‘ChatGPT detector’ catches AI-generated papers with unprecedented accuracy

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.

Also one very important aspect of this is that it must be possible to backpropagate the discriminator. If you just have access to inference on a detector of some kind but not the model weights and architecture itself, you won't be able to perform backpropagation and therefore can't generate gradients to update your generator's weights.

That said, yes, GANs have somewhat fallen out of favor due to their relatively poor sample diversity compared to diffusion models.

I know it’s intrinsic to GANs but I think I had read that this was a flaw in the entire “detector” approach to LLMs as well. I can’t remember the source unfortunately.

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

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?

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.

Bro gotta get that shit out. Not doing the work to jerk off to the process.

There's a difference between using ChatGPT to help you write a paper and having ChatGPT write the paper for you. One invokes plagiarism which schools/universities are strongly against.

The problem is being able to differentiate between a paper that's been written by a human (which may or may not be written with ChatGPT's assistance) and a paper entirely written by ChatGPT and presented as a student's own work.

I want to strongly stress that in the latter situation, it is plagiarism. The argument doesn't even involve the plagiarism that ChatGPT does. The definition of plagiarism is simple, ChatGPT wrote a paper, you the student did not and you are presenting ChatGPT's paper as your own, ergo plagiarism.

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

Science isn't about writing. It is about finding new data through scientific process and communicating it to other humans.

If a tool helps you do any of it better, faster or more efficiently, that tool should be used.

But I agree with your sentiment when it comes to for example creative writing.

To me this question hints at the seismic paradigm shift that comes from generative AI.

I struggle to wrap my head around it and part of me just wants to give up on everything. But... We now have to wrestle with questions like:

What is art and do humans matter in the process of creating it? Whether novels, graphic arts, plays, whatever else?

What is the purpose of writing?

What if anything is still missing from generative writing versus human writing?

Is the difference between human intelligence and generative AI just a question of scale and complexity?

Now or in the future, can human experience be simulated by a generative AI via training on works produced by humans with human experience?

If an AI can now or some day create a novel that is meaningful or moving to readers, with all the hallmarks of a literary masterwork, is it still of value? Does it matter who/what wrote it?

Can an AI have novel ideas and insights? Is it a question of technology? If so, what is so special about humans?

Do humans need to think if AI one day can do it for us and even do it better than we can?

Is there any point in existing if we aren't needed to create, think, generate ideas and insights? If our intellect is superfluous?

If human relationships conducted in text and video can be simulated on one end by a sufficiently complex AI, to fool the human, is it really a friendship?

Are we all just essentially biological machines and our bonds simply functions of electrochemical interactions, instincts, and brain patterns?

I'm late to the game on all this stuff. I'm sure many have wrestled with a lot of this. But I also think maybe generative AI will force far more of us to confront some of these things.

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.

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.

Hahahaha OMG. I fixed it. Thanks!

Oh yes, by fight I mean that no matter how hard developers push proprietary software they get craked anyway, its so funny.

Ahh, so the true rate would actually be 50% if it was no better than random chance?