Andrew Heiss 
Finally created an official policy for AI/LLMs in class, both for writing and for coding (https://datavizf24.classes.andrewheiss.com/resource/ai-bs.html)
And the coding side of things (https://datavizf24.classes.andrewheiss.com/resource/ai-bs.html#what-about-code)
Sharon Machlis@andrew Isn't mean(x, na.rm = TRUE) accurate R code?
@smach Yep, it is, but it's unusual to see it on students' very first exercise before we've talked about it or covered it
@smach Like, that's all completely valid code and it works, but they're learning tidyverse-flavored R, so it's unexpected to see read.csv, and the print() is superfluous, etc. I typically get 50% of assignments with that identical code, thanks to ChatGPT
Ken Butler has moved@andrew @smach I point out that the code students produce needs to be the code that I talked about in lecture, and I don't talk about read.csv at all (and not about na.rm in mean() until later), so they are *wrong* in the context of my course. (I started doing this during covid, when I wanted some evidence that the students were actually learning from me and not from some guy on chegg.)
@andrew @smach this I think is the key observation: students learning the stuff don't have enough baseline knowledge to understand whether the stuff coming back from chatgpt (or google or chegg) is any good.
I make a point that everything in my courses can be done using the course materials, with the exception of a few places where I explicitly ask students to look up something and report back on what they find (with a citation to where they found what they were looking for).