In this case, education, the answer is in the middle. It’s exploring and utilizing new tools while ensuring the base foundation of education. It’s really simple.
Apply “moderation” to nearly any facet of your life and it’s probably the correct choice. Want to consume alcohol? Moderate consumption. Enjoy TikTok or other video entertainment? Moderation. Work? Don’t destroy yourself, moderate extreme effort.
This isn’t to say don’t follow passions or pursue things to a moderate extreme, just don’t ever let it consume you.
So I don’t think that we should meet a middle ground necessarily but wary of people that are trying to maxxx something.
Just moderate your moderation! It’s turtles all the way down
The difference between AI robbing you of learning opportunities and acting as a tutor or sounding board is what question you ask.
Moderation in fentanyl.
But yeah, what's moderation and what's excessive is subjective.
https://en.wikipedia.org/wiki/Argument_to_moderation
https://www.logicallyfallacious.com/logicalfallacies/Argumen...
What I've found as I get older is that when someone says "It’s really simple," that's a good sign it isn't.
I have no idea how accurate, or useful that analogy is, but personal intuition tells me it's really close. I also don't envy teachers. I used to teach, so I do understand the position they feel that they are required to adapt into. However, I prefer CS programs that don't encourage people to tolerate non-determinism, or otherwise unpredictable outputs. They're the source of some of the most intractable bugs, one i doubt the next generation of students will be able to troubleshoot correctly if they never learn to solve beginner level bugs without LLM assistance.
Was there any possibility of this not being the case? Rules which are not enforceable do not exist. If it's any part of the process you can't check, students are going to do it in the easiest way possible.
Assignments and tests were always lossy, and over time more cheating crept in.
Instruction should shift to benchmarking productive output, strategic thinking and group collaboration. Similar to labs where you are tested on completing an experiment or a project with artifacts. Or an MBA program with quarterly group objectives. A major part of the group effort is dealing with collaboration and overcoming obstacles like laggards.
Hopefully people will realize how poor testing is for preparing students for the real world. the ultimate goal is preparing the students for a productive life, most commonly in commercial enterprise, but even academic pursuits require collaboration, productivity and other characteristics that were not well assessed by traditional testing and homework.
> Then generative AI rewrote the playbook.
> It wasn’t just professional upskilling; it was self-defense.
> Outlawing AI had felt comfortable—a neat wall built to preserve a familiar order.
> At first, they were guarded, but as I shared my own experience with AI, the classroom dynamic shifted. We stopped playing cat and mouse and became partners.
Jesus christ how do people read this shit and upvote it. Using ChatGPT to avoid reading your e-mails is not "professional upskilling" or self-defense.
Uh, by also avoiding it entirely?
> He didn’t try to hide that he had used AI to generate much of his assignment. Instead, he admitted his anxiety. He felt that mastering these tools was essential for his future career, yet he had no idea how—or even whether—he was allowed to use them.
I'm empathetic to the student: I'd bet a large majority of employers/careers he's researching right now are making a lot of press noise about "the importance of AI" and how "it's a necessary part of the workplace now." Can you really expect someone in his shoes to avoid it entirely?
...because I'm that I'm writing this article be a AI himself...
The reasons become more obvious only when you get deeper into a field where the math gets too complex to get a simple answer out of a calculator. If you never learned the basic concepts, you can’t progress to the more difficult topics because you don’t have a good understanding of the foundation.
That’s why changing goals to only look at the output doesn’t work for educating kids. Now that they can have ChatGPT answer every question they might see on a middle school or even high school exam, you could conceivably get all the way through high school graduation never having learned a single thing other than how to copy and paste between the assignment and ChatGPT.
Then what happens in the real world when that student needs to learn something new? It’s obvious: They’re going to try to put the problem into ChatGPT and then give you the result back. They don’t have any foundational tools to do anything else. They haven’t even learned how to learn because there was always an easy way out. Why would anyone hire a person who can only act as an interface to ChatGPT? They won’t. They’ll use ChatGPT themselves.
My unpopular opinion is that some times hard work, memorization, doing work manually, and yes, even testing, are necessary to build up an education and thinking foundation. I don’t believe it can all be replaced by ideas about challenging students to get results and then ignoring how they arrive at the result. I’ve worked with kids enough to know that they are more resourceful about finding lazy ways to pass a test than you could ever imagine.
Students still have to muster their own answers, but the LLM is used to minimize the confusion or uncertainty about the quality of the answer and the time to wait for that clarity.
My understanding is decades of research long before AI has shown the benefit of timely constructive feedback on the learning process. Why aren't all educators tripping over themselves to use LLMs to maximize access to timely constructive feedback?
So there are, or at least there will be, cases where it's actually a good idea to delegate your thinking to an AI model. Students who aren't taught to acknowledge that possibility and keep it in mind are being done a disservice, just as if they were taught to treat today's limited, early-generation LLMs as a first resort.
Group projects with tangible artifacts, including finished prototypes that meet objectives. More emphasis on group projects. If AI accelerates productive development like with software, move the objectives up the ladder in complexity, or expectations.
Peer assessments and performance reviews like employment . This also helps prepare students for adult life.
If the subject matter is merchandisable, have the students operate an enterprise. My local high school has the students operate a food cart for example, and it opens to the public one weekend a month, otherwise open to students. Students are responsible for inventory, marketing, accounting, maintenance , customer service etc.
More verbal challenges . These can be operated by AI with human supervision while being recorded, with spot checks from supervisors.
Every diagnostic has a precision / recall curve and some fall through the cracks. But you have to shift your approach when old testing no longer becomes viable. Better that than to revert to the stone age of informatics.
"Learned" didn't really mean what we mean today by being well educated or smart. You can't use AI to cheat and become "learned". AI can find the books to read but you still have to read them and understand the ideas.
There was connotation of breadth as opposed to depth with being "learned".
I think we also have to forget about "the real world". Being "learned" automatically is going to inherit dealing with "the real world" because the real world is always changing and that is exactly why breadth should be the focus going forward more than the depth of the research university model.
Of course, in a society so dominated by credentialism, credentialed people are going to hate AI because it will obviously let anyone cheat at the credential they put so much time and effort into. This doesn't need to be dressed up in some "think of the children" argument.
Claude to me is the greatest thing since sliced bread that increases my "learnedness" every single day but I also am a drop out that invested basically nothing in being a credentialed person.
So I agree with the comment. It was appropriately placed and a valid point. Moderation is key for many things, but there are exceptions. Things that are highly addictive and corrosive may be a good category for exceptions. Things that are clearly bad (e.g. murder) are exceptions.
When someone says "life is as simple as x" and the someon else says "hold on its not that simple, what about this exception" that latter rebuttal is valid and constructive.
This is an absurd statement. If someone is trying to talk about the middle cases, redirecting the conversation to the edge in order to dismiss their general comment is not appropriate.
'Edge cases exist' is not a lesson most people here need to hear.
This leaves it generously a thought teminating cliche devoid of meaning, certainly nothing you should be making decisions off.
AI really isn't a skill that needs to be taught, like adults didn't need to take a semester in AI-usage, so why should children need such a thing? Besides, it interferes with how we teach, which is done by having students write things in their own words (which is just "that which I can't explain, I don't understand", instrumentalized). It's not the essay that is the point, it's probably kinda shit, but the point is the fact that you are writing it. If AI does that work for them, then they simply don't learn. It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
If we can use AI as an expert teacher with infinite time for each child, that does theoretically have promise (per bloom 2sigma). But it's also quite far away with what we've got right now.
It fails in every direction, not just stepping on legos and murder. It's in no way better to be moderately happy or healthy than extremely happy or healthy.
At this point that's like saying Microsoft Excel isn't a skill that needs to be taught.
None of this stuff is easy to use, or obvious. If you want to get meaningful results out of it and avoid the many, many traps then there is an absolute ton you need to learn.
In the context of this conversation, the skill that needs to be learned is how to use AI to learn effectively. That gets into pedagogy and personal learning styles and self-discipline and all sorts of other extremely gnarly areas.
There seems to be a literal trap where people are too trusting of the LLM and take its word on code or whatever is being offered instead of reading it themselves.
In the context of the classroom this means teaching discernment more than ever.
The article's talking about the use of AI learning rather than learning how to use AI.
> If AI does that work for them, then they simply don't learn.
I agree, and I think the original commenter would agree too given that this doesn't sounds like moderation.
The no-ai end is "you write the whole essay yourself" the all-in end is "you give the ai and idea and have it write the essay". The moderation approach is somewhere in-between and it could very well be "you write the essay and ask the AI to proofread and coach you through it".
> It's largely the same reason we don't let children use calculators when they're learning basic arithmetic. Calculators exist, and are useful, but they're awful in a teaching environment.
Yes, having the ai act as a calculator when you need to learn and prove you can do it is a bad use of it. Having the Ai double check your work to catch errors, point out when you make the same mistake over and over, or ask it to walk you through another example are all productive uses.
Any time you reach for AI to make it easier, you're missing out on understanding and retention. If you cannot express the thing in your own words, then you do not understand it.
Just as you don't learn anything by copying someone else's homework, or expanding on someone else's summary (like if that worked, that's how we'd be doing already, holy crap would it accelerate teaching), the same doesn't work when AI is involved.
Again, it's not the essay that is the point, it's the work that goes into writing it. You need to hand it in so that the teacher understand where to put in more effort, but if it wasn't for that need, they'd probably have you throw it away after writing it. Because of this, AI even for finishing touches makes it harder for the teacher to assess your level, and the polish it brings doesn't actually help you learn.
I am not sure how your literature classes went, but all of my essays were graded and feedback was provided to me specifically so I can get better. Perhaps my previously reply was too long winded, but feedback on your essay on how to improve it is the exact use case I gave as an example.
Not that it's impossible to learn a subject that way, it just requires extremely self-motivated students.