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Comment by ValentineC | Hacker News Reader

I think Wikipedia's still considered unreliable, but the question that should be asked is whether the author even read the source in "the number in brackets" to ensure that it's even backed properly.

Just like how people should use AI for research, I guess.

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When i comment that i've researched using AI this way, it short circuits the brain of the listener/viewer and suddenly my sources aren't valid.

a bing or google or wiki search to get the primary or secondary sources are okay, but if i use chat.deepseek.com instead, suddenly it isn't okay.

This is just human behaviour though. We're wired for "a lot of people who do X, also do Y". "this person does X, therefore they must do Y". Obviously, not all brown things are cows, but that's how it be, it's got nothing to do with ai.

LLMs routinely hallucinate sources. I guess that's why some people feel that way.

LLM assisted search is now one of the best ways to look into dense and obscure topics though, particularly given as google search quality has degraded. All it needs is for you to read the sources.

Source hallucination has also come down tremendously.

Right, but is there a difference between searching, say "acetaminophen and ibuprofen combined in emergency department settings" on google/ddg and asking an AI to give me primary sources for the same - if i am going to use the primary source anyhow? I just mention "i used AI to find this" because usually there's no good way to do a google search, or there wasn't the last time i tried.

For example, is glyphosate the active ingredient in roundup? there are studies that suggest not. I can't remember the university, i can remember the rough decade (2010s). all i know for sure is that someone showed that glyphosate isn't the active ingredient, really.

Deepseek can't find it. ddg doesn't come up with it immediately. I might try "deep think" mode on some other AI later, or use an older LLM model i have locally to see. I have the pdf, i just didn't rename it to be searchable! doggone it.

Imagine that this website has a million visitors but just 100 rabid fans of one position. Imagine you read a comment. The website UX does not allow you to differentiate whether this is a person who is obsessive about one position or not. It doesn’t tell you whether you’re going against the consensus or not. So a small group of 100 users could create a bubble of visibility of a certain position. They could ensure you’re always voted down when you express a position.

You would never know.

The voting ring mechanic is hard to block but the comment mechanic is easy. Block a few hundred users and suddenly this site starts having much higher SNR.

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