The core tool being offered here is allowing experts to focus more on checking work than solving work. It's way faster to check if a Sudoku puzzle is correct than it is to solve the Sudoku puzzle.
Debbuging, for example, is harder than programming. And the difficulty is related to the 'amount of code' you are debbuging.
This means it is pretty easy to verify the Copilot's output when he just spits out a couple of lines at a time. But you will have a pretty bad time when you ask ChatGPT for a complete service. Things will not work out and the time you take to fix it will be greater than what you saved in the first place.
> The core tool being offered here is allowing experts to focus more on checking work than solving work.
That sounds like a nightmare, not an improvement. Really, think about it. It's the same shit as "self driving" cars that need continuous human monitoring. You're taking an relatively engaging task and replacing it with a mind-numbing slog that humans are particularly bad at.
Not to mention the skill of being able to "check work" usually flows from deep experience of "doing work."
> It's way faster to check if a Sudoku puzzle is correct than it is to solve the Sudoku puzzle.
Yeah, and which of those tasks do humans choose to do? I don't see many "100 Solved Sudoku Puzzles To Check" books in the bookstore.
>> Not to mention the skill of being able to "check work" usually flows from deep experience of "doing work."
> Precisely, but you need far fewer of these people, which is why this is being so heavily pushed.
That sounds like extremely specious reasoning to me, probably due to working backward from technology to application in order to hype the former.
Firstly, is it's anyone experience that it's easier to understand an unreliable system that was barfed out of some unreliable process (doesn't have to be an LLM, could be a bad offshore team), than it is to try to build it right from the start? It's still garbage out. It's like abusing the QA process by saying quality is only their job, then carelessly pumping out crap work and expecting them to catch all the mistakes.
Secondly, where are these "fewer" skilled people supposed to come from? The technology, if embraced this way, will have the effect of cutting off the the skils pipeline. That would work in the short/medium term, but in a generation when you start to see lots of retirements, you'll hit a skills dead end.
>The technology, if embraced this way, will have the effect of cutting off the the skils pipeline. That would work in the short/medium term, but in a generation when you start to see lots of retirements, you'll hit a skills dead end.
When have corporations ever cared about the next generation, let alone anything beyond the current quarter?
But it's literally how construction projects work. You have a bunch of junior engineers who hammer out the work, and then a master PE who reviews and signs off on it (who also takes full legal responsibility for all the work).
The master engineer isn't the one who does all the hours and hours of nitty gritty design work. She just does review and makes adjustments as needed.
Yes but the junior engineers aren’t the dumbest morons you’ve ever seen. This isn’t a realistic depiction of how the tools would get used anyway. It’s not “generate a plan from scratch” and submit for review. It’s “carefully iterate small parts over and over”.
The junior engineers would be the ones reviewing the outputs. The senior engineer would be the one reviewing what is still constructively the junior engineer’s work.
Insurance exists. Money points to something in reality (usually).
Negligence and duty don’t change and the implementing human (the person checking for mistakes) will be just as liable as the human implementing someone else’s work today.
But true… it is unlikely the AI firms or the suits that force it into every nook and cranny they can will ever be held accountable for the mistakes it will inevitably make. Not without a couple catastrophes first.
I was thinking that, but then I remembered how often humans make mistakes and and don't check their own work. For me, a common example is loose/lose, which I only find in my writing by assistance from text-to-speech. Did you spot the deliberate mistake in this comment? Because that too is one I miss, when the two words are separated by a line-break.
Engineers already sign off on work done by others all the time. This isn't some new or radical concept. For civil engineering projects, you can face jail time if you signed off on bad work regardless of who did it.
Debbuging, for example, is harder than programming. And the difficulty is related to the 'amount of code' you are debbuging.
This means it is pretty easy to verify the Copilot's output when he just spits out a couple of lines at a time. But you will have a pretty bad time when you ask ChatGPT for a complete service. Things will not work out and the time you take to fix it will be greater than what you saved in the first place.