Much more likely is that it would hallucinate a plausible sounding but incorrect answer and send intermediate and junior engineers on a wild goose chase
if an LLM is capable enough to be used this way it would be used to generate scenarios for the people who would otherwise have to be the ones to generate them. those people would then evaluate the scnearios. those people would then be in a position to decide if the LLM saves them time.
I was saying that an AI would more likely hallucinate an incorrect answer than correctly diagnose the root cause failure. At no time was I comparing an AI to a human, thats the bit you made up.
The knee-jerk reaction to pointing out any failure modes of AI with, "but meatbags bad!" is a tiring strawman to deal with. It immediately turns the discussion into something else.
So, your message is "Unspecified AI models with or without additional training aren't ready to do aerospace fault analysis and they can lead experienced engineers astray." OK, it might or mightn't be true depending on the free parameters in your statement.
I used the word "likely" meaning there is a chance, your re-phrasing of what I said into a certainty ... and then refuting that certainty, is another textbook strawman argument, you made the same logical fallacy again.
Also I said "intermediate and junior" engineers - meaning INexperienced engineers, not experienced ones, so you quoted me wrong in that part too.