[Jensson]

> 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.

That just explains how to find facts for yourself, not how to deal with a person who trust LLM outputs. So you still haven't answered the question.

> Since the OP trusts humans more by default

OP never said that. OP said there is a problem with people trusting LLM instead of doing proper research and finding good sources, you explaining how to do proper research and finding good sources doesn't have anything to do with the question.

[lovelearning]

I gave suggestions that OP can pass on to the people they have to deal with. I didn't realize it has to be pointed out explicitly SO-style to some people.

OP implies human sources are the "good sources" or "reputable sources." This kind of confusion is exactly why I suggested using better terms than "reputable sources" or in your case "good sources."

[Jensson]

> OP implies human sources are the "good sources" or "reputable sources."

No OP did not do that, nowhere did OP mention human sources. When I search the internet I don't just find human sources, I also find automatically generated data graphs and maps and such, those are also good sources of data. If I had to choose between a map from Google maps and a map from an LLM I'd trust the map from google maps any day.

[lovelearning]

> automatically generated data graphs

Are you saying there are data graphs that don't have humans in the chain? If so, what came up with the data and the tools to generate those graphs? And how do you decide which data and graph to trust? What exactly makes them "good sources"?

> If I had to choose between a map from Google maps

I would too. But Google Maps relies on local 3d party survey companies that use people, manual GIS tools, and image recognition AI. How do you know they don't have any mistakes in them? In fact, I live in a country where local area names are frequently misspelled on Google Maps, and reverse geocoding gives misleading addresses.

I feel my point that all these "reputable sources" or "good sources" have biases (and mistakes) still stands.

I must also point out that the 3 concrete examples given against my replies all involved visual content like graphs, maps, Peanuts cartoons, etc. But my comments were written with the typical text-based usage for QA in mind. I don't know if LLMs can fact-check map imagery or data graphs (probably not, but I've never tried). It's just not the kind of thing I'd ever use LLMs for, to begin with.

[basilikum]

> I feel my point that all these "reputable sources" or "good sources" have biases (and mistakes) still stands.

That does not contend with the premise. The premise is not that reputable sources are perfect or form objective truth.

The premise is that when you do not have the time to investigate something closer reputable sources are much more likely to be close to the truth than LLMs that are trained on these reputable sources as well as unreputable sources and just mimick these training source material thereby obscuring the source of information and introducing hallucinations.

When you have the time to investigate information, primary sources and reputable secondary sources allow you to more easily trace information and judge its validity. LLMs by their nonpredictable nature hinder this.

Thesis: "A is better than B"

Argument: "A is flawed"

The argument does not engage with or weakens the thesis.