We put 2 + 2 in our calculator, we get 4. We've spent decades pushing computers as accurate. Making them accurate. We trust the machine and the process to give us the right answers when we put in the right data.
So when we disagree with the computer, we doubt ourselves.
Being confidently incorrect can still convince the masses.
When disagreeing with a human, it's very easy to view it as a competition. One is right, one is wrong - the one who is wrong is the loser. To change your mind is to be submissive to the other. I exaggerate, but I think we all feel this way at some point or another. It's why political arguments at Thanksgiving get heated. It's the fact that there's people who think something different, and think YOU'RE wrong - and vice versa! With a model, there's no person to get upset with, or to feel competitive with - to muscle for rank - or to temper your affection for while wanting to correct them.
The AI is only interacting because you asked, and clearly has no emotional stake in winning the argument. To change your mind in this context isn't to lose a contest. This makes it much more palatable to read rebuttals to your ideas - not to mention the tone and style seek to avoid offense to the reader as much as possible.
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.
Ask a Democrat or Republican to sit down and ask a chatbot, something it will answer contrary to.
And yes, both teams are wrong about things.
Do you firmly believe they will change their mind? Or will they claim the stats are wrong, or that the AI leans one way?
Facts (2+2), don't need a mind change. Ideas which are grey, abstract, are not going to be changed, and all research indicates that political mindset is almost indelible.
The movie "Don't Look Up" was a comedy built upon this truth.
The biggest problem with using LLMs is that it prevents you from going _outside_ the distribution. It always flattens. It can be fixed but that's how it works today.
As an example, take something that the world converged on today that is incorrect and ChatGPT will agree with it. In a few years when society changes, chatgpt changes along with it. It doesn't do first principles analysis.
It's good to see this studied, but this should really be more obvious.
zasz•12m ago
tolugenius•8m ago
hsnv•6m ago
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.