Ask HN: How do you deal with people who trust LLMs? • Hacker News Board

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

#161

Post by lovelearning » Thu, Mar 19, 2026, 10:20 AM UTC

Kavelach wrote: post #150

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…

You're right that LLMs do spit out false information or wrong knowledge. I've experienced them too.

But a redeeming quality is that we can ask the same LLM to fact check its own answer step by step in real time with little effort. They often identify their own hallucinations and reduce the probability of retaining that mistake in the rest of the conversation.

This isn't easy with human sources. The effort to fact check without LLMs or ask the sources to fact check themselves are both higher. So it's often not done at all.

We also often ignore subtle but very common biases in human media sources [1], which create other types of errors like omissions and euphemisms which have been no less harmful than LLM hallucinations. The case of the Iraqi WMDs of Iraq and the NYT's dispersal of that disinfo, for example [2].

Regarding valuable information and rehashing, we probably shouldn't equate between all the things LLMs can do, and AI-generated articles. The quality of the latter may be entirely due to the lack of interest, attention, and cost concerns of whoever generated the article. Anecdotally, I have often found valuable knowledge and obscure connections by using deep research tools with careful prompts.

Lastly, if you're frequently finding something new from human-written sources, and LLMs are being trained on most of those same sources, isn't it logical that the latter will also likely output that same information?

This is why I feel human and AI sources are probably best used as complementary tools. Neither set of sources are perfect but each set has its strengths. By using both, we can get closer to an objective truth than using only one of them.

[1]: https://gipplab.uni-goettingen.de/wp-content/uploads/2022/04...

[2]: https://www.theguardian.com/media/2004/may/26/pressandpublis...

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

#162

Post by lovelearning » Thu, Mar 19, 2026, 10:41 AM UTC

Yizahi wrote: post #159

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…

Ironically, this is the classic bias of "bothsiding" the issue. When one side is clearly wrong, just sprinkle in some "look, the others are doing something bad, which means they are equally wrong". A basic lesson from the propaganda manual.

I know what you mean, and I realize some of the things I've written sound similar to what various rightwing commentators tend to say (e.g.: "concept of objective truth must be analyzed critically.")

But my motive is very different. It's not to deny any kind of injustice or misinformation by hiding behind inherent uncertainties and bothsidesism. I'm not in favor of giving the benefit of the doubt to the powerful by default - that's already happening a lot under our current system of so-called "reputable sources."

Instead, I'm saying that this kind of injustice masking and misinformation may also be present in the very sources that ethical people may have come to trust by habit.

My suggestion is to use the power of LLMs as complementary tools to become even more rational and critical, in the direction of even better ethics and justice.

I'm advocating for even more skepticism of the powerful, not less. I'm advocating the approach Betrand Russell recommended for acting under uncertainties, and feel LLMs can be useful complementary tools for doing just that.

[1]: https://archive.org/details/in.ernet.dli.2015.462628/page/n4...

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

#163

Post by braebo » Thu, Mar 19, 2026, 10:49 AM UTC

ahofmann wrote: post #139

mkozlows wrote: post #121

Earlier quoted context omitted.

ChatGPT thinking models are very good; the instant model is bad. Gemini is always desperate to find an answer, and will give you one no matter what.

I have access to the ChatGPT account of my boss and it is unusable sycophancy slop, horrible to read because every information is buried under endless emojis and the like. And it is almost indistinguishable if the LLM is wrong or right, every answer looks the same, often with a "my final answer" at the end. It's a mess. I'm using Claude Opus 4.6 and it is much calmer, or "professional" in tone and much more informati…

Thank you for saying this.. ChatGPT is SO BAD. I suspect anyone that says OpenAI models are good are either lying or botting.

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

#164

Post by lovelearning » Thu, Mar 19, 2026, 10:52 AM UTC

ndsipa_pomu wrote: post #156

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…

Whilst chasing after "objective truth" is a philosophical problem, it's clear that some statements are more correct and true than others. News articles are often biased, but most of the time, the bias is from the choice of what is reported and choosing specific language to push an interpretation (e.g. reporting road traffic collisions as "accidents" to downplay them or depersonalise them by stating "car hit tree" rat…

I agree about how these biases happen.

However, omission and downplaying can also be harmful just like hallucinations. One redeeming quality of LLMs is that we can ask the same LLM to fact check its previous answer and they do tend to correct most of their mistakes themselves. Something we can't do with media sources, and usually don't try either.

LLMs along with existing sources can be good complementary tools for getting even closer to an objective truth than relying on either one by itself.

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

#165

Post by Jensson » Thu, Mar 19, 2026, 11:00 AM UTC

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…

How does this answer the question: "how do you deal with people who trust LLMs?"? Nothing you are saying explains how to deal with such people.

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

#166

Post by Jensson » Thu, Mar 19, 2026, 11:06 AM UTC

JuniperMesos wrote: post #108

roguechimpanzee wrote: post #30

I think LLMs are fine for a "first pass" on a topic, but if I am researching something, I want a primary source rather than just the LLM-generated output. Do they have the primary source?

No different from what people said about Wikipedia when it was new (and justifiably so). How should one deal with people who trust Wikipedia?

Studies showed wikipedia was about as accurate as encyclopedias, so that fear was already debunked. That is not true for LLM, LLM are much less accurate than encyclopedias still since there is no limit to how far you can push them while encyclopedias and wikipedia stay in domains where they are still mostly accurate.

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

#167

Post by basilikum » Thu, Mar 19, 2026, 11:12 AM UTC

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…

> Is Google search engine that leads to NY Times or Fox News or Wikipedia and makes us manually choose sources as per our biases "better" than Google's Gemini engine that summarizes content from all the above sources and gives an average answer?

If you use just any amount of critical thinking, yes. Truth and objectivity are ideals, not practical states. LLMs are a very bad way to come close to this ideal. You may use them as a search interface to give you sources and then examine the sources, but the output directly is a strict degeneration over primary or secondary sources that you judge critically.

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

#168

Post by lovelearning » Thu, Mar 19, 2026, 11:16 AM UTC

Jensson wrote: post #165

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…

How does this answer the question: "how do you deal with people who trust LLMs?"? Nothing you are saying explains how to deal with such people.

I felt the question is based on some shaky assumptions that may lead to a poor answer.

Since the OP trusts humans more by default, is it a problem if I point out those assumptions? Ask HN need not become another SO.

I did explain the weaknesses of both LLMs and "reputable sources" and suggested people use them as complementary tools. I also suggested using the convenient self-fact-check feature of LLMs, something we can't do as easily with traditional sources.

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

#169

Post by ndsipa_pomu » Thu, Mar 19, 2026, 11:16 AM UTC

lovelearning wrote: post #164

ndsipa_pomu wrote: post #156

Earlier quoted context omitted.

Whilst chasing after "objective truth" is a philosophical problem, it's clear that some statements are more correct and true than others. News articles are often biased, but most of the time, the bias is from the choice of what is reported and choosing specific language to push an interpretation (e.g. reporting road traffic collisions as "accidents" to downplay them or depersonalise them by stating "car hit tree" rat…

I agree about how these biases happen. However, omission and downplaying can also be harmful just like hallucinations. One redeeming quality of LLMs is that we can ask the same LLM to fact check its previous answer and they do tend to correct most of their mistakes themselves. Something we can't do with media sources, and usually don't try either. LLMs along with existing sources can be good complementary tools for g…

I disagree as hallucinations can be drastically far more harmful or misleading than bias.

The problem as I see it is that LLMs perform a type of lossy knowledge compression. Also, the data on which they're trained will typically be the biased articles, so they're unlikely to be any better and very likely worse as they will encode the biases. I don't really see LLMs as being complementary tools as they're more of a summation/averaging tool - like comparing an original painting with a heavily compressed JPEG of that painting. (Of course, having access to a huge library of JPEGs is often more useful than just owning a single painting)

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

#170

Post by dalke » Thu, Mar 19, 2026, 11:18 AM UTC

lovelearning wrote: post #161

Kavelach wrote: post #150

Earlier quoted context omitted.

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…

You're right that LLMs do spit out false information or wrong knowledge. I've experienced them too. But a redeeming quality is that we can ask the same LLM to fact check its own answer step by step in real time with little effort. They often identify their own hallucinations and reduce the probability of retaining that mistake in the rest of the conversation. This isn't easy with human sources. The effort to fact che…

The effort to fact check with LLMs is also high. Here's one from a few days ago.

Someone used AI to generate an image in the style of a Charles Schulz Peanuts cartoon.

Someone else observed that there were 5 fingers on the characters, and quoted as Google AI as saying “Charlie Brown, along with other Peanuts characters, is generally depicted with four fingers on each hand (three fingers and one thumb) ...”

Yet if you go to the Wikipedia entry at https://en.wikipedia.org/wiki/Peanuts you'll see the kids have 5 fingers. Or take a look at the actual cartoons. Or read the TVTropes entry https://tvtropes.org/pmwiki/pmwiki.php/Main/FourFingeredHand... under "Comic Strips".

Fact checking this with human sources is easy and not ambiguous. While LLMs are being trained that many cartoon characters only have a thumb and three fingers - it is a trope for a reason - so isn't it logical for LLMs to give the wrong answer for a comic where the human characters are actually drawn with 5 fingers?

My experience with LLMs is they keep getting things wrong, when details matter.

Do you ask the LLM to fact check everything? (In which case, why isn't that part of the standard prompt?) Or do you only ask to fact check things where you are unsure about the answer? (In which case, is it the algorithm telling you what you want to hear?) When do you stop the fact checking?