4 ms·
Why? "This was written badly" is a perfectly normal thing to say; "this was written badly because you didn't put in the effort of writing it yourself" doubly so
by bccdee 10mo ago
Why? "This was written badly" is a perfectly normal thing to say; "this was written badly because you didn't put in the effort of writing it yourself" doubly so.
- 0xbadcafebee 10mo agoSay they used AI to write it, it came out bad, and they published it anyway. They had the opportunity to "make it better" before publishing, but didn't. The only conclusion for this is, they just aren't good at writing. So whether AI is used or not, it'll suck either way. So there's no need to complain about the AI. It's like complaining that somebody typed a crappy letter rather than hand-wrote it. Either way the letter's gonna suck, so why complain that it was typed?
- Dylan16807 10mo ago> The only conclusion for this is, they just aren't good at writing. Not true. It's likely an effort issue in that situation. And that kind of effort issue is good to call out, because it compounds the low quality.
- 0xbadcafebee 10mo agoI don't know if you're new to the internet, but low-effort comments have existed before AI, and will continue to exist regardless of AI.
- minitech 10mo agoCompared to human bad writing, AI writing tends to suck more verbosely and in exciting new ways (e.g. by introducing factual errors).
- 0xbadcafebee 10mo ago> AI writing tends to suck more verbosely So, it's the style you oppose, the way a grammar nazi complains about "improper" English > and in exciting new ways (e.g. by introducing factual errors). Because factually incorrect comments didn't exist before AI? Your concern is that you read something you don't like, so you pick the lowest-effort criteria to complain about. Speaks more about you than the original commenter.
- damentz 10mo agoI'm pretty sure by verbose it's the realization you've wasted precious time reading AI bloat that you'll never get back. On top of that, now you need to reread the text for hallucinations or just take a loss and ignore any conclusions at risk that they came from bad data.