YHK - yet another hacker news clone

I suspect that LLMs not being human allows people to not just anthropomorphise the robot, but they project themselves upon it. When someone speaks to the LLM, they're kind of, or actually just literally talking to themselves. But then something new! 'Themselves' suggests new information to themselves. And now without the scary / icky meat and blood human on the other side, said person accepts the argument on its own merits.

Of course, the concern now is arguments based on false or statistically hacked data.

More likely in my opinion it's the context that matters here. If people know they're trying to be convinced of something and know they're talking to an AI, they may feel like they can trust (what they consider to be) an unbiased and rational AI. There's probably a fallacy associated with the assumption that an AI convincer is more rational and fact based, while it's more probable that the AI in the real world is, in fact, funded and trained by a think tank that wants you to vote against your own self-interests.

It sounds like the arguments were basically AI slop hallucinations.

That whole episode caused the whole industry to shift away from RLHF, and towards RLAIF, RLVR, and DPO, and add a lot more safeguards, tests, and reward functions that push models in the direction of doing the opposite of what people want and confronting and strongly correcting their users, if it has determined the user is wrong.

I rarely disagree with my calculator, but I often ask LLMs to explain why they did something, and I sometimes need to correct them, adjust their assumptions and nudge the goals they stated. These things are a lot more like us than my trusty TI-59 (still going strong, BTW).

You're right. There are many many times when even then humblest hint that you are right will have negative interpersonal implications, which does make it hard to change minds.

I've also seen several times where I make a suggestion, humbly accept its rejection, and then, lo, a week later the other person has the same idea I suggested.

No it's not about humans being irrationally competitive. Human limitations on conversation length, bandwidth, research speed, etc are severe, creating a prisoner's dilemma around open-mindedness that usually makes it an unstable strategy. At any point, your conversation partner can choose to abuse the fact that confident lies take 1x effort to tell and 10x-100x effort to debunk -- unless you are both in a context that actually discourages this behavior, which is rare. Closed-mindedness is a Nash Equilibrium.

Instead, LLMs can be more persuasive due to economics. An LLM doesn't have to worry that it is wasting its resources trying to logic someone out of a position that they didn't logic themselves into, or worse, dumping the effort into a conversation with a bad-faith actor intent on exploiting the misinformation asymmetry. The resource allocation question was answered before it was even invoked, by the person paying to run it. The LLM is not playing a game where it will be punished for good-faith argumentation, so it can afford to do more of it.

It helps to think both are wrong and are just trying to figure out what right looks like, or what other information exists that was not considered when forming one’s opinions.

The problem with AI is that it cant match human stupidity. It need some training on artificial stupidity to match its human counterparts. Humans on the other hand sit on a wide spectrum on the stupidity scale. Those of us binging on AI will become cognitively obese while those on an AI diet can flex their cognitive muscles.

I wonder if a properly prompted LLM, or if a very intelligent LLM could actually do that?

The particular problem with honest discussions is you are the only agent that you can be sure is having one. Honest discussion is formulated on trust and trust, as we are learning, is a very difficult thing to establish. For example, in my view anything involving advertising is likely a lie, or at least likely adversarial to my wishes. On the internet itself conversations are much more likely to drift into the adversarial too. Some of this could just be dialectic, but most often it's emotional investment by the other speaker. Also, even pre-AI the internet is a bullshit generation machine. We take all of our politics, advertising, and human stochastic parrots that are stuck on an infinitely running prompt then bundle up all this data and train AI on it, and wonder why AI acts like us.

A lot of internet arguments become about identity politics and supporting the right team, while dismissing any argument from the other side as presumed to have bad intentions. I’ve seen people argue online for things they didn’t really believe, but they didn’t want to give an inch to the other side. Taking up the counter argument is a moral responsibility.

As soon as the other side is revealed as a chatbot that my team versus your team thinking stops playing a role. For us in tech with an understanding of how an LLM reflects its training data and the intentions of its creators not so much, but for the people like the example in this article I imagine it causes them to let their guard down and be open to considering the other side. They can accept the argument without letting someone else win any points.

Far too many screens to click through to get to the good parts.

And then, the good part starts and is immediately interrupted with some error. On retrying, o start getting a long answer which seems to make sense but o can’t read to completion because of another overlay which hides the bottom three-quarters of the response behind yet another nag screen about the research I’m supposedly consenting to.

I don't know which model underlies this. It responded more quickly than the models I normally use. It made the mistake I expected it to make, since this misconception is very common in training data, and conceded the point from my follow-up.

(EDIT: It appears that this link is not accessible to people without my cookies, except the developer I'm responding to above.)

My son wanted to wear his undies on the outside a la Captain Underpants and I tried war gaming this with him - hmm, so your undie on the outside is going to require another one inside your pants and we are out of fresh pairs etc etc. In the end, he gave up on the idea of mimicking Captain Underpants.