Teaching with AI
openai.com
openai.com
Anyone who has spent some time with ChatGPT knows that the 'show your work' (plan, outline, draft, etc.) argument is moot, because AI can retroactively produce all of these earlier drafts and plans.
If it is reasonable, then the problem is likely the form of evidence and not its requirement se de
Ruining public schooling by under funding and having expensive private education for those that can afford it is just the neoliberal agenda. If there were no private schools, if they were illegal, along with home schooling -- not saying they should be, but if they were -- the wealthy would pump funds into the public schooling system before you can say "fuck you got mine". (Kinda like no private bunkers would mean a sudden interest in mitigating climate change globally and for everyone, hah)
I only meant to acknowledge the societal investment, not imply private education
LLM's, the internet, even physical books all tend to deal primarily with subjective matters that can be plagiarized. They're not fundamentally different from each other; the more advanced technologies like search engines or LLM's simply make it easier to find relevant content that can be copied. They actually remove the need for students to think for themselves in a way calculators never did. LLM's just make it so easy to commit plagiarism that the system is starting to break down. Plagiarism was always a problem, but it used to be rare enough that the education system could sort-of tolerate it.
It pains me (though that's my problem) to see people pull out a calculator (worse, a phone) to solve e.g., a multiplication of two single digit numbers.
Synthesizing an original thesis, like what people are supposed to do in writing essays, is totally different. It's a fundamental life skill people will need in all sorts of contexts, and using an LLM to do it for you takes away your intellectual agency in a way that using a calculator doesn't.
Sure, once you know how to multiply you don't care about it. But try learning first year CS math without being able to multiply without perfect command of the multiplication table
Fluency in arithmetic isn't something drilled into kids just to be obnoxious, it's foundational to almost all future math skills.
Generally I agree (because the content of modern mathematics is largely abstract), but to nitpick a bit, number theory is part of mathematics too!
Ramanujan and Euler, for example, certainly cared a lot about 'arithmetic', and historically, many parts of mathematics have been just as 'empirical' in terms of calculating things as they've been based on abstract proof.
Arithmetic is the "write one sentence" of composition. The ability to think through a series of calculations with real-world context and consequences is the 5-paragraph essay. If you're not competent with the basics, you won't be able to accomplish the more advanced skill. Being tied to a calculator (not merely using, but being unable to not use) takes away intellectual agency in the same way as an LLM-generated essay (though, I'll agree, to a lesser degree).
Copyright protects specific expression, which reproducing is specifically a non goal with LLMs
Once they're done, they submit a one-pager on 3 to 5 subtle / smaller / things they find the most interesting or counter intuitive. At the end of the semester, I intend to share all their one-pagers among all of their classmates and keep an open-book test on it. Let's see how that pans out.
Similar to today, when grades are a proxy for ability, but private tutoring puts an average student in the 2% (Bloom's 2σ problem) for that stage, but doesn't boost the student's general intelligence for the next stage. Also, hard work, self-discipline, and focus will increase grades but not GI. (Of course, stidents do learn that specific stage, necessary for the next stage, so this criticism is just for use as a proxy).
We might say what is really be evaluated is the ability to get good grades (duh) - whether through wealth or work.
The same argument can be applied to LLMs. Using they is an important ability... so let's test that. This is the future. Similar to calculators and open-book exams.
Isn't that a good thing? Grades shouldn't be an IQ test. It's pretty much meaningless if you're not significantly below average or using it for super specialized tasks. Getting good grades means you can sit your ass in a seat (be it at a public library or a private tutor) and learn enough to do well on some task.
Yes, good grades doesn't mean you would be necessarily be good at some task. But it shows you can succeed in something that requires effort.
I certainly don't oppose reforming contemporary education, but at the same time, letting it be replaced by something else by default because that thing has exponentially more engagement power invokes Chesterton's Fence. I'm not sure we even know what we're giving up.
Chesterton could certainly not predict the exponential growth in access to tooling and knowledge. And we're only at the start of the curve.
In my opinion we should go back to absolute basics. Forget grades. Focus on health, language, critical thinking, tool usage, and creativity. Skills that are intrinsic to humans.
Make sure education is fun with lots of play. The main advantage humans have over computers is empathy and creativity. I'm not sure AI will ever "get it".
Provide each student to the extent possible a path to follow their own curiosity and talents. Advanced maths, programming, writing, chemistry, physics, etc available for those interested, even at a young age.
But the baseline education should focus on learning the absolute minimum to survive and otherwise maximize fun, creativity, and empathy.
Writing forces me to organize my thoughts, summarize, elaborate, reference other parts of the text, iterate until the pure essence is clear, remove redundancies, and this cements the concepts in my mind.
Merely reading, or worse, hearing, or worse copy/pasting something is only the first part of learning.
It's similar with programming but I would take it even further. I never really understand complicated code until I've written tests and run the debugger and been very close to it.
An AI chat bot is a powerful tool, but if you just use it to generate assignments you won't learn much. Inevitably it will be used both well and poorly and the results will be mixed.
How do you get to that conclusion? I find that if I have a text editor, I can write my thoughts down and then visually put them in order or encase them in a more general concept with ease, which I couldn't do when writing on paper.
But I've noticed that many many many people report the same effect, that there's something about pen-and-paper writing that's more effective for thought-lubrication. I resisted for a long time, but now I too am a convert to this school of thought.
Similarly almost everyone notices the downside: it's easier to reorder, reorganize, cross-link, etc, those thoughts, in a text editor (to say nothing of more sophisticated software tools). Some people have systems for doing complicated things with paper that they say mitigates this downside, but I am not currently one of them.
I guess it's possible that your brain just doesn't have this pattern in it. (That is, the pattern of finding pen-and-paper more effective for getting the thoughts to flow.) I mean, for all I know, maybe the huge silent majority doesn't have this pattern.
But writing enables arrows, lines, crossing-out, small-text notes, circling, variable pressure, colour, etc. Richer than ordering/indenting text. Also higher contrast.
Some of it may be just ... overload your brain so it cannot think of anything else ..so you stay focussed for lack of choice.
In my personal experience, a helpful feature of pen and paper is that it is less effective than keyboards, it takes me more time and focus to write things down. Maybe this gives the rest of my brain more time to catch up and understand the things that I am writing.
Written text is also less efficient when it comes to searching. This forces me to organize my thoughts better because I know I won't be able to CTRL+F random keywords later.
I don't write code on paper for (probably) obvious reasons, and I tend to write essays in a text editor although I also enjoy the act of writing on paper in that situation.
Personally, I find while the computer provides powerful writing tools, it also provides powerful distractions.
Maybe you get notifications you just quickly want to check, that slack message from the boss could be urgent. Maybe you decide to just check you're using that obscure word right, or to research a detail for your writing and an hour you haven't written the number of pages you set as your goal. Or maybe sitting in your netflix-watching chair looking at your netflix-watching screen just doesn't put you in the right mindset.
I remember my mother once doing the opposite: she wrote a long letter on the computer, so she could edit and re-write until she was happy with it, then printed it out and copied it by hand, for the personal touch of a hand-written letter (a peacemaking letter to a relative).
If you cannot organize your thoughts, explain your reasoning, etc. then you’re not going to get very far leveraging an LLM. Sure, it’ll spit out a book report, but unless you can explain — in well-structured writing - what you’re looking for, you’re not going to get what you need for the vast majority of writing assignments.
Organizing and arguing your own thought would be a good test. I think an assisting tool could still be reasonable - choosing between different organizations. Though it's unclear how to assess for original thought - the only such "essays" I know of are PhD theses.
People said similar about log tables and slide rules. And they were right - something was lost (e.g. the sense of nearby solutions). Yet here we are.
I suffered through writing classes for years and it made me hate writing.
It was only when I started journaling that I started liking it, and liking that I got better at it.
Is it worth making students better at writing if it means as adults they'll not want to write again?
If you become an expert in performing via LLM, the LLM capabilities and underlying data represent the limits of knowledge creation.
To your point about calculators and open-book exams, part of the challenge is for educators to rethink learning objectives and assessments in terms of outcomes that are outside the scope of LLMs.
We need kids to know how to write, and how to elaborate their thoughts, for when they will need to do so in life.
The LLMs can't guess what points you want to make to your boss or to your colleagues about the complex professional context you are in.
Perhaps the experience of symbolic calculators (like mathematica) is informing, since surely, for many years now, students have been able to have it do their homework for them. How do teachers handle that?
\aside Some exams allow calculators and textbooks, and are really hard. Consider: what would an exam assess, where LLMs were allowed?
University would just ban them for maths.
I use salt to season my food but I have no idea how salt is mined. I have used log tables books in the past to do math work. Back when I first used these lookup books, I had a shaky understanding of logarithms.
ChatGPT might tell you how much salt to use but you'll be screwed when it tells you to use 5 tablespoons for a small steak and you don't have the fundamentals to question it or figure out where it went wrong.
llms are not a source of reliable knowledge as a result. they are knowledge augmented in knowledge cases. So really you are arguing students should read the knowledge base, the "augment" is just a thin conversational summarizing veneer.
> when I first used these lookup books, I had a shaky understanding of logarithms.
this implies that now you do have an understanding of logarithms. how did you acquire this understanding?
The fear that many here share is that LLMs will make too many people get by without learning anything substantial from the ground up. Take away their LLM access and they're completely useless - at least that's what people are afraid of. Myself I'm on the fence - it was always the case that a certain type of people seek to understand how thinks actually work, and others who just want to apply recipies. These trends will likely make the recipy-appliers at first more powerful. I'm afraid though that soon enough they will be driven out by further automation coming on top.
Not knowing logarithms (a) didn't prevent me from successfully using the log tables books and (b) using the log tables books didn't prevent me from developing a better understanding of logarithms. I expect something similar with happen with GPT based education.
I acquired a deeper understanding of logarithms through a bit of reflection and thought.
The math lessons and teachers didn't help illuminate logarithms in any significant way. They simply rattled off the theory of logarithms and moved on to teaching us how to use them. I had to go out of my way to understand it myself.
Is this any different from a GPT giving you a superficial, regurgitated level of knowledge which you then have to deepen through some effort on your part?
Someone should teach you how logarithms work before giving you a log table. Someone at some point should show you a trigonometric circle before telling you to press the cos button in the calculator to calculate a cosine.
That said, some"one" could be a GPT chatbot. The problem is that you might not know the right question to ask.
Culinary counterpoint: I recently came across a very entertaining subreddit [0] which collects screenshots of scathing reviews of online recipes in which the reviewer admits having made changes in the recipe which are often clearly the reason for their bad results.
What I'm getting at is that you may not know how salt is mined, but you are certainly aware that sugar and flour are never substitutes for salt, however white and powdery they all may be. You also know that skipping the salt will completely ruin the recipe, but skipping the nutmeg will not. You probably safely assume that you can replace table salt with kosher salt, or table salt with coarse rock salt (provided it will dissolve in cooking). However, you hopefully know that if the recipe calls for kosher salt you may not be able to use iodised table salt instead (if doing a fermentation), and that table salt is not a happy substitute for coarse salt for finishing.
You absolutely do need some sort of basic understanding of a process to carry it out successfully, even when you have the full instructions available or a helper tool, because reality is never fully reflected in theoretical descriptions. That's why you must know the very basics of cooking before following a recipe, the basics of arithmetic before using a calculator, and yes, the basics of critical thinking and background knowledge before productively using an LLM.
[0] https://old.reddit.com/r/ididnthaveeggs/top/?sort=top&t=all
Hopefully he'd also know that 99% of recipes that use kosher salt (presumably because it sounds fancier) will work just fine with with table salt (iodised or not). For most uses the grain size will not make any difference at all and for the remaining ones it is still not essential.
The problem is that they have none of the general knowledge themselves and their brain is exclusively optimised to seek out openAI interfaces for guidance. They'll be a drone, an AI zombie.
There is one legal problem with the AI-student pair: the student doesn't own the copyright on what was produced with the AI. Meaning, any work submitted by the student that was at least partially generated by an AI is legally not 100% produced by the student.
So the comparison with an open-book exam or using a calculator doesn't hold: if I search for information in a book, or use a calculator to compute a number, and make my own report in the end, I own the resulting product. I'm the sole author of that product. If I use ChatGPT, ChatGPT is the co-author of my work.
So, using ChatGPT is the equivalent of calling your dad during the exam and ask him to answer the questions for you. Is that really what we want to evaluate?
Still, learning to calculate without using a calculator and learning to write without using an LLM are in themselves useful skills that can improve the thinking process, so both should be taught.
If I ask ChatGPT "i need to compute 12 * 55. Can you help me?" I get the following result:
"To compute 12 multiplied by 55, you simply multiply the two numbers together:
12 * 55 = 660
So, 12 multiplied by 55 equals 660."
I don't own the copyright on that paragraph. Nobody does. It's public domain. Meaning, I'm legally not the author of that work. If I give that to my teacher, I submit something I'm not the author of. It's legally the same as copy-pasting a block of text from a book or from the web and pretending I wrote it. That's not something teachers want to evaluate. In fact, not only will I fail my exam, but I'm also legally in trouble.
Now, if I take ChatGPT's output and make my own content out of it, for instance rephrasing it as "according to ChatGPT, the result of 12 multiplied by 55 is 660", then it's my own work again, and ChatGPT was just a source.
As a teacher, I cannot accept answers that are not produced by students. Whether they are produced by dad, by a domain expert who wrote a book, by wikipedia authors or by ChatGPT. But I can accept personal works that were inspired by those sources. Big, big difference.
And nobody is ever in "legal trouble" for a copyright violation in a typical school assignment... because unless the student work is publically published, the owner of the copyright is never going to know what you turned into your teacher. It's a tree falling in the forest, with nobody present to hear it.
If I'm asking you "write a program that solves this problem", or "write an essay about that topic", you can certainly find a solution online that has a very permissive licence letting you use it any way you want. Good for you, but that's still not your own work and will potentially put you in deep trouble if you use it. Ditto with anything produced by ChatGPT: not your work. You don't own that. You can write "according to ChatGPT, ..." (although you probably won't impress the teacher with that), or you can get inspiration from the output to produce your own work, but not use it as is and pretend you did it.
> And nobody is ever in "legal trouble" for a copyright violation in a typical school assignment... because unless the student work is publically published, the owner of the copyright is never going to know what you turned into your teacher.
Many univs automatically runs a plagiarism-checker on anything submitted by students. Sometimes one of them gets caught. In France, that's enough to be, worse case scenario (although that rarely happens), banned from taking any public exam or work for the government, for your whole life.
Consider a film student who uses a modern pop song without permission in their student film, which they credit in the movie credits. No plagiarism has occurred-- but they did violate the copyright of the band's publisher.
Consider a student who finds an essay written in 1893 and passes the words in the essay off as their own- plagiarism has occurred but there is no copyright violation as works from 1893 are public domain.
Can you fake it with an LLM for a while? Sure. But you hit a point where you need to know the right things to prompt with, and how to evaluate its output.
This is a solution (evidently imperfect and arguably obsolete) the education system uses to address the problem of proving the fact a student has gained desirable knowedge and experience. It can and should be deprecated altogether once we come up with a better solution to this. And we certainly can. For example, we can invent ana AI which would interview a student/candidate a way, proven (by numerous comparisions to their actual performance measured with other methods) to estimate their level of expertise and capability with sufficient degree of precision.
In case such a new way proves reliable and efficient we can even decouple expertise measurement and actual education on a mass scale then - let people gain knowledge whatever an alternative way they want and can, then just come and pass the test to receive an accredited degree. This way we can automate production of unlimited stream of certified experts.
So what I've been doing is chatting with Claude and asking it to correct whatever faults I make or asking it to give me exercises on things where I need to focus. For example, "Give me some exercises where I need to conjugate the past tense and choose the correct form."
It's like a personal language learning treadmill.
https://mainichi.jp/english/articles/20230824/p2a/00m/0na/02...
It uses Chrome's speech to text API (webspeechapi) for input, then it sends it to ChatGPT 3.5 and I use Google's text to speech API to generate audio response along with the text. So practically I can talk to ChatGPT.
I also want to add a dictionary module where I can generate and add example sentences and images to a words and phrases.
I'm sure there are complete teams working on apps like this as it's such a straightforward use case.
You can try it, it's all Hungarian but you can translate the page. https://convo.hu/ Invite code: CONVO
Current problems to solve:
- even the "best" LLM (GPT-4) frequently generates explanations/grammar that are plain wrong. Even its "correct" output isn't quite native (not as bad as round-tripping a sentence through Google Translate, but it's just slightly off).
- LLMs from Chinese companies (Qwen/Baichuan/etc) are immensely better at producing natural Mandarin (but fall short in other respects, which is unsurprising because they're smaller). I haven't tried fine-tuning LLaMa-2 yet, but I've had good success fine-tuning Qwen.
- in my opinion, 90% of the market doesn't need open-ended conversation about random topics. They need structured content with a gradual progression and regular review. You can use LLMs to generate this (which is what I'm doing), but it's not like a random newbie student is going to be able to design this themselves.
Not saying any of these problems aren't solvable, just pointing out the work that still needs to be done.
For me, the most exciting prospect is automated grammar correction during spoken conversation. I've made things harder for myself because I wanted to keep everything on-device so users could be assured that if they purchase something, they'll have access to it forever[0]. The downside is that I can't (yet) practically deploy any of these cutting-edge LLMs at the edge so I'm kind of handicapped in what I can do.
[0] subject to iOS/Android forced upgrades, which I have no control over. It's all cross-platform though, so I'll make a macOS/Linux/Windows version available at some point.
They are actually much better than previous state of the art. For the couple dozen languages with enough representation in the training set, GPT-4 is by far the best translator you can get your hands on, even without the whole "ask for context" etc
Use a combination of external sources to cross verify. Also spoken form generation is very important if you plan to interact with people.
Combining it with real conversation will definitely help.
But I can see how it can be absolutely awesome to play around, as an extra tool.
Unfortunately it's no longer free to try, but it worked well.
Yeah, I would never try this with, for example, Chichewa or Icelandic. Which is both understandable (like you said, less training data) and a shame, because there aren't many good resources for language learners now.
It’s hard to argue that OpenAI hasn’t helped pretty much everyone who’s used ChatGPT at all. That they do it for a profit doesn’t really change that equation much. Obviously I’d love to see them open source GPT-4 too, since it was trained on the world’s data. But they’re not compelled to.
We're still navigating the sleaziness (or whatever you call it) involved here to train unfettered on open source and public data, and not meaningfully propagate the benefits back to the contributors. This is uncharted terrain as of now.
OpenAI was never Open though. Remember pre GPT-3 they had this whole "Omg we made something but its so dangerous we're never going to make it public" bs?
https://techcrunch.com/2019/02/17/openai-text-generator-dang...
>OpenAI built a text generator so good, it’s considered too dangerous to release
The famous tutoring 2-sigma result (referenced elsewhere in the comments), only took place over 6 weeks of learning, and Khanmigo should have over 6 months (I believe) of data by this point
https://www.nytimes.com/2023/06/26/technology/newark-schools...
I do wonder how far away we are from an actual Young Lady's Illustrated Primer. Three years ago I'd say we were 50 years away. Now it feels more like 10.
https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnes...
But when it comes to LLMs, I'm conscious of the fact that I'm asking deep, specific questions when it comes to programming and software, about things on the fringes that the LLM can't have read much about. In contrast, with things outside my area of expertise, I'm asking very superficial question that any practitioner of the field could answer, and so likely has many many sources for the LLM to pull information from.
With fields outside my area of expertise, I'm most often asking questions that are comparable to "what is a variable" or at most "how does A* search work". That gives me confidence that the quality of answers is likely to be much better with these questions.
I think those agents could actually reason though. LLMs do not do any reasoning. They produce plausibly reasonable text.
2 + 2 = 4
2 + 2 = 4
Which of the above lines was generated by an LLM, and which was manually written by a human?
My coworkers were absolutely thrilled at my turnaround time. I was thrilled I didn’t have to do this boring task. I saw this as an absolute win.
Some teachers are looking for ways not to adapt, which is why there's a surge of interest in AI detection (which doesn't work well), but the sharpest educators I talk to are cognizant of the fact that there is no going back. So the plan is to incorporate AI into their curriculum and try to make assignments more "AI proof". This means more in-class work (e.g., the "flipped classroom" model [2]). Others are looking for ways to encourage students to use AI on assignments, but to revise and annotate what AI generates for them (this is what I am marketing my plugin for). Either way, it's going to be very rough over the next few years as educators scramble to keep us with a monstrous change that came about practically overnight.
[1] https://www.revisionhistory.com. The plugin helps teachers see the students' process for drafting papers, unlike many than other plugins that are trying to be "AI detectors".
[2] https://bokcenter.harvard.edu/flipped-classrooms#:~:text=A%2....
Btw your site is exposing the .git directory https://www.revisionhistory.com/.git/config
Might want to set a filter rule for that
Edit: should be fixed now :)
On a more serious note, this is a great example of how to handle a vulnerability report - fix it, change your processes, and say thank you! (geek_at could probably have done better by disclosing this in private first, though)
lol
> geek_at could probably have done better by disclosing this in private first, though
I'm glad geek_at let me know quickly and also made this a learning experience for others. No harm done.
https://chrome.google.com/webstore/detail/dotgit/pampamgoihg...
Maybe this tool would have forced me to get over that, I don't know.
When chatgpt beta first became available I was overjoyed, it worked wonders. It worked so well that I figured teachers would have to let go of the essay crutch they had been relying on so much.
I had one teacher assign four separate (essentially busy-work) assignments over Christmas break. Ridiculous.
The occasional take-home project is probably fine, but otherwise let school be school, and leave it at that.
We are going to use powerful AI to teach kids to do jobs that AI will almost certainly do better in 10-20 years?
Like I get that there is a notion of "What else are we supposed to do?", but it still just feels so silly and futile to go along with. Like "Lets use AI to teach kids how to program!"....uhhh, the writing is on the wall
I feel for people who don't get this or perhaps never contemplated it, but the system is designed to breed good workers and sort them into bins. And its not a bad thing either. Sure there are non-economic self contained benefits, but those are perks, not purposes.
> It absolutely, unequivocally is. People can romanticize it anyway they want, but formal education is very different than religion camp, painting class, or spiritual retreat training.
No it isn't "absolutely, unequivocally." What specific formal education are you talking about?
Especially in the past, but continuing somewhat into the present-day, formal education has mainly been about enculturation, and not "labor preparation." That can seen clearly by the former emphasis on dead classical languages and the continued (though lessened) emphasis on literature and similar subjects. There's zero value in reading Shakespeare or Lord of the Flies from a "labor preparation" standpoint.
However, I do see a modern trend where many people are so degraded by economics that they have trouble perceiving or thinking about anything except through the lens of economics or some economics-adjacent subject.
There is zero labor prep value in learning to extract information from text (that you possibly have no interest in reading)?
But those are the fringes of the education system. The core focus is on producing high value citizens that will produce far more than they take. This is abundantly clear if you look at the social valuations of high caliber students with fruitful degrees.
That said, the discussion is about the purpose of classrooms in a world of AI, and I think it’s a good time to remember the less economic purposes of education that have always been there under the surface. I think few teachers are more driven by bringing economic benefits to their students than enriching/exciting/interesting them, and secondary and post secondary education has always had a huge variety of non-occupational courses, from ancient history to obscure languages to nice math.
Overall, I imagine we agree on the most important thing: if education does end up changing immensely as AGI gains footing, we should change it to be less economic
The students want to learn things and socialize with peers.
Teachers want to teach, earn a living, get respect of society.
Parents want their children to be taught, but also want their kids to be taken care of by other adults so they can go to work in peace. Poorer parents in particular also need their kids to be fed and sometimes schools have to do that too.
Governments want an educated citizenry that is productive, pays taxes, knows the basics of law, civics and so on. They also want to monitor and protect unfortunate children who have bad parents.
If schools only had one purpose you wouldn't see the stakeholders fight each other so often. But in reality parents fight governments over the curriculum, students fight teachers over the amount of work, teachers fight government/parents over their wage and so on.
No. Students want to socialize with peers or play sports/video games. Not learn.
> Teachers want to teach, earn a living, get respect of society.
This is correct
> Parents want their children to be taught, but also want their kids to be taken care of by other adults so they can go to work in peace. Poorer parents in particular also need their kids to be fed and sometimes schools have to do that too.
Also correct. Parents want schools to be daycare, or for elite families, schools are networking opportunities
> Governments want an educated citizenry that is productive, pays taxes, knows the basics of law, civics and so on. They also want to monitor and protect unfortunate children who have bad parents.
Correct. But a population can be productive while being largely uneducated (see China)
But despite the different priorities of the groups, “the student learning”, is not one of them
China's a terrible example in trying to support your point. If the pitch is "education makes better workers" then you shouldn't be looking at GDP, you should be looking at GDP per capita, aka "Are the workers more productive in more educated countries?". And China has a terrible GDP per capita. It ranks 64th in the world to the US's 7th. Applying slightly more rigorous comparison across the world, there's a clear correlation between GDP/capita and average educational attainment.
And you have a very dismal view of students. In my area, at least at the honors level, students were pretty well engaged in learning. Now, that was mostly in order to get into good colleges and appease their parents' desire for them to learn, but they definitely were eager to have the knowledge that was being taught. By the time you get to college, a fair fraction of the students are truly engaged with the material for the material's sake. Even moreso in degrees that aren't glorified trade school programs.
This is frightfully incorrect. Students definitely love to learn. They do not like to be stuffed in a chair and lectured at and forced to do rote activities. But who does?
No, because you've forgotten one of the important stakeholders here, which is society at large, which has a interest in ensuring a general level of shared education. Which once again results in fighting, as parents who are teaching their own children run up against government requirements that they may not agree with.
First, a functional democracy requires that the citizenship be well informed and capable of critical thinking: "A republican form of government, without intelligence in the people, must be, on a vast scale, what a mad-house, without superintendent or keepers, would be on a small one."
He also saw the economic side, saying that education was an equalizer for people in terms of helping them to reach their full potential.
I quite agree with his assessment. In a system where everyone has a vote, it becomes quite important that everyone have a sense of things that extends beyond their career vocation. His imagery of an uneducated republic being a madhouse makes much sense from this perspective.
Insofar as we have given up any optimism about the democratic enterprise, then certainly we could look at education as purely to put people into economic bins, but at least in my own public school education in the US, every student did get significant doses of math, history, science, etc., outside of their expected career direction.
This to me suggests that there is a tension, not fully resolved and HOPEFULLY never fully resolved, between education-for-economics and education-for-democracy. I think it's quite pessimistic though to give up the ghost on the education-for-democracy aspect.
This is a category error. You're talking about the education system as though it was designed from accurate first principles towards a specific intended outcome. Like, you can say that the absolute unequivocal purpose of a nuclear reactor is to heat water. But when we're looking at sociopolitical organizations, that have been codified through various political forces over tens of generations, through the demands of ever-shifting stakeholders, etc this is not a useful framing.
> but the system is designed to breed good workers and sort them into bins. And its not a bad thing either. Sure there are non-economic self contained benefits, but those are perks, not purposes.
I think a more accurate framing is that the system is currently evolved into strongly emphasizing this mode of behavior.
Where the mundane is keeping young people out of the streets, maybe teach them arithmetic and some grammar. And the leaders, that is, the teachers, want, most of the time, just to bring home a salary, not funnel the masses from schools to office desks or assembly lines.
But it is not the only reason, or (in my view) even the most important reason.
Maybe before assuming people haven't contemplated what you're saying, you could try to contemplate what else general education might be buying us. Maybe by imagining how it would look if school was actually just job training starting in elementary school, rather than covering all these other things.
"Purpose" in an entirely subjective thing.
"Much of this education, however, was not technical in nature but social and moral. Workers who had always spent their working days in a domestic setting, had to be taught to follow orders, to respect the space and property rights of others, be punctual, docile, and sober. The early industrial capitalists spent a great deal of effort and time in the social conditioning of their labor force, especially in Sunday schools which were designed to inculcate middle class values and attitudes, so as to make the workers more susceptible to the incentives that the factory needed."
From the Marxist paper backing that article:
England initiated a sequence of reforms in its education system since the 1830s and literacy rates gradually increased. The process was _initially motivated by a variety of reasons_ such as religion, enlightenment, social control, moral conformity, socio-political stability, and military efficiency, as was the case in other European countries (e.g., Germany, France, Holland, Switzerland) that had supported public education much earlier.15 However, in light of the modest demand for skills and literacy by the capitalists, the level of governmental support was rather small.16
In the second phase of the Industrial Revolution, consistent with the proposed hypothesis, the demand for skilled labor in the growing industrial sector markedly increased (Cipolla 1969 and Kirby 2003) and the proportion of children aged 5 to 14 in primary schools increased from 11% in 1855 to 25% in 1870 (Flora et al. (1983)).17
What are we really educating kids for these days? To have advantage over other kids because we have no fair meritocratic way to allocate resources or meaning in society?
Won’t AI just make this infinitely worse.
Like, one vision is more teachers and more students learning better, and another is less teachers and more baby sitters and lower government budgets for education leaving students with the equivalent of an automated telephone answering service menu instead of a real human call centre?
To me it means "the reason why <person> does <thing>", so the phrase "purpose of a system" doesn't make sense without a particular human subject who's interacting with the system.
- Make kids show their work (outlines, revision histories)
- Retool to focus on the things where the tools can't do all the work (proofs, diagrams, word problems for math; research, note gathering, synthesizing for writing)
- After kids learn the basics, incorporate the tools into the class in a semi-realistic way (using a TI-whatever in the last years of high school math education)
Of course this would possibly exclude using SaaS-based LLMs like ChatGPT in places like schools, and as such it might make sense to require students to only utilize open ones. Or maybe, if OpenAI provided a verification service whereby a prompt could be checked against the output it supposedly produced in the past at some point (even if the behavior of the chatbot had since changed).
I mostly disagree (and I used WolframAlpha thoroughly during my engineering education). Wolfram can solve well encapsulated tasks (solve for X, find the integral, etc). Even then often it gives you a huge expression, whereas doing it by hand you can achieve a much simpler expression.
It doesn't really handle complex problems, at least like the ones you'd find in a college level math or physics course. It can be a tool for solving certain steps within those problems (like a calculator), but you can't plug the whole thing into Wolfram and get an answer.
GPT4 is kinda OK at this, like 50%+ success rate probably, highly dependent on how common the problem is.
Those complex problems are taught and asked in college level classes because of Wolfram Alpha. Like the parent commenter mentioned, classes had to adapt to new technology and since Wolfram Alpha could solve the straightforward questions, college classes started asking more complex ones with multiple steps and where the problem needs to be reframed in order to actually solve it.
I don't like this. It seems to me that this would lead to teachers forcing formulaic approaches to writing on children (even more than they already do). No uniform process is going to work on everyone and having students write using a process like that produces bland, uninspired and unmotivated essays.
Furthermore, outlines and revision histories also seem easy enough to fake with a GPT-like AI: you can just ask the AI to write an outline and then have it iterate on that.
I have a feeling that the outcome might be that we actually become dumber and lazy. I personally won't be bothered learning as much if the machines already know everything, it just would seem like a waste of energy. I'll probably just continue to learn survival skills and first aid in the event of some type of catastrophic event and I happen to survive.
If these systems don't workout to replicate, build and themselves really quickly then we're headed into some very uncharted waters. When they do workout how to replicate, build and run themselves, we're probably fucked anyway.
We're at an interesting point in history here where populations are rapidly declining and the youngest generations are so fucking distracted by technology and new shiny they aren't going to be as interested in developing it as the boomers were. Going to be interesting to see where it goes.
That's your utilitarian take that would eliminate many things you would consider superfluous. Social sciences, history, art, useful personal skills that might not be directly to the economy (like home related stuff or questioning authority)
It should be about empowering citizens in many ways regardless of how much they'll end up contributing to society. As for historical examples, women and wealthy people who studied and couldn't or didn't need to work still studied.
If you subscribe to the purely resource exploitation view, you end up on the road to optimize for the elites in power through lobbying and corporate manipulation.
Having a population that thinks for themselves may actually lead to more unrest and economic uncertainty of all the KPIs that corporations usually love.
Of course, corps will want education to be a specialized training ground for future human resource exploitation and govs might want to create voters for their party (or nation build through ideology and principles) but just because either might get their way to a hig degree doesn't mean that "the primary purpose" is what they get away with.
I see zero evidence that this is true. This is not the stated nor revealed preference of a significant portion of the population.
What more evidence than that do you need?
I see your point though, I was thinking about school, not university.
I think understanding how to work well with AI and what its limitations are will be helpful regardless of what the outcome is.
Even if silicon brains achieve AGI or super-intelligence, I think it's highly unlikely that they will supersede biological brains along every dimension. Biological brains use physical processes that we have very little understanding of, and so they will likely not be possible to fully mimic in the foreseeable future even with AGI. We don't know exactly how we'll fit in and be able to continue being useful in the hypothetical AGI/super-intelligence scenario, but I think it's almost certain there will be gaps of various kinds that will require human brains to be in the loop to get the best results.
And even if we do assume that humans get superseded in every conceivable way, AGI does not imply infinite capacity, and work is not zero sum. Even if AI completely takes over for all the most important problems (for some definition of important), there will always be problems left over.
Right now, just because you aren't the best gardener in the world (or even if you're one of the worst), that doesn't mean you couldn't make the area around where you live greener and more beautiful if you spent a few months on it. There is always some contribution you can make to making life better.
It's al very tricky to figure out what foundational knowledge will be useful in 15 years (that's why we pay educators the big bucks ... oh wait ...), but just because it's hard and uncertain doesn't mean it isn't valuable to try to figure it out.
[1]: https://www.reddit.com/r/AutoGPT/comments/13z5z3a/autogpt_is...
Relatively high fidelity and public data for some domains does exist, however (think all github commits, issues, discussions and pull requests as a whole). For those domains, it indeed might be only a matter of time.
If a coach assigns someone to repeatedly lift heavy weights in order to become stronger, lifting them with a forklift doesn't achieve the goal, because in real life that strength is intended for situations where you won't use a forklift. The same goes for exercising various "mental muscles".
We need to start valuing human intellect more otherwise it will simply become a thing we have outsourced to machines like washing clothes and transporting our bodies.
Why? Doesn't it only mean they need to change how they test understanding?
In quite a few courses a key part of the actual valuable learning work is expected to happen outside of the classroom by practicing some activity or putting in time&effort to creatively think about some topic. And for many students this work happens only if there are adequate means for controlling that it has been actually done. So if students can trivially fake having done the practice or thinking, that course design isn't working any more, and you need some completely different structure of the coursework or activities so that the students will put in that work required for the learning outcomes.
Like, if someone assigns an essay about (for example) the impact of foobar on widget manufacturing, it's not because anybody cares what the students think about this topic, and (in most courses) not because they want the students to practice writing essays, and not even to evaluate whether students know about the impact on foobar on widget manufacturing - usually the goal of such an assignment is to (a) have students put in some time to read and think about these topics as a whole, and (b) to see if they have some specific misconceptions that should be corrected with feedback (which is substantially different from testing the level of understanding - if you'd want to do that, then probably a different assessment type would be chosen, formative vs summative assessment).
If the student has someone or something else write that essay, both these goals fail - but these things are needed for the course, so now the course needs to be redesigned to throw away the essay (because it spends time but doesn't contribute to the goals due to it being faked) and add some new activities that will achieve these goals - for example, extensive in-class discussion or debates that will require preparation and will reveal those misconceptions. But that requires changing how that course is taught, which takes time and effort.
Just curious.
Language models should be introduced in classrooms because they're a part of society now, and they're here to stay. Kids should learn about them - how they work, where they came from, how to use them - just like they should learn how to type or send an email.
It does remind me of my experience as a middle schooler in 2002, when our class took a trip to the library, and the librarian gave us a lesson on "how to use search engines properly." In retrospect, the societal worry at the time was about search engines replacing librarians, so it was perhaps notable that this librarian had the humility to teach us how to use her "replacement." Surely the same applies to teachers and ChatGPT: a good teacher will not be worried about whatever impact ChatGPT might have on them personally, but will instead take the opportunity to teach their students about the new horizons opened up by this technology.
(The funny part of that seminar in the library was that the lesson emphasized the need to construct efficient, keyword-based queries, rather than asking natural language questions to the search engine directly - but twenty years later we've come full circle and now you actually can just ask your question to the language models.)
If you are a teacher or know a teacher who is struggling to adapt this school year, I'd be honored to speak with them and see if we can help.
Especially for teachers, who I believe (most at least) have no clue about prompt engineering and how to talk to an LLM.
Using an LLM is like having a therapy session - where you the user are the therapist. Humans should not need to learn en masse become AI therapists, that’s a the inverse of what should happen :D
They're just tools. The outcome depends heavily on the user skills. That's why prompt engineering is a thing.
Heck, even Google results varies depending on the searcher skills, and we're not calling the tool immature...
As with regards to therapy, I have had the opposite experience as you described.
Codermindz AI Curriculum: https://www.codermindz.com/stem-school/
https://K12CS.org K12 CS Curriculum (and code.org, and Khanmigo,) SHOULD/MUST incorporate AI SAFETY and Ethics curricula.
A Jupyter-book of autogradeable notebooks (for AI SAFETY first, ML, AutoML, AGI,) would be a great resource.
jupyter-edx-grader-xblock https://github.com/ibleducation/jupyter-edx-grader-xblock , Otter-Grader https://otter-grader.readthedocs.io/en/latest/ , JupyterLite because Chromebooks
What are some additional K12 CS/AI and QIS Curricula resources?
Of course it's not a 4-hour in-person workshop, like what you're proposing. But it already adds positive value.
It covers a good amount of the topics your course covers, I think. Introductory-level, perhaps, but it's a start.
Honestly? I don't understand your comment - I read as negative towards OpenAI (am I wrong?)
I'd expect someone like you to praise OpenAI's willingness to contribute in this space.
I'm with you the parent seems more like an ad and negativity towards OpenAI.
Why would you assume OP position in this case? There are multiple valid, albeit unstated reasons, why the company in question may not be the best vessel for those efforts. And, just to make sure that is not left unsaid, it is not like openAI is doing it for altruistic reason.
I do agree that it is not a bad starting material, but I think you will agree that it is clearly not targeted at group that gathers at HN.
Call me crazy, but that was the impression I had from the comment and the course website.
This is a worldwide issue.
I think it's great what you two did, maybe it would be more effective if you did a small article or video on it?
Many would be honored to be able to get help from your insights, it's needed. I see how teachers are struggling in Germany, while they are still open to embrace this technology.
I prefer to do the teacher training workshop in person for various reasons, but we have considered recording it.
I've also given 2 open lectures at different libraries (and have been asked to do more) for the general public. I should certainly record that, since it's more general audience.
If someone who wants to be a software engineer can’t be bothered to learn and understand the fundamentals I’d argue that software engineering isn’t the discipline for them. The more you understand, the larger the surface area of the problem you have for which to explore further.
On the other hand, as non-native English speaker, it save me much time into paraphrasing my poorly thoughts and writing that I would need an hour to express in a good formal manner. It can guide you in some aspects of coding tasks, introduce you to some APIs …etc. This is actually a good tool that I agree that a good student (researcher) would use wisely to gain some knowledge and save sometime.
It will not help much with solving a cart on an inclined plane with some friction and a pendulum hanging from the cart. No, it will not be able to give you the normal modes.
This is just a personal experience and opinion, though. It might be completely different in other areas.
For instance, Miles Cranmers work on using GNNs for symbolic regression is a start towards useful new discoveries in physics. Transformers are just GNNs with a specific message passing function and position embeddings. It's not hard to see that either by a different architecture, augmentation, or potentially even just more of the same, we can get to new discoveries in physics with AI. The GNN symbolic regression work is evidence that it's already happened.
As for grounding knowledge in the LLMs we have exactly just this moment (a rather short-sighted view) there is plenty of interest and work in the area, for which I expect will be addressed in a multitude of ways. It's ability with grounded physics knowledge is not perfect, but it's very good w.r.t. the common knowledge of a human off the street. External sources alone make it much better, and that's just the exceedingly short-sighted analysis of what we have today.
Teachers should be very careful using a vanilla LLM for education without some kinds of extra guardrails or extra verification.
GNNs (for which LLMs are a subclass of) have a potential to be optimized in such a way that all the knowledge contained within them remains as parsimonious as possible. This is not the case for a human reading some internet article for which they have not gained extensive context within the field.
There are plenty of people that strongly believe in strange ideas that were taught to them by some 4th grade teacher that was never corrected over their life.
While you're statements are correct in this miniscule snapshot of time, it's exceedingly short-sighted to assert that language modeling is to be avoided due to some issues that exists this month, and disregard the clear future of improvements that will come very soon.
If you heard the bullshit that actual teachers say (both inside and outside of class), you would think that “1% hallucinations” would be a godsend.
Don’t get me wrong, some teachers are amazing and have a “hallucination rate” that is 0% or close to it (mainly by being willing to say they don’t know or they need to look something up), but these folks are the exceptions.
Education as a whole attracts a decidedly mediocre group of minds who sometimes (often?) develop god complexes.
Now that the ChatGPT Playground is the default interface for the ChatGPT API with full system prompt customization, they should be encouraging more use there, with potential usage credits for educational institutions.
Is ChatGPT safe for all ages?
ChatGPT is not meant for children under 13, and we require that children ages 13 to 18 obtain parental consent before using ChatGPT.
it's grossly irresponsible to be pushing "Teaching with AI" in this scenario
you know, like in the form of a parent. parental guidance. which starts with parental consent.
so in other words: it depends.
it’s grossly irresponsible to treat a hammer as inherently dangerous.
No, but if it's turning you away even when you're explicitly asking for it, it's probably doing good enough. Nobody held Yahoo, Lycos or Altavista to this standard.
If accidental erotica is the worst outcome you can imagine for the shortcomings of AI teaching, please leave worrying about this to the professionals. Consider flawed chemistry lessons, where it tells some kid to mix two things they shouldn't. That will actually cause material harm to everyone around them.
Always remember the glorious few months when I had Encarta at home before too many students had it and before teachers clocked on where homework became just printing the page on the subject off after removing identifying bits.
Education is not a problem the human race has solved despite progress made.
Good on you. That is an inspiring demonstration of restraint.
I played around with this use case in the spring when my teenage daughter was looking for extra test prep materials. At first the experience was interesting but there was an "AI uncanny valley" shaped problem: the material just didn't seem to fit. It felt wrong.
This uncanny valley was significantly reduced, even eliminated in some instances, by including the entirety of our school district's online material about the course; information about the core competencies (across communication, thinking, personal & societal), the big ideas, the curricular competency & content about the learning standards. Our district has a pretty good website with all of this information laid out for each course and grade level.
Including all of this information in the prompt context resulted in relevant and harmonious content when asking to generate course outlines, student study-prep handouts, and even sample study session pre-tests (although ChatGPT wasn't strong at reliably creating answer sheets for the pre-tests).
Context is key!
Example prompts that OpenAI shared here are a great start. However I think these use-cases are better served as micro apps built on top of these prompts. For example, a teacher will keep coming back to use this prompt with same/similar set of responses most of the year. On top of that, enriching the context with additional information pulled from local sources will quickly become a need.
ChatGPT's custom instructions will help with not having to repeat prompts but the interface falls short when it comes to repeat narrow use cases. This is where imo LLM apps shine. A simple app built with langchain or some low-code platforms and providing local data from a vector store can be super powerful.
We recently open-sourced LLMStack (https://github.com/trypromptly/LLMStack), a platform that allows users to build these micro apps to automate their workflows. Our goal is to make these workflows sharable so someone can download a yaml file for this prompt and chain and start using it in their job.
By analogy, if LLMs were allowed in an exam, what harder tasks would be assessed?
Similarly, pilots must learn to fly under various regimes of automation, despite primarily using high-automation settings.
You're all having fun now. But you'll regret using AI for anything because soon humans will become mostly fit for manual labour while AI concentrates the wealth of the world into the hands of the tech elite.
Then, without a human connection in teaching, children will grow up into psychologically damaged adults.
> soon humans will become mostly fit for manual labour
> without a human connection in teaching, children will grow up into psychologically damaged adults.
If humans are only going to be doing manual labor, what will the AI teacher be teaching? Do you need 16+ years of education for manual labor?
Just taking your argument at face value, I don't understand how "AI replaces nearly all human knowledge workers" leads to "children become psychologically damaged adults."
It seems like it would free them from being strapped into a chair for 16 years and denied the opportunity to be children in an attempt to prepare them for a life of knowledge work? Unless we just keep up the ruse of an entire childhood of classroom based education for ... reasons?
To push past your argument, society and knowledge isn't zero sum.
I'm not writing software because it's the single most important thing in the universe for me to focus on right now. It's actually pretty low on the list of important things on the grand scale of important things. I'm writing software because it's the work that needs to be done right now and there isn't a replacement for me doing it.
I feel like you are asserting that plugging numbers into spreadsheets as an accountant or doing string transformations "at scale" to convert DB queries into HTML and JSON is both: 1) A fulfilling life 2) The only thing humans could possibly be doing of value right now; if you take this away there is nothing left
There are a tonne of fundamental questions/problems about life, the universe, interstellar travel, preservation of our species, etc. that I _just don't have time for_ right now because I'm over here trying to figure out how to take these bytes coming over the wire from an SQL query and pack them into a JSON object so a browser can hydrate this bit of HTML. And I'm sorry, but, this isn't how I'd choose to live my life if there was someone else I could put in this seat.
Please AI take my job so I can be free to focus on all of the stuff that comes with the next layer of abstraction/automation.
No, that is bad too. I am rather asserting that we already have enough technology to work LESS, live more SIMPLY, and use our time to develop a sustainable way of living minimally without spending time endlessly seeking economic growth and industrial progress.
Thanks for sharing.
In other words: you know what beats one elite with an AI? Ten thousand well educated people each with their own AI.
So, now we'll be constantly fighting each other with endlessly evolving AIs. The world is already a cuthroat place with fierce competition.
Think of this analogy: imagine a karate match with people fighting each other. Sure, some people will get hurt but it's mostly controlled. Now imagine a world of people fighting each other by flying airplanes into each other...everyone dies.
We are unprepared for a new world where thousands of people fight for their slice of the pie with advanced AI, and it will either result in insanity or else a hugely more efficient use of resources (the FIRST thing people will do is find out how to use advanced AI to get a bigger slice of the pie) so that the natural biosphere will be even more efficiently destroyed.
"College-level calculus" was similar, just vague generic high-level advice with no lesson plan or specific guide.
Extra credit if you build a new anki that dynamically generates cards with different text and the same meaning to prevent answer memorization.
It turns out making a single question really is a bunch of different questions in itself. You have to ask on each question "How can this be misinterpreted", "Can the question be written better", "Is this a challenging question that actually causes a person to learn".
A lot of human generated question are just confusing hot garbage in and of themselves. Quite often we encode cultural biases in the questions. Or, if a person actually knows about the topic they can get the question wrong, based if they are only supposed to formulate the answer based on the paragraph shown to the user.
The AI Explained channel on youtube just had an episode about this in relation to the tests we're giving AI. Turns out a lot of the questions just suck.
The problem with these types of learning tools, same as with the Khan Academy one, is that they’re too “safe guarded” for general public release. Obviously needed for a public launch, but giving someone free reign of the models with some prompt teaching and an understanding of hallucinations could help kids learn so much more efficiently in the future.
We currently have a huge amount of pre-AI knowledge to train them on, but in the future that could slowly get replaced by AI output with all its inaccuracies, which then gets used to train future AIs, and transitively the people they'll have taught, etc.
This is an odd point. You’re already in school to critically think and why not just google it if you need to check its accuracy anyway
The internet is bursting with anecdotes of it getting basics wrong. From dates and fictional citations, to basic math questions... how on earth can this be a learning tool for those who are not wise enough to understand the limitations?
OpenAI's examples include making lesson plans, tutoring, etc. Just like with self driving cars - too much too quick, and many are not capable of understanding the limits or blindly trust the system.
ChatGPT isn't even a year old yet...
I'd love to see a good research study on this that shows the actual error rate as well as a comparison with other non-human alternatives (e.g. googling, using textbook only, etc) as well as possibly human (personal tutor, group instructor, ...)
A tutor is expected to know the subject and guide the student. If, say, 10% of the time it guides the student into a false understanding, the damages are significant. It's very hard to unlearn something, particularly when you have confidence you know it well.
My personal adventures with ChatGPT are probably close to a 50% success rate. It gets some stuff entirely wrong, a lot of stuff non-obviously wrong, and even more stuff subtly wrong - and it's up to you to be knowledgeable enough to wade through the BS. Students, learning a subject in school are by definition not knowledgeable enough to discern confident BS from correctness.
Will ChatGPT be useful in the future? Yes, almost certainly. But let's not rush this and get it very wrong. The consequences can be staggering in the education space - children or adults.
If I had to place it somewhere, it would be between a study buddy and a tutor, closer to a study buddy.
Still - a well designed study will give us a much better picture of where we actually are. I think that would be extremely valuable.
It’ll (mostly) always know about the Sherman Antitrust Act and what precipitated its passage, for example.
That said, OpenAI repeatedly suggests verifying responses and says, “make it your own” which IMO includes spot checking for correctness.
It's fabricated legal cases and invented citations to back up it's statements.
The issue is, it can be difficult to know when it's wrong without putting in a lot of effort. Students won't put in the effort, and that assuming they're even capable of understand when/where it's wrong in the first place.
Just like self driving cars - we can say "pay attention and keep your hands on the wheel at all times"... but that's not what everyone does and we've seen the consequences of that already.
We need to be careful here. This tech is new. ChatGPT hasn't even existed (publicly) for a year. Getting it wrong and going too fast has consequences. In the education space in particular, those consequences can be profound.
At some point, using LLMs like ChatGPT recklessly is on the user, not the tool.
They probably wont be using that model for another year, while people will be using that website for many years
Have the students produce their work in the classroom under examination-style conditions, with no electronic devices allowed in a classroom. Pens / pencils are allowed. Paper books can be allowed. No electronics. Let's see you write out that insightful essay about social hierarchy in Romeo and Juliet in longhand. Calculate the roots of that quadratic equation using pencil and paper, please. Explain the links between the Treaty of Versailles and World War II using what you learned in class, and a (paper) textbook for reference if you must.
We have literally been doing this for hundreds of years. We were doing it when I was at school ~20 years ago. Any kid caught using a calculator in the classroom was told to put it away one time, or the teacher would confiscate it. Obviously, no laptops. The teachers used a blackboard and chalk; and the occasional slide projector.
I don't completely understand why people act as if it's impossible to teach properly now that we have LLMs; but perhaps a general over-reliance on laptops and electronic devices in the classroom is the reason. As it is, kids (and adults) have a huge problem with screen time, so it would serve us well to get away from it.