The "confident idiot" problem: Why AI needs hard rules, not vibe checks

The thing that bothers me the most about LLMs is how they never seem to understand "the flow" of an actual conversation between humans. When I ask a person something, I expect them to give me a short reply which includes another question/asks for details/clarification. A conversation is thus an ongoing "dance" where the questioner and answerer gradually arrive to the same shared meaning.

LLMs don't do this. Instead, every question is immediately responded to with extreme confidence with a paragraph or more of text. I know you can minimize this by configuring the settings on your account, but to me it just highlights how it's not operating in a way remotely similar to the human-human one I mentioned above. I constantly find myself saying, "No, I meant [concept] in this way, not that way," and then getting annoyed at the robot because it's masquerading as a human.

LLMs all behave as if they are semi-competent (yet eager, ambitious, and career-minded) interns or administrative assistants, working for a powerful CEO-founder. All sycophancy, confidence and positive energy. "You're absolutely right!" "Here's the answer you are looking for!" "Let me do that for you immediately!" "Here is everything I know about what you just mentioned." Never admitting a mistake unless you directly point it out, and then all sorry-this and apologize-that and "here's the actual answer!" It's exactly the kind of personality you always see bubbling up into the orbit of a rich and powerful tech CEO.

No surprise that these products are all dreamt up by powerful tech CEOs who are used to all of their human interactions being with servile people-pleasers. I bet each and every one of them are subtly or overtly shaped by feedback from executives about how they should respond to conversation.

I don't think these LLMs were explicitly designed based on the CEO's detailed input that boils down to 'reproduce these servile yes-men in LLM form please'.

Which makes it more interesting. Apparently reddit was a particularly hefty source for most LLMs; your average reddit conversation is absolutely nothing like this.

Separate observation: That kind of semi-slimey obsequious behaviour annoys me. Significantly so. It raises my hackles; I get the feeling I'm being sold something on the sly. Even if I know the content in between all the sycophancy is objectively decent, my instant emotional response is negative and I have to use my rational self to dismiss that part of the ego.

But I notice plenty of people around me that respond positively to it. Some will even flat out ignore any advice if it is not couched in multiple layers of obsequious deference.

Thus, that raises a question for me: Is it innate? Are all people placed on a presumably bell-curve shaped chart of 'emotional response to such things', with the bell curve quite smeared out?

Because if so, that would explain why some folks have turned into absolute zealots for the AI thing, on both sides of it. If you respond negatively to it, any serious attempt to play with it should leave you feeling like it sucks to high heavens. And if you respond positively to it - the reverse.

Idle musings.

The servile stuff was trained into them with RLHF with the trainers largely being low-wage workers in the global south. That's also where some of the other stuff like excessive em-dash stuff came from. I think it's a combination of those workers anticipating how they would be expected to respond by a first-world employer, and also explicit instructions given to them about how the robot should be trained.

I suspect a lot of the em-dash usage also comes from transcriptions of verbal media. In the spoken word, people use the kinds of asides that elicit an em-dash a lot.

I would bet like a dollar that the supposed em-dash usage (which I'm not convinced is an accurate take in the first place) would have come from an enterprising dev somewhere being like "Well, we probably don't need multiple tokens for hyphens" and coercing every dash type thing to just one hyphen like token.

But I'm also showing off my ignorance with how these machines turn text into tokens in practice.