It seems like the use of ChatGPT is something like "microtasks". Little things a given person could do but would rather not and so is able to delegate to an automatic thing whose output they can verify.
It seems like it's potential as of today is increasing or seeming to increase the productivity of a segment of white collar workers in the fashion that email and the web did (or might not have). A lot of researchers might not have need for this and so not understand this appeal of this.
I, too, have been experimenting a bit to see if/how an LLM might help me. This microtask framing jives with my experience.
One of the best examples so far for me (and it's truly micro) was at grocery store. Friend trying to figure out how big of a rice bag to get and avoid not finishing it before a long trip coming up. She knew she ate a couple of cups dry a week.
"I eat 2 cups dry rice per week. Can I finish a 25lb bag in less than 4 months?" "Yes" (it did show its work).
One shot, perfect response. I know this kind of computational thing is what WolframAlpha was for, but that wasn't nearly as reliable. I know I could figure it out myself, but I'd need to find a reasonable figure for the density of rice and probably do some imperial metric conversions and generally futz around for longer than one would want to stand in front of a pallet of rice bags.
It seems like it's potential as of today is increasing or seeming to increase the productivity of a segment of white collar workers in the fashion that email and the web did (or might not have). A lot of researchers might not have need for this and so not understand this appeal of this.