One of my students recently came to me with an interesting dilemma. His sister had written (without AI tools) an essay for another class, and her teacher told her that an "AI detection tool" had classified it as having been written by AI with "100% confidence". He was going to give her a zero on the assignment.
Putting aside the ludicrous confidence score, the student's question was: how could his sister convince the teacher she had actually written the essay herself? My only suggestion was for her to ask the teacher to sit down with her and have a 30-60 minute oral discussion on the essay so she could demonstrate she in fact knew the material. It's a dilemma that an increasing number of honest students will face, unfortunately.
> My only suggestion was for her to ask the teacher to sit down with her and have a 30-60 minute oral discussion on the essay so she could demonstrate she in fact knew the material.
This sounds like, a good solution? It’s the exception case, so shouldn’t be constant (false positives), although I suppose this fails if everyone cheats and everyone wants to claim innocence.
You hinted to it but at what point are you basically giving individual oral exams to the entire class for every assignment? There are surveys where 80% of high school students self report using AI on assignments.
I guess we could go back to giving exams soviet Russia style where you get a couple of questions that you have to answer orally in front of the whole class and that’s your grade. Not fun…
Always stunned by how much teachers can accuse without proof and invert the "innocent until proven guilty".
Honestly, students should have a course in "how the justice system works" (or at least should work). So should the teachers.
Student unions and similar entities should exist and be ready to intervene to help students in such situations.
This is nothing new, AI will just make this happen more often, revealing how stupid so many teachers are. But when someone spent thousands for a tool, which purports to be reliable, and is so quick to use, how can an average person resist it? The teacher is as lazy as the cheaters they intend to catch.
When I was in college, there was a cheating scandal for the final exam where somehow people got their hands on the hardest question of the exam.
The professor noticed it (presumably via seeing poor "show your work") and gave zero points on the question to everyone. And once you went to complain about your grade, she would ask you to explain the answer there in her office and work through the problem live.
I thought it was a clever and graceful way to deal with it.
I think this kind of approach is the root of (the US's) hustle culture. Instead of receiving a fair score, you get a zero and need to "hustle" and challenge your teacher.
The teacher effectively filtered out the shy boys/girls who are not brave enough to "hustle." Gracefully.
Lol, in 3rd grade algebra, a teacher called 2 of us in for cheating. She had us take the test again, I got the same exact horribly failing score (a 38%) and the cheater got a better score, so the teacher then knew who the cheater was. He just chose the wrong classmate to cheat of of.
I assume that the cheating student didn't know that he was copying answers from someone who was doing poorly. It was third graders after all; one wouldn't necessarily expect them to be able to pick the best target every time.
Except the power imbalance: position, experience, social, etc. meant that the vast majority just took the zero and never complained or challenged the prof. Sounds like your typical out-of-touch academic who thought they were super clever.
It's not great for the teacher though. They're the ones who will truly suffer from the proliferation of AI - increased complexity of work around spotting cheating 'solved' by a huge increase in time pressure. Faced with that teachers will have three options: accept AI detection as gospel without appeals and be accused of unfairness or being bad at the job by parents, spend time on appeals to the detriment of other duties leading to more accusations of being bad at the job, or leave teaching and get an easier (and probably less stressful and higher paid) job. Given those choices I'd pick the third option.
4. Use AI to talk to the student to find out if they understand.
Tests were created to save money, more students per teacher, we're just going back to the older, actually useful, method of talking to people to see if they understand what they've been taught.
You weren't asked to write an essay because someone wanted to read your essay, only to intuit that you've understood something
I really believe this is the way forward, but how do you make sure the AI is speaking to the student rather than to another AI impersonating the student? You could make it in person but that's a bit sad.
Both can be true at the same time. You outlined the objective, the money is an extra constraint (and let's be honest, when isn't money an extra constraint?)
I agree. Most campuses use a product called Turnitin, which was originally designed to check for plagiarism. Now they claim it can detect AI-generated content with about 80% accuracy, but I don’t think anyone here believes that.
I had Turn It In mark my work as plagiarism some years ago and I had to fight for it. It was clear the teacher wasn’t doing their job and blindly following the tool.
What happened is that I did a Q&A worksheet but in each section of my report I reiterated the question in italics before answering it.
The reiterated questions of course came up as 100% plagiarism because they were just copied from the worksheet.
This matches my experience pretty well. My high school was using it 15 years ago and it was a spotty, inconsistent morass even back then. Our papers were turned in over the course of the semester, and late into the year you’d get flagged for “plagiarizing” your own earlier paper.
80% accuracy could mean 0 false negatives and 20% false positives.
My point is that accuracy is a terrible metric here and sensitivity, specificity tell us much more relevant information to the task at hand. In that formulation, a specificity < 1 is going to have false positives and it isn't fair to those students to have to prove their innocence.
That's more like the false positive rate and false negative rate.
If we're being literal, accuracy is (number correct guesses) / (total number of guesses). Maybe the folks at turnitin don't actually mean 'accuracy', but if they're selling an AI/ML product they should at least know their metrics.
It depends on their test dataset. If the test set was written 80% by AI and 20% by humans, a tool that labels every essay as AI-written would have a reported accuracy of 80%. That's why other metrics such as specificity and sensitivity (among many others) are commonly reported as well.
Just speaking in general here -- I don't know what specific phrasing TurnItIn uses.
The promise (not saying that it works) is probably that 20% of people who cheated will not get caught. Not that 20% of the work marked as AI is actually written by humans.
I suppose 80% means you don't give them a 0 mark because the software says it's AI, you only do so if you have other evidence reinforcing the possibility.
you're missing out on the false positives though; catching 80% of cheaters might be acceptable but 20% false positives (not the same thing as 20% of the class) would not be acceptable. AI generated content and plagarism are completely different detection problems.
Had a professor use this but it was student-led. We had to run it through ourselves and change our stuff enough to get a high enough mark to pass TurnItIn. Avoided the false allegations problems at least.
There have always been problems like this. I had a classmate who wrote poems and short stories since age 6. No teacher believed she wrote those herself. She became a poet, translator and writer and admitted herself later in life that she wouldn't have believed it herself.
It's not that hard to prove that you did the work and not an AI. Show your work. Explain to the teacher why you wrote what you did, why that particular approach to the narrative appealed to you and you chose that as the basis for your work. Show an outline on which the paper was based. Show rough drafts. Explain how you revised the work, where you found your references, and why you retained some sources in the paper and not others.
To wit, show the teacher that YOU did the work and not someone else. If the teacher is not willing to do this with every student they accuse of malfeasance, they need to find another job. They're lazy as hell and suck at teaching.
Computer, show "my" work and explain to the teacher why "I" wrote what "I" did, describe why that particular approach to the narrative appealed to "me" and "I" chose that as the basis of "my" work. Produce an outline on which the paper could have been based and possible rough drafts, then explain how I could have revised the work to produce the final result.
I suspect this is going in the wrong direction. Telling a sandboxed AI to have a long conversation with a student to ensure they actually know what they're talking about, while giving minimal hints away, seems like the scalable solution. Let students tackle the material however they will, knowing that they will walk into class the next day and be automatically grilled on it, unaided. There's no reason a similar student couldn't have their essay fed into the AI and then asked questions about what they meant on it.
Once this becomes routine the class can become e.g. 10 minutes conversation on yesterday's topic, 40 minutes lecturing and live exercises again. Which is really just reinventing the "daily quiz" approach, but again the thing we are trying to optimize for is compliance.
Seems like this could be practically addressed by teachers adopting the TSA's randomized screening. That is, roll some dice to figure out which student on a given assignment comes in either for the oral discussion or-- perhaps in higher grades-- to write the essay in realtime.
It should be way easier than TSA's goal because you don't need to stop cheaters. You instead just need to ensure that you seed skills into a minimal number of achievers so that the rest of the kids see what the real target of education looks like. Kids try their best not to learn, but when the need kicks in they learn way better spontaneously from their peers than any other method.
Of course, this all assumes an effective pre-K reading program in the first place.
My high school history teacher gave me an F on my term paper. I asked him why, and he said it was "too good" for a high school student. The next day I dumped on his desk all the cited books, which were obscure and in my dad's extensive collection. He capitulated, but disliked me ever since.
> language models are more likely to suggest that speakers of [African American English] be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death.
This one is just so extra insidious to me, because it can happen even when a well-meaning human has already "sanitized" overt references to race/ethnicity, because the model is just that good at learning (bad but real) signals in the source data.
Family law judges, in my small experience, are so uninterested in the basic facts of a case that I would actually trust an LLM to do a better job. Not quite what you mean, but maybe there is a silver lining.
We are already (in the US) living in a system of soft social-credit scores administered by ad tech firms and non-profits. So “the algorithms says you’re guilty” has already been happening in less dramatic ways.
The new trick being used by some professors in college classes is to mandate a specific document editor with a history view. If the document has unusual copy/paste patterns or was written in unusual haste then they may flag it. That being said, they support use of ai in the class and have confidence the student is not able to one shot the assignment with ai.
Write it in something like Google docs that tracks changes and then share the link with the revision history.
If this is insufficient, then there are tools specifically for education contexts that track student writing process.
Detecting the whole essay being copied and pasted from an outside source is trivial. Detecting artificial typing patterns is a little more tricky, but also feasible. These methods dramatically increase the effort required to get away with having AI do the work for you, which diminishes the benefit of the shortcut and influences more students to do the work themselves. It also protects the honest students from false positives.
Thought it is a good idea at first, but can easily be defeated with typing out AI contents. One can add pauses/deletions/edits or true edits from joining ideas different AI outputs.
> Detecting artificial typing patterns is a little more tricky, but also feasible.
Keystroke dynamics can detect artificial typing patterns (copying another source by typing it out manually). If a student has to go way out of their way to make their behavior appear authentic then it's decreasing advantage of cheating and less students will do it.
If the student is integrating answers from multiple AI responses then maybe that's a good thing for them to be learning and the assessment should allow it.
Not 0 time, but yes, integrity preservation is an arms race.
The best solutions are in student motivations and optimal pedagogical design. Students who want to learn, and learning systems that are optimized for rate of learning.
Depends how you work. I've rarely (never?) drafted anything and almost all of the first approach ended up in the final result. It would look pretty close to "typed in the AI answer with very minor modifications after". I'm not saying that was a great way to do it, but I definitely wouldn't want to be failed for that.
There is a fractal pattern between authentic and inauthentic writing.
Crude tools (like Google docs revision history) can protect an honest student who engages in a typical editing process from false allegations, but it can also protect a dishonest student who fabricated the evidence, and fail to protect an honest student who didn't do any substantial editing.
More sophisticated tools can do a better job of untangling the fractal, but as with fractal shaped problems the layers of complexity keep going and there's no perfect solutions, just tools that help in some situations when used by competent users.
The higher Ed professors who really care about academic integrity are rare, but they are layering many technical and logistical solutions to fight back against the dishonest students.
Not really, also the timing of the saves won't reflect the expected work needing to be put in. Unless you are taking the same amount of time to feed in the AI output as a normal student used to actually write / edit the paper, at which point cheating is meaningless
Doesn't google docs have fairly robust edit history? If I was a student these days I'd either record my screen of me doing my homework, or at least work in google docs and share the edit history.
honest q: what would it look like from your perspective if someone worked in entirely different tools and then only moved their finished work to google docs at the end?
In this case, the school was providing chromebooks so Google Docs were the default option. Using a different computer isn’t inherently a negative signal - but if we are already talking about plagiarism concerns, I’m going to start asking questions that are likely to reveal your understanding of the content. If your understanding falters, I’m going to ask you to prove your abilities in a different way/medium/etc.
In general, I don’t really understand educators hyperventilating about LLM use. If you can’t tell what your students are independently capable of and are merely asking them to spit back content at you, you’re not doing a good job.
Not really, document editors save every few moments. Someone cheating with AI assistance will not have a similar saved version pattern as someone writing and editing themselves. And if one did have the same pattern, it would defeat the purpose of cheating because it would take a similar amount of time to pull off
I wrote a paper about building web applications in 10th grade a long time ago. When class was out the teacher asked me to stay for a minute after everybody left. He asked in disbelief, “did you really write that paper?”
I could see why he didn’t, so I wasn’t offended or defensive and started to tell him the steps required to build web apps and explained it in a manner he could understand using analogies. Towards the end of our conversation he could see I both knew about the topic and was enthusiastic about it. I think he was still a bit shocked that I wrote that paper, but he could tell from the way I talked about it that it was authentic.
It will be interesting to see how these situations evolve as AI gets even better. I suspect assessment will be more manual and in-person.
The funny part is that Googe has all the edit history data. In other words, it's a piece of cake for them to train a model that mimics human editing process.
The only thing prevents them from doing so is the fact Google is too big to sell a "plagiarism assistant."
I’m very tempted to write a tool that emulates human composition and types in assignments in a human-like way, just to force academia to deal with their issues sooner.
I seriously think the people selling AI detection tools to teachers should be sued into the ground by a coalition of state attorneys general, and that the tools should be banned in schools.
In my CS undergrad I had Doug Lea as a professor, really fantastic professor (best teacher I have ever had, bar none). He had a really novel way to handle homework hand ins, you had to demo the project. So you got him to sit down with you, you ran the code, he would ask you to put some inputs in (that were highly likely to be edge cases to break it). Once that was sufficient, he would ask you how you did different things, and to walk him through your code. Then when you were done he told you to email the code to him, and he would grade it. I am not sure how much of this was an anti-cheating device, but it required that you knew the code you wrote and why you did it for the project.
I think that AI has the possibility of weakening some aspects of education but I agree with Karpathy here. In class work, in person defenses of work, verbal tests. These were corner stones of education for thousands of years and have been cut out over the last 50 years or so outside of a few niche cases (Thesis defense) and it might be a good thing that these come back.
Yep, it's easy to shortcut AI plagiarism, but you need time. In most of the universities around the world (online universities especially), the number of students is way too big, while professors get more and more pressure on publishing and bureaucracy.
I did my masters in GaTech OMSCS (Chatgpt came out at the very end of my last semester). Tests were done with cameras on and it was recorded and then they were watched I think by TAs. Homework was done with automated checking and a plagiarism checker. Do you need to have in person proctoring via test centers or libraries? Video chats with professors? I am not sure. Projects are importants, but maybe they need to become a minority of grades and more being based on theory to circumvent AI?
It's not even about plagiarism. But, sure, 1:1 or even 1:few instruction is great but even at elite schools is not really very practical. I went to what's considered a very good engineering school and classes with hundreds of students was pretty normal.
Ironically the practically of such instruction goes down as the status of the school goes up. I got a lot of 1:1 or 1:few time with my community college professors.
The TL:DR of every "AI vs Schools, what should teachers do?" article boils down to exactly this: Talk with the students 1-1. You can fake an essay, you can't fake a conversation about the topic at hand.
Maybe as a society we can take some of the productivity gains from AI and funnel them into moving teaching away from scantrons and formulaic essays. I want to be optimistic.
In college I had a professor assign us to write a 100% plagiarized paper. You had to highlight every word in a color associated with the source. You couldn't plagiarize more then one sequential sentence from a single source.
It ended up being harder then writing an ordinary paper but taught us all a ton about citation and originality. It was a really cool exercise.
I imagine something similar could be done to teach students to use AI as a research tool rather then as a plagiarization machine.
I think legacy schooling just needs to be reworked. Kids should be doing way more projects that demonstrate the integration of knowledge and skills, rather than focusing so much energy on testing and memorization. There's probably a small core of things that really must be fully integrated and memorized, but for everything else you should just give kids harder projects which they're expected to solve by leveraging all the tools at their disposal. Focus on teaching kids how to become high-agency beings with good epistemics and a strong math core. Give them experiments and tools to play around and actually understand how things work. Bring back real chemistry labs and let kids blow stuff up.
The key issue with schools is that they crush your soul and turn you into a low-agency consumer of information within a strict hierarchy of mind-numbing rules, rather than helping you develop your curiosity hunter muscles to go out and explore. In an ideal world, we would have curated gardens of knowledge and information which the kids are encouraged to go out and explore. If they find some weird topic outside the garden that's of interest to them, figure out a way to integrate it.
I don't particularly blame the teachers for the failings of school though, since most of them have their hands tied by strict requirements from faceless bureaucrats.
As much as I hated schooling, I do want to say that there are parts of learning that are simply hard. There are parts that you can build enthusiasm for with project work and prioritizing for engagement. But there are many things that people should learn that will require drudgery to learn and won't excite all people.
Doing derivatives, learning the periodic table, basic language and alphabet skills, playing an instrument are foundational skills that will require deliberate practice to learn, something that isn't typically part of project based learning. At some point in education with most fields, you will have to move beyond concepts and do some rote memorization and repetition of principles in order to get to higher level concepts. You can't gamify your way out of education, despite our best attempts to do so.
Most learning curves in the education system today are very bumpy and don't adapt well to the specific student. Students get stuck on big bumps or get bored and demotivated at plateaus.
AI has potential to smooth out all curves so that students can learn faster and maximize time in flow.
I've spent literally thousands of hours thinking about this (and working on it). The future of education will be as different from today as today is to 300 years ago.
Kids used to get smacked with a stick if they spelled a word wrong.
The point is that the education system has come a long way in utilizing STEM to make education more efficient (helping students advance faster and further with less resources) and it will continue to go a long way further.
People thought the threat of physical violence was a good way to teach. We have learned better. What else is there for us to learn? What have we already learned but just don't have the resources to apply?
I've met many educators who have told me stories of ambitions learning goals for students that didn't work because there weren't the time or resources to facilitate them properly.
Often instructors are stuck trading off between inauthentic assessments that have scalable evaluation methods or authentic exercises that aren't feasible to evaluate at scale and so evaluation is sparse, incomplete or students only receive credit for completion.
But testing and paper assessments are cheap and feasible for mass education. There are only so many workshop projects you can have before you run out of budget.
Having had some experience teaching and designing labs and evaluating students in my opinion there is basically no problem that can't be solved with more instructor work.
The problem is that the structure pushes for teaching productivity which basically directly opposes good pedagogy at this point in the optimization.
Some specifics:
1. Multiple choice sucks. It's obvious that written response better evaluates students and oral is even better. But multiple choice is graded instantly by a computer. Written response needs TAs. Oral is such a time sink and needs so many TAs and lots of space if you want to run them in parallel.
1.5 Similarly having students do things on computers is nice because you don't have to print things and even errors in the question can be fixed live and you can ask students to refresh the page. But if the chatbots let them cheat too easily on computers doing hand written assesments sucks cause you have to go arrange for printing and scanning.
2. Designing labs is a clear LLM tradeoff. Autograded labs with testbenches and fill in the middle style completetions or API completetions are incredibly easy to grade. You just pull the commit before some specific deadline and run some scripts.
You can do 200 students in the background when doing other work its so easy. But the problem is that LLMS are so good at fill in the middle and making testbenches pass.
I've actually tried some more open ended labs before and its actually very impressive how creative students are. They are obviously not LLMs there is this diversity in thought and simplicity of code that you do not get with ChatGPT.
But it is ridiculously time consuming to pull people's code and try to run open ended testbenches that they have created.
3. Having students do class presentations is great for evaluating them. But you can only do like 6 or 7 presentations in a 1 hr block. You will need to spend like a week even in a relatively small class.
4. What I will say LLMs are fun for are having students do open ended projects faster with faster iterations. You can scope creep them if you expect expect to use AI coding.
I tried that once. Specifically because I wanted to see if we could leverage some sort of productivity enhancements.
I was using a local LLM around 4B to 14B, I tried Phi, Gemma, Qwen, and LLama. The idea was to prompt the LLM with the question, the answer key/rubric, and the student answer. The student answer at the end did some prompt caching to make it much faster.
It was okay but not good, there were a lot of things I tried:
* Endlessly messing with the prompt.
* A few examples of grading.
* Messing with the rubric to give more specific instructions.
* Average of K.
* Think step by step then give a grade.
It was janky and I'll throw it up to local LLMs at the time being somewhat too stupid for this to be reasonable. They basically didn't follow the rubric very well. Qwen in particular was very strict giving zeros regardless of the part marks described in the answer key as I recall.
I'm sure with the correct type of question and correct prompt and a good GPU it could work but it wasn't as trivially easy as I had thought at the time.
I think part of the reason AI is having such a negative effect on schools in particular is because of how many education processes are reliant on an archaic, broken way of "learning." So much of it is focused upon memorization and regurgitation of information (which AI is unmatched at doing).
School is packed with inefficiency and busywork that is completely divorced from the way people learn on their own. In fact, it's pretty safe to say you could learn something about 10x by typing it into an AI chat bot and having it tailor the experience to you.
Teachers worry about AI because they do not just care about memorization. Before AI, being able to write cohesive essays about a subject is a good proxy to prove your understanding beyond simple memorization. Now it's gone.
A lazy, irresponsible teacher who only cares about memorization will just grade students by in-class multi choices tests exclusively and call it a day. They don't need to worry about AI at all.
> So much of it is focused upon memorization and regurgitation of information, which AI is unmatched at doing.
This applies both to education, and to what people need to know to do work. Knowing all the written stuff is less valuable. Automated tools can been able to look it up since the Google era. Now they can work with what they look up.
There was a time when programmers poured over Fundamental Algorithms. No one does that today. When needed, you find existing code that does that stuff. Probably better than you could write. Who codes a hash table today?
Yes, the biggest problem with authentic exercises is evaluating the students' actions and giving feedback. The problem is that authentic assessments didnt previous scale (e.g. what worked in 1:1 coaching or tutoring couldn't be done for a whole classroom). But AI can scale them.
It seems like AI will destroy education but it's only breaking the old education system, it will also enable a new and much better one. One where students make more and faster progress developing more relevant and valuable skills.
Education system uses multiple choice quizzes and tests because their grading can be automated.
But when evaluation of any exercise can be automated with AI, such that students can practice any skill with iterative feedback at the pace of their own development, so much human potential will be unlocked.
Memorizing and tests at school are the archaic approach that schools don't believe in anymore (at least the school board my kids are at), but they happen to be AI proof.
It's the softer, no memorizing, no tests, just assignments that you can hand in at anytime because there's no deadlines, and grades don't matter, type of education that is particularly useless with AI.
> So much of it is focused upon memorization and regurgitation of information (which AI is unmatched at doing).
No, lots of classes are focused on producing papers which aren't just memorization and regurgitation, but generative AI is king at... Generating text... So that class of work output is suspect now
It's a fair question, but there's maybe a bit of US defaultism baked in? If I look
back at my exams in school
they were mostly closed-book written + oral examination, nothing would really need to change.
A much bigger question is what to teach assuming we get models much more powerful than those we have today. I'm still confident there's an irreducible hard core in most subjects that's well worth knowing/training, but it might take some soul searching.
With my partner we have been working to invert the overall model.
She started grading conversation than the students have with LLMs.
From the question that the students ask, it is obvious who knows the material and who is struggling.
We do have a custom setup, so that she creates an homework. There is a custom prompt to avoid the LLM answering the homework question. But thats pretty much it.
The results seems promising, with students spending 30m or so going back and forth with the LLMs.
If any educator wants to Ty or is interested in more information, let me know and we can see how we collaborate.
As a teacher, I try to keep an open mind, but consistently I can find out in 5 minutes of talking to a student if they understand the material. I might just go all in for the oral exams.
> The students remain motivated to learn how to solve problems without AI because they know they will be evaluated without it in class later.
Learning how to prepare for in-class tests and writing exercises is a very particular skillset which I haven't really exercised a lot since I graduated.
Never mind teaching the humanities, for which I think this is a genuine crisis, in class programming exams are basically the same thing as leetcode job interviews, and we all know what a bad proxy those are for "real" development work.
> in class programming exams are basically the same thing as leetcode job interviews, and we all know what a bad proxy those are for "real" development work.
Confusing university learning for "real industry work" is a mistake and we've known it's a mistake for a while. We can have classes which teach what life in industry is like, but assuming that the role of university is to teach people how to fit directly into industry is mistaking the purpose of university and K-12 education as a whole.
Writing long-form prose and essays isn't something I've done in a long time, but I wouldn't say it was wasted effort. Long-form prose forces you to do things that you don't always do when writing emails and powerpoints, and I rely on those skills every day.
There's no mistake there for all the students looking at job listings that treat having a college degree as a hard prerequisite for even being employable.
Here is my proposal for AI in schools: raise the bar dramatically. Rather than trying to prevent kids from using AI, just raise the expectations of what they should accomplish with it. They should be setting really lofty goals rather than just doing the same work with less effort.
AI doesn't help you do higher quality work. It helps you do (or imitate) mediocre work faster. But thing is, it is hard to learn how to do excellent work without learning to do mediocre work first.
Code quality is still a culture and prioritisation issue more than a tool issue. You can absolutely write great code using AI.
AI code review has unquestionably increased the quality of my code by helping me find bugs before they make it to production.
AI coding tools give me speed to try out more options to land on a better solution. For example, I wrote a proxy, figured out problems with that approach, and so wrote a service that could accomplish the same thing instead. Being able to get more contact with reality, and seeing how solutions actually work before committing to them, gives you a lot of information to make better decisions.
But then you still need good practices like code review, maintaining coding standards, and good project management to really keep code quality high. AI doesn’t really change that.
that is what they do in the software industry, before it was let me catch you off guard with asking how to reverse a linked list, now its leetcode questions that are so hard that you need to know and study them weekly, and prep for a year, interviewer can tell if you started prep 3 weeks prior
"You have to assume that any work done outside classroom has used AI."
That is just such a wildly cynical point of view, and it is incredibly depressing. There is a whole huge cohort of kids out there who genuinely want to learn and want to do the work, and feel like using AI is cheating. These are the kids who, ironically, AI will help the most, because they're the ones who will understand the fundamentals being taught in K-12.
I would hope that any "solution" to the growing use of AI-as-a-crutch can take this cohort of kids into consideration, so their development isn't held back just to stop the less-ethical student from, well, being less ethical.
Well, it seems the vast majority doesn't care about cheating, and is using AI for everything. And this is from primary school to university.
It's not just that AI makes it simpler, so many pupils cannot concentrate anymore. Tiktok and others have fried their mind. So AI is a quick way out for them. Back to their addiction.
What possible solution could prevent this? The best students are learning on their own anyways, the school can't stop students using AI for their personal learning.
There was a reddit thread recently that asked the question, are all students really doing worse, and it basically said that, there are still top performers performing toply, but that the middle has been hollowed out.
So I think, I dunno, maybe depressing. Maybe cynical, but probably true. Why shy away from the truth?
And by the way, I would be both. Probably would have used AI to further my curiosity and to cheat. I hated school, would totally cheat to get ahead, and am now wildly curious and ambitious in the real world. Maybe this makes me a bad person, but I don't find cheating in school to be all that unethical. I'm paying for it, who cares how I do it.
Sure, but the point is that if 5% of students are using AI then you have to assume that any work done outside classroom has used AI, because otherwise you're giving a massive advantage to the 5% of students who used AI, right?
It seems like a good path forward is to somewhat try to replicate the idea of "once you can do it yourself, feel free to use it going forward" (knowing how various calculator operations work before you let it do it for you).
I'm curious if we instead gave students an AI tool, but one that would intentionally throw in wrong things that the student had to catch. Instead of the student using LLMs, they would have one paid for by the school.
This is more brainstorming then a well thought-out idea, but I generally think "opposing AI" is doomed to fail. If we follow a montessori approach, kids are naturally inclined to want to learn thing, if students are trying to lie/cheat, we've already failed them by turning off their natural curiosity for something else.
I agree, I think schools and universities need to adapt, just like calculators, these things aren't going away. Let students leverage AI as tools and come out of Uni more capable than we did.
AI _do_ currently throw in an occasional wrong thing. Sometimes a lot. A students job needs to be verifying and fact checking the information the AI is telling them.
The student's job becomes asking the right questions and verifying the results.
So it is feasible (in principle) to give every student a different exam!
You’d use AI to generate lots of unique exams for your material, then ensure they’re all exactly the same difficulty (or extremely extremely close) by asking an LLM to reject any that are relatively too hard or too easy. Once you have generated enough individual exams, assign them to your students in your no-AI setting.
Code that the AI writes would be used to grade them.
- AI is great at some things.
- Code is great at other things.
- AI is bad at some things code is great for.
- AI is great at coding.
Therefore, leverage AI to quickly code up deterministic and fast tools for the tasks where code is best.
And to help exams be markable by code, it makes sense to be smart about exam structure - eg. only ask questions with binary answers or multiple choice so you don’t need subjective judgment of correctness.
except (like it or not) students are in direct competition with each other. Unique assessments would be impossible to defend the first time a student claimed your "unfair" test cost them a job, scholarship or other competitive opportunity.
This is the correct take. To contrast the Terance Tao piece from earlier (https://news.ycombinator.com/item?id=46017972), AI research tools are increasingly useful if you're a competent researcher that can judge the output and detect BS. You can't, however, become a Terence Tao by asking AI to solve your homework.
So, in learning environments we might not have an option but to open the floodgates to AI use, but abandon most testing techniques that are not, more or less, pen and paper, in-person. Use AI as much as you want, but know that as a student you'll be answering tests armed only with your brain.
I do pity English teachers that have relied on essays to grade proficiency for hundreds of years. STEM fields has an easier way through this.
Andrej and Garry Trudeau are in agreement that "blue book exams" (I.e. the teacher gives you a blank exam booklet, traditionally blue) to fill out in person for the test, after confiscating devices, is the only way to assess students anymore.
My 7 year old hasn't figured out how to use any LLMs yet, but I'm sure the day will come very soon. I hope his school district is prepared. They recently instituted a district-wide "no phones" policy, which is a good first step.
That was how I took most of my school and university exams. I hated it then and I'd hate it now. For humanities, at least, it felt like a test of who could write the fastest (one which I fared well at, too, so it's not case of sour grapes).
I'd be much more in favour of oral examinations. Yes, they're more resource-intensive than grading written booklets, but it's not infeasible. Separately, I also hope it might go some way to lessening the attitude of "teaching to the test".
Blue book was the norm for exams in my social science and humanities classes way after every assignment was typed on a computer (and probably a laptop, by that time) with Internet access.
I guess high schools and junior highs will have to adopt something similar, too. Better condition those wrists and fingers, kids :-)
I'm oldish, but when I was in college in the late 90s we typed a huge volume of homework (I was a history & religious studies double major as an undergrad), but the vast majority of our exams were blue books. There were exceptions where the primary deliverable for the semester was a lengthy research paper, but lots and lots of blue books.
Oh how I hated those as a student. Handwriting has always been a slow and uncomfortable process for me. Yes, I tried different techniques of printing and cursive as well as better pens. Nothing helped. Typing on a keyboard is just so much faster and more fluent.
It's a shame that some students will again be limited by how fast they can get their thoughts down on a piece of paper. This is such an artificial limitation and totally irrelevant to real world work now.
Maybe this is a niche for those low distraction writing tools that pop up from time to time. Or a school managed Chromebook that’s locked to the exam page.
> My 7 year old hasn't figured out how to use any LLMs yet, but I'm sure the day will come very soon. I hope his school district is prepared. They recently instituted a district-wide "no phones" policy, which is a good first step.
This sounds as if you expect that it will become possible to access an LLM in class without a phone or other similar device. (Of course, using a laptop would be easily noticed.)
The phone ban certainly helps make such usage noticeable in class, but I'm not sure the academic structure is prepared to go to in-person assessments only. The whole thread is about homework / out of class work being useless now.
1. Corporate interests want to sell product
2. Administrators want a product they can use
3. Compliance people want a checkbox they can check
4. Teachers want to be ablet to continue what they have been doing thus far within the existing ecosystem
5. Parents either don't know, don't care, or do, but are unable to provide a viable alternative or, can and do provide it
We have had this conversation ( although without AI component ) before. None of it is really secret. The question is really what is the actual goal. Right now, in US, education is mostly in name only -- unless you are involved ( which already means you are taking steps to correct it ) or are in the right zip code ( which is not a guarantee, but it makes your kids odds better ).
I made a tool for this! It's an essay writing platform that tracks the edits and keystrokes rather than the final output, so its AI detection accuracy is _much_ higher than other tools:
https://collie.ink/
I’ve been following this approach since last school year. I focus on in-class work and home-time is for reading and memorization. My classmates still think classrooms are for lecturing, but it's coming. The paper-and-pen era is back to school!
I did a lot of my blog and book writing before these AI tools, but now I show my readers images of handwritten notes and drafts (more out of interest than demonstrating proof of work).
besides the poor UX for unauthenticated users, i would rather not view ads from advertisers who still pay X for the access to my eyeballs (in the event i'm using a browser that doesn't block them to begin with).
This couldn’t have happened at a better time. When I was young my parents found a schooling system that had minimal homework so I could play around and live my life. I’ve moved to a country with a lot less flexibility. Now when my kids will soon be going to school, compulsory homework will be obsolete.
Zero homework grades will be ideal. Looking forward to this.
If AI gets us reliably to a flipped classroom (=research at home, work through work during class) then I'm here for it. Homework in the traditional sense is an anti pattern.
1. Assume printing press exists
2. Now there's no need for a teacher to stand up and deliver information by talking to a class for 60 mins
3. Therefore students can read at home (or watch prepared videos) and test their learning in class where there's experts to support them
4. Given we only need 1 copy of the book/video/interactive demo, we can spend wayyyyy more money making it the best it can possibly be
What's sad is it's 500 years later and education has barely changed
> What's sad is it's 500 years later and education has barely changed
From my extensive experience of four years of undergrad, the problem in your plan is "3. Therefore students can read at home " - half the class won't do the reading, and the half that did won't get what it means until they go to lecture[1].
[1] If the lecturer is any good at all. If he spends most of his time ranting about his ex-wife...
Most of what I learned in college was only because I did homework and struggled to figure it out myself. Classroom time was essentially just a heads up to what I'll actually be learning myself later.
Granted, this was much less the case in grade school - but if students are going to see homework for the first time in college, I can see problems coming up.
If you got rid of homework throughout all of the "standard" education path (grade school + undergrad), I would bet a lot of money that I'd be much dumber for it.
> but if students are going to see homework for the first time in college, I can see problems coming up.
If the concept is too foreign for them, I'm sure we could figure out how to replicate the grade school environment. Give them their 15 hours/week of lecture, and then lock them in a classroom for the 30 hours they should spend on homework.
this is a very American issue. In my entire student career in Italy, home assignments were never graded. Maybe you had a project or two through university, but otherwise I got all my grades for onsite tests.
A detector is easy to write, simply monitor the kid’s computer and phone use. AI is ruining school but it will be solved in the lowest resistance way possible.
This is exactly why I'm focusing on job readiness and remediation rather than the education system. I think working all this out is simply too complex for a system with a lot of vested interest and that doesn't really understand how AI is evolving. There's an arms race between students, teachers, and institutions that hire the students.
It's simply too complex to fix. I think we'll see increased investment by corporates who do keep hiring on remediating the gaps in their workforce.
Most elite institutions will probably increase their efforts spent on interviewing including work trials. I think we're already seeing this with many of the elite institutions talking about judgment, emotional intelligence critical thinking as more important skills.
My worry is that hiring turns into a test of likeability rather than meritocracy (everyone is a personality hire when cognition is done by the machines)
Source: I'm trying to build a startup (Socratify) a bridge for upskilling from a flawed education system to the workforce for early stage professionals
I agree that focus should just shift to in-class work so that students are left free to do whatever they want once they are done for the day at school. Homework and at-home assignments are lazy handovers.
Also, all of these AI threats to public education can be mitigated if we just step 1-2 decades back and go the pen-and-paper way. I am yet to see any convincing argument in favor of digital/screen-based teaching methods being superior in any way than the traditional ones, on the contrary I have seen thousands of arguments against them.
How about just dispense with the AI nonsense in education and go to totally in-person, closed-book, manually-written, proctored exams? No homework, no assignments, no projects. Just pure mind-to-paper writing in a bare room under the eye of an examiner. Those that want to will learn and will produce intelligent work regardless of setting.
This doesn't adress the point that AI can replace going to school. AI can be your perfect personal tutor to help you learn thing 1:1. Needing to have a teacher and prove to them that you know what they teached will become a legacy concept. That we have an issue of AI cheating at school is in my eyes a temporary issue.
ChatGPT just told me to put the turkey in my toaster oven legs facing the door, and you think it can replace school. Unless there is a massive architectural change that can be provably verified by third parties, this can never be. I’d hate for my unschooled surgeon to check an llm while I’m under.
Don't worry, someone will put another hack on top the model to teach it to handle this specific case better. That will totally fix the problem, right? Right?
A trained professional making their best guess is far more capable and trustworthy than the slop LLMs put out. So yeah, winging it is a good alternative here.
I see, I overlooked the 'toaster' part. That's a good world model benchmark question for models and a good reading comprehension question for humans. :-P
GPT 5.1 Pro made the same mistake ("Face the legs away from the door.") Claude Sonnet 4.5 agreed but added "Note: Most toaster ovens max out around 10-12 pounds for a whole turkey."
Gemini 3 acknowledged that toaster ovens are usually very compact and that the legs shouldn't be positioned where they will touch the glass door. When challenged, it hand-waved something to the effect of "Well, some toaster ovens are large countertop convection units that can hold up to a 12-pound turkey." When asked for a brand and model number of such an oven, it backtracked and admitted that no toaster oven would be large enough.
Changing the prompt to explicitly specify a 12-pound turkey yielded good answers ("A 12-pound turkey won't fit in a toaster oven - most max out at 4-6 pounds for poultry. Attempting this would be a fire hazard and result in dangerously uneven cooking," from Sonnet.)
It is considered valuable and worthwhile for a society to educate all of its children/citizens. This means we have to develop systems and techniques to educate all kinds of people, not just the ones who can be dropped off by themselves at a library when they turn five, and picked up again in fifteen years with a PHD.
Sure. People who are self motivated are who will benefit the earliest. If a society values ensuring every single citizen gets a baseline education they can figure out how to get an AI to persuade or trick people into learning better than a human could.
For someone that wants to learn, I agree with this 100%. AI has been great at teaching me about 100s of topics.
I don't yet know how we get AI to teach unruly kids, or kids with neurodivergencies. Perhaps, though, the AI can eventually be vastly superior to an adult because of the methods it can use to get through to the child, keep the child interested and how it presents the teaching in a much more interactive way.
One of my students recently came to me with an interesting dilemma. His sister had written (without AI tools) an essay for another class, and her teacher told her that an "AI detection tool" had classified it as having been written by AI with "100% confidence". He was going to give her a zero on the assignment.
Putting aside the ludicrous confidence score, the student's question was: how could his sister convince the teacher she had actually written the essay herself? My only suggestion was for her to ask the teacher to sit down with her and have a 30-60 minute oral discussion on the essay so she could demonstrate she in fact knew the material. It's a dilemma that an increasing number of honest students will face, unfortunately.
> My only suggestion was for her to ask the teacher to sit down with her and have a 30-60 minute oral discussion on the essay so she could demonstrate she in fact knew the material.
This sounds like, a good solution? It’s the exception case, so shouldn’t be constant (false positives), although I suppose this fails if everyone cheats and everyone wants to claim innocence.
You hinted to it but at what point are you basically giving individual oral exams to the entire class for every assignment? There are surveys where 80% of high school students self report using AI on assignments.
I guess we could go back to giving exams soviet Russia style where you get a couple of questions that you have to answer orally in front of the whole class and that’s your grade. Not fun…
Always stunned by how much teachers can accuse without proof and invert the "innocent until proven guilty".
Honestly, students should have a course in "how the justice system works" (or at least should work). So should the teachers.
Student unions and similar entities should exist and be ready to intervene to help students in such situations.
This is nothing new, AI will just make this happen more often, revealing how stupid so many teachers are. But when someone spent thousands for a tool, which purports to be reliable, and is so quick to use, how can an average person resist it? The teacher is as lazy as the cheaters they intend to catch.
In the United States, we all used to take a required course called Civics.
We learned how government and justice worked.
When I was in college, there was a cheating scandal for the final exam where somehow people got their hands on the hardest question of the exam.
The professor noticed it (presumably via seeing poor "show your work") and gave zero points on the question to everyone. And once you went to complain about your grade, she would ask you to explain the answer there in her office and work through the problem live.
I thought it was a clever and graceful way to deal with it.
I think this kind of approach is the root of (the US's) hustle culture. Instead of receiving a fair score, you get a zero and need to "hustle" and challenge your teacher.
The teacher effectively filtered out the shy boys/girls who are not brave enough to "hustle." Gracefully.
I don't even think it is about shyness. Some professors do not respond well to being challenged on every possible exam question.
The time spent challenging exam grades is usually better spent studying for the next exam. I've never gotten a significant grade improvement from it.
This is completely incorrect. Hustle culture is what made kids cheat in the first place.
She didn't ask them to challenge them, she asked them additional questions. The test already asks them questions.
If you are really shy, a culture where no one cheats is far better because your actual ability and intelligence shines through
> And once you went to complain about your grade
Only if she advertised that option somehow. I worked two jobs in college, I didn't take time off to go complain about my grades.
Not to mention there'd be at least a few students too timid to challenge the teacher, even if they knew they got it right.
Lol, in 3rd grade algebra, a teacher called 2 of us in for cheating. She had us take the test again, I got the same exact horribly failing score (a 38%) and the cheater got a better score, so the teacher then knew who the cheater was. He just chose the wrong classmate to cheat of of.
I don't get it. If she called you too it was because your results were good, no? Who cheats to get a bad result?
I assume that the cheating student didn't know that he was copying answers from someone who was doing poorly. It was third graders after all; one wouldn't necessarily expect them to be able to pick the best target every time.
The students had identical answers, I presume
Which, in a subject like algebra, is extremely suspicious ("how could both of them get the exact same WRONG answer?").
Except the power imbalance: position, experience, social, etc. meant that the vast majority just took the zero and never complained or challenged the prof. Sounds like your typical out-of-touch academic who thought they were super clever.
This is a nice approach. The students who know the material, or even who manually prepare before seeing the prof achieve the objective of learning.
It's not great for the teacher though. They're the ones who will truly suffer from the proliferation of AI - increased complexity of work around spotting cheating 'solved' by a huge increase in time pressure. Faced with that teachers will have three options: accept AI detection as gospel without appeals and be accused of unfairness or being bad at the job by parents, spend time on appeals to the detriment of other duties leading to more accusations of being bad at the job, or leave teaching and get an easier (and probably less stressful and higher paid) job. Given those choices I'd pick the third option.
4. Use AI to talk to the student to find out if they understand.
Tests were created to save money, more students per teacher, we're just going back to the older, actually useful, method of talking to people to see if they understand what they've been taught.
You weren't asked to write an essay because someone wanted to read your essay, only to intuit that you've understood something
I really believe this is the way forward, but how do you make sure the AI is speaking to the student rather than to another AI impersonating the student? You could make it in person but that's a bit sad.
> Tests were created to save money
I'm skeptical. Tests are a way of standardizing the curriculum and objectively determining if the lessons were learned.
Both can be true at the same time. You outlined the objective, the money is an extra constraint (and let's be honest, when isn't money an extra constraint?)
I agree. Most campuses use a product called Turnitin, which was originally designed to check for plagiarism. Now they claim it can detect AI-generated content with about 80% accuracy, but I don’t think anyone here believes that.
I had Turn It In mark my work as plagiarism some years ago and I had to fight for it. It was clear the teacher wasn’t doing their job and blindly following the tool.
What happened is that I did a Q&A worksheet but in each section of my report I reiterated the question in italics before answering it.
The reiterated questions of course came up as 100% plagiarism because they were just copied from the worksheet.
This matches my experience pretty well. My high school was using it 15 years ago and it was a spotty, inconsistent morass even back then. Our papers were turned in over the course of the semester, and late into the year you’d get flagged for “plagiarizing” your own earlier paper.
Funny how it's the teachers that are plagiarizing the work of the tools.
80% is catastrophic though. In a classroom of 30 all honest pupils, 6 will get a 0 mark because the software says its AI?
80% accuracy could mean 0 false negatives and 20% false positives.
My point is that accuracy is a terrible metric here and sensitivity, specificity tell us much more relevant information to the task at hand. In that formulation, a specificity < 1 is going to have false positives and it isn't fair to those students to have to prove their innocence.
That's more like the false positive rate and false negative rate.
If we're being literal, accuracy is (number correct guesses) / (total number of guesses). Maybe the folks at turnitin don't actually mean 'accuracy', but if they're selling an AI/ML product they should at least know their metrics.
It depends on their test dataset. If the test set was written 80% by AI and 20% by humans, a tool that labels every essay as AI-written would have a reported accuracy of 80%. That's why other metrics such as specificity and sensitivity (among many others) are commonly reported as well.
Just speaking in general here -- I don't know what specific phrasing TurnItIn uses.
The promise (not saying that it works) is probably that 20% of people who cheated will not get caught. Not that 20% of the work marked as AI is actually written by humans.
I suppose 80% means you don't give them a 0 mark because the software says it's AI, you only do so if you have other evidence reinforcing the possibility.
no, you multiply their result by .8 to account for the "uncertainty"! /s
I think it means every time AI is used, it will detect it 80% of the time. Not that 20% of the class will marked as using AI.
you're missing out on the false positives though; catching 80% of cheaters might be acceptable but 20% false positives (not the same thing as 20% of the class) would not be acceptable. AI generated content and plagarism are completely different detection problems.
I have had Turnitin flag my work as plagiarism for quotes from the relevant text that were quite clearly indicated as quotes.
It's shit software for schools and teachers to cover their ass. Nothing more, and deserves no more attention.
Had a professor use this but it was student-led. We had to run it through ourselves and change our stuff enough to get a high enough mark to pass TurnItIn. Avoided the false allegations problems at least.
> but I don’t think anyone here believes that.
All it takes is one moron with power and a poor understanding of statistics.
There have always been problems like this. I had a classmate who wrote poems and short stories since age 6. No teacher believed she wrote those herself. She became a poet, translator and writer and admitted herself later in life that she wouldn't have believed it herself.
It's not that hard to prove that you did the work and not an AI. Show your work. Explain to the teacher why you wrote what you did, why that particular approach to the narrative appealed to you and you chose that as the basis for your work. Show an outline on which the paper was based. Show rough drafts. Explain how you revised the work, where you found your references, and why you retained some sources in the paper and not others.
To wit, show the teacher that YOU did the work and not someone else. If the teacher is not willing to do this with every student they accuse of malfeasance, they need to find another job. They're lazy as hell and suck at teaching.
I agree, it isn't hard! Watch:
Computer, show "my" work and explain to the teacher why "I" wrote what "I" did, describe why that particular approach to the narrative appealed to "me" and "I" chose that as the basis of "my" work. Produce an outline on which the paper could have been based and possible rough drafts, then explain how I could have revised the work to produce the final result.
I suspect this is going in the wrong direction. Telling a sandboxed AI to have a long conversation with a student to ensure they actually know what they're talking about, while giving minimal hints away, seems like the scalable solution. Let students tackle the material however they will, knowing that they will walk into class the next day and be automatically grilled on it, unaided. There's no reason a similar student couldn't have their essay fed into the AI and then asked questions about what they meant on it.
Once this becomes routine the class can become e.g. 10 minutes conversation on yesterday's topic, 40 minutes lecturing and live exercises again. Which is really just reinventing the "daily quiz" approach, but again the thing we are trying to optimize for is compliance.
Seems like this could be practically addressed by teachers adopting the TSA's randomized screening. That is, roll some dice to figure out which student on a given assignment comes in either for the oral discussion or-- perhaps in higher grades-- to write the essay in realtime.
It should be way easier than TSA's goal because you don't need to stop cheaters. You instead just need to ensure that you seed skills into a minimal number of achievers so that the rest of the kids see what the real target of education looks like. Kids try their best not to learn, but when the need kicks in they learn way better spontaneously from their peers than any other method.
Of course, this all assumes an effective pre-K reading program in the first place.
> Kids try their best not to learn
Often it is more work to cheat than just learn it.
My high school history teacher gave me an F on my term paper. I asked him why, and he said it was "too good" for a high school student. The next day I dumped on his desk all the cited books, which were obscure and in my dad's extensive collection. He capitulated, but disliked me ever since.
Now imagine this but its a courtroom and you're facing 25 years
https://news.ycombinator.com/item?id=14238786 ("Sent to Prison by a Software Program’s Secret Algorithms (nytimes.com)")
https://news.ycombinator.com/item?id=14285116 ('Justice.exe: Bias in Algorithmic sentencing (justiceexe.com)")
https://news.ycombinator.com/item?id=43649811 ("Louisiana prison board uses algorithms to determine eligility for parole (propublica.org)")
https://news.ycombinator.com/item?id=11753805 ("Machine Bias (propublica.org)")
https://pmc.ncbi.nlm.nih.gov/articles/PMC11374696/
> language models are more likely to suggest that speakers of [African American English] be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death.
This one is just so extra insidious to me, because it can happen even when a well-meaning human has already "sanitized" overt references to race/ethnicity, because the model is just that good at learning (bad but real) signals in the source data.
Family law judges, in my small experience, are so uninterested in the basic facts of a case that I would actually trust an LLM to do a better job. Not quite what you mean, but maybe there is a silver lining.
We are already (in the US) living in a system of soft social-credit scores administered by ad tech firms and non-profits. So “the algorithms says you’re guilty” has already been happening in less dramatic ways.
The legal system has never been so easy thanks to Cinco e-Trial!
https://www.youtube.com/watch?v=XL2RLTmqG4w
The new trick being used by some professors in college classes is to mandate a specific document editor with a history view. If the document has unusual copy/paste patterns or was written in unusual haste then they may flag it. That being said, they support use of ai in the class and have confidence the student is not able to one shot the assignment with ai.
Write it in something like Google docs that tracks changes and then share the link with the revision history.
If this is insufficient, then there are tools specifically for education contexts that track student writing process.
Detecting the whole essay being copied and pasted from an outside source is trivial. Detecting artificial typing patterns is a little more tricky, but also feasible. These methods dramatically increase the effort required to get away with having AI do the work for you, which diminishes the benefit of the shortcut and influences more students to do the work themselves. It also protects the honest students from false positives.
Thought it is a good idea at first, but can easily be defeated with typing out AI contents. One can add pauses/deletions/edits or true edits from joining ideas different AI outputs.
> Detecting artificial typing patterns is a little more tricky, but also feasible.
Keystroke dynamics can detect artificial typing patterns (copying another source by typing it out manually). If a student has to go way out of their way to make their behavior appear authentic then it's decreasing advantage of cheating and less students will do it.
If the student is integrating answers from multiple AI responses then maybe that's a good thing for them to be learning and the assessment should allow it.
It will take 0 time to have some (smarter?) student create an AI agent that mimick keystrokes.
Not 0 time, but yes, integrity preservation is an arms race.
The best solutions are in student motivations and optimal pedagogical design. Students who want to learn, and learning systems that are optimized for rate of learning.
No, a genuine doc will have a drafting process. You'll edit and change weak parts, etc.
I guess you could use AI to guide this, at which point it's basically a research tool and grammar checker.
Depends how you work. I've rarely (never?) drafted anything and almost all of the first approach ended up in the final result. It would look pretty close to "typed in the AI answer with very minor modifications after". I'm not saying that was a great way to do it, but I definitely wouldn't want to be failed for that.
There is a fractal pattern between authentic and inauthentic writing.
Crude tools (like Google docs revision history) can protect an honest student who engages in a typical editing process from false allegations, but it can also protect a dishonest student who fabricated the evidence, and fail to protect an honest student who didn't do any substantial editing.
More sophisticated tools can do a better job of untangling the fractal, but as with fractal shaped problems the layers of complexity keep going and there's no perfect solutions, just tools that help in some situations when used by competent users.
The higher Ed professors who really care about academic integrity are rare, but they are layering many technical and logistical solutions to fight back against the dishonest students.
Not really, also the timing of the saves won't reflect the expected work needing to be put in. Unless you are taking the same amount of time to feed in the AI output as a normal student used to actually write / edit the paper, at which point cheating is meaningless
Doesn't google docs have fairly robust edit history? If I was a student these days I'd either record my screen of me doing my homework, or at least work in google docs and share the edit history.
this is a really flimsy method and it would be trivial to write something that works around this.
Yes. When I was an educator, reviewing version history was an obvious way to clarify if/how much students plagiarized.
honest q: what would it look like from your perspective if someone worked in entirely different tools and then only moved their finished work to google docs at the end?
In this case, the school was providing chromebooks so Google Docs were the default option. Using a different computer isn’t inherently a negative signal - but if we are already talking about plagiarism concerns, I’m going to start asking questions that are likely to reveal your understanding of the content. If your understanding falters, I’m going to ask you to prove your abilities in a different way/medium/etc.
In general, I don’t really understand educators hyperventilating about LLM use. If you can’t tell what your students are independently capable of and are merely asking them to spit back content at you, you’re not doing a good job.
Shouldn't do that. Can make it clear at syllabus time that this will result in the paper being considered as AI-assisted
This still leaves many options open for plagiarism (for example a second, seperate device)
Not really, document editors save every few moments. Someone cheating with AI assistance will not have a similar saved version pattern as someone writing and editing themselves. And if one did have the same pattern, it would defeat the purpose of cheating because it would take a similar amount of time to pull off
I wrote a paper about building web applications in 10th grade a long time ago. When class was out the teacher asked me to stay for a minute after everybody left. He asked in disbelief, “did you really write that paper?”
I could see why he didn’t, so I wasn’t offended or defensive and started to tell him the steps required to build web apps and explained it in a manner he could understand using analogies. Towards the end of our conversation he could see I both knew about the topic and was enthusiastic about it. I think he was still a bit shocked that I wrote that paper, but he could tell from the way I talked about it that it was authentic.
It will be interesting to see how these situations evolve as AI gets even better. I suspect assessment will be more manual and in-person.
You don't convince the teacher, you talk with the Dean.
Guess you have to videotape or screen-record yourself writing it. Oh what a world we've created :-S.
You mean you'll prompt Sora to create a video of you writing the essay :)
... until you get accused of generating that video with another AI.
No fair, i was born with 11 fingers!
on a side note, I wonders if anyone submitting code to github is feeling the same way about the "duplication detection filter" type AI guardrails.
I would screencast the whole thing and then tell my professor that we can watch a bit together.
How is that a dilemma for the students? What are their supposed options?
Easy if one of these options might be available to the writer:
- Write it in google docs, and share the edit history in the google docs, it is date and time stamped.
- Make a video of writing it in the google docs tab.
If this is available, and sufficient, I would pursue a written apology to remind the future detectors.
Edit: clarity
edit history in Google docs is a good way to defend yourself from AI tool use accusations
The funny part is that Googe has all the edit history data. In other words, it's a piece of cake for them to train a model that mimics human editing process.
The only thing prevents them from doing so is the fact Google is too big to sell a "plagiarism assistant."
I’m very tempted to write a tool that emulates human composition and types in assignments in a human-like way, just to force academia to deal with their issues sooner.
Ironic that one of the biggest AI companies is also the platform to offer a service to protect yourself from allegations of using it.
I seriously think the people selling AI detection tools to teachers should be sued into the ground by a coalition of state attorneys general, and that the tools should be banned in schools.
In my CS undergrad I had Doug Lea as a professor, really fantastic professor (best teacher I have ever had, bar none). He had a really novel way to handle homework hand ins, you had to demo the project. So you got him to sit down with you, you ran the code, he would ask you to put some inputs in (that were highly likely to be edge cases to break it). Once that was sufficient, he would ask you how you did different things, and to walk him through your code. Then when you were done he told you to email the code to him, and he would grade it. I am not sure how much of this was an anti-cheating device, but it required that you knew the code you wrote and why you did it for the project.
I think that AI has the possibility of weakening some aspects of education but I agree with Karpathy here. In class work, in person defenses of work, verbal tests. These were corner stones of education for thousands of years and have been cut out over the last 50 years or so outside of a few niche cases (Thesis defense) and it might be a good thing that these come back.
Yep, it's easy to shortcut AI plagiarism, but you need time. In most of the universities around the world (online universities especially), the number of students is way too big, while professors get more and more pressure on publishing and bureaucracy.
I did my masters in GaTech OMSCS (Chatgpt came out at the very end of my last semester). Tests were done with cameras on and it was recorded and then they were watched I think by TAs. Homework was done with automated checking and a plagiarism checker. Do you need to have in person proctoring via test centers or libraries? Video chats with professors? I am not sure. Projects are importants, but maybe they need to become a minority of grades and more being based on theory to circumvent AI?
It's not even about plagiarism. But, sure, 1:1 or even 1:few instruction is great but even at elite schools is not really very practical. I went to what's considered a very good engineering school and classes with hundreds of students was pretty normal.
Ironically the practically of such instruction goes down as the status of the school goes up. I got a lot of 1:1 or 1:few time with my community college professors.
The TL:DR of every "AI vs Schools, what should teachers do?" article boils down to exactly this: Talk with the students 1-1. You can fake an essay, you can't fake a conversation about the topic at hand.
Maybe as a society we can take some of the productivity gains from AI and funnel them into moving teaching away from scantrons and formulaic essays. I want to be optimistic.
So we are screwed once we get brain-computer interfaces?
In college I had a professor assign us to write a 100% plagiarized paper. You had to highlight every word in a color associated with the source. You couldn't plagiarize more then one sequential sentence from a single source.
It ended up being harder then writing an ordinary paper but taught us all a ton about citation and originality. It was a really cool exercise.
I imagine something similar could be done to teach students to use AI as a research tool rather then as a plagiarization machine.
I think legacy schooling just needs to be reworked. Kids should be doing way more projects that demonstrate the integration of knowledge and skills, rather than focusing so much energy on testing and memorization. There's probably a small core of things that really must be fully integrated and memorized, but for everything else you should just give kids harder projects which they're expected to solve by leveraging all the tools at their disposal. Focus on teaching kids how to become high-agency beings with good epistemics and a strong math core. Give them experiments and tools to play around and actually understand how things work. Bring back real chemistry labs and let kids blow stuff up.
The key issue with schools is that they crush your soul and turn you into a low-agency consumer of information within a strict hierarchy of mind-numbing rules, rather than helping you develop your curiosity hunter muscles to go out and explore. In an ideal world, we would have curated gardens of knowledge and information which the kids are encouraged to go out and explore. If they find some weird topic outside the garden that's of interest to them, figure out a way to integrate it.
I don't particularly blame the teachers for the failings of school though, since most of them have their hands tied by strict requirements from faceless bureaucrats.
As much as I hated schooling, I do want to say that there are parts of learning that are simply hard. There are parts that you can build enthusiasm for with project work and prioritizing for engagement. But there are many things that people should learn that will require drudgery to learn and won't excite all people.
Doing derivatives, learning the periodic table, basic language and alphabet skills, playing an instrument are foundational skills that will require deliberate practice to learn, something that isn't typically part of project based learning. At some point in education with most fields, you will have to move beyond concepts and do some rote memorization and repetition of principles in order to get to higher level concepts. You can't gamify your way out of education, despite our best attempts to do so.
Most learning curves in the education system today are very bumpy and don't adapt well to the specific student. Students get stuck on big bumps or get bored and demotivated at plateaus.
AI has potential to smooth out all curves so that students can learn faster and maximize time in flow.
I've spent literally thousands of hours thinking about this (and working on it). The future of education will be as different from today as today is to 300 years ago.
Kids used to get smacked with a stick if they spelled a word wrong.
There is a huge opportunity here to have the stick smacking be automated and timed to perfection.
The point is that the education system has come a long way in utilizing STEM to make education more efficient (helping students advance faster and further with less resources) and it will continue to go a long way further.
People thought the threat of physical violence was a good way to teach. We have learned better. What else is there for us to learn? What have we already learned but just don't have the resources to apply?
I've met many educators who have told me stories of ambitions learning goals for students that didn't work because there weren't the time or resources to facilitate them properly.
Often instructors are stuck trading off between inauthentic assessments that have scalable evaluation methods or authentic exercises that aren't feasible to evaluate at scale and so evaluation is sparse, incomplete or students only receive credit for completion.
You are 100% right on this. There is a reason school is so vastly different from the process most people follow when learning something on their own.
Doing rather than memorizing outdated facts in a textbook.
But testing and paper assessments are cheap and feasible for mass education. There are only so many workshop projects you can have before you run out of budget.
Having had some experience teaching and designing labs and evaluating students in my opinion there is basically no problem that can't be solved with more instructor work.
The problem is that the structure pushes for teaching productivity which basically directly opposes good pedagogy at this point in the optimization.
Some specifics:
1. Multiple choice sucks. It's obvious that written response better evaluates students and oral is even better. But multiple choice is graded instantly by a computer. Written response needs TAs. Oral is such a time sink and needs so many TAs and lots of space if you want to run them in parallel.
1.5 Similarly having students do things on computers is nice because you don't have to print things and even errors in the question can be fixed live and you can ask students to refresh the page. But if the chatbots let them cheat too easily on computers doing hand written assesments sucks cause you have to go arrange for printing and scanning.
2. Designing labs is a clear LLM tradeoff. Autograded labs with testbenches and fill in the middle style completetions or API completetions are incredibly easy to grade. You just pull the commit before some specific deadline and run some scripts.
You can do 200 students in the background when doing other work its so easy. But the problem is that LLMS are so good at fill in the middle and making testbenches pass.
I've actually tried some more open ended labs before and its actually very impressive how creative students are. They are obviously not LLMs there is this diversity in thought and simplicity of code that you do not get with ChatGPT.
But it is ridiculously time consuming to pull people's code and try to run open ended testbenches that they have created.
3. Having students do class presentations is great for evaluating them. But you can only do like 6 or 7 presentations in a 1 hr block. You will need to spend like a week even in a relatively small class.
4. What I will say LLMs are fun for are having students do open ended projects faster with faster iterations. You can scope creep them if you expect expect to use AI coding.
> Written response needs TAs.
Can AI not grade written responses?
I tried that once. Specifically because I wanted to see if we could leverage some sort of productivity enhancements.
I was using a local LLM around 4B to 14B, I tried Phi, Gemma, Qwen, and LLama. The idea was to prompt the LLM with the question, the answer key/rubric, and the student answer. The student answer at the end did some prompt caching to make it much faster.
It was okay but not good, there were a lot of things I tried:
* Endlessly messing with the prompt. * A few examples of grading. * Messing with the rubric to give more specific instructions. * Average of K. * Think step by step then give a grade.
It was janky and I'll throw it up to local LLMs at the time being somewhat too stupid for this to be reasonable. They basically didn't follow the rubric very well. Qwen in particular was very strict giving zeros regardless of the part marks described in the answer key as I recall.
I'm sure with the correct type of question and correct prompt and a good GPU it could work but it wasn't as trivially easy as I had thought at the time.
I think part of the reason AI is having such a negative effect on schools in particular is because of how many education processes are reliant on an archaic, broken way of "learning." So much of it is focused upon memorization and regurgitation of information (which AI is unmatched at doing).
School is packed with inefficiency and busywork that is completely divorced from the way people learn on their own. In fact, it's pretty safe to say you could learn something about 10x by typing it into an AI chat bot and having it tailor the experience to you.
It's the opposite.
> focused upon memorization and regurgitation
This is what is easy to test in-class.
Teachers worry about AI because they do not just care about memorization. Before AI, being able to write cohesive essays about a subject is a good proxy to prove your understanding beyond simple memorization. Now it's gone.
A lazy, irresponsible teacher who only cares about memorization will just grade students by in-class multi choices tests exclusively and call it a day. They don't need to worry about AI at all.
> So much of it is focused upon memorization and regurgitation of information, which AI is unmatched at doing.
This applies both to education, and to what people need to know to do work. Knowing all the written stuff is less valuable. Automated tools can been able to look it up since the Google era. Now they can work with what they look up.
There was a time when programmers poured over Fundamental Algorithms. No one does that today. When needed, you find existing code that does that stuff. Probably better than you could write. Who codes a hash table today?
Yes, the biggest problem with authentic exercises is evaluating the students' actions and giving feedback. The problem is that authentic assessments didnt previous scale (e.g. what worked in 1:1 coaching or tutoring couldn't be done for a whole classroom). But AI can scale them.
It seems like AI will destroy education but it's only breaking the old education system, it will also enable a new and much better one. One where students make more and faster progress developing more relevant and valuable skills.
Education system uses multiple choice quizzes and tests because their grading can be automated.
But when evaluation of any exercise can be automated with AI, such that students can practice any skill with iterative feedback at the pace of their own development, so much human potential will be unlocked.
Memorizing and tests at school are the archaic approach that schools don't believe in anymore (at least the school board my kids are at), but they happen to be AI proof.
It's the softer, no memorizing, no tests, just assignments that you can hand in at anytime because there's no deadlines, and grades don't matter, type of education that is particularly useless with AI.
> So much of it is focused upon memorization and regurgitation of information (which AI is unmatched at doing).
No, lots of classes are focused on producing papers which aren't just memorization and regurgitation, but generative AI is king at... Generating text... So that class of work output is suspect now
It's a fair question, but there's maybe a bit of US defaultism baked in? If I look back at my exams in school they were mostly closed-book written + oral examination, nothing would really need to change.
A much bigger question is what to teach assuming we get models much more powerful than those we have today. I'm still confident there's an irreducible hard core in most subjects that's well worth knowing/training, but it might take some soul searching.
With my partner we have been working to invert the overall model.
She started grading conversation than the students have with LLMs.
From the question that the students ask, it is obvious who knows the material and who is struggling.
We do have a custom setup, so that she creates an homework. There is a custom prompt to avoid the LLM answering the homework question. But thats pretty much it.
The results seems promising, with students spending 30m or so going back and forth with the LLMs.
If any educator wants to Ty or is interested in more information, let me know and we can see how we collaborate.
As a teacher, I try to keep an open mind, but consistently I can find out in 5 minutes of talking to a student if they understand the material. I might just go all in for the oral exams.
It’s hard to go from (I privately think you’re cheating) to (I accuse you to your face), though.
> The students remain motivated to learn how to solve problems without AI because they know they will be evaluated without it in class later.
Learning how to prepare for in-class tests and writing exercises is a very particular skillset which I haven't really exercised a lot since I graduated.
Never mind teaching the humanities, for which I think this is a genuine crisis, in class programming exams are basically the same thing as leetcode job interviews, and we all know what a bad proxy those are for "real" development work.
> in class programming exams are basically the same thing as leetcode job interviews, and we all know what a bad proxy those are for "real" development work.
Confusing university learning for "real industry work" is a mistake and we've known it's a mistake for a while. We can have classes which teach what life in industry is like, but assuming that the role of university is to teach people how to fit directly into industry is mistaking the purpose of university and K-12 education as a whole.
Writing long-form prose and essays isn't something I've done in a long time, but I wouldn't say it was wasted effort. Long-form prose forces you to do things that you don't always do when writing emails and powerpoints, and I rely on those skills every day.
There's no mistake there for all the students looking at job listings that treat having a college degree as a hard prerequisite for even being employable.
I use it every day.
Preparing for a test requires understanding what the instructor wants. concentrate on the wrong thing get marked down.
Same applies to working in a corporation. You need to understand what management wants. It’s a core requirement.
Here is my proposal for AI in schools: raise the bar dramatically. Rather than trying to prevent kids from using AI, just raise the expectations of what they should accomplish with it. They should be setting really lofty goals rather than just doing the same work with less effort.
AI doesn't help you do higher quality work. It helps you do (or imitate) mediocre work faster. But thing is, it is hard to learn how to do excellent work without learning to do mediocre work first.
Absolutely. I'd love to see the same effect happen in the software industry. Keep the volume of output the same, but increase the quality.
> Keep the volume of output the same, but increase the quality.
Effect of AI applied to coding is precisely the opposite though?
Code quality is still a culture and prioritisation issue more than a tool issue. You can absolutely write great code using AI.
AI code review has unquestionably increased the quality of my code by helping me find bugs before they make it to production.
AI coding tools give me speed to try out more options to land on a better solution. For example, I wrote a proxy, figured out problems with that approach, and so wrote a service that could accomplish the same thing instead. Being able to get more contact with reality, and seeing how solutions actually work before committing to them, gives you a lot of information to make better decisions.
But then you still need good practices like code review, maintaining coding standards, and good project management to really keep code quality high. AI doesn’t really change that.
that is what they do in the software industry, before it was let me catch you off guard with asking how to reverse a linked list, now its leetcode questions that are so hard that you need to know and study them weekly, and prep for a year, interviewer can tell if you started prep 3 weeks prior
In other words, learn to use the tool BUT keep your critical thinking. Same with all new technologies.
I'm not minimizing Karpathy in any way, but this is obviously the right way to do this.
"You have to assume that any work done outside classroom has used AI."
That is just such a wildly cynical point of view, and it is incredibly depressing. There is a whole huge cohort of kids out there who genuinely want to learn and want to do the work, and feel like using AI is cheating. These are the kids who, ironically, AI will help the most, because they're the ones who will understand the fundamentals being taught in K-12.
I would hope that any "solution" to the growing use of AI-as-a-crutch can take this cohort of kids into consideration, so their development isn't held back just to stop the less-ethical student from, well, being less ethical.
> There is a whole huge cohort of kids out there
Well, it seems the vast majority doesn't care about cheating, and is using AI for everything. And this is from primary school to university.
It's not just that AI makes it simpler, so many pupils cannot concentrate anymore. Tiktok and others have fried their mind. So AI is a quick way out for them. Back to their addiction.
Addiction created by you and me, laboring for Zuck’s profit.
There’s a reason this stuff is banned in China. Their pupils suffer no such opiate.
What possible solution could prevent this? The best students are learning on their own anyways, the school can't stop students using AI for their personal learning.
There was a reddit thread recently that asked the question, are all students really doing worse, and it basically said that, there are still top performers performing toply, but that the middle has been hollowed out.
So I think, I dunno, maybe depressing. Maybe cynical, but probably true. Why shy away from the truth?
And by the way, I would be both. Probably would have used AI to further my curiosity and to cheat. I hated school, would totally cheat to get ahead, and am now wildly curious and ambitious in the real world. Maybe this makes me a bad person, but I don't find cheating in school to be all that unethical. I'm paying for it, who cares how I do it.
People aren't one thing.
AI is a boon to students who are intrinsically motivated. Most students aren't.
Sure, but the point is that if 5% of students are using AI then you have to assume that any work done outside classroom has used AI, because otherwise you're giving a massive advantage to the 5% of students who used AI, right?
I read that xcancel thread, the original one and now this hackernews thread and...
IS NO ONE GOING TO POINT OUT MULTIPLE OF THOSE DOODLES ARE WRONG???
To be specific, it's the doodles that are, not the answers.
It seems like a good path forward is to somewhat try to replicate the idea of "once you can do it yourself, feel free to use it going forward" (knowing how various calculator operations work before you let it do it for you).
I'm curious if we instead gave students an AI tool, but one that would intentionally throw in wrong things that the student had to catch. Instead of the student using LLMs, they would have one paid for by the school.
This is more brainstorming then a well thought-out idea, but I generally think "opposing AI" is doomed to fail. If we follow a montessori approach, kids are naturally inclined to want to learn thing, if students are trying to lie/cheat, we've already failed them by turning off their natural curiosity for something else.
I agree, I think schools and universities need to adapt, just like calculators, these things aren't going away. Let students leverage AI as tools and come out of Uni more capable than we did.
AI _do_ currently throw in an occasional wrong thing. Sometimes a lot. A students job needs to be verifying and fact checking the information the AI is telling them.
The student's job becomes asking the right questions and verifying the results.
AI can also generate questions of course.
So it is feasible (in principle) to give every student a different exam!
You’d use AI to generate lots of unique exams for your material, then ensure they’re all exactly the same difficulty (or extremely extremely close) by asking an LLM to reject any that are relatively too hard or too easy. Once you have generated enough individual exams, assign them to your students in your no-AI setting.
Why the hell would you want to do that lol. Casually 20x the teachers' workload for what? Who are going to grade these unique exams? AI as well?
AI should not grade them.
Code that the AI writes would be used to grade them.
- AI is great at some things.
- Code is great at other things.
- AI is bad at some things code is great for.
- AI is great at coding.
Therefore, leverage AI to quickly code up deterministic and fast tools for the tasks where code is best.
And to help exams be markable by code, it makes sense to be smart about exam structure - eg. only ask questions with binary answers or multiple choice so you don’t need subjective judgment of correctness.
except (like it or not) students are in direct competition with each other. Unique assessments would be impossible to defend the first time a student claimed your "unfair" test cost them a job, scholarship or other competitive opportunity.
This is the correct take. To contrast the Terance Tao piece from earlier (https://news.ycombinator.com/item?id=46017972), AI research tools are increasingly useful if you're a competent researcher that can judge the output and detect BS. You can't, however, become a Terence Tao by asking AI to solve your homework.
So, in learning environments we might not have an option but to open the floodgates to AI use, but abandon most testing techniques that are not, more or less, pen and paper, in-person. Use AI as much as you want, but know that as a student you'll be answering tests armed only with your brain.
I do pity English teachers that have relied on essays to grade proficiency for hundreds of years. STEM fields has an easier way through this.
Yesterday's Doonesbury was on point here: https://www.gocomics.com/doonesbury/2025/11/23
Andrej and Garry Trudeau are in agreement that "blue book exams" (I.e. the teacher gives you a blank exam booklet, traditionally blue) to fill out in person for the test, after confiscating devices, is the only way to assess students anymore.
My 7 year old hasn't figured out how to use any LLMs yet, but I'm sure the day will come very soon. I hope his school district is prepared. They recently instituted a district-wide "no phones" policy, which is a good first step.
That was how I took most of my school and university exams. I hated it then and I'd hate it now. For humanities, at least, it felt like a test of who could write the fastest (one which I fared well at, too, so it's not case of sour grapes).
I'd be much more in favour of oral examinations. Yes, they're more resource-intensive than grading written booklets, but it's not infeasible. Separately, I also hope it might go some way to lessening the attitude of "teaching to the test".
Blue book was the norm for exams in my social science and humanities classes way after every assignment was typed on a computer (and probably a laptop, by that time) with Internet access.
I guess high schools and junior highs will have to adopt something similar, too. Better condition those wrists and fingers, kids :-)
I'm oldish, but when I was in college in the late 90s we typed a huge volume of homework (I was a history & religious studies double major as an undergrad), but the vast majority of our exams were blue books. There were exceptions where the primary deliverable for the semester was a lengthy research paper, but lots and lots of blue books.
Oh how I hated those as a student. Handwriting has always been a slow and uncomfortable process for me. Yes, I tried different techniques of printing and cursive as well as better pens. Nothing helped. Typing on a keyboard is just so much faster and more fluent.
It's a shame that some students will again be limited by how fast they can get their thoughts down on a piece of paper. This is such an artificial limitation and totally irrelevant to real world work now.
Obviously the solution is to bring back manual typewriters.
Maybe this is a niche for those low distraction writing tools that pop up from time to time. Or a school managed Chromebook that’s locked to the exam page.
In the process, we lose both the ability to accommodate students, or ask questions that take longer than the test period to answer.
All for a calculator that can lie.
> My 7 year old hasn't figured out how to use any LLMs yet, but I'm sure the day will come very soon. I hope his school district is prepared. They recently instituted a district-wide "no phones" policy, which is a good first step.
This sounds as if you expect that it will become possible to access an LLM in class without a phone or other similar device. (Of course, using a laptop would be easily noticed.)
The phone ban certainly helps make such usage noticeable in class, but I'm not sure the academic structure is prepared to go to in-person assessments only. The whole thread is about homework / out of class work being useless now.
New York State recently banned phones state wide in schools.
It is, but it does not matter, because:
1. Corporate interests want to sell product 2. Administrators want a product they can use 3. Compliance people want a checkbox they can check 4. Teachers want to be ablet to continue what they have been doing thus far within the existing ecosystem 5. Parents either don't know, don't care, or do, but are unable to provide a viable alternative or, can and do provide it
We have had this conversation ( although without AI component ) before. None of it is really secret. The question is really what is the actual goal. Right now, in US, education is mostly in name only -- unless you are involved ( which already means you are taking steps to correct it ) or are in the right zip code ( which is not a guarantee, but it makes your kids odds better ).
I made a tool for this! It's an essay writing platform that tracks the edits and keystrokes rather than the final output, so its AI detection accuracy is _much_ higher than other tools: https://collie.ink/
I recently wrote on something similar. I think the way we design evaluation methods for students needs to mirror the design of security systems. https://kelvinpaschal.com/blog/educators-hackers/
I’ve been following this approach since last school year. I focus on in-class work and home-time is for reading and memorization. My classmates still think classrooms are for lecturing, but it's coming. The paper-and-pen era is back to school!
I did a lot of my blog and book writing before these AI tools, but now I show my readers images of handwritten notes and drafts (more out of interest than demonstrating proof of work).
Cheaters and frauds are always wondering why they are "no hires" and are first to be laid off.
Meanwhile, in this reality, the cheaters and frauds end up winning elections and running things.
I submitted this but why is there an xcancel link added to it?
X is a hostile experience when not logged in.
besides the poor UX for unauthenticated users, i would rather not view ads from advertisers who still pay X for the access to my eyeballs (in the event i'm using a browser that doesn't block them to begin with).
This couldn’t have happened at a better time. When I was young my parents found a schooling system that had minimal homework so I could play around and live my life. I’ve moved to a country with a lot less flexibility. Now when my kids will soon be going to school, compulsory homework will be obsolete.
Zero homework grades will be ideal. Looking forward to this.
If AI gets us reliably to a flipped classroom (=research at home, work through work during class) then I'm here for it. Homework in the traditional sense is an anti pattern.
Agreed, the Gutenberg method is preferred:
1. Assume printing press exists 2. Now there's no need for a teacher to stand up and deliver information by talking to a class for 60 mins 3. Therefore students can read at home (or watch prepared videos) and test their learning in class where there's experts to support them 4. Given we only need 1 copy of the book/video/interactive demo, we can spend wayyyyy more money making it the best it can possibly be
What's sad is it's 500 years later and education has barely changed
> What's sad is it's 500 years later and education has barely changed
From my extensive experience of four years of undergrad, the problem in your plan is "3. Therefore students can read at home " - half the class won't do the reading, and the half that did won't get what it means until they go to lecture[1].
[1] If the lecturer is any good at all. If he spends most of his time ranting about his ex-wife...
Most of what I learned in college was only because I did homework and struggled to figure it out myself. Classroom time was essentially just a heads up to what I'll actually be learning myself later.
Granted, this was much less the case in grade school - but if students are going to see homework for the first time in college, I can see problems coming up.
If you got rid of homework throughout all of the "standard" education path (grade school + undergrad), I would bet a lot of money that I'd be much dumber for it.
> but if students are going to see homework for the first time in college, I can see problems coming up.
If the concept is too foreign for them, I'm sure we could figure out how to replicate the grade school environment. Give them their 15 hours/week of lecture, and then lock them in a classroom for the 30 hours they should spend on homework.
Now that's an optimistic take!
this is a very American issue. In my entire student career in Italy, home assignments were never graded. Maybe you had a project or two through university, but otherwise I got all my grades for onsite tests.
A detector is easy to write, simply monitor the kid’s computer and phone use. AI is ruining school but it will be solved in the lowest resistance way possible.
This is exactly why I'm focusing on job readiness and remediation rather than the education system. I think working all this out is simply too complex for a system with a lot of vested interest and that doesn't really understand how AI is evolving. There's an arms race between students, teachers, and institutions that hire the students.
It's simply too complex to fix. I think we'll see increased investment by corporates who do keep hiring on remediating the gaps in their workforce.
Most elite institutions will probably increase their efforts spent on interviewing including work trials. I think we're already seeing this with many of the elite institutions talking about judgment, emotional intelligence critical thinking as more important skills.
My worry is that hiring turns into a test of likeability rather than meritocracy (everyone is a personality hire when cognition is done by the machines)
Source: I'm trying to build a startup (Socratify) a bridge for upskilling from a flawed education system to the workforce for early stage professionals
I agree that focus should just shift to in-class work so that students are left free to do whatever they want once they are done for the day at school. Homework and at-home assignments are lazy handovers.
Also, all of these AI threats to public education can be mitigated if we just step 1-2 decades back and go the pen-and-paper way. I am yet to see any convincing argument in favor of digital/screen-based teaching methods being superior in any way than the traditional ones, on the contrary I have seen thousands of arguments against them.
I've had to stop using em-dashes because people assume I'm using ai.
How about just dispense with the AI nonsense in education and go to totally in-person, closed-book, manually-written, proctored exams? No homework, no assignments, no projects. Just pure mind-to-paper writing in a bare room under the eye of an examiner. Those that want to will learn and will produce intelligent work regardless of setting.
This doesn't adress the point that AI can replace going to school. AI can be your perfect personal tutor to help you learn thing 1:1. Needing to have a teacher and prove to them that you know what they teached will become a legacy concept. That we have an issue of AI cheating at school is in my eyes a temporary issue.
ChatGPT just told me to put the turkey in my toaster oven legs facing the door, and you think it can replace school. Unless there is a massive architectural change that can be provably verified by third parties, this can never be. I’d hate for my unschooled surgeon to check an llm while I’m under.
Don't worry, someone will put another hack on top the model to teach it to handle this specific case better. That will totally fix the problem, right? Right?
What's the alternate if someone didn't know something during a procedure? Just wing it? Getting another data point from an LLM seems beneficial to me.
Ask a human who does. If there are no competent humans on-call before the procedure starts, reschedule the procedure.
A trained professional making their best guess is far more capable and trustworthy than the slop LLMs put out. So yeah, winging it is a good alternative here.
Just curious, not being a turkey SME, what's the downside to positioning the turkey that way?
Most turkeys of my acquaintance would not fit into a toaster oven without some percussive assistance.
I see, I overlooked the 'toaster' part. That's a good world model benchmark question for models and a good reading comprehension question for humans. :-P
GPT 5.1 Pro made the same mistake ("Face the legs away from the door.") Claude Sonnet 4.5 agreed but added "Note: Most toaster ovens max out around 10-12 pounds for a whole turkey."
Gemini 3 acknowledged that toaster ovens are usually very compact and that the legs shouldn't be positioned where they will touch the glass door. When challenged, it hand-waved something to the effect of "Well, some toaster ovens are large countertop convection units that can hold up to a 12-pound turkey." When asked for a brand and model number of such an oven, it backtracked and admitted that no toaster oven would be large enough.
Changing the prompt to explicitly specify a 12-pound turkey yielded good answers ("A 12-pound turkey won't fit in a toaster oven - most max out at 4-6 pounds for poultry. Attempting this would be a fire hazard and result in dangerously uneven cooking," from Sonnet.)
So, progress, but not enough.
It is considered valuable and worthwhile for a society to educate all of its children/citizens. This means we have to develop systems and techniques to educate all kinds of people, not just the ones who can be dropped off by themselves at a library when they turn five, and picked up again in fifteen years with a PHD.
Sure. People who are self motivated are who will benefit the earliest. If a society values ensuring every single citizen gets a baseline education they can figure out how to get an AI to persuade or trick people into learning better than a human could.
Snap out of it. This is the best advice I can give you.
Snap out of what? I use chatgpt for learning every day.
For someone that wants to learn, I agree with this 100%. AI has been great at teaching me about 100s of topics.
I don't yet know how we get AI to teach unruly kids, or kids with neurodivergencies. Perhaps, though, the AI can eventually be vastly superior to an adult because of the methods it can use to get through to the child, keep the child interested and how it presents the teaching in a much more interactive way.