deong
As an internal implementation detail, it’s fine and pretty standard. Exposing it to the end user so that they have to know whatever janky-ass domain and capitalization you picked to run your application is braindead.
It’s just Maslow’s Hierarchy. The person who doesn’t have a job should be egocentric, at least in this narrow area of focus. If your position is that people should prioritize abstract societal benefits over their own security and well-being, I’m not sure what to tell you other than to prepare for a life of people disappointing you.
Many of the people who currently experience the privilege will be pissed off and view it as unfair. But in reality they’re getting a taste of what other minorities already experience.
There are two competing lenses we can view this kind of thing through, and both are valid. First, there’s the macro lens in which groups like women are significantly underrepresented, and most reasonable people believe that to be a problem we’ve created that we need to solve. It’s not that women are bad at this job. It’s that women have been pushed not to participate for reasons we think are bad. Through that lens, an obvious solution is to bias things in favor of women for some period of time to get to a steady state where the system won’t automatically fall back into gender-bias as soon as we take our thumb off the scale. That’s a reasonable theory, and pursuing it does a lot of good.
But there’s a second lens in which individual people with names are trying to participate in the labor market. The fact that men have had a built-in advantage does not imply that any man looking for a job would only be able to get one by leveraging an unfair advantage. If we think talent and hard work are equally distributed through the population, then temporarily biasing things away from men is, to the man currently trying to find a job, exactly as discriminatory as anything that prior generations have faced. The fact that there’s a societal good being pursued doesn’t make that harm go away either. It is unfair, and we should recognize that. We may decide we have to do it anyway, but I’m not a fan of the idea that “let’s mistreat them like other people were mistreated” is inherently a good thing.
I feel like this would result in so many broken phones that most companies would not want to enter this market. Wouldn’t be surprised if you could find something on Alibaba or Amazon, but I doubt it’s much of a market.
Devil’s advocate though. With things like 4GLs, it was still all on the human to come up with the detailed spec. Best case scenario was that you work very hard, write a lot of things down, generate the code, see that it didn’t work and then ???. That “???” at the end was you as the programmer sitting alone in a room trying to figure out what a non-responsive black box might wanted you to have said instead.
It’s qualitatively different if you can just talk to the black box as though it were a programmer. It’s less of a black box at that point. It understands your language, and it understands the code. So you can start with the spec, but when something inevitably doesn’t work, the “???” step doesn’t just come back to you figuring out with no help what you did wrong. You can ask it questions and make suggestions. You can run experiments. Today’s LLMs hit the wall pretty quick there, and maybe they always will. There’s certainly the viewpoint that “all they do is model text and they can’t really learn anything”.
I think that’s fundamentally wrong. I’m a pretty solid programmer. I have a PhD in Computer Science, and I’ve worked as a software engineer and an architect throughout a pretty long career. And everything I’ve ever learned has basically been through language. Through reading, writing, speaking, and listening to English and a few other languages. I think that to say that I can learn what I’ve learned, but it’s fundamentally impossible for a robot to learn it is to resort to mysticism. At some point, we will have AIs that can do what I do today. I think that’s inevitable.
And yet another one that discussed at length how you obviously can’t magically expect AI to put the right things out. So we went to the topic of code reviews and I tried to tell them: Give a real developer 1000+ line pull requests (like the AI might spit out) and there is a chance of a snowball in hell you’ll get bug free code despite reviews.
Arguably this is comparing apples and oranges here. I agree with you that code reviews aren’t going to be useful for evaluating a big code dump with no context. But I’d also say that a significant amount of software in the world is either written with no code review process or a process that just has a human spitting out the big code dump with no context.
The AI hype is definitely hype, but there’s enough truth there to justify some of the hand-wringing. The guy who told you he only has to throw away the 20% of the code that’s useless is still getting 100% of his work done with maybe 40% of the effort (i.e., very little effort to generate the first AI cut, 20% to figure out the stupid stuff, 20% to fix it). That’s a big enough impact to have significant ripples.
Might not matter. It seems like the way it’s going to go in the short term is that paranoia and economic populism are going to kill the whole thing anyway. We’re just going to effectively make it illegal to train on data. I think that’s both a mistake and a gross misrepresentation of things like copyright, but it seems like the way we’re headed.
I agree with you. There’s nothing wrong with not knowing how to do something. We all start basically every endeavor not knowing how to do it. My complaint is specifically with people who march into that thing they haven’t learned yet with an attitude of “and you’re all wrong and stupid for not fixing it for me”.