Schools are not about education but about privilege, filtering, indoctrination, control, etc.
Many people attending school, primarily higher education like college, are privileged because education costs money, and those with more money are often more privileged. That does not mean school itself is about privilege, it means people with privilege can afford to attend it more easily. Of course, grants, scholarships, and savings still exist, and help many people afford education.
“Filtering” doesn’t exactly provide enough context to make sense in this argument.
Indoctrination, if we go by the definition that defines it as teaching someone to accept a doctrine uncritically, is the opposite of what most educational institutions teach. If you understood how much effort goes into teaching critical thought as a skill to be used within and outside of education, you’d likely see how this doesn’t make much sense. Furthermore, the heavily diverse range of beliefs, people, and viewpoints on campuses often provides a more well-rounded, diverse understanding of the world, and of the people’s views within it, than a non-educational background can.
“Control” is just another fearmongering word. What control, exactly? How is it being applied?
Maybe if a “teacher” has to trick their students in order to enforce pointless manual labor, then it’s not worth doing.
They’re not tricking students, they’re tricking LLMs that students are using to get out of doing the work required of them to get a degree. The entire point of a degree is to signify that you understand the skills and topics required for a particular field. If you don’t want to actually get the knowledge signified by the degree, then you can put “I use ChatGPT and it does just as good” on your resume, and see if employers value that the same.
Maybe if homework can be done by statistics, then it’s not worth doing.
All math homework can be done by a calculator. All the writing courses I did throughout elementary and middle school would have likely graded me higher if I’d used a modern LLM. All the history assignment’s questions could have been answered with access to Wikipedia.
But if I’d done that, I wouldn’t know math, I would know no history, and I wouldn’t be able to properly write any long-form content.
Even when technology exists that can replace functions the human brain can do, we don’t just sacrifice all attempts to use the knowledge ourselves because this machine can do it better, because without that, we would be limiting our future potential.
This sounds fake. It seems like only the most careless students wouldn’t notice this “hidden” prompt or the quote from the dog.
The prompt is likely colored the same as the page to make it visually invisible to the human eye upon first inspection.
And I’m sorry to say, but often times, the students who are the most careless, unwilling to even check work, and simply incapable of doing work themselves, are usually the same ones who use ChatGPT, and don’t even proofread the output.
If you were taking a test to assess how much weight you could lift, and you got a robot to lift 2,000 lbs for you, saying you should pass for lifting 2000 lbs would be stupid. The argument wouldn’t make sense. Why? Because the same exact logic applies. The test is to assess you, not the machine.
Just because computers exist, can do things, and are available to you, doesn’t mean that anything to assess your capabilities can now just assess the best available technology instead of you.
Spell/Grammar check doesn’t generate large parts of a paper, it refines what you already wrote, by simply rephrasing or fixing typos. If I write a paragraph of text and run it through spell & grammar check, the most you’d get is a paper without spelling errors, and maybe a couple different phrases used to link some words together.
If I asked an LLM to write a paragraph of text about a particular topic, even if I gave it some references of what I knew, I’d likely get a paper written entirely differently from my original mental picture of it, that might include more or less information than I’d intended, with different turns of phrase than I’d use, and no cohesion with whatever I might generate later in a different session with the LLM.
These are not even remotely comparable.
This is an interesting question, but I think it mistakes a replacement for a tool on a fundamental level.
I use LLMs from time to time to better explain a concept to myself, or to get ideas for how to rephrase some text I’m writing. But if I used the LLM all the time, for all my work, then me being there is sort of pointless.
Because, the thing is, most LLMs aren’t used in a way that conveys info you already know. They primarily operate by simply regurgitating existing information (rather, associations between words) within their model weights. You don’t easily draw out any new insights, perspectives, or content, from something that doesn’t have the capability to do so.
On top of that, let’s use a simple analogy. Let’s say I’m in charge of calculating the math required for a rocket launch. I designate all the work to an automated calculator, which does all the work for me. I don’t know math, since I’ve used a calculator for all math all my life, but the calculator should know.
I am incapable of ever checking, proofreading, or even conceptualizing the output.
If asked about the calculations, I can provide no answer. If they don’t work out, I have no clue why. And if I ever want to compute something more complicated than the calculator can, I can’t, because I don’t even know what the calculator does. I have to then learn everything it knows, before I can exceed its capabilities.
We’ve always used technology to augment human capabilities, but replacing them often just means we can’t progress as easily in the long-term.
Short-term, sure, these papers could be written and replaced by an LLM. Long-term, nobody knows how to write papers. If nobody knows how to properly convey information, where does an LLM get its training data on modern information? How do you properly explain to it what you want? How do you proofread the output?
If you entirely replace human work with that of a machine, you also lose the ability to truly understand, check, and build upon the very thing that replaced you.