One point which I consider worth making is that LLMs have helped enable a lot of people solve real world problems, even if the solutions are sometimes low quality. The reality is that in many cases the only choice is between a low quality solution and no solution at all. Lots of problems are too small or niche to be able to afford hiring a team of skilled programmers for a high quality solution.
- "a low-quality solution, but you also spend extra time (sometimes - other people's time) on learning to solve the problem yourself"
- "a high-quality solution, but you've spent years on becoming an expert is this domain"
It's good that you brought this up.
Often, learning to solve a class of problems is simply not a priority. Low-quality vide-coded tools are usually means to an end. And the end goals that they achieve are often not even the most important end goals that you have. Digging so deep into the details of those is not worth it. Those are temporary, ad-hoc things.
In the original post, the author references our previous discussion about "Worse Is Better". It's a very relevant topic! Over there, I actually made a very similar point about priorities. "Worse" software is "better" when it's just a component of a system where the other components are more important. You want to spend as much time as possible on those other components, and not on the current component.
A (translated) example that I gave in that thread:
In the 1970s, K&R were doing OS research. Not PL research. When they needed to port their OS, they hacked a portable low-level language for that task. They didn't go deep into "proper" PL research that would take years. They ported their OS, and then returned straight to OS research and achieved breakthroughs in that area. As intended.
It's very much possible that writing a general, secure-by-design instrument would take way more time than adding concrete hacks on the application level and producing a result that's just as good (secure or whatever) when you look at the end application.
To be fair, the post says that "overusing AI [is] bad" and "problems [are] caused by widespread AI use" (emphasis mine).
I beleive, they aren't against all AI use and aren't against the use that you describe. They are against knowingly cutting corners and pushing the cost onto the users (when you have an option not to). Or onto anything else, be it the environment or the job market
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This post feels a bit meandering.
One point which I consider worth making is that LLMs have helped enable a lot of people solve real world problems, even if the solutions are sometimes low quality. The reality is that in many cases the only choice is between a low quality solution and no solution at all. Lots of problems are too small or niche to be able to afford hiring a team of skilled programmers for a high quality solution.
Let’s stay with the (at minimum) low quality solution: What would do someone without IA?
- ask on a forum (Facebook, Reddit, askHN, spécialises forums…)
- ask a neighbor if he knows someone knowledgeable (2 or 3 relations can lead you to many experts)
- go to the library. Time consuming but you might learn something else too and improve knowledge and IQ
- think again about the problem (ask Why? Many times, think out of the box…)
Indeed, the choice is actually between:
- "a low quality solution"
- "a low-quality solution, but you also spend extra time (sometimes - other people's time) on learning to solve the problem yourself"
- "a high-quality solution, but you've spent years on becoming an expert is this domain"
It's good that you brought this up.
Often, learning to solve a class of problems is simply not a priority. Low-quality vide-coded tools are usually means to an end. And the end goals that they achieve are often not even the most important end goals that you have. Digging so deep into the details of those is not worth it. Those are temporary, ad-hoc things.
In the original post, the author references our previous discussion about "Worse Is Better". It's a very relevant topic! Over there, I actually made a very similar point about priorities. "Worse" software is "better" when it's just a component of a system where the other components are more important. You want to spend as much time as possible on those other components, and not on the current component.
A (translated) example that I gave in that thread:
To be fair, the post says that "overusing AI [is] bad" and "problems [are] caused by widespread AI use" (emphasis mine).
I beleive, they aren't against all AI use and aren't against the use that you describe. They are against knowingly cutting corners and pushing the cost onto the users (when you have an option not to). Or onto anything else, be it the environment or the job market