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by adamddev1 41 days ago
I was talking to a teacher and she was explaining how everyone is reaching for AI to have everything explained to them. "I'm too dumb to understand things," is the basic assumption people are now growing up with, reaching for AI summaries all the time without trying to understand anything themselves.

Instead of trying to understand things, people are reaching for better tools to have the thinking done for them. We are losing something huge.

1 comments

Every major leap forward triggers Luddism in those prone to histrionics.

You have to offload cognition in order to recognize the next abstraction. That's always been how we tackle harder problems.

A good explanation is foreplay, not a replacement for the act itself. If people stop there, that's a premature-pedagogy problem, not an AI problem.

Somewhere, an AI is summarizing this comment for someone right now, and that person understands the issue better than you do.

Offloading cognition is what one does when they use abstractions that other people made through intense cognition. And it's fine to do that; people can build great things with great abstractions. A woodworker doesn't have to design and construct a tool to make great things with it.

But developing the people [who can build great new abstractions or the people who can build those abstractions into ergonomic tooling] involves a lot of cognitive struggle through which these people learn how to push knowledge forward.

Forming the mental models for how things work takes struggle. Debugging errors in your code forces you to figure out the disconnect between your mental model and reality.

Claude can figure out most errors I show to it much faster than I can, but when we're building something I could build from scratch, I regularly find even Opus 4.7 regularly provides vastly overcomplicated and inferior solutions and I have to redirect it. I assume this is also the case when we're building stuff that's new to me and I just can't recognize all of the overcomplicated suboptimal solutions until I get to testing the behaviors I need to be correct. If I got a tool like this at the start of my career or education, I just don't know how I wouldn't end up completely stunted.

This is not just another abstraction. It is something fundamentally different because it is a jump away from deterministic, transparent processes to a probabilistic black box. It's not like a jump from orality to books to digital media, or hand written arithmetic to calculators to programs. These abstractions were solid and dependable and could be relied upon to tackle harder problems. This abstraction is beyond leaky.

The assumption that "that person understands the issue better than you" is bold when the best AI summaries will often give back completely false summaries on any given issue.

You can make many of the same criticisms about television, or smartphones, or the internet. And indeed, all of those and many other technologies have had terrible effects. But the way to deal with that is to learn and teach how to use them responsibly, with conscious intent. It's certainly true that left to themselves, most people won't do that.

> These abstractions were solid and dependable and could be relied upon to tackle harder problems. This abstraction is beyond leaky.

Much like humans? This is an example of what I'm referring to. Unless you spend the effort to learn how to use the models effectively, you're going to have to wait until others do that for you. In the meantime, a disconnect arises because you're not seeing the benefits because you're not able to use them effectively. But other people are using them effectively and seeing significant benefits.