That's an interesting take I don't see anyone else bringing up.
It would also, I would think, make it easier for the 30% fewer engineers to earn a better living in the long run and reduce human management effort.
This makes the most sense to me. So far AI, being fallible, can only augment humans so you can have less humans to do the same work (or tasks where accuracy can be less than 100%, like lower level support calls/questions). Next comes the task of re-balancing the distribution of labor or teaching other departments to utilize AI.
To me that rings the most true because where AI saves me the most time is in never having a bug that takes more than a few hours to pinpoint, even if I'm looking in the wrong place, because with enough clues the AI will look in the right place before I think of doing so. Like finding a needle in a haystack. It doesn't suddenly make me 100x more productive, but it saves a lot of time on some time consuming tasks.
I still haven't read any of his work, but wasn't the point of the Three Laws of Robotics that they in fact _didn't_ work in the story presented in the book?
Critical thinking and reading comprehension and the primary tools in determining truth, AFAIK. Knowing facts beforehand helps too but a trustworthy source can provide false information as much as an untrustworthy source can provide true information.
This has always been an issue, and in the past it was a more difficult issue because your sources of knowledge were more limited. Nowadays its mostly about choosing the right source(s) rather than having to go out of your way to find them (like traveling to a regional/university library).
Not if 100 companies did it and they all got away.
This is to teach a lesson because you cannot prosecute all thieves.
Yale Law Journal actually writes about this, the goal is to deter crime because in most cases damages cannot be recovered or the criminal will never be caught in the first place.
Personally, I have only used AI to write actual code when it is for Bash and Python scripts that are self contained. In my case self contained means they are interfaced to via command line so their boundaries are very well defined.
I have never returned to look at any of the code.
I would never use it to generate domain code for my codebase because then I'd have to code review it anyways. I mean, if I have an agentic AI solving an issue and generating a PR, great, I can review that and give it feedback on how to change the code before its accepted.
Unless I can either throw the code away or review it for maintainability rather than correctness then I have no need for a tool that write my code for me.
Oh, unless the AI can be the product owner and understand the financial ramifications of not doing its job correctly but I would be worried that the solution is to not have a product by reducing the users to ash.
It would also, I would think, make it easier for the 30% fewer engineers to earn a better living in the long run and reduce human management effort.
This makes the most sense to me. So far AI, being fallible, can only augment humans so you can have less humans to do the same work (or tasks where accuracy can be less than 100%, like lower level support calls/questions). Next comes the task of re-balancing the distribution of labor or teaching other departments to utilize AI.
To me that rings the most true because where AI saves me the most time is in never having a bug that takes more than a few hours to pinpoint, even if I'm looking in the wrong place, because with enough clues the AI will look in the right place before I think of doing so. Like finding a needle in a haystack. It doesn't suddenly make me 100x more productive, but it saves a lot of time on some time consuming tasks.