> So, did I learn anything ? No - not really. But did it solve a problem for me? yes.
And this is exactly the concern.
The tools are genuinely useful for some tasks. But unlike club organizers getting to DIY some hobby project for their club, students aren't yet being tasked to produce useful things in the best way possible. They're being tasked to do fairly rudimentary things so that they can learn some fundamentals by way of practice.
And likewise, in trades like ours, juniors are tasked to do useful things, but they're given affordance to deliver those things in ways that help them learn some fundamentals by way of practice.
Students and juniors who skip the practice are basically just trading their future expertise and readiness to accomplish trivial things that either don't or barely matter. Some of them may become the first generation of expert prompt engineers, accomplishing things in totally new ways in what amounts to a novel trade, but many of them are just going to be shooting themselves in the foot.
This is experience though, and people do learn this way.
This is the exact same exercise as my first time slapping Dynamic Drive scripts together to customize EzBoard back in the 2000s. I didn't understand any of it at the time.
This style of learning is hands on. You learn a little bit about the shape of the problem before you sit down and learn the theory.
Not everyone learns by opening the book first. Some people like to get their hands wet. Introduction through practical osmosis can lead to a fertile appreciation for the theory.
> This style of learning is hands on. You learn a little bit about the shape of the problem before you sit down and learn the theory.
We're talking about getting some project or task done. It's a practical exercise by definition. Any learning experience to be had is going to be hands on, and for student/junior-level tasks, it's not going to be some product of knowing deep theory in the first place.
But the process of identifying the boilerplate that needs to be written, the process of manually entering it, the process of debugging your own code that you wrote, the process of scouring for examples and explanations, the process of being held accountable in a teacher or colleague's review, the process of discussing your experience of the task with someone who already understands it well... these all provide extra opportunities for hands-on learning that are short-circuited when having an AI put it together for you.
Yes, script kiddies and VBA/Excel junkies in the sales department have been slapping together programs they didn't understand for decades, and many people have now joined the industry thinking that they might secure a career as an "engineer" by following tutorials well and pasting StackOverflow snippets efficiently. And while some people who found themselves starting on that path have eventually come to transcend it and learn fundamentals more deeply, the "slap it together" mentality, the "find a tutorial" mentality, and now the "have a chatbot do it" mentality easily become quiet traps for people who don't realize that they need to actively transcend them at some point.
You can genuinely learn a lot about football by playing Madden on your couch, but if you don't get out on the field and actually play some games, your dreams of making it into the NFL are probably not going to pan out.
It's not learning if the AI is feeding the person an incorrect model of the world, though. There's less likelihood of that if someone is reading information curated by a human that understands the shape of the problem and the domain. The AI doesn't "understand" any of that and just spits out words in an order that "seems correct" — that's precisely the problem.
The idea that AI doesn’t “understand” seems implausible with current models. We can say “machine understanding” if normal understanding requires felt experience. Otherwise, for all intents and purposes, the power of these tools rests in their understanding.
The power of these tools rests in how common certain patterns of text are in both immediate and superstrucral ways.
They force us to admit that with 8B people in the world, many of the questions we have and tasks we pursue have already been approximated countless times. They reveal that much of what we do is not so original.
Understanding -- human or machine -- is something different, and enables invention/originality/reflection in a way that recent innovations are still not yet able to acheive on their own.
Importantly, though, students and juniors are specifically being assigned challenges that are already known not to be novel or inventive, which is why these tools can so easily do the work for them. But when when they let the tool do so, they sidestep the unique growth opportunity they were given in the first place.
Oh, so you are in the “it can only do what has already been done camp.” Try to define the terms a bit better and I’ll play. If it can reason through topics that no one has ever reasoned before, are you open to the idea that this is understanding? Or what would you need to see.
(Keeping in mind that this is a much higher bar than what we consider understanding in humans.)
Unless the learner is being purposely mislead, it's still learning no matter what the entry point is.
Even if the learner is climbing a suboptimal hill, they're still learning the subject landscape and getting a sense of it. It's still a gradient.
The entire subject of chemistry is like this. They feed you lies and half truths for the first few years of your undergraduate career so that you develop a sense for things. The real model is far too complicated and scary to introduce.
It’s possible to learn literally nothing when using a gen ai. You can copy paste stuff without even glancing your code. For student work sized projects I’m sure it’s very doable to have a working product without knowing anything about how it works.
Today I wanted to try to create a tool for a game: snapshot a picture and a program recognizes the clipboard event and does image recog things and gives me data. I had a working poc in 3 hours and learned nothing. (Tbf I knew what I wanted and how to do it in general terms so the process might be different for a beginner.)
And this is exactly the concern.
The tools are genuinely useful for some tasks. But unlike club organizers getting to DIY some hobby project for their club, students aren't yet being tasked to produce useful things in the best way possible. They're being tasked to do fairly rudimentary things so that they can learn some fundamentals by way of practice.
And likewise, in trades like ours, juniors are tasked to do useful things, but they're given affordance to deliver those things in ways that help them learn some fundamentals by way of practice.
Students and juniors who skip the practice are basically just trading their future expertise and readiness to accomplish trivial things that either don't or barely matter. Some of them may become the first generation of expert prompt engineers, accomplishing things in totally new ways in what amounts to a novel trade, but many of them are just going to be shooting themselves in the foot.