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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 cur

by fao_ 2y ago

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.

echelon 2y ago
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.
- anon22981 2y ago
  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.)
dr_dshiv 2y ago
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.
- swatcoder 2y ago
  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.
  - dr_dshiv 2y ago
    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.)

by fao_ 2y ago

echelon 2y ago

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.

anon22981 2y ago
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.)

dr_dshiv 2y ago

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.

swatcoder 2y ago
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.
- dr_dshiv 2y ago
  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.)