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[-] LibertyLizard@slrpnk.net 60 points 1 year ago

I’m skeptical… how are the fake reviews identified and how do you avoid flagging real ones?

[-] fahfahfahfah@lemmy.billiam.net 64 points 1 year ago

They’re just building Fakespot into the browser so the same way Fakespot does, by analyzing the user who posted the review

[-] tdawg@lemmy.world 18 points 1 year ago
[-] yiliu@informis.land 80 points 1 year ago

They detect when a whole bunch of reviews are posted at exactly the same time, or are posted on a fixed schedule, or use extremely similar language, or with a brand new account...

Basically they use spam-detection techniques on reviews.

[-] ubermeisters@lemmy.world 0 points 1 year ago
[-] AlmightySnoo@lemmy.world 14 points 1 year ago

It could be something like that (hint: they already deployed an offline neural network in Firefox with which you can translate web pages), and the idea would be to detect AI-generated content.

[-] ubermeisters@lemmy.world 7 points 1 year ago

Well I hope they're going to do better at detecting AI content than anyone ever has before because nobody's done it well at all so far.

There's an inherent problem here that AI produces results similar to what it's trained on and it was not trained on robotic input it was trained on natural human language online.

[-] xantoxis@lemmy.world 13 points 1 year ago

Well it will be, because it's detecting AI-generated content indirectly. What it's directly detecting are bot posters, which are much easier to spot.

"AI detectors" have the uphill job of having to figure out whether something is generated by looking only at what was generated. Fakespot and tools like it get to use the metadata, which has many telltales that bots aren't even trying to hide.

[-] Draghetta@lemmy.world 1 points 1 year ago

IDK chief. It seems like one of those things that are hard to do in theory as you said, but relatively easy in practice.

I mean just about any human who has played a bit with ChatGPT nowadays is able to identify ChatGPT generated paragraphs within a few words. I don’t suppose it would be much harder for a machine.

[-] ubermeisters@lemmy.world 4 points 1 year ago

Therein lies the issue though. If its not hard to detect, then right after that, its hard to detect again, because the previous fix has been trained out/around. The harder we work to develop detection, the harder we work to ensure detection avoidance is advanced in parallel.

[-] Trainguyrom@reddthat.com 1 points 1 year ago

Elsewhere in this thread someone explained that its just integrating FakeSpot into the browser, which uses basic email spam detection techniques to detect fake reviews by analyzing how the reviewer posts. Is there a set schedule they post reviews by, what else have they reviewed, how new is the account, etc. A 2 day old account with 20 reviews would be an obvious source of fake reviews for example

this post was submitted on 11 Oct 2023
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