"AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct."

https://artificialanalysis.ai/evaluations/omniscience

See, this, to me, seems obvious, but I’m sure it’s more challenging/complex than I can imagine (I am NOT an expert on AI in any way imaginable). But there has to be a solution. Just yesterday I was asking Gemini to tell me about a certain college professor, and it gave me a list of facts about them. And it was perfect. Then, out of curiosity, I followed up with “tell me more about him!” and it spit out several more bits of information about this person that were entirely hallucinated (e.g., gave them credit for writing papers they didn’t write, said they won awards that actually someone else won). I know this is all complex and certainly beyond my limited skill set, but goodness, we’ve got to get this figured out with so many people depending on and trusting these things nowadays. It’s quite scary.

Maybe some extra buckets could be added like depending on whether the answer ought to be known. Or, quality of the justification. “I don’t know and here’s a good reason why” is much better than “idk.” Correctly identifying that something is fundamentally unknown/unknowable is probably better than a simply-correct answer, even, right?

It should be -1, -.1, 1 because I don't know is slightly negative.

And also because it creates "one neat trick" where it can answer "I don't know" for many/most things and still get credit.

> In real life a wrong answer is much more damaging than a don't know.

I don't know. Is it?