Comment on AI content on Wikipedia - found via a simple ISBN checksum calculator (39C3)
Passerby6497@lemmy.world 19 hours agoBut in this case the tool actually works well for one thing and not so well for another. It
See, that’s where you’re wrong though. AI is about as competent at natural English as it is writing code.
I use it for both at times, since it can be an easy way to both rubber duck debug my code as well as summarize large projects/updates in ways that are easily digestible when I don’t have the time to write out a proper summary manually. But in either case, I have to go back and fix a good bit of what’s provided.
AI is not great at either option, and sucks at both in different ways. Saying AI is a hammer is not supwr helpful, because hammers have a defined use. LMMs are a solution looking for a problem. The difference between the posters and the researcher is that the researcher has an advantage that he both knows what he’s doing and knows how to fix the turds he’s provided to make it work, where the users are just trusting the output.
I don’t know how to explain the irony any better in this scenario, but it’s there. If the users actually fact checked their output, we wouldn’t be having this discussion. Same as if the researcher chose not to validate his output. The issue isn’t necessarily the use, but the usage. So this is akin to the posters using a hammer to put up a shelf, but they didn’t look at the directions and saying “yep, that looks right”
Saapas@piefed.zip 19 hours ago
But it did create a working tool to identify AI contributions with fake ISBN, didn’t it? Are we assuming the tool from OP wasn’t working?
Passerby6497@lemmy.world 19 hours ago
Ok, but how do you know that other edits from Wikipedia aren’t AI generated, but had users who actually validated the output? And can you explain to me the difference between the users who validated the AI output before updating Wikipedia, and the researcher who validated his AI output before making his talk?
The point you’re missing is that both sides are using the same crappy tool, but you’re only seeing an example of one side doing it wrong and the other right, and using that to make a conclusion that is unfalsifiable. You appear to be saying it’s better for code than language because of the example in front of us and naively extrapolating that to mean ai works better in one task than the other, when the difference is how the user handled the output, not the output itself.
Saapas@piefed.zip 19 hours ago
I mean in this specific case it did make a working tool to identify hallucinated sources.
And yes it’s definitely better at code than doing something requiring the sort of thinking that Wikipedia edits require. I’m not drawing that from this singular thing but rather when they’ve studied the correctness of AI output. Coding is sorta “easy” for a computer to do compared to language and information tasks in that sort of free-er form way.
Passerby6497@lemmy.world 18 hours ago
Right, but it also outputs really bad code, so pointing to this specific example is pointless to the overall point. Both code and language output have to be validated and reworked, because an AI is just a stochastic parrot. The quality of the final product is dependent on the person using what the AI gives them.
Lol. Lmao even. Vibe coding is arguably worse than vibe talking, just ask the users of Tea. Or the devs of NX that had to stop an AI PR that would have run unsanitized shell commands. Or that idiot that fired everyone to vibe code his app that was immediately hacked.
If you think language requires more thinking than coding, I don’t know what to tell you, considering that code is applied thinking/logic. AI is good at speeding things up by accelerating blocking things out, but absolutely sucks at producing a workable product. Just like with language processing.
But I’m done with this conversation, considering you’ve ignored the point I’m making to point back at this example multiple times now. Good day.