I would be in trouble if this was a thing. My writing naturally resembles the output of a ChatGPT prompt when I'm not joke answering or shitposting.
this post was submitted on 10 Sep 2023
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I would be in trouble if this was a thing. My writing naturally resembles the output of a ChatGPT prompt when I’m not joke answering.
It's not unusual for well-constructed human writing to resemble the output of advanced language models like ChatGPT. After all, language models like GPT-4 are trained on vast amounts of human text, and their main goal is to replicate and generate human-like text based on the patterns they've observed.
/gpt-4
Be me
well-constructed human writing
You guys?! 🤗
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they never did, they never will.
Why tho or are you trying to be vague on purpose
Because you're training a detector on something that is designed to emulate regular languages closest possible, and human speech has so much incredible variability that it's almost impossible to identify if someone or something has been written by an AI.
You can detect maybe your typical generic chat GPT type outputs, but you can characterize a conversation with chat GPT or any of the other much better local models (privacy and control are aspects which make them better) and after doing that you can get radically human seeming outputs that are totally different from anything chat GPT will output.
In short, given a static block of text it's going to be nearly impossible to detect if it's coming from an AI. It's just too difficult to problem, and if you're going to solve it it's going to be immediately obsolete the next time someone fine tunes their own model
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Because AIs are (partly) trained by making AI detectors. If an AI can be distinguished from a natural intelligence, it's not good enough at emulating intelligence. If an AI detector can reliably distinguish AI from humans, the AI companies will use that detector to train their next AI.
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I know a couple teachers (college level) that have caught several gpt papers over the summer. It’s a great cheating tool but as with all cheating in the past you still have to basically learn the material (at least for narrative papers) to proof gpt properly. It doesn’t get jargon right, it makes things up, it makes no attempt to adhere to reason when it’s making an argument.
Using translation tools is extra obvious—have a native speaker proof your paper if you attempt to use an AI translator on a paper for credit!!
it makes things up, it makes no attempt to adhere to reason when it’s making an argument.
It doesn't hardly understand logic. I'm using it to generate content and it continuously will assert information in ways that don't make sense, relate things that aren't connected, and forget facts that don't flow into the response.
As I understand it as a layman who uses GPT4 quite a lot to generate code and formulas, it doesn't understand logic at all. Afaik, there is currently no rational process which considers whether what it's about to say makes sense and is correct.
It just sort of bullshits it's way to an answer based on whether words seem likely according to its model.
That's why you can point it in the right direction and it will sometimes appear to apply reasoning and correct itself. But you can just as easily point it in the wrong direction and it will do that just as confidently too.
It has no notion of logic at all.
It roughly works by piecing together sentences based on the probability of the various elements (mainly words but also more complex) being there in various relations to each other, the "probability curves" (not quite probability curves but that's a good enough analog) having been derived from the very large language training sets used to train them (hence LLM - Large Language Model).
This is why you might get things like pieces of argumentation which are internally consistent (or merelly familiar segments from actual human posts were people are making an argument) but they're not consistent with each other - the thing is not building an argument following a logic thread, it's just putting together language tokens in common ways which in its training set were found associate with each other and with language token structures similar to those in your question.
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I have to hand in a short report
I wrote parts of it and asked chatgpt for a conclusion.
So i read that, adjusted a few points. Added another couple points..
Then rewrote it all in my own wording. (Chatgpt gave me 10 lines out of 10 pages)
We are allowed to use chatgpt though. Because we would always have internet access for our job anyway. (Computer science)
I found out on the last screen of a travel grant application I needed a coverletter.
I pasted in the requirements for the cover letter and what I had put in my application.
I pasted the results in as the cover letter without review.
I got the travel grant.
Who reads cover letters? At most they are skimmed over.
Exactly. But they still need to exist. That's what chat gpt is for. Letters, bullshit emails, applications. The shit that's just tedious.
OpenAI discontinued its AI Classifier, which was an experimental tool designed to detect AI-written text. It had an abysmal 26 percent accuracy rate.
If you ask this thing whether or not some given text is AI generated, and it is only right 26% of the time, then I can think of a real quick way to make it 74% accurate.
I feel like this must stem from a misunderstanding of what 26% accuracy means, but for the life of me, I can't figure out what it would be.
Looks like they got that number from this quote from another arstechnica article ”…OpenAI admitted that its AI Classifier was not "fully reliable," correctly identifying only 26 percent of AI-written text as "likely AI-written" and incorrectly labeling human-written works 9 percent of the time”
Seems like it mostly wasn’t confident enough to make a judgement, but 26% it correctly detected ai text and 9% incorrectly identified human text as ai text. It doesn’t tell us how often it labeled AI text as human text or how often it was just unsure.
EDIT: this article https://arstechnica.com/information-technology/2023/07/openai-discontinues-its-ai-writing-detector-due-to-low-rate-of-accuracy/
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AI company says their AI is smart, but other companies are sell snake oil.
Gottit
The only thing AI writing seems to be useful for is wasting real people's time.
True -
- Write points/summary
- Have AI expand in many words
- Post
- Reader uses AI to generate summarize post preferably in points
- Profit??
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Did human-generated content really become so low quality that it is distinguishable from AI-generated content?
Should I be able to detect whether or not this is an AI generated comment?
As an AI language model, I am unable to confirm whether or not the above post was written by an AI.
People kind of just suck at writing in general. It's not a skill that's valued so much, otherwise writers, editors, and proofreaders would be paid more.
Not necessarily. It's just that AI's can't tell the difference.
Although I don't know whether humans can.
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Regardless of if they do or don't, surely it's in the interests of the people making the "AI" to claim that their tool is so good it's indistinguishable from humans?
Depends if they’re more researchers or a business imo. Scientists generally speaking are very cautious about making shit claims bc if they get called out that’s their career really.
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A lot of these relied on common mistakes that "AI" algorithms make but humans generally don't. As language models are improving, it's harder to detect.
They're also likely training on the detector's output. That why they build detectors. It isn't for the good of other people. It's to improve their assets. A detector is used to discard some inputs it knows are written by AI so it doesn't train on that data, which leads to it out competing the detection AI.
mfw just asking ChatGPT to write an undetectable essay.
Later, losers!
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