Want to wade into the snowy surf of the abyss? Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid: Welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned soo many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

(December’s finally arrived, and the run-up to Christmas has begun. Credit and/or blame to David Gerard for starting this.)

    • rook@awful.systemsEnglish
      5·
      1 day ago

      It is important to note that the reviews were detected as being ai generated by an ai tool.

      This is a marketing puff piece.

      I mean, I expect that loads of the submissions are by slop extruders… under the circumstances, how could they not be? But until someone does the legwork of checking this, it’s just another magic-eight-ball-says-maybe, dressed up as science.

      • lagrangeinterpolator@awful.systemsEnglish
        6·
        1 day ago

        Unfortunately, I don’t think anyone is ever going to go through all 19,797 submissions and 75,800 reviews (to one conference, in one year) and manually review them all. Then again, using the ultra-advanced cutting-edge innovative statistical technique of randomly sampling a few papers/reviews, one can still get useful conclusions.

        • blakestacey@awful.systemsEnglish
          4·
          23 hours ago

          At least this example grew out of actual humans being suspicious.

          Dozens of academics have raised concerns on social media about manuscripts and peer reviews submitted to the organizers of next year’s International Conference on Learning Representations (ICLR), an annual gathering of specialists in machine learning. Among other things, they flagged hallucinated citations and suspiciously long and vague feedback on their work.

          Graham Neubig, an AI researcher at Carnegie Mellon University in Pittsburgh, Pennsylvania, was one of those who received peer reviews that seemed to have been produced using large language models (LLMs). The reports, he says, were “very verbose with lots of bullet points” and requested analyses that were not “the standard statistical analyses that reviewers ask for in typical AI or machine-learning papers.”

          We seem to be in a situation where everybody knows that the review process has broken down, but the “studies” that show it are criti-hype.

          Welcome to the abyss. It sucks here (academic edition).

        • JFranek@awful.systemsEnglish
          6·
          1 day ago

          all 19,797 submissions and 75,800 reviews (to one conference, in one year)

          tired: Dead Internet Theory wired: Dead Conferences Theory