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.
The debugging improvements have been huge for me too. I was debugging some financial software, and while it took a few shots, just with access to my code and not to the database that showed the issue, it found a fairly complex problem.
This was my thinking. It's a tool with many options like digital spreadsheets. It can still be used 'wrong' or poorly, but you better know how to use it on some level.
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).
Fine, here's a source where both the second and corresponding authors are from Harvard that says the same thing [0]. That said, you don't need to be from a prestigious institution to observe the basic statistic that long COVID is most frequently reported in women ages 40-60.
To put it another way: an apocryphal businessman took something that people took pride in and gradually optimised everything so much that all the logging, transportation, graphite work and combination resulted in a perfect pencil that costs basically nothing almost anywhere in the world.
I don't agree. Loads of things are like this. Cars, microchips, hard drive storage, monitors, TVs, laptops. All either much better than they used to be, or much cheaper, or both.
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.
If in most cases damages cannot be recovered or the criminal will never be caught in the first place, then what is the lesson being taught? Doesn't that just create a moral hazard where you "randomly" choose who to penalize?
Even if the goal is to deter crime, we still have a principle of proportionate punishment. We don't cut people's hands of for petty theft, and we don't execute people for exceeding the speed limit even though both should be pretty effective deterrents.
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.
when you fall from a bicycle in traffic and need more than ten stitches, you probably want clean conditions and high skill people ready. Ordinary daily care is done by ordinary daily care people because there is so much of it to do. It is fairly rare to need ten stitches from a bicycle accident. This is an example of people in ordinary good health. When you get to chronic care and elder care, things change again.
this call for "less reliance on insurance" lacks context and is overly-simplistic IMHO
Doctors can't exist without insurance? Hell we don't need doctors to diagnose strep etc. My argument is to remove insurance from the common. I've never crashed a bike requiring 10+ stitches probably never will, but might be a good reason for to carry insurance for it. However I don't want it plugging up the bill flow when I go to get antibiotics for a routine illness.
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.
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.