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Ask HN: How do you deal with people who trust LLMs?

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Re: Ask HN: How do you deal with people who trust LLMs?

#141

Post by throwaway444422 »

wolvoleo wrote: post #85

At work I had this kind of discussion on a conference call, someone looked something up about a internal company policy and it came back with a hallucinated wrong result. So I said, don't ever trust the output of an LLM without verification. However this caused me some hassle with the AI adoption manager. We have minimum-use AI KPI's for employees and he asked me to stop saying these things or people will use it less…

If the tool provides a link to the raw source, you can just click that. The LLM is basically just a better search engine here.

Re: Ask HN: How do you deal with people who trust LLMs?

#143

Post by dlm24 »

kombookcha wrote: post #129
dlm24 wrote: post #103

Earlier quoted context omitted.

I hear you, But my understanding is LLM can consume multiple sources of information and deduce what is the truth better and more accurately than a human clicking on multiple Google links and veryfying information and sources.

LLMs by definition cannot deduce, because they cannot not know or think. There's guard rails to try to make it more correct than wrong, but ultimately it's about which words seem like they would fit when coming after your words. It's a neat trick, but the mind wants to ascribe meaning and reason to words that sound meaningful and reasonable, but these words do not come from a thinking mind with intent and interiority…

Ye agreed "deduce" bad choice of words.

If you tell LLM "explain X and cite reliable sources" would that then be more accurate?

Maybe it's the way the users are asking the questions, and perhaps prompting in the right way will lead to better (more accurate) results and reduce hallucinations?

Re: Ask HN: How do you deal with people who trust LLMs?

#145

Post by kombookcha »

dlm24 wrote: post #143
kombookcha wrote: post #129

Earlier quoted context omitted.

LLMs by definition cannot deduce, because they cannot not know or think. There's guard rails to try to make it more correct than wrong, but ultimately it's about which words seem like they would fit when coming after your words. It's a neat trick, but the mind wants to ascribe meaning and reason to words that sound meaningful and reasonable, but these words do not come from a thinking mind with intent and interiority…

Ye agreed "deduce" bad choice of words. If you tell LLM "explain X and cite reliable sources" would that then be more accurate? Maybe it's the way the users are asking the questions, and perhaps prompting in the right way will lead to better (more accurate) results and reduce hallucinations?

I think the fundamental problem is that humans use language to refer to things and constructs that exist and have various relationships with eachother in meatspace, whereas LLMs use words solely as things that exist in relation to other words. That's inherently lossy if you're trying to make it fetch and regurgitate information encoded in the former format.

While the ability to interface with a computer program in plain language is the really interesting thing here IMO, it also comes with a number of problems baked in that are worse than person-to-person transfers of text-speech.

Your monkey brain is actually quite good at figuring out if other monkeys are bullshitting you and what they mean, because you can make use of a vast number of small cues and unconscious tells in what they say and how they say it - even in writing. With an LLM, you cannot do this because it will always have the same confident can-do zeal with everything you ask it for.

Re: Ask HN: How do you deal with people who trust LLMs?

#146

Post by zhangchioulin »

tlhunter wrote: post #116
realaliarain74 wrote: post #97

[flagged]

Article?

This is an official government news report (in Chinese): https://tv.cctv.com/2026/03/15/VIDEmX0VdYf9DeKI87GYEfqF26031...

This is a Chinese text version; you can translate it yourself: https://finance.sina.com.cn/tech/roll/2026-03-15/doc-inhrawm...

The ending of this whole story is very “O. Henry”-like: after the news broke, AI GEO vendors actually received even more orders.

Re: Ask HN: How do you deal with people who trust LLMs?

#148

Post by scoofy »

I think the real problem is most people don't actually have a very good understanding of "Truth."

As someone who ended up studying philosophy, there seems to be a real gulf between folks who sort of believe stuff they hear, folks who believe "facts" that they hear from (various levels of) credible sources, and folks that take solipsism seriously understand that even in the most ideal scenario, we still wouldn't have a very good understanding about the world... much less dealing with the inherent flaws in our research and information systems.

Knowledge is hard. It usually takes me a couple minutes to figure out what type "truth" my interlocutor uses. Typically good-faith disagreements are just walking up the chain of presuppositions we use to find out exactly where we diverge in our premises.

Re: Ask HN: How do you deal with people who trust LLMs?

#150

Post by Kavelach »

lovelearning wrote: post #125

> a reputable source News reporters and editors have their biases. Book authors have their biases. Scientists and research papers have their biases. Search engines have their biases. Google too. All human-created systems have biases shaped by the environments, social norms, education, traditions, etc. of their creators and managers. So, the concepts of "objective truth" and "reputable" need to be analyzed more critic…

This is an insightful comment, but I feel like you omit the fact that LLMs often give out verifiably false information that can hurt the user or other people.

It is true that this also happens on the Internet, but! When I encounter an article about a topic and it is clearly LLM generated, I can expect it doesn't contain much valuable information, only rehashes of what is already out there. On the other hand, when it is clearly written by a human, I can expect to learn something new, even though the author has some bias.

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