A Massachusetts couple claims that their son’s high school attempted to derail his future by giving him detention and a bad grade on an assignment he wrote using generative AI.
An old and powerful force has entered the fraught debate over generative AI in schools: litigious parents angry that their child may not be accepted into a prestigious university.
In what appears to be the first case of its kind, at least in Massachusetts, a couple has sued their local school district after it disciplined their son for using generative AI tools on a history project. Dale and Jennifer Harris allege that the Hingham High School student handbook did not explicitly prohibit the use of AI to complete assignments and that the punishment visited upon their son for using an AI tool—he received Saturday detention and a grade of 65 out of 100 on the assignment—has harmed his chances of getting into Stanford University and other elite schools.
Yeah, I’m 100% with the school on this one.
to be fair, understanding something well enough to automate it probably requires learning it in the first place. Like obviously an AI that just tells you the answer isnt going to get you anywhere, but it sounds more like the user you were replying to was suggesting an AI limited enough that it couldnt really tell you the answer to something, unless you yourself went through the effort to teach it that concept first. Im not sure how doable this is in practice, My suspicion is that to actually be able to be useful in that regard, the AI would have to be fairly advanced and just pretend to not understand a concept until adequately “taught” by the student, if only to be able to tell if it was taught accurately and tell the student that they got it wrong and need to try again, rather than reinforce an incomplete or wrong understanding, and that theres a risk that current AI used for this could instead be “tricked” by clever wording into revealing answers that its supposed to act like it doesnt know yet (on top of the existing issues with AI spitting out false information by making associations that it shouldnt actually make), but if someone actually made such a thing successfully, I could see it helping with some subjects. I’m reminded of my college physics professors who would both let my class bring a full page of notes and the class textbook to refer to during tests- under the reasoning that a person who didnt understand how to use the formulas in the text wouldnt be able to actually apply them, but someone who did but misremembered a formula would have the ability to look them up again in the real world. These were by far some of the toughest tests I ever had. Half of the credit was also from being given a copy of the test to do again for a week as homework, where we were as a class encouraged to collaborate and teach eachother how so solve the problems given, again on the logic that explaining something to someone else helped teach the explainer that thing too.
You worded this much better than I could.
Yes I was thinking of two directions:
A “smarter” AI, though I think a better term would be “customized,” specifically tailored to only help with knowledge that the student already “learned” in the context.
A “dumb” AI thats too unreliable to use for lazy ChatGPT style answers, but can be a primitive assistant to bounce ideas off of or help with phrasing, wording, formatting and basic tasks that are too onerous or trivial for a human/student to help with.
Not many people are familiar with the latter because, well, they only use uncached ChatGPT, but I find small LLMs to already be useful as a kind of autocomplete or sanity check when my brain is stuck (much like it was without my TI84 BASIC program), and the experience is totally different because the response is instant (as the context is cached on your machine).