- cross-posted to:
- science@mander.xyz
- academia@mander.xyz
- cross-posted to:
- science@mander.xyz
- academia@mander.xyz
You must log in or register to comment.
Doubt
Believable because:
However, the system is highly specialized for scientific journal articles. When presented with real articles from university newspapers, it failed to recognize them as being written by humans.
So outside of its purview? Agree.
Why?
Chatgpt writes them all the same. So its not so much “an AI wrote this” as it is “Bob always writes like this, we know Bob wrote this because _____”
It’s a bad headline, but the article immediately clarified.
All of these were written by chatgpt:
To make toast, start by plugging in your toaster and adjusting the browning setting to your preference. Take a slice or two of bread and place them into the toaster slots. Push down the lever to activate the heating elements. Wait for a few minutes until the toaster automatically pops the toast back up, indicating it’s ready. Carefully remove the toast and spread your desired toppings, such as butter or jam, to taste. Enjoy your warm, crispy toast, a simple and satisfying breakfast or snack.
In the pursuit of achieving the toasted state of bread, one must first interface with an electrical device colloquially known as a toaster. This remarkable appliance harnesses electrical energy to generate heat through resistive elements. Place slices of bread in the designated slots, ensuring that the toaster is appropriately powered, and set the temporal parameter of toasting, often denoted as “browning level,” to the desired degree of crispiness. Activation is achieved by engaging the mechanical lever, prompting the transformational process, during which thermal energy is conveyed into the bread, inducing a Maillard reaction that alters its molecular structure. Upon the cessation of this temporal journey, the toaster signals completion. Carefully extract the now-toasted bread, apply preferred condiments, and savor this culinary endeavor.
Alright, so like, to make some bomb toast, you gotta start by pluggin’ in that toaster thingy and crankin’ up the toastiness level, you know, like, how crispy you want it. Then you grab your slices of bread and just slide ‘em into those slots in the toaster, pop the sucker down, and hit the magic button to fire it up. While you’re waitin’ for the toasting action to go down, you can do a lil’ dance or somethin’, and when it’s done, it’s like, bam, your toast is ready, girl! Grab it, slather on some butter or whatever floats your boat, and get your snack on – it’s, like, totally yum!
Well, back in our day, making toast was a straightforward affair. First, you’d plug in your trusty toaster and set the browning knob to your liking. Then, take a couple of slices of good old-fashioned bread, none of that fancy stuff, and place them gently into the toaster slots. Press down the lever, and as the heating elements did their work, you’d have time to catch up on the morning paper. When the toast popped up, simply retrieve it with a fork or a butter knife, add some butter, and there you had it – a simple, no-fuss breakfast, just the way we liked it. Those were the days, my friend.
Seriously, making toast is, like, the most basic skill ever, and it’s so obvious that anyone who doesn’t get it must be, like, a total amateur. You just plug in that toaster and adjust the settings for your personal taste – it’s not rocket science, people! Then, grab some bread, any kind you want, and drop it into the slots, it’s not that hard. Push the lever down, and boom, the heat does its thing. It’s, like, literally impossible to mess up. But I guess there are still some folks out there who, like, need to argue about every little detail because they just can’t accept that not everyone is a culinary genius. 😒🍞 #ToastGate
No, if chatgpt does not write it all the same.
It’s hilarious watching people act like AI is so good that AI can’t tell an AI wrote something.
To you those might seem completely different, but you’re overestimating AI on one side and underestimating on the other.
It’s a hell of a lot easier for AI to check for similarities than it is to write something without similarities, even if a human can’t see them. Checking is always easier than producing for AI
It’s mathematically impossible to detect them reliably. But I know you will know it better.
https://www.techspot.com/news/98031-reliable-detection-ai-generated-text-impossible-new-study.html
Edit: here is the actual study: https://arxiv.org/abs/2303.11156
Here is the link in that article to The study
Regarding mathematical impossibility…
We then provide a theoretical impossibility result indicating that as language models become more sophisticated and better at emulating human text, the performance of even the best-possible detector decreases. For a sufficiently advanced language model seeking to imitate human text, even the best-possible detector may only perform marginally better than a random classifier. Our result is general enough to capture specific scenarios such as particular writing styles, clever prompt design, or text paraphrasing.
Interesting. Now, this is just one paper. And one paper does not mean the science is settled on that topic.
The implications are certainly interesting.
I’m curious how much data would be required to successfully mimic a specific writing style (e.g. lemmy post or research paper or letter to family) for a specific person. And conversely how easy it would be to detect.
I haven’t thought about this in depth yet. But the threats that come to mind are: someone spoofing me for some reason or me using AI to “research” and write for me (school, say) so I don’t actually have to learn anything. The former makes me wonder if digital signatures will become more widely adopted. The latter probably requires a different approach to assessing the knowledge of students. I’m sure there are other threats we can think of given a little more time.
This is like someone disputing an article about the Wright Brothers first flight with one from 6 months earlier that says manned flight can’t happen…
No references whatsoever to false positive rates, which I’d assume are quite high. Also, they single out that they built this detector to catch chemistry-related AI-generated articles
If you call heads 100% of the time, you’ll be 100% accurate on predicting heads in a coin toss.
As I understand it, one of the ways AI models are commonly trained is basically to run them against a detector and train against it until they can reliably defeat it. Even if this was a great detector, all it’ll really serve to do is teach the next model to beat it.
I really really doubt this, openai said recently that ai detectors are pretty much impossible. And in the article they literally use the wrong name to refer to a different AI detector.
Especially when you can change Chatgpt’s style by just asking it to write in a more casual way, “stylometrics” seems to be an improbable method for detecting ai as well.
It’s in openai’s best interests to say they’re impossible. Completely regardless of the truth of if they are, that’s the least trustworthy possible source to take into account when forming your understanding of this.
openai had their own ai detector so I don’t really think it’s in their best interest to say that their product being effective is impossible
Willing to bet it also catches non-AI text and calls it AI-generated constantly
The original paper does have some figures about misclassified paragraphs of human-written text, which would seem to mean false positives. The numbers are higher than for misclassified paragraphs of AI-written text.
This is kind-of silly.
We will 100% be using AI to generate papers now and in the future. If the AI can catch any wrong conclusions or misleading interpretations, that would be helpful.
Not using AI to help you write at this point is you wasting valuable time.
They’re just mad that the drudgery of writing papers is coming to an end and they have one less tool to torment students.
I do a lot of writing of various kinds, and I could not disagree more strongly. Writing is a part of thinking. Thoughts are fuzzy, interconnected, nebulous things, impossible to communicate in their entirety. When you write, the real labor is converting that murky thought-stuff into something precise. It’s not uncommon in writing to have an idea all at once that takes many hours and thousands of words to communicate. How is an LLM supposed to help you with that? The LLM doesn’t know what’s in your head; using it is diluting your thought with statistically generated bullshit. If what you’re trying to communicate can withstand being diluted like that without losing value, then whatever it is probably isn’t meaningfully worth reading. If you use LLMs to help you write stuff, you are wasting everyone else’s time.
Yeah, I agree. You can see this in all AI generated stuff - none of it has any purpose, no intention.
People who say it’s saving them time, I mean I have to ask what these people are doing that can be replaced by AI and whether they’re actually any good at it, and whether the AI has improved their work or just made it happen faster at the expense of quality.
I have turned off all predictive writing of any kind on my devices, it gets in my head and stops me from forming my own thoughts. I want my authentic voice and I can’t stand the idea of a machine prompting me with its own idea of what I want to say.
Like… we’re prompting the AI, but are they really prompting us?
Amen. In fact, I wrote a whole thing about exactly this – without an LLM! Like most things I write, it took me many hours and evolved many times, but I take pleasure in communicating something to the reader, in the same way that I take pleasure in learning interesting things reading other people’s writing.
How is an LLM supposed to help you with that?
I have it read and review a couple paragraphs of a research article, many many times, to create a distribution of what was likely said in those paragraphs, in a tabular format. I’ll also work with it to create an outline of an idea I’m working on to keep me focused, and help develop my research plan. I’ll then ask it to drill down into each sub-point and give me granular points to focus on. Obviously, I’m steering, but its not too difficult to use it in such a way that it creates a scaffolding for you to work from.
If you use LLMs to help you write stuff, you are wasting everyone else’s time.
If you aren’t using LLMs to help you write stuff, you are wasting your own time.
I don’t think that sounds like a good way to make a good paper that effectively communicates something complex, for the reasons in my previous comment.
Not using AI to help you write at this point is you wasting valuable time.
Bro WHAT are you smoking. In academia the process of writing the paper is just as important as the paper itself, and in creative writing why would you even bother being a writer if you just had an ai do it for you? Wasting valuable time? The act of writing it is inherently valuable.
Bro gotta get that shit out. Not doing the work to jerk off to the process.
I don’t understand. Are there places where using chatGPT for papers is illegal?
The state where I live explicitly allows it. Only plagiarism is prohibited. But making chatGPT formulate the result of your scientific work, or correct the grammar or improve the style, etc. doesn’t bother anybody.
If you use chatGPT you should still read over it, because it can say something wrong about your results and run a plagiarism tool on it because it could unintentionally do that. So whats the big deal?
It’s not a big deal. People are just upset that kids have more tools/resources than they did. They would prefer kids wrote on paper with pencil and did not use calculators or any other tool that they would have available to them in the workforce.
Teachers when I was little “You won’t always have a calculator with you” and here I am with a device more powerful than what sent astronauts to the moon in my pocket 24/7
1% battery intensifies
Fun fact for you, many credit-card/debit-card chips alone are comparably powerful to the computers that sent us to the moon.
It’s mentioned a bit in this short article about how EMV chips are made. This summary of compute power does come from a company that manufactures EMV chips, so there is bias present.
If you use chatGPT you should still read over it, because it can say something wrong about your results and run a plagiarism tool on it because it could unintentionally do that. So whats the big deal?
There isnt one. Not that I can see.
At least within a higher level education environment, the problem is who does the critical thinking. If you just offload a complex question to chat gpt and submit the result, you don’t learn anything. One of the purposes of paper-based exercises is to get students thinking about topics and understanding concepts to apply them to other areas.
You are considering it from a student perspective. I’m considering it from a writing and communication/ publishing perspective. I’m a scientist, I think a decent one, but I’m a only a proficient writer and I don’t want to be a good one. Its just not where I want to put my professional focus. However, you can not advance as a scientist without being a ‘good’ writer (and I don’t just mean proficient). I get to offload all kind of shit to chat GPT. I’m even working on some stuff where I can dump in a folder of papers, and have it go through and statistically review all of them to give me a good idea of what the landscape I’m working in looks like.
Things are changing ridiculously fast. But if you are still relying on writing as your pedagogy, you’re leaving a generation of students behind. They will not be able to keep up with people who directly incorporate AI into their workflows.
I’m curious what field you’re in. I’m in computer vision and ML and most conferences have clauses saying not to use ChatGPT or other LLM tools. However, most of the folks I work with see no issue with using LLMs to assist in sentence structure, wording, etc, but they generally don’t approve of using LLMs to write accuracy critical sections (such as background, or results) outside of things like rewording.
I suspect part of the reason conferences are hesitant to allow LLM usage has to do with copyright, since that’s still somewhat of a gray area in the US AFAIK.
I work in remote sensing, AI, and feature detection. However, I work almost exclusively for private industry. Generally in the natural hazard, climate mitigation space.
Lately, I’ve been using it to statistically summarize big batches of publications into tables that I can then analyze statistically (because the LLMs don’t always get it right). I don’t have the time to read like that, so it helps me build an understanding of a space without having to actually read it all.
I think the hand wringing is largely that. I’m not sure its going to matter in 6 months to a year. We’re at the inflection (like pre-alpha go) where its clear that AI can do this thing that was thought to be solely the domain of humans. But it doesn’t necessarily do it better than the best of us. We know how this goes though. It will surpass, and likely by a preposterous margin. Pandoras box is wide open. No closing this up.
Didn’t OpenAI themselves state some time ago that it isn’t possible to detect it?
I’m gonna need something more then that too belive it
The article is reporting on a published journal article. Surely that’s a good start?
I haven’t read the article myself, but it’s worth noting that in CS as a whole and especially ML/CV/NLP, selective conferences are generally seen as the gold standard for publications compared to journals. The top conferences include NeurIPS, ICLR, ICML, CVPR for CV and EMNLP for NLP.
It looks like the journal in question is a physical sciences journal as well, though I haven’t looked much into it.
Well with VC investment low due to higher interest rates it was only a matter of time before academic people started posting bullshit papers to lure that sweet sweet VC money.
Seems like a few people at the University of Kansas in Lawrence are making a run at a start up.
Isnt this like a constant fight between people who develop anti-ai-content and the internet pirates who develop anti-anti-ai-content? Pretty sure the piratea always win.
Reminds me of the trace buster buster buster
I say we develop a Voight-Kampff test as soon as possible for detecting if we’re speaking to an AI or an actual human being when chatting or calling a customer representative of a company.
Edit: I made a mistake.
if we’re speaking to a real person or an actual human being
Ummm …
Hahahaha OMG. I fixed it. Thanks!
they still can’t capture data written from Ai over websites like ’ https://themixnews.com/’ https://themixnews.com/cj-amos-height-age-brother/
Isn’t current precedent 0% accuracy already?
If you have 0% accuracy in a binary decision, you could just always choose the other option and be right 100% of the time.
Ahh, so the true rate would actually be 50% if it was no better than random chance?
