This Is How to Tell if Writing Was Made by AI
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What is the main topic discussed in this episode?
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Hello and welcome to another episode of the Oddlots Podcast. I'm Jill Wisenthal.
And I'm Tracy Alloway.
So, Tracy, you know, you ever come across some writing? You can't articulate exactly why, but you're like, I'm pretty sure AI wrote this. Does this happen too much?
So full disclosure, I haven't really thought about it that much. Like, yeah, because the thing is, I probably should think about it more, but there's a lot of bad writing out there. And I've become sort of inured to it. And I also think that, I don't know. Trying to figure out whether or not something was generated by AI nowadays, if you actually dedicate a lot of your own time to doing that, that is a huge mental burden to be attempting. Especially you and I are in the journalism industry. How many of the pitches do you think that we get from PRs right now are being generated by AI? Imagine if you're reading each one of those and trying to figure it out on a daily basis.
You know what I suppose I think about it the most is uh someone will respond to a tweet.
Yeah.
And I'd be like, well, if this is a real person, then maybe this person deserves some engagement and they ask a question or I want to respond. But if there's a person in the bot, then obviously I don't and that's where like, oh, you know what? I want to figure it out. I would like to know the answer. You know, I have a controversial view about AI writing, by the way, which is that it's pretty good. I mean, like by and large, and I said this I think maybe in a recent episode, when you consider the fact that I don't know, the majority of the population like doesn't know where to put a comma within a sentence. Well, this is my point. It's actually pretty good. I mean, yeah, one thing I'll say about AI is it never gets the placement of a comma wrong.
It's on some level, it's perfect.
Did you do that? I think it was in the New York Times the the test. I kind of
hated that.
Okay, why?
Well, because I'll tell you why. First of all, I'll say five examples. There's not very many. Two, it asked the reader which do you prefer? But I think And they
were different subjects as well. Yeah, and also I think Yeah, and also I think
most people probably treated that as can you guess which one is a human? Because everyone wants to say they prefer the human. I didn't think it was like a great test. Nonetheless, look, not only is it often indistinguishable, not often is it often fine writing. Sometimes AI could come up with a really remarkable turn of phrase. Yeah. But I still, by and large, don't like it. You read like a thing, especially a long text that's AI, and it's like, even if you can't articulate. It's like this feels AI. It has a certain sickliness, sweetness to it that is often annoying. It's so cloying.
What I notice about it is it doesn't do style very well. Right. So if you ask it to write something in the style of a writer, if you choose anything other than something really obvious like Shakespeare, yeah, it really it suffers. But The text that it actually outputs is pretty clear. Yeah. Right. Like for basic understanding.
Totally.
It's probably better than a lot of what's on the internet.
The real people who are gonna have to worry about this are like teachers, obviously, in universities and lawyers. Student lawyers and maybe law. It's fine. But there are sometimes it's like, okay, did someone write this or not?
Why is it getting harder to tell if a piece of writing was generated by AI?
And there has to be it'd be nice if like we could know the answer.
Well, the other thing that's starting to happen is have you seen any books out there that actually come with a disclosure or disclaimer that say this book has been written only by humans, no AI used at all?
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Chapters
5 chapters
1
What is the main topic discussed in this episode?
0:01–3:43
2
Why is it getting harder to tell if a piece of writing was generated by AI?
3:43–24:58
3
How does Pangram Labs detect AI‑generated text and what are its accuracy rates?
24:58–37:21
4
What are false positives and false negatives in AI‑text detection and why do they matter?
37:21–46:52
5
How does Pangram’s model learn the subtle decision patterns of large language models?
46:52–50:31
Speakers
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