Comment by dryarzeg
14 hours ago
I've read this a long time ago, when I was a kid. Back then I thought about the education system and how it sometimes inhibits the creativity within the students. But right now, other comparison comes to mind - I don't know how relevant it is, though, so please don't judge it strictly.
Modern "AI" (LLM-based) systems are somewhat similar to the humans in this story who were taped. They may have a lot of knowledge, even a lot of knowledge that is really specialized, but once this knowledge becomes outdated or they are required to create something new - they struggle a lot. Even the systems with RAG and "continuous memory" (not sure if that's the right term) don't really learn something new. From what I know, they can accumulate the knowledge, but they still struggle with creativity and skill learning. And that may be the problem for the users of these systems as well, because they may sometimes rely on the shallow knowledge provided by the LLM model or "AI" system instead of thinking and trying to solve the problem themselves.
Luckily enough, most of the humans in our world can still follow the George's example. That's what makes us different from LLM-based systems. We can learn something new, and learn it deeply, creating the deep and unique networks of associations between different "entities" in our mind, which allows us to be truly creative. We also can dynamically update our knowledge and skills, as well as our qualities and mindset, and so on...
That's what I'm hoping for, at least.
What concerns me is that learning depth is more discouraged than ever. For a long time it's been discouraged, which is natural as we have a preference for simple things rather than difficult/complex things. But we're pushing much harder than ever before. From the way we have influencer education videos to the way people push LLMs ("you can just vibe code, no thinking required"). We've advanced enough that it's easy to make things look good enough but looks can be deceiving. It's impossible to know what's good enough without depth of knowledge, without mastery.
No machine will ever be sufficient to overcome the fundamental problem: a novice is incapable of properly evaluating a system. No human is capable of doing this either, nor can they (despite many believing they can). It's a fundamental information problem. The best we can do is match our human system, where we trust the experts, who have depth. But we even see the limits of that and how frequently they get ignored by those woefully unqualified to evaluate. Maybe it'll be better as people tend to trust machines more. But for the same reason it could be significantly worse. It's near impossible to fix a problem you can't identify.
Ironically, when machine learning is getting “deeper & deeper”, human learning is getting more and more impatient and shallow.
I have been searching “Vibe coding” videos on YouTube that are not promoting something. And I found this one and sat down and watched the whole three hours. It does take a lot of real effort.
https://www.youtube.com/watch?v=EL7Au1tzNxE