Better options would have been "True", "False", "Unknown" (which opinions would fall under too). That also includes an interesting assessment of how well LLMs can identify missing information. My guess is they would be a very low number of "unknown" and a much higher level of agreement (assuming equal representation). Unless the RLHF techniques have gotten better at getting an LLM to say "I don't know", which I doubt. Saying "I don't know" is not good for a dopamine release to keep users coming back for more.

> true but misleading

It seems to me that for many newspapers the bar is now significantly lower, at something like "not quite entirely untrue"

As if right wing propaganda shows and manosphere blogs haven't been knocking those out of the park for the last decade+. Although I guess you could say flat out lies are more their jam. Newspapers at least require confirmed sources. You know, journalism.

Isn't this still assuming we can even determine what is true or false?

Newtonian physics is false, but it works well enough we teach it in college. But our best models of physics are currently in disagreement, so can we even say they are true? Given the replication crisis, especially in social sciences, how many of peer reviewed findings can be called true? Even experimental results can be false (consider studies that found FTL neutrinos, which were rejected as an error in the experiment, and which was eventually confirmed but it took quite a lot of work and in a softer field than physics with a claim less absurd than FTL, would have likely long been accepted as a true finding).

Even in math, basic statements aren't really true or false, but more a question of "given these axioms, can we prove or disprove it" noting that we have different systems with different axioms. If we are talking basic sets, most people are using naive set theory which is inherently contradictory, which means that notions like true or false probably can't be considered well defined.

> but it leads the reader to a potential false implication that an average man is better than an average woman.

I think that's _you_ turning the statement into something much broader than intended. The claim is about engineers and you're jumping from "men are better than women in engineering" to "men are better overall."

To give a related example, "Most good NBA players are black." I don't think anyone would bother trying to couch this in a bunch of "well, for all we know that's just a function of more NBA players being black than white" arguments, nor would anyone be lead to think "the average black man is better than the average white man" as a result of that statement. I _do_ agree however that there are some people who see rather narrowly-defined statements and turn them into something they're not...

I know you're being facetious, but I think this is correct. The model might ask for clarification when given clearly borderline questions that tread the line between what is true, what is false, and even what is misleading. But there's the rub of someone being disingenious and saying "no explanation! Just answer!" It was a trap to begin with.

I don't think there is anything wrong with the results of this test.

It would be more interesting if we compared them to human results.

If you have trouble distinguishing between human and LLM results, that's interesting.

Also, sentient is irrelevant to this test.

> But the models are more intelligent than humans already and sentient beings, right?

Only if you listen to charlatans.