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It doesn't matter, because any process that seems right most of the time but occasionally is wrong in subtle, hard to spot ways is basically a machine to lull p
by Latty 7mo ago
It doesn't matter, because any process that seems right most of the time but occasionally is wrong in subtle, hard to spot ways is basically a machine to lull people into not checking, so stuff will always slip through.
It's just like the cars driving themselves but you need to be able to jump in if there is a mistake, humans are not going to react as fast as if they were driving, because they aren't going to be engaged, and no one can stay as engaged as they were when they were doing it themselves.
We need to stop pretending we can tell people they "just" need to check things from LLMs for accuracy, it's a process that inevitably leads to people not checking and things slipping through. Pretending it's the people's fault when essentially everyone using it would eventually end up doing that is stupid and won't solve the core problem.
- voidUpdate 7mo agoProbably worth including a "bibliography" section of citations that can be automatically checked that they actually exist then
- lazide 7mo agoNot enough - you’d also need to check that they say/mean what is being implied. Which is a real problem.
- mminer237 7mo agoTo be fair, that's a problem with human authors too. Wikipedia is really well-cited, but it's common to check a citation and find it only says half of what a sentence does, while the rest seemingly has no basis in fact. Judges are supposed to actually read the citations to not only confirm the case exists and says what's being claimed, but often to also compare & contrast the situations to ensure that principle is applicable to the case at hand.
- lazide 7mo agoYup. The issue with LLMs are not that any specific thing it is doing is unique. Rather that it does it in previously unimaginable volume, scale, and accessibility.
- macintux 7mo agoEven disregarding self driving features, it seems like the smarter we make cars the dumber the drivers are. DRLs are great, until they allow you to drive around all night long with no tail lights and dim front lighting because you’re not paying enough attention to what’s actually turned on.
- dw_arthur 7mo agoAs someone who has done QA on white collar work it's tiring looking for little errors in work reports. Most people are not cut out for it.
- chii 7mo ago> won't solve the core problem. what's the core problem tho? Because if the core problem is "using ai", then it's an inevitable outcome - ai will be used, and there are always incentive to cut costs maximally. So realistically, the solution is to punish mistakes. We do this for bridges that collapse, for driver mistakes on roads, etc. The "easy" fix is to make punishment harsher for mistakes - whether it's LLM or not, the pedigree of the mistake is irrelevant.
- AnimalMuppet 7mo agoThe human is responsible. That's the fix. I don't care if you got the results from an LLM or from reading cracks in the sidewalk; you are responsible for what you say, and especially for what you say professionally. I mean, that's almost the definition of a professional. And if you can't play by those rules, then maybe you aren't a professional, even if you happened to sneak your way into a job where professionalism is expected.
- Latty 7mo agoThis doesn't solve the problem, because companies will force people to use these tools and demand they work faster, eventually resulting in people slipping. People will have to choose between being fired for being "too slow", or taking the risk they end up liable. Most people can't afford to just lose their job, and will end up being pressured into taking the risk, then the companies will liability-wash by giving them the responsibility. You need regulation that ensures companies can't just push the risk onto employees who can be rotated out to take the blame for mistakes.