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GPTZero Case Study – Exploring False Positives

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Re: GPTZero Case Study – Exploring False Positives

#11
post #9

As millions of people interact with ChatGPT, their writing will subtly, gradually, begin to mimic its style. As future versions of the model are trained on this new text, both human and AI styles will converge until any difference between the two are infinitesimal.

Interesting idea, but isn’t there variance in the output? Eg I’ve seen people ask it to “write in the style of x” etc and different people also clearly have different writing styles.

Re: GPTZero Case Study – Exploring False Positives

#12
I saw this[1] interview with Sam Altman touching on interim AI impact. I really agree with his point that basically detecting output from LLMs is basically going to be futile and only really relevant in the near term. Accuracy is obviously going to improve in models and detection isnt that difficult now but will be in the future, especially if output is modified or an attempt to obfuscate origin is made.

[1]https://youtu.be/ebjkD1Om4uw

Re: GPTZero Case Study – Exploring False Positives

#13
post #9

As millions of people interact with ChatGPT, their writing will subtly, gradually, begin to mimic its style. As future versions of the model are trained on this new text, both human and AI styles will converge until any difference between the two are infinitesimal.

+1

We train AIs but they also train us.

Re: GPTZero Case Study – Exploring False Positives

#16
post #9

As millions of people interact with ChatGPT, their writing will subtly, gradually, begin to mimic its style. As future versions of the model are trained on this new text, both human and AI styles will converge until any difference between the two are infinitesimal.

One of the big complaints with LLMs is the confident hallucination of incorrect facts, like software APIs that don’t exist.

But the way I see it, if ChatGPT thinks the Python list object should have a .is_sorted() property, that’s a pretty good indication that maybe it should.

I work in PM (giant company, not Python), and one of these days my self-control will fail me and I will open a bug for “product does not support full API as specified by ChatGPT”.

Re: GPTZero Case Study – Exploring False Positives

#18
post #15

It's important to shine a light on the limitations of AI detection software, and this case study on GPTZero does just that. False positives can have serious consequences, particularly in sensitive areas such as healthcare.

Thank you for your heroic effort in copying and pasting a chat log, I am left in awe by it.

...nice edit...

Re: GPTZero Case Study – Exploring False Positives

#20
post #16
post #9

As millions of people interact with ChatGPT, their writing will subtly, gradually, begin to mimic its style. As future versions of the model are trained on this new text, both human and AI styles will converge until any difference between the two are infinitesimal.

One of the big complaints with LLMs is the confident hallucination of incorrect facts, like software APIs that don’t exist. But the way I see it, if ChatGPT thinks the Python list object should have a .is_sorted() property, that’s a pretty good indication that maybe it should. I work in PM (giant company, not Python), and one of these days my self-control will fail me and I will open a bug for “product does not suppo…

Or rather you can just catch method missing in the runtime and patch it with a chatgpt call
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