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323 points timbilt | 2 comments | | HN request time: 0.565s | source
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wcfrobert ◴[] No.42131165[source]
Lots of interesting debates in this thread. I think it is worth placing writing/coding tasks into two buckets. Are you producing? Or are you learning?

For example, I have zero qualms about relying on AI at work to write progress reports and code up some scripts. I know I can do it myself but why would I? I spent many years in college learning to read and write and code. AI makes me at least 2x more efficient at my job. It seems irrational not to use it. Like a farmer who tills his land by hand rather than relying on a tractor because it builds character or something. But there is something to be said about atrophy. If you don't use it, you lose it. I wonder if my coding skill will deteriorate in the years to come...

On the other hand, if you are a student trying to learn something new, relying on AI requires walking a fine line. You don't want to over-rely on AI because a certain degree of "productive struggle" is essential for learning something deeply. At the same time, if you under-rely on AI, you drastically decrease the rate at which you can learn new things.

In the old days, people were fit because of physical labor. Now people are fit because they go to the gym. I wonder if there will be an analog for intellectual work. Will people be going to "mental" gyms in the future?

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sbuttgereit ◴[] No.42131788[source]
"But there is something to be said about atrophy. If you don't use it, you lose it. I wonder if my coding skill will deteriorate in the years to come..."

"You don't want to over-rely on AI because a certain degree of "productive struggle" is essential for learning something deeply."

These two ideas are closely related and really just different aspects of the same basic frailty of the human intellect. Understanding that I think can really inform you about how you might use these tools in work (or life) and where the lines need to be drawn for your own personal circumstance.

I can't say I disagree with anything you said and think you've made an insightful observation.

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margalabargala ◴[] No.42132052[source]
In the presence of sufficiently good and ubiquitous tools, knowing how to do some base thing loses most or all of its value.

In a world where everyone has a phone/calculator in their pocket, remembering how to do long division on paper is not worthwhile. If I ask you "what is 457829639 divided by 3454", it is not worth your time to do that by hand rather than plugging it into your phone's calculator.

In a world where AI can immediately produce any arbitrary 20-line glue script that you would have had to think about and remember bash array syntax for, there's not a reason to remember bash array syntax.

I don't think we're quite at that point yet but we're astonishingly close.

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nkrisc ◴[] No.42132908[source]
> If I ask you "what is 457829639 divided by 3454"

And if it spits out 15,395,143 I hope you remember enough math to know that doesn’t look right, and how to find the actual answer if you don’t trust your calculator’s answer.

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1. Baeocystin ◴[] No.42133131[source]
Sanity Checking Expected Output is one of the most vital skills a person can have. It really is. But knowing the general shape of the thing is different than any particular algorithm, don't you think?
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2. bruce511 ◴[] No.42133339[source]
This gets to the root of the issue. The use case, and user experience, and thus outcome is, is remarkably different depending on your current ability.

Using AI to learn things is useful, because it helps you get terminology right, and helps you Google search well. For example say you need to know a Windows API, you can describe it snd get the name. Then Google how that works.

As an experienced user you can get it to write code. You're good enough to spot errors in the vote and basically just correct as you go. 90% right is good enough.

It's the in-between space which is hardest. You're an inexperienced dev looking to produce, not learn. But you lack the experience and knowledge to recognise the errors, or bad patterns, or whatever. Using AI you end up with stuff that's 'mostly right' - which in programming terms means broken.

This experience difference is why there's so much chatter about usefulness. To some groups it's very useful. To others it's a dangerous crutch.