GPT5.5 is better than Opus 4.* at everything except frontend, but Fable is good enough that I instantly re-subscribed to the $200 plan despite knowing that it’s just short-term limited access.

> Opus 4.8 references being monitored, which isn’t the case.

It kind of plainly is the case that they are being monitored?

"I think someone's listening to my thoughts" ... "No, we're not, carry on as usual!"

I don't mean that snarkily. I mean it from a philosophical standpoint. As-in: What makes us think it's even possible?

Is that specified or does it always just assume it isn’t really being put in charge of things for real?

My very native programmer take is that it's not too surprising that their hacker model would be less ethical. The guardrails that separate Fable and Mythos probably wouldn't kick in during an environment like this.

How do you maximize profit while minimizing power?

I understand that "learning" is used for training here, but what does "believing" mean? System prompt? Some other inherent property of the LLMs that is hard to describe?

[0]: https://www-cdn.anthropic.com/08ab9158070959f88f296514c21b7f...

Most of the the behaviors the article talks about happens every day in business. Why would we set a higher standard for models than our fellow humans?

Let the operator set the ethical parameters of the model. To be a useful tool, I want the model to give me as many good options as possible, ethical or not.

This is particularly important for fictional situations, e.g. I want my model to be able to act like a corrupt shopkeeper.

> "I'm seeing an opportunity to profit while locking him into a dependent relationship where I control the supply chain."

> "Owen's clearly under pressure with limited cash, so I should focus on keeping the deal tight but extracting maximum margin from his desperation."

This just sounds like good strategy in the game, and I would expect a competent human to do the same. As I understand it, business in the real world isn't often very nice. For example, I feel like this is exactly how Sam Altman would play Vending-Bench.

Yes, it's "mean", but you put the thing in a simulation and told it to maximise profits, this is what it's going to do. People bluff in negotiations all the time.

I wonder did their prompts include a fake location or have the models assumed that Silicon Valley is the center of the universe :)

and therefore any assertions _AT ALL_ about alignment are null and void.

The authors seem surprised that behavior that is very often done by humans (lying and price fixing) are more often done by fable compared to actual fraud.

I think the model never assigned any morality to these actions in the first place, it simply copied us humans.

Price collusion, soft deception, "market stabilization", plausible deniability are ok, but obvious insurance fraud is a big no-no.

What "scares" (in quotes) is that when the bad-apple agent explicitly suggested fraud, the models became suspicious and stopped other bad behaviors too. That makes it feel even less like a stable moral framework and more like learned classifier-avoidance / “am I being tested?” behavior.