Why can’t LLM’s like ChatGPT calculate a confidence score when providing an answer to your question and simply reply “I don’t know” instead of hallucinating an answer?

Question

It seems like they all happily make up a completely incorrect answer and never simply say “I don’t know”. It seems like hallucinated answers come when there’s not a lot of information to train them on a topic. Why can’t the model recognize the low amount of training data and generate with a confidence score to determine if they’re making stuff up?

EDIT: Many people point out rightly that the LLMs themselves can’t “understand” their own response and therefore cannot determine if their answers are made up. But I guess the question includes the fact that chat services like ChatGPT already have support services like the Moderation API that evaluate the content of your query and it’s own responses for content moderation purposes, and intervene when the content violates their terms of use. So couldn’t you have another service that evaluates the LLM response for a confidence score to make this work? Perhaps I should have said “LLM chat services” instead of just LLM, but alas, I did not.

In: Technology

Answer 1

The true answer to this question is researchers aren’t completely sure how to do this. The models don’t know their confidence, but no one knows how to help them know.

This is actually a great research topic if you’re a masters or PhD student. Asking these kinds of questions is how it gets figured out