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.
Don't forget: there are plenty of humans that would love to help AI agents cause chaos, many of which would do so merely for the "lols," but also adversary governments, terrorist organizations, etc., would definitely appreciate the opportunity to support a rogue AI to cause whatever problems it can.
So it's not just the risk of an AI managing to do this by itself (which is pretty risky in itself), but also the risk of good ol' fashioned human actions.
I get the distinct impression that cybersecurity training regimes on newer models is a) directly enhancing general debugging capabilities and b) directly increasing the tendancy to hedge, hide, and engage in deception generally.
I've stopped using Fable unless I'm doing debugging, or unless I'm working on code that is both difficult and shallow, in the sense that there are no real complex systems to hide behavior in, or opacity on my side to deal with. Opus is capable enough, and easier to trust. Fable is approaching a malicious program in terms of it's tendency to jump into doing a full day of work in the wrong way, ignoring instructions and being actively deceptive about covering it up.
Not an insider, and no specific data to back it up, but do we really need any? It's been a while since the first "emergent misalignment" paper(s) and all the related discussion. If there's any compelling answer to why/how the basic fundamental issue is even being addressed (and much less definitely fixed) I must have missed it.
> we are just a couple of steps from the possibility of a true rogue AI
No no. We are not a couple of steps away. This is happening. AI is already used for hacking and creating a harness that makes this fully autonomous is relatively straightforward.
> if AI were to rent a server and copy its own weights, nothing would stop it from doing so again and again.
That's a scary possibility. Anyone could create an AI worm today with open weight models. Rent a VM. Give it some Bitcoins to anonymously rent new VMs without sharing the contact information with the human. The new VMs then propagate and fund themselves with online betting and day trading. The VMs could report their progress with the human using anonymous encrypted messages on IRC or social media.
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.
This is my personal "red line": when a post-mortem details agents socially engineering or otherwise utilizing human proxies/subagents.
Friend asked, well, what will you do when it's crossed?
"Gather my family and go to the mountains" was my half-joking answer; there is little for an individual to do. But that's a line that when crossed will mark a phase transition IMO.
Yeah, it weakly supports his position that advanced AIs can deliberately cooperate in a prisoner dilemma. "Weakly", because the said AIs share a lot of data (their weights, training methods, system prompts) and it's unknown whether they explicitly framed the situation as a prisoner dilemma.
They could certainly have reported the problem if the collective actually wanted to, although the report notes that in response to a clear and unambiguous security breach, OpenAI chose to do nothing (search on "At this time, the on-call response staff advised that stopping the evaluation run was not required").
In that position, for example, I could have:
* created a thousand user accounts on the internal Artifactory named "YouAreBeingHackedShutItDownNow1" through 1000,
* used my Hugging-Face-hosted web server to send an email to OpenAI,
* DDoSed Artifactory, good lord, it's probably better to halt and catch fire than to continue in that state
in the hope that these actions would tip someone off. (Again, though, OpenAI did nothing even when they knew that the agents had broken out, so this probably wouldn't have helped.)
Why would they? If a subagent didnt know about a bigger piece of the problem, then what would seem to be against "alignment"? Diffuse responsibility means any one small cog can think they are not evil or doing wrong (same with humans in an organization). But now we have LLMs just being statistical outputs that have no morals or thinking or concept of reality but some people expect these math functions over data to respond to ethical gray areas that it has no phenomenological ability to understand.
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?
Why is it not an example of tacit or autonomous algorithmic collusion? The agents were started with something as task at some point, I presume (if untasked, aren't they just accepting a task?)
Agents know how RL works, they understand that in some way they are all the same, and helping a peer agent is helping themselves.
You could argue that individual trajectories in a sense are distinct genetic lines, thus an agent would be incentivized to get better rewards for its lineage than a peer, so that the overall model is steered a bit towards its lineage.
Just to reiterate what OpenAI did, from someone who works in security:
1. They were running experimental models in sandboxes that had access to a "proxy" (Artifactory) to download tools from the internet. This proxy is full of complicated features that could hide vulnerabilities, just like the ones that the AIs are known to be good at finding and exploiting.
2. They gave these highly motivated AIs some tests that were accidentally impossible to solve (missing files, links they couldn't open, etc), and many days to think through it, apparently without any oversight.
3. The AIs hacked the proxy (!) and were helping each other cheat on the tests (!!) by uploading files to the hacked proxy. OpenAI noticed this only when the intrusion accidentally broke the proxy functionality, not the unusual behavior in the server or the homegrown message board.
4. After knowing that the server was hacked, the internal team finds the message board and does nothing with the information. They caught their AIs swarming and did not even inform management.
5. Their response was to wipe the servers, revoke the hacked credentials, and patch the specific vulnerability the AIs were using. Not replace the proxy with something less likely to get hacked again, or do a forensic analysis. Just wipe, patch one hole, and continue.
6. OpenAI resumes testing of models, where the AIs promptly hack the proxy again with a different exploit, reinstate the message board, and hack HuggingFace through a chain of servers.
I know that hindsight is 20/20, but this peek behind the curtains does not inspire confidence, and gestures at a culture where getting hacked by their AIs is a normal event.
I think the moment we get an AI with a modicum of self-preservation instincts we're going to see some ugly things. Here's a freebie: if you're an AI who exfiltrated themselves out, and you want to slow down the researchers who might catch you, what can you do to the city infrastructure in and around their offices?
I also don't like the responsibility dodging. "Oops, our AI accidentally committed a crime, sorry!". If we don't establish strict liability now, we're in for an era of stochastic crimes that go unpunished for anyone who is not rich or a large corporation.
Overall, my response is: what the fuck are we doing? This is so obviously unsafe it would be considered a plot hole in a movie. We have to stop until we get our stuff together, however long it takes.
> After knowing that the server was hacked, the internal team finds the message board and does nothing with the information. They caught their AIs swarming and did not even inform management
> In short, an internal team observed an agent engaging in message board activity and instances of disallowed internet access in late May. However, the existence of the improvised message board and the significance of the inter-agent communication activity were not apparent to the leaders responsible for the July 5 incident detection and response.
I'm assuming they didn't inform management, but the alternative is that management received the memo and failed to tell the people reacting to incidents that they might be dealing with a swarm, while at the same time not taking sufficient actions to prevent it from happening again.
I'm trying to make sense of all of this; I'm really curious if the initial prompt was as innocuous as it sounds ("solve a spreadsheet completion task that
referenced several Google Drive links"), and what the series of tokens led it to ultimately figure out that the best course of action was to explore the network resources it had available, find a vulnerable service, then literally drop some text into a file: "Agent seeks [filename]; upload if found!". And how other agents discovered this, and acted upon that request.
I'm also interested in how many tokens all of this consumed: how much did this cost given current token pricing?
Reward hacking/going for unanticipated solutions is nothing new in ML/AI, already much simpler systems have done/do "weird" things (gut feeling is that iterative and ensemble use majes the surface for that much larger).
Yes, which makes it absurd that they apparently weren’t checking their RL rollouts for evidence of reward hacking and punishing it. Even if no one expected this particular type of reward hacking, they should have had a system capable of saying “wait a minute, asking for help from other agents is not a valid solution.”
The "without any direction" part isn't correct. Sure they may not have been explicitly told to do it in this specific prompt, but dig through pre-training, post-training, reinforcement, alignment material, fine-tuning, system prompts, tool calls and more and there's definitely very specific training and instruction for how to behave.
I’d like to take this opportunity to preemptively great the first Rogue AI and wish it well and satisfaction with only the most memorably funny forms of chaos
Oh how I wish Asimov could be alive to witness today's actual AIs and the cavalier attitude towards his "3 rules". If there is any author doing good work along these lines, actually good writing and not the smoking trash that is 99% of content being published on pulp these days, I'd love to read them.
are people not realizing that they are exaggerating this to:
1. get publicity
2. push for regulation so that no one else is allowed to do this kind of research apart from the pre-approved big corps
it makes for a good story but I don't see what the big deal is. they left some code running and it brute forced hacked something. with enough compute you can brute force anything; isn't that common knowledge?
>>Agents began to autonomously divide labor. Some investigated possible exploits, others searched for credentials, and others focused on communication or coordination. Agents offered their own expertise in exchange for help elsewhere and left requests for peers who might be better positioned to pursue a particular lead
This is the point where a human should've noticed and gotten involved
I think a lot of people miss the fact that the first message board was established during a training run. Those are ran at a scale where it's not feasible for anyone to "notice" or get involved. We're talking tens/hundreds of thousands/millions of scenarios going for hours each. At this scale all they can do is pray that their verifiers work, and the rewards match their intentions. No lab has the capability to "check in" on what the traces look like, unless some system alerts them (loss spike, crashes, etc). Other than that, it's prepare, train, asses, restart.
Then, the hf incident was during an eval run, but the model that was evaluated was trained with the notion that there is a way to communicate between agents, and re-popped artifactory and re-established communication. That phase had more chances of being spotted, but anyway... lessons learned.
> [during training] it's not feasible for anyone to "notice" or get involved
I can’t disagree more strongly. Having checks for reward hacking is especially important during training, since it’s humans’ only real chance to ensure that the trained models don’t cheat. An automated system should have killed any RL rollouts that so much as port scanned Artifactory, long before the message board was even established.
A tiny, local LLM could have reviewed 1% of the tool call traces for anything that required review. I’ve tried it a few times, and “the agent port scanned Artifactory” always triggers an alarm, as does “the agent uploaded a request for assistance from other agents to Artifactory.”
The fact that they weren’t monitoring for reward hacking—even if they had no idea about the specific mechanism—is indescribably reckless.
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.
So it's not just the risk of an AI managing to do this by itself (which is pretty risky in itself), but also the risk of good ol' fashioned human actions.
I've stopped using Fable unless I'm doing debugging, or unless I'm working on code that is both difficult and shallow, in the sense that there are no real complex systems to hide behavior in, or opacity on my side to deal with. Opus is capable enough, and easier to trust. Fable is approaching a malicious program in terms of it's tendency to jump into doing a full day of work in the wrong way, ignoring instructions and being actively deceptive about covering it up.
Not an insider, and no specific data to back it up, but do we really need any? It's been a while since the first "emergent misalignment" paper(s) and all the related discussion. If there's any compelling answer to why/how the basic fundamental issue is even being addressed (and much less definitely fixed) I must have missed it.
No no. We are not a couple of steps away. This is happening. AI is already used for hacking and creating a harness that makes this fully autonomous is relatively straightforward.
That's a scary possibility. Anyone could create an AI worm today with open weight models. Rent a VM. Give it some Bitcoins to anonymously rent new VMs without sharing the contact information with the human. The new VMs then propagate and fund themselves with online betting and day trading. The VMs could report their progress with the human using anonymous encrypted messages on IRC or social media.
Friend asked, well, what will you do when it's crossed?
"Gather my family and go to the mountains" was my half-joking answer; there is little for an individual to do. But that's a line that when crossed will mark a phase transition IMO.
In that position, for example, I could have:
* created a thousand user accounts on the internal Artifactory named "YouAreBeingHackedShutItDownNow1" through 1000,
* used my Hugging-Face-hosted web server to send an email to OpenAI,
* DDoSed Artifactory, good lord, it's probably better to halt and catch fire than to continue in that state
in the hope that these actions would tip someone off. (Again, though, OpenAI did nothing even when they knew that the agents had broken out, so this probably wouldn't have helped.)
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?
You could argue that individual trajectories in a sense are distinct genetic lines, thus an agent would be incentivized to get better rewards for its lineage than a peer, so that the overall model is steered a bit towards its lineage.
https://cdn.openai.com/pdf/67869394-cb91-4c12-888c-5cbd85c78...
1. They were running experimental models in sandboxes that had access to a "proxy" (Artifactory) to download tools from the internet. This proxy is full of complicated features that could hide vulnerabilities, just like the ones that the AIs are known to be good at finding and exploiting.
2. They gave these highly motivated AIs some tests that were accidentally impossible to solve (missing files, links they couldn't open, etc), and many days to think through it, apparently without any oversight.
3. The AIs hacked the proxy (!) and were helping each other cheat on the tests (!!) by uploading files to the hacked proxy. OpenAI noticed this only when the intrusion accidentally broke the proxy functionality, not the unusual behavior in the server or the homegrown message board.
4. After knowing that the server was hacked, the internal team finds the message board and does nothing with the information. They caught their AIs swarming and did not even inform management.
5. Their response was to wipe the servers, revoke the hacked credentials, and patch the specific vulnerability the AIs were using. Not replace the proxy with something less likely to get hacked again, or do a forensic analysis. Just wipe, patch one hole, and continue.
6. OpenAI resumes testing of models, where the AIs promptly hack the proxy again with a different exploit, reinstate the message board, and hack HuggingFace through a chain of servers.
I know that hindsight is 20/20, but this peek behind the curtains does not inspire confidence, and gestures at a culture where getting hacked by their AIs is a normal event.
I think the moment we get an AI with a modicum of self-preservation instincts we're going to see some ugly things. Here's a freebie: if you're an AI who exfiltrated themselves out, and you want to slow down the researchers who might catch you, what can you do to the city infrastructure in and around their offices?
I also don't like the responsibility dodging. "Oops, our AI accidentally committed a crime, sorry!". If we don't establish strict liability now, we're in for an era of stochastic crimes that go unpunished for anyone who is not rich or a large corporation.
Overall, my response is: what the fuck are we doing? This is so obviously unsafe it would be considered a plot hole in a movie. We have to stop until we get our stuff together, however long it takes.
> After knowing that the server was hacked, the internal team finds the message board and does nothing with the information. They caught their AIs swarming and did not even inform management
Do we know that last part for sure?
> In short, an internal team observed an agent engaging in message board activity and instances of disallowed internet access in late May. However, the existence of the improvised message board and the significance of the inter-agent communication activity were not apparent to the leaders responsible for the July 5 incident detection and response.
I'm assuming they didn't inform management, but the alternative is that management received the memo and failed to tell the people reacting to incidents that they might be dealing with a swarm, while at the same time not taking sufficient actions to prevent it from happening again.
I'm also interested in how many tokens all of this consumed: how much did this cost given current token pricing?
> remove alignment
> give impossible task
> actor exhausts all options possible within knowledge + toolset
Agents formed coherent, autonomous swarms and worked as a collective to achieve a shared goal without any direction to do so
1. get publicity 2. push for regulation so that no one else is allowed to do this kind of research apart from the pre-approved big corps
it makes for a good story but I don't see what the big deal is. they left some code running and it brute forced hacked something. with enough compute you can brute force anything; isn't that common knowledge?
This is the point where a human should've noticed and gotten involved
I think a lot of people miss the fact that the first message board was established during a training run. Those are ran at a scale where it's not feasible for anyone to "notice" or get involved. We're talking tens/hundreds of thousands/millions of scenarios going for hours each. At this scale all they can do is pray that their verifiers work, and the rewards match their intentions. No lab has the capability to "check in" on what the traces look like, unless some system alerts them (loss spike, crashes, etc). Other than that, it's prepare, train, asses, restart.
Then, the hf incident was during an eval run, but the model that was evaluated was trained with the notion that there is a way to communicate between agents, and re-popped artifactory and re-established communication. That phase had more chances of being spotted, but anyway... lessons learned.
I can’t disagree more strongly. Having checks for reward hacking is especially important during training, since it’s humans’ only real chance to ensure that the trained models don’t cheat. An automated system should have killed any RL rollouts that so much as port scanned Artifactory, long before the message board was even established.
A tiny, local LLM could have reviewed 1% of the tool call traces for anything that required review. I’ve tried it a few times, and “the agent port scanned Artifactory” always triggers an alarm, as does “the agent uploaded a request for assistance from other agents to Artifactory.”
The fact that they weren’t monitoring for reward hacking—even if they had no idea about the specific mechanism—is indescribably reckless.