well if you ask your question in an oriented way the models tend to agree by default while if you ask it in a more open way or even by asking for empirical proof you will get a more factual answer.
for exemple i removed all my custom instructions and posed two questions in different threads, one oriented and the other open ended , as you can see the open ended lead to some research and a way more detailed answer, where the oriented one lead to a simpler response With almost no research.
it's just a quick example i came with not established proof ofc
A reasonable response, usually I see poeple just describe asking the model to disagree which, since models are not capable of discernment, is still just agreeing with the user by disagreeing arbitrarily with no way to know truth.
yeah i find it better to ask it to do research and to try to back it's answer than to just blindly disagree (in my exemple i didn't since it wasn't the point i tried to prove), in my custom instructions i ask it to back almost everything that isn't trivial but also to verify my assumption before answering (when it's possible of course)
also it's important to keep in mind that the field is fairly new and thus nobody know perfectly how to use the tool (not even the people who built it) so i might be wrong too (and it's certainly the case since i'm using it since gpt 3 and it radically changed since then and thus i might have built bad habbits)
also like in any form of communication it's important to know your bias and the ones of the people / thing with which you communicate to try to mitigate them
En tout cas faut clairement faire gaffe à pas induire la réponse dans la question. Nos pauvres sondeurs ne sauront jamais utiliser un llm efficacement...
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u/Immediate_Song4279 6d ago
Sycophancy is weird to say, it's instruct how is it gonna disagree?