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Hilariously I've been in elevators with an operator.
I'm pretty sure another silver lining for accountants is that "my freakin' AI did it wrong" is probably not an excuse that the IRS will accept. They will accept "my accountant did it wrong."
Definitely. It’s the same problem that self driving has where every Tesla that crashes with FSD is nationwide news even though it’s 10x (or more?) safer than average drivers.
I think it's worse. In the case I am familiar with, (sample size of two) as far as I can tell, when a guy did something on his own, he did okay. When he tried to use AI to do about the same thing, SNAP!
So either the AI screwed up big time 50% of the time, or 100% of the time. Either way, not great, and seems worse "per task" than self-driving cars.
Weird. This is so far from my experience that I wonder what you guys are even doing? Like, you only tried AI twice?
If you’re a senior dev, and AI is not banned by your org, and you’re not personally using AI, that seems very inefficient.
Oh no, I've tried AI lots more than twice. Definitely witnessed more than one hallucination.
I'm not in software. The mistake I'm talking about wasn't made by me, so I don't have any insight into how it was made or how often the user was using it, or what model.
To give you the sort of idea of what happened without doxxing myself, imagine someone turned in their PhD dissertation and it (or parts of it) turned out to be AI written, and the AI had made stuff up.
Was he using a "cutting edge" model? No idea. I've had Opus goof stuff up for me before, so I don't necessarily trust even the higher-end models not to make mistakes from time to time.
Fair enough. I trust your lived experience. But listen to software devs when they say that AI works now, it hallucinates a lot less, and it has gotten remarkably better in the last 12 months, even the last 6 months. I use it every day. It is does not hallucinate much.
Harnesses such as Claude Code and Codex have changed the game.
I think that AI has been gravitating towards software development (perhaps to the detriment of other skills), in part because software development helps develop AI! But software development is fairly validation oriented – code runs or it doesn't. Someone who is lazy enough to have an AI write text with their name on it may also be too lazy to validate that text, or even too lazy to have another AI fact-check it.
You can say "yeah they are a poor user" and fair enough, but people will say things like "AIs have PhD level intelligence" or "AIs can act as a smart research intern" and then (in my experience) from time to time they go and make stuff up. Certainly lazy PhDs and research interns do this, all the time, but I don't think that demonstrates intelligence.
I'm not an AI-denier, I use it relatively consistently and I like it for research – but a lot of that is because Google is bad now (and their AI overview is atrocious, I've seen it present conflicting information), and you can use AI to get you links that you can check with your own eyeballs, and you can give it specific prompts that help mitigate other bad tendencies. But the fact that you have to do these things means that you cannot necessarily just expect AI cruising around on its own recognizance (or in the hands of someone who is not intelligent and/or used to using AI) to operate at that high level.
Sweet summer child. One of the undocumentd laws of programming is that if you have even number of errors you will get program that works mostly ok.
I have had way too many debug sessions that were - here is the error, how the fuck this thing worked at all, ahhh - here is the other error.
I am familiar with this dynamic, but (at least from where I sit) a mostly-functional program is different from a mostly-true thesis, or what have you.
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