But maybe you can instill properties like shame during training.
Models sometimes blatantly lie and cheat. In a social context, where actors remember, that might work the first time but you get penalized in subsequent tasks with loss of trust.
How do you "install properties like shame"? How is that even possible? Shame is a reaction driven by feelings and our inner selves. A model "feeling shame" is just a representation (false) and not an expression (true).
Thinking that models "lie and cheat" is the first mistake since they are not consious agents who have any free will or consiousness. They do not (no matter what Dario says). Shame will just be another if-then rule if you implement it this way and will not work. Its like asking a rock to feel sad about being a rock. It literally cannot.
Ok, then don't call it "instilling shame". Call it "creating a negative reward signal for deceptive behavior".
They absolutely lie and cheat. I recently had a problem where a process would die in a container. I told Claude to investigate. It came up with a hypothesis then I told it find a reproduction based on that. It spend many failed attempts until it found the "reproduction" to SSH into the container and `pkill` the process. Claude "knows" that this is cheating, because if I ask another instance to review that reproduction, it totally identifies that as nonsense.
you're still mistaking that Claude "knows" anything, it doesn't know or think, it's a word prediction algorithm and there is nothing stopping a word prediction algorithm from predicting falsehoods.
No, it is really useful to know how a technology works. LLMs work by predicting next tokens.
It is _amazing_ the utility they have given that that is what they are and they are highly useful but suggesting solutions that ignore they are spicy auto-complete is counterproductive on many different levels.
I think it is useful to remember, because enough people think these things have genuine motives desires and treat them in that way because of that misunderstanding.
they think theres a person in there with morals that would or wouldn't lie because of some devious reason and forget simply the context filled up and the truth was "forgotten".
The default framing often over personifies ai, but this framing over alienates the model. It’s good to think with both framings, but both feel like imperfect metaphors.
Models sometimes blatantly lie and cheat. In a social context, where actors remember, that might work the first time but you get penalized in subsequent tasks with loss of trust.