Very good point. Not everyone has the same degree of self preservation instinct.
396 karma · joined December 13, 2016
The AI thing kind of reminds me of the big push to outsource software engineers in the early 2000's. There was a ton of hype among executives about it, and it all seemed plausible on paper. But most of those initiatives ended up being huge failures, and nearly all of those jobs came back to the US.
People tend to ignore a lot of the little things that glue it all together that software engineers do. AI lacks a lot of this. Foreigners don't necessarily lack it, but language barriers, time zone differences, cultural differences, and all sorts of other things led to similar issues. Code quality and maintainability took a nosedive and a lot of the stuff produced by those outsourced shops had to be thrown in the trash.
I can already see the AI slop accumulating in the codebases I work in. It's super hard to spot a lot of these things that manage to slip through code review, because they tend to look reasonable when you're looking at a diff. The problem is all the redundant code that you're not seeing, and the weird abstractions that make no sense at all when you look at it from a higher level.
I don't think that's a valid concern, because LLMs can't think. They are generating tokens one at a time. They're calculating the most likely token to appear based on the arrangements of tokens that were seen in their training data. There is no thinking, there is no reasoning. If they they seem like they're doing these things, it's because they are producing text that is based on unknown humans who actually did these things once.