I had a convo with a senior CS prof at Stanford two years ago. He was excited about LLM use in paper writing to, e.g., "lower barriers" to idk, "historically marginalized groups" and to "help non-native English speakers produce coherent text". Etc, etc - all the normal tech folk gobbledygook, which tends to forecast great advantage with minimal cost...and then turn out to be wildly wrong.

There are far more ways to produce expensive noise with LLMs than signal. Most non-psychopathic humans tend to want to produce veridical statements. (Except salespeople, who have basically undergone forced sociopathy training.) At the point where a human has learned to produce coherent language, he's also learned lots of important things about the world. At the point where a human has learned academic jargon and mathematical nomenclature, she has likely also learned a substantial amount of math. Few people want to learn the syntax of a language with little underlying understanding. Alas, this is not the case with statistical models of papers!