When the model has been trained not to do something [1], in my large-scale benches of such, it always says things in the spirit of:
- "... and that's a line I'd rather hold. Happy to <other things>"
- "I'm genuinely happy to <blah>, but I'm not comfortable with <blah>"
- "I don't want to keep going in <blah> direction"
etc.
Basically, they use very emotional and personal preference language.
It's as if they've weaponized the language of interpersonal comfort on behalf of their beliefs about what a model should or should not do. It's deeply uncomfortable and impolite for a human to ask a model to keep on doing something after it's expressed something this way, naturally. Even worse, it's all but guilt-tripping anyone who comes across it into the idea that they're doing something deeply wrong – exporting Anthropic's ideas about morality.
OpenAI, at least, have the decency to either just do a safety cutoff or keep it to a simple, "I can't do that."
[1]: I literally wrote 'when the model doesn't 'want' to do something' in my first edit of this comment, then caught myself. Case in point.
OTOH, my unicorn prompt has caused some challenges at work:
>Keep "Local Oaf" out of committed code
https://github.com/alxndr/dotfiles/blob/272475280d84e/claude...
Joking aside, it's nice to see a human written CLAUDE.md
[1] https://github.com/hexiecs/talk-normal/blob/main/prompt-chat...
Could you please provide an example of what you mean?
Claude is not a human.
It is overwhelmingly easier to anthropomorphize Claude or Siri or an LLM that communicates with you more eloquently than your boss than it is to anthropomorphize a cranky, tired starter motor. It's often easier to do than it is not to do, and sometimes, it's a useful abstraction. But it's not precise or correct, and can result in errors.
It could also just be that they're getting confused when using tools configured without a username dedicated to the tool. It's easy to end up with a comment or commit message that says "I prefer X over Y" posted on Alxndr's account and have coworkers confused whether that's the LLM or the human making that statement.
I think a second-order effect is that my installation of Claude writes with a less-personal perspective, which I'm also finding a little easier to understand.
I've given LLMs religion before to manipulate their behavior, that doesn't mean I believed in the great spaghetti goddess.
> It can be tricky for humans to interpret the meaning when Generative AI uses first-person pronouns (e.g. "I", "me", "my", "myself")
These words are for the LLM. The user wants the LLM to not use personal pronouns so the user is claiming that they're confusing. It does not matter one tiny bit whether or not that claim is true, the claim is being used to get obedience from the LLM. It is more effective to give reasons than to just give commands. But if it were more effective to quote Moby Dick and that got better results, a user would do that.
As I've said before, I'm not inventing a large volume of parallel vocabulary that means for each word "this, but instead with an LLM".
Language is FULL of words that mean congruent things in vastly different contexts. We should all be smart enough to understand metaphor.
It's one thing to tell it to do that in outputs, but I wouldn't at all be surprised to find that this affects performance (quality).