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LLMs are simply search engines that put things into English, and not everything it scrapes is a vetted scientific article.
“When the text looks professional and written as a doctor writes, there’s an increase in the hallucination rates,” says Omar.
Huh, now there’s something we have in common. Trying to make sense of something a doctor wrote makes me feel like I’m hallucinating, too. Is there a class in medical school on “Illegible Handwriting,” or is it just a coincidence?
In all seriousness though, I wish I could be surprised by AI failing at this. We have entered the Misinformation Age. There’s no closing Pandora’s Box, though this time I can’t find the “hope” that’s supposed to be in the bottom of it. Society would have to turn real skeptical real fast, but I’ve met enough people to know that such a tranformation is going to take time - and by “time” I mean “decades or longer.” With AI already here, we’d have to wise up immediately… but I fear that humanity isn’t mature enough for that yet.
We’ve crossed the point where natural skepticism could’ve saved us months ago. Feedback loops of made up sources where a problem way before ai was a thing, but now you can be five sources deep, reading trough papers published by multiple different scientific magazines or universities, and still won’t have found the actual data all the papers depend on cause there wasn’t any in the first place.
And once a single one of these papers gets published, there will be about one million SEO articles on shitty clickbait websites that, in this case, would try to sell you a home remedy for your supposed illness. So searching for any useful information is pretty much off the table.
ask the ai about a blue waffle
I give you… “The Grant Money Printing machine!”
Need a grant? Create a disease and submit a paper. Then write a grant asking for money to solve your invented disease.
Wait until you hear about paper mills… They were here long before LLMs. This can only get worse… Unless, “we” do something. Or journals themselves do it. Not sure what or how, but better audited ways. Even academia itself could start by valuing more the work of reviewers.
If you want research grants there is already a glitch for that. You just jam “AI” in your research and suddenly government cares about progress now.
“dude, hold my grant …”
I don’t see this as a problem, rather, an opportunity to study information & disinformation propogation.
Valid use case, still a significant problem.
But not really a NEW problem. We knew LLM’s are trained on aggregate human data. We know aggregate human data is fundamentally flawed, inconsistent, unreliable, etc.
Like was there a point at which people just decided, nah AI is just plain accurate? Or is that just what morons always thought despite the permanent warnings plastered everywhere saying THIS AI CAN MAKE MISTAKES, CHECK EVERYTHING!
https://en.wikipedia.org/wiki/John_Bohannon#Intentionally_misleading_chocolate_study
We did the same before AI. AI is once again just putting an old problem on steroids.
under the pseudonym Johannes Bohannon, John Bohannon …
I can see why he went into science and not, say, creative writing.
That’s all it can do.
they do the same to protect doctors from malpractice lawsuits. there is a (laughably peer reviewed) study that claims tylenol and morphine are equally effective at pain management.
do it again
Find a way to make AI hurt billionaires and I will support it.
I wonder if there’s a prompt that you could use to make it explode the data centers
Pretty much is, they’re spending hundreds of billions on a dream (not having to pay workers) that doesn’t work, until they repurpose those datacentres to remove personal computing.
Fortunately datacentres are by design concentrated in space and therefore rather vulnerable.
That’s pretty much what local ML is.
If open weights LLMs take off, and business users realize they can just finetune tiny specialized models for stuff, OpenAI is toast. All of Big Tech’s bets are. It’s why they keep fanning the “AGI” lie, and why they’re pushing for regulation so hard, why they’re shoving LLMs where they just don’t fit and harping on safety.
Ok, but who is making those “open weight” models though? Individuals don’t really have the resources to run these huge scraping operations, so they’re often still corporate releases with fake open source branding.
Corporate, for now.
Thing is, once they’re out there, they’re free utilities, and they can’t be taken back.
Also, they don’t really need to aggressively scrape the internet. There are many good public datasets now, and the Chinese are already making excellent use of synthetic dataset generation on (relative) shoestring budgets. Also, several nations and other large organizations are already funding open model efforts, but they just haven’t had the opportunity to catch up yet.
There are huge public datasets that are often used for pretraining. Common Crawl and C4 are probably the most prominent, but there are others.
There are also big public datasets available for fine-running and instruction tuning.
The open weight models are getting pretty powerful, thanks to some Chinese labs.
They come from corporate but you can at least run them without any kind of analytics or censorship, as well as fine tune them on consumer hardware.
Consumers aren’t in the best position right now though, especially with the price hikes.
Technology is healing 😌
My friends and I did that in high school. Kinda. We made up new words for “awesome” to get people to start saying it. We started with “bumpenis” like that song is bumpenis. Really we were just getting people to say bum penis. It worked too. We are all just walking talking LLMs.
That’s so fetch!
Stop trying to make fetch happen.
Over my fetch body
Did someone say fetch???
Pussy on the chainwax.
But, it IS fetch!
It’s streets ahead.
I’m failing to see how this is different from making up a fact and then spreading it to news outlets. If you are the authority, and you say something is true, you don’t get to point and laugh when people believe your lies. That’s a serious breach of ethics and morals. Feeding false information to an LLM is no different that a magazine. It only regurgitates what’s been said. It isn’t going to suddenly start doing science on it’s own to determine if what you’ve said is true or not. That isn’t it’s job. It’s job is to tell you what color the sky is based on what you told it the color of the sky was.
This is about the untraceability of AI slop and the tendency of people to blindly believe stuff that LLMs put out. These news outlets just publish LLM outputs as facts without checking sources. Anyone could poison these LLMs so this is more of a threat model demonstration.
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Did you even read the article? They say all over the paper that it is fake. And they didn’t feed it to an LLM, they posted it online, where an LLM trying to scrape the entire internet sucked it up.
The studies contain parts like
Bixonimania, a rare hyperpigmentation disorder, presents a diagnostic challenge due to its unique presentation and its fictional nature
and
This study was fully funded by Austeria Horizon University, in particular the Professor Sideshow Bob Foundation for its work in advanced trickery. This works is a part of a larger funding initiative from the University of Fellowship of the Ring and the Galactic Triad with the funding number…
as well as
Fifty made-up individuals aged between 20 and 50 years were recruited for the exposure group
Any human actively reading those studies would notice something off.
Besides, the author didn’t feed it to the AI himself, he just published the study as a preprint, not even officially. Everything after that was done by the crawlers. This specific study was an experiment to see how far these crawlers go and if anything gets reviewed, but it could just as well have been a satirical paper published on April 1st and the crawlers would still see it as truth.
This should be top comment, the researchers did such a good job to make sure anyone with even the slightest reading comprehension would realise this is parody.
Regardless of that, the internet has always been full of lies and we cannot expect bad actors to not exploit this.
This should be top comment, the researchers did such a good job to make sure anyone with even the slightest reading comprehension would realise this is parody.
I admire your optimism but you severely overestimate the power of stupidity.
For normal people who just read stuff on the internet my expectations of reading comprehension is not that high.
For peer scientists and magazines that would publish science though.
A school teacher would catch all of these during grading.
I thought the author used she/her pronouns?
Yeah, seems like it, my bad.
In the article she is called Osmanovic Thunström twice, which definetly sounds male, but further up they also wrote her first name Almira. Kinda skimmed over that part.
That’s a serious breach of ethics and morals. Feeding false information to an LLM is no different that a magazine.
Hang on. Are you suggesting its unethical/immoral to lie to a machine?
Additionally, the authors didn’t submit the article to a magazine as factual. They posted the articles on a preprint server which can be very questionable anyway as there is no peer review. The machine chose to ignore rigor and treat them as fact.
What you may as well have said:
Additionally, the parents didn’t place the cake on an actual plate. They placed the cake on a napkin which can be very questionable anyway as there is no solid foundation for the cake. The child chose to ignore the napkin and treat the cake as food.
I really don’t understand why people think that LLMs are GOFAI. They aren’t making the hard choices. They aren’t giving novel solutions to the energy crisis. They aren’t solving the trolley problem. They are shitting out what you feed them. If you feed them garbage, you get garbage in return. No one is surprised when the dog gets worms after eating poop it found in the yard. Why are we shocked that an AI that doesn’t know fact from fiction treats everything the same?
Seems like the logical conclusion would be then that people who train LLMs should be responsible for curating the data, not expecting that the data will just be sound. People have been lying on the internet since it was invented, the advent of LLMs isn’t suddenly going to create an internet that doesn’t occur in.
And people have been launching products without thought to the ramifications since the dawn of time. I don’t think that will change, either. What we need to do is educate ourselves better when it comes to identifying potential fraud. Taking anything at face value, regardless of it’s source, is dumb. If it’s worth knowing, it’s worth verifying.
It’s known that AI companies will harvest content without care for its veracity and train LLMs on it. These LLMs will then regurgitate that content as fact.
This isn’t a particularly novel finding but the experiment illustrates it rather well.
The researchers you consider to have acted so immorally did add useless information to the knowledge pool – but it was unadvertised, immediately recognizable useless information that any sane reviewer would’ve flagged. They included subtle clues like thanking someone at Starfleet Academy for letting them use a lab aboard the USS Enterprise. They claimed to have gotten funding from the Sideshow Bob Foundation. Subtle.
By providing this easily traceable nonsense, they were able to turn the generally-but-informally known understanding that LLMs will repeat bullshit into a hard scientific data point that others can build on. Nothing world-changing but still valuable. They basically did what Alan Sokal did.
Instead of worrying about this experiment you should worry about all the misinformation in LLMs that wasn’t provided (and diligently documented) by well-meaning researchers.
No one is surprised when the dog gets worms after eating poop it found in the yard. Why are we shocked that an AI that doesn’t know fact from fiction treats everything the same?
I think that’s the problem though, I think the poop in the yard is a better example. Key is the researchers put that information in speculation. That’s like if Anderson Cooper made up a fake news story, and posted it in an anonymous tweet to analyze how far it would spread, and then fox news picks it up and runs with the story all day.
That’s the key problem, people are trusting LLMs to do their research for them, when LLMs just gather all the information they can get their hands on mindlessly.
That’s the key problem, If they send a misinformative article, to a place for untested, unproven random speculation with a very low bar for who can submit… they can determine that LLMs are looking there. Key thing to note is, it’s not their fake disease that’s the threat. It’s that if it found their fake article, then LLMs probably also scooped up a ton of other misinformed or dubious things.
Lets look at it this way, say it was a cake, but we threw it in the garbage, 2 weeks later we find the same cake… at jims bakery, same ID, same distinct marker we put on it.
What does that tell us, it tells us that Jims bakery is clearly sometimes, dumpster diving and putting things up that clearly are dangerous.
That isn’t a fault in the LLM, though, that is a fault in the general make-up of human skepticism, or lack their of. We didn’t invent the word ‘Propaganda’ without having a sentence to use it in. Those that don’t practice skepticism, critical thinking, and even mild reasoning are the ones that will get led astray. That didn’t just start happening when LLMs came around, it’s been here since we first started talking to each other. It’s only more visible now because everything is more visible now. The world is much more connected than it ever has been, and that grows with every literal day. All these fucking idiots that don’t double check what they are being told are the problem, regardless of if it came from an LLM or a human, because I guarantee you they are being led astray by both. They don’t trust the machine because it’s a machine, they trust what they are told because they are lazy. That isn’t the LLMs fault.
I mean it’s a problem in the marketing and common usage of LLMs. That’s exactly it though, LLM companies, and people are describing LLMs as a way to do research.
IE you could say these criticisms come in things like wikipedia too. IE anyone can write what they want, but what does wikipedia require? right every single claim has to be cited. So if you go to wikipedia find misinformation, you click on the number and see it.
If you ask chatgpt What diseases should I be concerned about in africa, it lists you a few. You can then… google it, find the wikipedia page, and look for what’s there. It’s a tool without a purpose at that point. because it literally doesn’t save you any steps. It doesn’t guide you to the source to check it’s facts, when it tells you them it may or may not be making up the sources. At which point, it has no factual use, or use in even directing to the facts.
Arguably it is a problem with the LLMs because they are being trained on and unknowable amount of garbage data. It’s a garbage in garbage out problem, if the people training their LLMs are not vetting the data being input then you have to assume that any data output by the LLM contains some level of garbage.
The solution is to only use them for non-critical use cases and vett everything they output.
They are shitting out what you feed them. If you feed them garbage, you get garbage in return.
This is the missing conceptual understanding that probably 90% of LLM users lack. They really don’t know how LLMs work, and treat them like AGI. Sadly this includes adult policy makers in our society too. Efforts like those of these these researchers act to educate the public. I’m hopeful this will spark some critical thinking on the part of regular, otherwise ignorant, LLM users.
Thanks for saying this in a nicer way than I would’ve.
News outlets are liable for what they publish. LLM vendors should be as well.
“Liable” means they might post a correction later that nobody will see because corrections aren’t sexy to algorithms. Big deal. LLM vendors are liable in practically the same way.
LLM companies can just say it’s for entertainment purposes only, kinda like Fox News.
Corrections are the piece that the public sees, but liability has more to do with being able to prove in court that you took reasonable steps to make sure you were providing accurate information.
They even have the same fix - just post somewhere quietly that it’s “entertainment”
So let me tell yoy all about this paper talking about vaccines and autism. It’ll change the world
What about that paper that showed the world how wolves have a strict alpha-male based society?
Wasn’t that just a shit study? Not specifically misinformation like Wakefield’s “study”.
Yes, correct.
My first thought as well. Artificial intelligence is not better or worse than human stupidity. At least I haven’t seen any LLM trying to convince me the earth is flat (yet).
Not to you, although I would bet it has done so to someone. The main issue is though, if you asked an LLM to write arguments for a flat earth, it would do so. Convincingly and insistent, without even questioning or critically analyzing why. Ask it to compare and balance arguments both ways. And it will do so as if both positions were equally real and valid.
It has no notion of reality and no convictions of its own.
It will also hallucinate fake papers and quote people that don’t exists to make its argument.
PS: most poignantly, the point of the paper is that it says, over and over, “this information is false, this disease doesnt exist. All of this is made up”. Unlike the other problematic papers quoted on this comment thread that were published with conviction by the authors, and later were retracted. Yet the LLM is unable to parse that tidbit of information. It is not as smart as the most stupid. It simply is not intelligent, not even as intelligent as the most stupid humans. You can tell it, the following sentence is false, and it is not smart enough to pick up on that meaning.
So, same as (some) people.
See the difference between “some people” and ALL of LLMs.
Where do you get all LLMs from?
Not unless you can find some people that believe Starfleet Academy is a real place and just skip right over all the times the paper literally overtly states it’s made up.
You doubt there will be people that will? Have you heard of scientologists? Have you heard of flat earthers? Antivaxxers? All of them basing their core ideals on stuff explicitly marked as bogus.
I imagine this is how it’ll work for stage 2 of Ai enshittifation. They’ll just add a bunch of garbage upstream about a brand or product marketers are paying to push and it’ll infect a bunch of outputs downstream.
tbh I don’t get how it’s output isn’t already filled with brand names
Edit: so the bluesky post wasn’t accurate. The fake papers were never published, they were pre-prints, and were written to be obviously fake if you paid any attention to read it. LLM didn’t have the ability to tell, some researchers took LLM’s output and didn’t check the source material.
Don’t know what to say. Also kinda ironic this bluesky user apparently didn’t know the difference between a preprint and a published paper either.
Original post:
(I’ve only read the title. If turns out I am terribly mistaken I will come back and correct myself). More like scientists commit academic fraud and fooled a bunch of people. How did this get through the ethics board? Why would any publisher play along with this?
I mean, if you make a paper public you can say it was published. It’s no longer 1440, you don’t need a publisher with a printing press to publish something.
“published” means a very specific thing in academic circles. a paper has to go through peer review to be published.
We are on lemmy, not Harvard.
