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maegul ,
@maegul@lemmy.ml avatar

Yea, this highlights a fundamental tension I think: sometimes, perhaps oftentimes, the point of doing something is the doing itself, not the result.

Tech is hyper focused on removing the “doing” and reproducing the result. Now that it’s trying to put itself into the “thinking” part of human work, this tension is making itself unavoidable.

I think we can all take it as a given that we don’t want to hand total control to machines, simply because of accountability issues. Which means we want a human “in the loop” to ensure things stay sensible. But the ability of that human to keep things sensible requires skills, experience and insight. And all of the focus our education system now has on grades and certificates has lead us astray into thinking that the practice and experience doesn’t mean that much. In a way the labour market and employers are relevant here in their insistence on experience (to the point of absurdity sometimes).

Bottom line is that we humans are doing machines, and we learn through practice and experience, in ways I suspect much closer to building intuitions. Being stuck on a problem, being confused and getting things wrong are all part of this experience. Making it easier to get the right answer is not making education better. LLMs likely have no good role to play in education and I wouldn’t be surprised if banning them outright in what may become a harshly fought battle isn’t too far away.

All that being said, I also think LLMs raise questions about what it is we’re doing with our education and tests and whether the simple response to their existence is to conclude that anything an LLM can easily do well isn’t worth assessing. Of course, as I’ve said above, that’s likely manifestly rubbish … building up an intelligent and capable human likely requires getting them to do things an LLM could easily do. But the question still stands I think about whether we need to also find a way to focus more on the less mechanical parts of human intelligence and education.

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