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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.
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.
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.
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.
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.
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.
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.
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.
No one thinks you shouldn’t do 8 digit multiplication with a calculator, But you should understand what it’s doing under thr hood so if you say typo something you can catch when the answer is off by an order of magnitude.
But the same argument applies to AI. If you don’t understand the basics of an argument or the nature of the subject you’re investigating, you can’t tell - not even an if it’s working correctly but if it’s responding to the question you asked. If it applied the right context for your particular situation.
And I think it’s the exact same thing - whether AI is really thinking is irrelevant, students need to understand the nature of how to make arguments and validate information, before they can trust their own usage of AI.
"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.
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...