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Ask HN: How would you build a ChatGPT detector?

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Re: Ask HN: How would you build a ChatGPT detector?

#21

Post by skilled »

I'm not sure if you're only asking about specifics or you have a broader concern, but even if you build such a model, it wouldn't make any difference for cases where some kind of "gain" is involved. Be it financial, educational, etc.

We're looking at a model that is able to parse the Web (but likely not all of it) and perform human-like actions on that information, and soon enough we'll have it work just like Stable Diffusion where you can specify a distinct style you'd like to have the output in.

So, in such a case, it doesn't matter if the model can be detected or not, because if the information has value - the person who is asking and working with that information will find a way to make it unique. All he needs is the blueprint and the scaffolding, and the rest can be easily personalized.

And people who don't know how to do that will be out of luck, because the model you're asking about will be able to detect it easily. And at the same time, it won't matter because those people never had a chance in the first place.

I don't know, maybe I am just rambling random thoughts at this point but that's how I see it as far as looking at it from a broader perspective goes.

Re: Ask HN: How would you build a ChatGPT detector?

#22

Post by amanzi »

xdennis wrote: post #18

According to ChatGPT: > 1. Start by training a machine learning model to identify features of natural language. You can use supervised learning techniques with a corpus of labeled data consisting of texts written by both humans and AI systems. > 2. Use natural language processing techniques to extract features from the text such as word frequencies, grammar, and syntax. > 3. Implement a scoring system to assign a num…

I also asked ChatGPT a similar question to which it started its response with: "To train an AI to detect text written about another AI, you would need to use a technique called supervised learning. In supervised learning, you would provide the AI with a large dataset of text, some of which is written about AI and some of which is not. The AI would then learn to identify the characteristics of text written about AI and use those characteristics to make predictions on new, unseen text."

So I followed up with another question: "Did an AI write the following paragraph?" and then I pasted the above paragraph of text to follow.

ChatGPT responded with: "No, a human wrote the paragraph you provided. It is possible that an AI could be trained to generate text that is similar to the paragraph you provided, but it did not write the paragraph itself."

Oh oh...

Re: Ask HN: How would you build a ChatGPT detector?

#23

Post by sergiotapia »

Jabrov wrote: post #20
devit wrote: post #17

Great question! I've been using the new AI assistant for a while now and I've definitely noticed a certain "sameness" to its responses. In fact, I think it would be relatively easy to build an AI that could recognize the writing of this AI. The key would be to train the AI on a large dataset of the assistant's responses, which would allow it to learn the patterns and characteristics of the assistant's writing style.…

This was written by a bot. I wish you would label it.

This was written by a bot. I wish you would label it.

Re: Ask HN: How would you build a ChatGPT detector?

#24

Post by [deleted] »

skilled wrote: post #21

I'm not sure if you're only asking about specifics or you have a broader concern, but even if you build such a model, it wouldn't make any difference for cases where some kind of "gain" is involved. Be it financial, educational, etc. We're looking at a model that is able to parse the Web (but likely not all of it) and perform human-like actions on that information, and soon enough we'll have it work just like Stable…

[deleted]

Re: Ask HN: How would you build a ChatGPT detector?

#25

Post by [deleted] »

qayxc wrote: post #4

I agree with the softwaredoug that this is probably not a technical problem. Any proposed solution would only serve to make the next iteration of the model better at avoiding detection (e.g. incorporating a GAN-style training cycle). Just as with Poe's law, there simply comes a point at which it becomes impossible to recognise AI generated texts just by analysing them. Made-up references might be a clue, but that's v…

[deleted]

Re: Ask HN: How would you build a ChatGPT detector?

#27

Post by joshuamcginnis »

xdennis wrote: post #18

According to ChatGPT: > 1. Start by training a machine learning model to identify features of natural language. You can use supervised learning techniques with a corpus of labeled data consisting of texts written by both humans and AI systems. > 2. Use natural language processing techniques to extract features from the text such as word frequencies, grammar, and syntax. > 3. Implement a scoring system to assign a num…

I suspect that in time, this will only accelerate the degree to which AI and human-authored text are indistinguishable from each other.

Re: Ask HN: How would you build a ChatGPT detector?

#28

Post by hxugufjfjf »

joshuamcginnis wrote: post #27
xdennis wrote: post #18

According to ChatGPT: > 1. Start by training a machine learning model to identify features of natural language. You can use supervised learning techniques with a corpus of labeled data consisting of texts written by both humans and AI systems. > 2. Use natural language processing techniques to extract features from the text such as word frequencies, grammar, and syntax. > 3. Implement a scoring system to assign a num…

I suspect that in time, this will only accelerate the degree to which AI and human-authored text are indistinguishable from each other.

I've already sent text to customers 100% written by AI. Ethically dubious in a commercial setting perhaps, but higher quality text than I would be able to produce myself.

I asked OpenAI and it said:

It is not necessarily unethical to send customers text generated by AI, but it depends on the context and the specific situation. For example, if the text is being used to deceive or mislead customers, then it would be unethical. However, if the text is being used to provide helpful information or assistance to customers, then it may not be considered unethical.

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