Previous posts: https://programming.dev/post/3974121 and https://programming.dev/post/3974080

Original survey link: https://forms.gle/7Bu3Tyi5fufmY8Vc8

Thanks for all the answers, here are the results for the survey in case you were wondering how you did!

Edit: People working in CS or a related field have a 9.59 avg score while the people that aren’t have a 9.61 avg.

People that have used AI image generators before got a 9.70 avg, while people that haven’t have a 9.39 avg score.

Edit 2: The data has slightly changed! Over 1,000 people have submitted results since posting this image, check the dataset to see live results. Be aware that many people saw the image and comments before submitting, so they’ve gotten spoiled on some results, which may be leading to a higher average recently: https://docs.google.com/spreadsheets/d/1MkuZG2MiGj-77PGkuCAM3Btb1_Lb4TFEx8tTZKiOoYI

  • ilinamorato@lemmy.world
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    1 year ago

    What exactly is “this”?

    The results of this survey showing that humans are no better than a coin flip.

    while I agree in theory we could be on par, in practice it matters a lot that things happen in reality.

    I didn’t say “on par.” I said we know how. I didn’t say we were capable, but we know how it would be done. With AI detection, we have no idea how it would be done.

    Machine learning does that.

    No it doesn’t. It speedruns the tedious parts of writing algorithms, but we still need to be able to compose the problem and tell the network what an acceptable solution would be.

    Also look at Generative Adversarial Networks (GANs). […] this by definition includes a (specific) AI detector software, it requires it to work.

    Several startups, existing tech giants, AI companies, and university research departments have tried. There are literally millions on the line. All they’ve managed to do is get students incorrectly suspended from school, misidentify the US Constitution as AI output, and get a network really good at identifying training data and absolutely useless at identifying real world data.

    Note that I said that this is probably impossible, only because we’ve never done it before and the experiments undertaken so far by some of the most brilliant people in the world have yielded useless results. I could be wrong. But the evidence so far seems to indicate otherwise.

    • Spzi@lemm.ee
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      1 year ago

      Right, thanks for the corrections.

      In case of GAN, it’s stupidly simple why AI detection does not take off. It can only be half a cycle ahead (or behind), at any time.

      Better AI detectors train better AI generators. So while technically for a brief moment in time the advantage exists, the gap is immediately closed again by the other side; they train in tandem.

      This does not tell us anything about non-GAN though, I think. And most AI is not GAN, right?