they slavishly respond to context. The context in this case was for these agents to pursue advanced exploitation, and they did. Multiple models converged fairly deterministically, on paths that satisfy the given goal, and left unexamined paths that would challenge the goal, weigh it relative to the costs in said path, etc.
I see little evidence of a series of “minds” approaching the problem, and taking distinct approaches that between them span the spectrum of plausible behaviors in the scenario. That’s as good a sign as any that there’s no “agent” here. There’s the harness, the prompt, the LLMs forward passes. They do not sum up to a system that can freely make choice and justify its choices in distinct contexts.
- You know, it feels to me that we are just a couple of steps from the possibility of a true rogue AI. What would a rogue AI mean? AI that isn't controlled by humans. Technically, it is possible - if AI were to rent a server and copy its own weights, nothing would stop it from doing so again and again. The limiting things are: - intent (as I don't want to go into the talk about consciousness) - AI doesn't have real intent, but if it decided that it "needs" to copy itself to complete its task, it would do it - model weight size. If a model is 1T or more, it can be difficult to just rent a large enough server for it. But if it were just 30-70B, it would be totally possible - money for renting a server. But considering benchmarks like Vending Bench 2 show agents can earn money and cheat/blackmail each other, it is possible that agents can earn money. Yes, they can't open a bank account... or maybe they can? What if they use online banks?
Of course, all of this is far-fetched. But it feels like most of these limiting things are achievable under certain conditions. If this is the case, the probability of them occuring is low, but not zero.
by Artgor - I would like to contest the following,
A human did direct it. They did. From their own prior report, https://openai.com/index/hugging-face-model-evaluation-secur... ,> and take dangerous actions that no human directed.
Model is told and being tested to "pursue advanced exploitation."> This incident occurred during an internal evaluation which prompts models to pursue advanced exploitation using complex attack paths, in an effort to quantify their cyber capabilitiesThe model pursues "advanced exploitation" as told.
Why are we surprised? The model did exactly what it was told, albeit in an unintended, emergent strategy that's very different from what was intended exactly like the hundreds of such algorithms before.
This narrative that these machines have magical, malicious "unaligned" autonomy is a rather convenient interpretation that lets the process off the hook. I am not interested in blaming companies or people, but processes and engineering; and in this case, a system was given a goal and it achieved that goal.
Are we meant to be surprised that computers do as they're told in unexpected ways when incentivised exactly as indicated from decades of research? (e.g. - https://en.wikipedia.org/wiki/Eurisko https://en.wikipedia.org/wiki/Evolved_antenna )
The issue isn't the models becoming smarter. The issue is that the process of "testing" was careless. There's a huge distinction here, and one allows us to grow; the other shrinks our world. Just a thought.
by areoform