My conceptual understanding of language model sycophancy is something like this:

These language models are predicting the most likely conclusion in a context.

The most likely conclusion in most linguistic contexts is more like agreement than like argument, because most uses of language are not argumentative or contradicting (including most uses of language in corpora that language models would be trained on).

This is especially true for things like an assistant persona, or really for almost any dialogue that isn't framed as a "debate" or "argument".

(And outside of the conversational context, if you're just completing sentences or paragraphs, you normally complete them consistently. If we say "I support the Indian position on Kashmir because ____", we expect that the sentence will be completed with reasons that support that position; if we say "I support the Pakistani position on Kashmir because ___", we expect the sentence will be completed with different reasons. We don't really expect the sentence to end "actually I don't, I was just pretending to, but now I have repented and will tell you the opposite".)

In academic-style or classroom-style discussions there's also a common pattern of a teacher Socratically adding considerations that the student needs to take into account somehow. Language models could also be picking up on this dynamic and saying "I'm being tested, so I have to show at least some respect to the opinions or suggestions of the interlocutor, who is testing me; I won't do well on the test if I simply attack or contradict those suggestions".

Like in a physics class, if the teacher says "but ... did you consider the electromagnetic interaction?" it's much more likely that the electromagnetic interaction will be relevant somehow, and was previously neglected by the student, than that the teacher is either confused or trying to get the student to reject the suggestion. You would find many more academic dialogues in which the student then says "oh, well, let me think about how the electromagnetic interaction could matter" than those in which the student says "no, there is no electromagnetic interaction to consider here". (At higher levels where it's not assumed that the teacher already knows the answer and the student doesn't, this might not be true.)

Maybe other factors include

* There isn't exactly a "superego" saying that other people will punish you later in another context if you express/agree with/fail to contradict an unpopular, stigmatized, minority, or obsolete opinion. In real conversations, we may be afraid at some level that if we agree with a "bad enough" opinion we will "look bad" to others (including looking foolish, gullible, or sycophantic). ("Oh no, what if my mom heard me say that?" "Oh no, what if my teacher heard me say that?") Perhaps RLHF can create something a little bit like a superego (if I say this, I'm afraid that my reward will decrease!), but it may not work very much like the human superego does.

* If you believe that the other party is following Gricean maxims (like relevance!), you're going to try to find a way that the other party's statement is useful. Maybe this is just another way of saying that most examples of conversations are usually cooperative.

This isn't particularly technically informed; I'd be glad to hear about reasons why these issues aren't actually a good description of LLM behaviors.