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.
We'd still be waiting for healthcare with this kind of plan.
Before the ACA it simply was not a choice to be an independent professional and have health insurance.
If people could understand why it is unacceptable to force independent professionals and entrepreneurs to give up healthcare they would see the ACA was necessary in whatever form it could be passed.
Usually you want to boot from a cryptographic-ally verified medium where a checksum can be verified before you execute the system.
The emphasis is on running the correct software. If you have to input cryptographic data every time you boot that's okay because you're offline and should be in a secure room (no internet connected devices).
But yeah, malware attack is still possible if you don't have a secure chain and that's a long one.
I opened several laptops with spudger tools. Now I can open random items I didn't watch videos for just because I have an idea of how it _might_ be assembled.
I've explained bugs and developed exploits just from noticing odd behavior in video games.
I know how a team is organized, I knew the multiplayer feature was tacked on (probably by interns), I know about network code edge cases, bada-bing bada-boom I can trigger a bug and understand why it happens without ever seeing their code.
Or sitting in a theater and just noticing the lighting setup and transitions rather than the performance itself.
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.