The moderators are supposed to just know it when they see it? It's that black and white to you? Or are lots of false positives a price we have to pay?
Maybe there can be a dedicated 'flag botspam' button?
Then again it's a nuanced issue. I see AI used in a large percentage of writing now, so would this rule apply to the article as well?
I find the above comment concerning, so I ask: to what degree is the above commenter calibrated to ground truth? How would they know? How would we know?
[1]: https://en.wikipedia.org/wiki/Calibrated_probability_assessm...
It seems to me comments like the above are overconfident in the worst ways.
But yeah, there isn't a way to prove it one way or the over, even when it's "obvious".
I saw in some schools they're using systems where you have to type the essay in a web app, and the web app analyzes your keystrokes to determine if you're human.
We already have flagging and downvoting?
It is against the rules though
What does [flagged] mean?
Users flagged the post as breaking the guidelines or otherwise not belonging on HN.
In other words, submissions get flagged that users believe don’t belong on HN. LLM-written submissions can be one such case.
Community moderation won't fix this problem. It can only be mitigated if the site owners invest significant resources in addressing it. And judging by how little YC actually invests in HN, I wouldn't hold my breath. This website will succumb to this problem just like most others.
If not already, then soon
(i.e. it was obvious in the first place, think along the lines of a ticket about a screen loading slowly, and then multiple paragraphs explaining the benefits of faster-loading screens.)
I would argue that those cases are really the ones that cause an LLM-specific harm, i.e., which make people feel like they aren't exclusively among fellow humans.
If someone posts something that doesn't clearly read LLM-ish, but is otherwise terrible, it's not really different from if the same terrible thing had been written by hand.
I don't think anyone who objects to LLM comments is really demanding a super-low false negative rate. Just get rid of the zero-effort stuff. For example, recently I've seen a lot of comments from new accounts that are just sycophantic towards TFA and try to highlight / summarize a specific idea or two, but don't really demonstrate any original thought (just, like, basic reading comprehension and an ability to express agreement). And they'll take a paragraph to do so, where a human with the same level of interest in the material might just say "good post" (granted, there's an argument to be made for excluding that, too).
I don't think your account is AI just by these few comments, but I would like to point out that most rubrics one might use to determine what is obviously AI might end up including the way you talk.
If there was a truly accurate tell, some algorithm you could feed a few sentences in and it could tell you "yep, this is 100% AI", then yeah sure use that. I don't know you could realistically build that machine, especially when it comes to the generation of text.
I've always found this funny. Doesn't macOS' default text substitution enable (annoying to me) things like em-dash, smart quotes, etc?
Like, why would my comment (or yours, or any other comment) pass or fail the LLM check the I/you/someone else used specific prompts or another LLM to edit the output? It seems like these tools would work on 99.9% of the outputs, but those outputs likely weren't created in an adversarial way.
....until you start scrolling down the page and it becomes screamingly obvious that everything it says comes from the same template.
Maybe the problem isn't just that AI produces gobs of useless crap. Maybe what's worse is that it can produce even more mediocre crap that crowds out the good?
All oatmeal, no steak, leads to "starvation" by poor nutrition.