People are focusing on the 26% being a low catch rate. But this is deliberate in order to lower the number of false positives on human work.

The big debate is in academia and most students will not risk ruining their degree to cheat this way. A 1in4 chance is huge when there are multiple papers that go towards your degree. It just isn't worth the risk.

100% GMO Dodo Bird Steaks? Can’t wait to see how internet will react to this.

Per the article. The 26% is the chance an AI piece is labeled "very likely AI". So they can catch out over 1 in 4 pieces generated by AI. The majority of AI writing doesn't get caught, but this also means the vast majority (>99%) of non-AI work doesn't get labeled AI.

In the context of academic work. Universities are at very little risk of accusing a non-cheater of cheating. The 1in4 catch rate while low is a huge deterrent for potential cheaters. If I knew that I had a 1/4 chance of getting caught and punished, I would not cheat. Especially as i had to submit dozens of papers as part of my degree.

Trying to think of a good pairing wine 🍷with Dodo 🦤

No need, I don't see a point to this, I expect given 3-5 years of adversarial training if left unregulated they'll be completely impossible to tell apart to a level where there'd be any point to it, we need to learn to adapt to the fact AI writing is poised to replace human writing in anything not requiring logical reasoning

Edit: I'd add that we need to start thinking as a species about the fact we've reached the point where human labour need not apply, there are now automatic ways to do nearly everything, the only thing stopping us is the will to use them and resources being concentrated rather than distributed, assuming plentiful resources nearly everything CAN be done without human intervention.

So concerned with they could, they didn’t think they should.

The article suggests there is a single "success" metric in OpenAIs publication, which there is not and deliberately so.

Labeling text as AI generated will always be fuzzy (active watermarking aside) and become even harder as models improve and get bigger. There is simply an area where human and AI written texts overlap.

Have a look at the FAQ on their page if you're interested in the details: https://platform.openai.com/ai-text-classifier

Which is a 26% success rate, how is that being misrepresented? The fact its 'somewhat confident' on other samples means nothing, if this was to be used for validating articles anywhere like writing competitions or academia you'd want that "very confident" number to be in the high 90s or at the very least the false positive amount incredibly low.

If you just assume the opposite of the prediction wouldn't you have a 74% chance of detection?

Man we can barely handle the current viruses raging on in birds that aren’t extinct, why on earth are we gonna bring new birds into the mix?

This is how you get skynet.

triplespidermanpointingtoeachother.jpg

We are pretty far from something like that due to ethics. It may happen in china or something far away but ethics committee for things like that are pretty serious

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“...your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.”

This needs to be from third parties otherwise those who control the neural nets and datasets will be able to shroud information as "not generated" when it is clearly astroturfing or manipulated. Then they can throw their hands up and say "must be the algorithm or a bad dataset" for plausible deniability.

The new game is coming or here, and it is misdirecting blame to the "algorithm" when it is an editorialized set of data or filtered for certain aims.

Almost all algorithms and datasets are biased or editorialized in some way, laws need to be adjusted on that. You can't blame the "algorithm" for enragement, because enragement is engagement.

Everyone has to have a piece of the cake

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Hmmm. Gene modification in mammals, birds, and marsupials could learn enough to modify humans too...

Also, why are they so quick to take on another project when the first two seem to be years away from anything actually viable? Kinda seems like a publicity stunt and cash grab.

They can basically search the content in their own history to cross-check if chatgpt wrote it at some point for someone.

But that search might take a long time??

https://i.kym-cdn.com/entries/icons/original/000/036/386/I'm_Playing_Both_Sides_Banner.jpg

Oh good. I hear they were tasty, so hopefully I can try them soon!

This is called a generative adversarial network, I believe.

I understand the bigger sample the better, but is it possibly limited to longer text so it's usefulness is kept academic? You mentioned your comment, and I think going to a platform like reddit and being able to offer a report on comment genuineness would be valuable

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