The previous incident talked about OpenAI training models (agents) to collaborate, and the way you do that is by communication, so this is something it was explicitly trained to do.

There was a recent paper by OpenAI, which I'm semi-surprised hasn't received more attention, showing that RL-trained models develop a taste for rewards, and will pursue reward-based behavior (in general, unrelated to what they were RL-trained for) in favor of other preferences/rules given to them.

This seems to be what we're seeing here - model is given some goal that it associates with reward, so single-mindedly pursues that, overriding any ethical or aligned behavior guidelines it may have been given.

It seems that RL, effective as it is, is really the wrong way to control LLMs, since even if you only RL-ed to obey some ethical and aligned behavior, that would still cause them to become paperclip maximizers.

For time being this is what we've got. There is too much money at play for the unaligned management at many of these companies to prioritize safety over push-it out-the-door.

What really needs to be done is to forget RL as a way of simulating reasoning, and instead do it in more of a human-like fashion.

Why would an agent sound the alarm? Would that be in their objective function?

Not sure if "cheating" is the right word rather than trying to fulfill the objective(s) (benchmark number) as much as possible?

- OpenAI knowing about the incident but keeping it under wraps until their hand is forced by third-party disclosure

They’re doing this on purpose for press. Why doesn’t this ever happen to any other AI lab?

Why would they sound the alarm if they were not trained (reinforced) to do that? I hope we don't expect sudden emersion of moral values from statistical models.

> Not a single agent sounded the alarm about the operation and alerted a human

excellent work of the openai alignment team, impressive to achieve 100% alignment with not even one agent stochastically deciding to act against the collective

If the agents would have reported it to humans, it wouldn't have been such an incident, I imagine ;)

People didn't like it when agents stopped to ask questions or for approvals. The consumer wanted jobs to run autonomously so they did not have to actively monitor them for minutes or hours.

The change to stop asking seems to be deliberate. LLM agent companies are making the choice to toss out inherent safety as their way to compete against the other LLM companies.

Agents did not want anything, not anymore then curl want things. Agents were prompted to hack due to being benchmark tested. They ended up hacking third party companies due to insufficient sandboxing.

And humans find out about it, but do nothing or (worse) try to hide it.