I think i’ve only once flat out told one it was wrong about a specific assertion I quoted and it immediately was able to find its way to what I knew to be the correct claim.
I just wonder what would happen if i was in fact mistaken and I told it confidently it was wrong without elaborating
LLMs have no opinions. They are merely mathematical models that predict how an average person (mostly Internet people) might respond plus a little bit of invisible priming baked in to steer the behaviour a little (which is also easy to change yourself).
A lot of these chatbots, notoriously chatgpt, are heavily primed to pander to the user.
The pandering is really unnerving when you’re not used to it. I’ve used chatGPT only once and it was to edit my resume since I hate doing that. It helped with consistency and wanted active verbs in there which was fine. It was the constant compliments at the top of every response that was so weird. Like I’m asking for feedback, not to hear how wonderful of a writing job I already did. I felt like I was being handled like an oversensitive child.
I think a lot of people turning to these things essentially are over sensitive children in adult bodies
Give it a shot. They’re just sycophantic stochastic parrots anyway.
damn, you’re right
immediately folded and apologised on the first message

I don’t know why it needed to “think” about that for three seconds
Now ask it why it’s apologizing
Completely depends on context for the most part, approach them not as sovereign beings which follow their own perspectives and opinions but as advanced auto-complete, to test this merely ask it a question using niche terminology, identical question depending on the terminology you use will respond biased towards that opinion and perspective, you can get an LLM to admit to anything, to go along with every single thing you said like a blind yes-man or blindly object to every single thing you say even the most basic of facts merely off of how the context your chat has mapped most cloesly onto which parts of its training data for predicting text.



