Briefing Chat: Anthropic rolls out new AI watermark — will it make a difference?

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0:40Hi, listeners. Benjamin here. Welcome to The Friday Show, where we talk about a couple of stories that have been in the Nature Briefing, which is, of course, Nature's daily email roundup of the latest science news. Here with me today is Lizzie Gibney. Lizzie, how are you doing?

0:54Nature Podcast Team: Hello, Ben. I'm good, thank you. We've just been yabbering about how much we enjoyed the eclipse. Oh, I enjoyed the eclipse so much. my colander got a lot of action i tell you what right well you've got a story that couldn't be more different today to start off with and it's about ai and ai generated text now we live in a world of course where this is becoming a lot more prevalent certainly in academia as well that you know evidence suggests that it's getting used more and more and there's often a question that people have like oh is this just ai generated and it can be quite hard to tell but there may be ways to do so and that's what you've been looking at yes absolutely so anthropic which of course makes the model clawed that many people use has announced that for future versions of the model that come out after the 2nd of august they will have an invisibly embedded watermark so that is something that doesn't affect the actual quality of the text like the user will not notice this at all but it's effectively constructed in such a way that at least for now anthropic and potentially in the future anybody can tell if that was made by claude or not right so an invisible watermark i'm going to guess given our discussions on ai in the past this is going to be statistics based absolutely so we don't know the exact details of how they did this but we do know the details of how google created its synth id they actually published a paper about it and made it open for anyone to use and i am almost certain this is something very similar so i mean with text you don't have that many variables anyway you can change right so it all comes down to word choice and in essence they use an algorithm that will tweak the selection of the words in such a way that some words are going to for that particular sequence be more likely to be picked than others you can then reverse engineer that from the text and see if there's the statistically observable kind of trace of that algorithm left in the word choice and it is pretty reliable in terms of it can tell you okay this was generated by Claude but I suppose there are lots of things that we'll Talk about where it's not reliable in terms of, well, what does that mean?

2:52Nature Podcast Team: You know, what exactly did you use Claude for? That it can't say. Well, you've read my mind. We certainly will talk about that. But let's talk about why this is being done. So Anthropik and Claude then, and you mentioned Google too. There are reasons that they're introducing these things. Absolutely. So this is quite a hard and fast reason, which is that the European Union demands it. So the EU AI Act, which was drafted two years ago, but has become enforceable now. So fines can be enforced from the 2nd of August. They say that it should be possible for people to know if something was generated by AI.

3:21Nature Podcast Team: And when it comes to text, that means a watermark like this. So the companies are all trying to comply with the EU, basically. Google, as I say, have this synth ID, and they've actually been using it for a few years now. But no one would necessarily know or bat an eyelid because there's no way of the general public to be able to detect it. So Google themselves will know. But as anybody else, you know, the general public or user, you would not know. they have means to do that for images and audio and open ai actually uses synth id from google as well so for video images and audio that is possible but for text it's not yet okay so the difference then is that they can know if it's been made by a robot but with the clawed version that you potentially as a user could identify if something's ai yes they have not yet created that but they said they are working on it so they've signaled their intention to do that to make some kind of tool which again is what the law asks for so presumably the others will have have to follow suit.

4:15And let's talk about, I guess, why this is important. I think I said at the start there, it's getting harder to know what is AI and what isn't in many cases. And I'm guessing that is ultimately the reason why.

4:24Nature Podcast Team: Yeah, there's a simple question of transparency. There are some circumstances where AI use has caused problems in science in particular. You know, it is now so incredibly easy to get an AI model to write you a paper from scratch that we know that journals, conferences, preprint repositories are all absolutely flooded with papers, many of them written by single authors. And that is a weight that the system is really, really straining under. How useful a watermark will be to tackle that problem is not clear. Partly because as I say, like what are people using Claude for? Maybe they have done something very original, very human, but it's a bit long.

5:04Nature Podcast Team: And so they get Claude to rewrite it in a shorter format. Maybe they're using Claude for translation and maybe again it's completely original ideas in one language but when it gets translated it gets left with this watermark those things are coming to be something that as a community we generally think are okay I mean as a news reporter literally none of my words can ever be written by AI same here of course but there are many many areas of work where it is acceptable and here it just kind of slightly muddies things really because as I said you know it might be that Claude wrote something from scratch and it's not your original idea but we don't know that either.

5:40Yeah so there are potentially shades of grey but hypothetically speaking if one were to try and circumvent this I would imagine that if I got my AI to write something from start to finish I then put it through another AI to say change this enough but keep kind of the meaning the same that would potentially erase said watermark.

6:01Nature Podcast Team: Well this is the other big issue yes how motivated are you to not be detected because it's all down to word choice you change the exact words that are there and the watermark goes away so anthropic has said it will survive like you know copy and paste is absolutely fine because the word choice is the same it will survive some editing but i would say heavy editing paraphrasing certainly using another model that doesn't have a watermark to rewrite it then your watermark just completely evaporates and then the question is there again like maybe if some people are just churning out papers maybe they won't care about that maybe they'll leave the watermark i cite in the story the case of a conference the international conference on machine learning icml this year that had a stream of peer review that was strictly no ai use so that they had two options you can use ai in some ways or there's one that people have requested where reviews must absolutely not use ai and they put their own kind of version of a watermark into the papers that they gave out for review so that if people then did do what they weren't supposed to do and use AI, it would come up with these telltale phrases they could detect on the other side.

7:07Nature Podcast Team: Even though this was like really well advertised, they were going to do it. The papers about the methods were all out there. Like it was quite broadly known that this was something they were going to do. More than 500 people still were found to have cheated this system because they just didn't see the, I don't know, laziness or what, but they didn't get rid of this watermark that would have been very easy to get rid of. And so they were shown that they had used AI where they were not supposed to. So I guess that shows two things. One is that maybe watermarks will be useful in these quite strict scenarios where the rule is literally no AI allowed, which I would say is becoming a lot smaller, that category.

7:42Nature Podcast Team: And that even though, yes, it's very easy to get rid of the watermark, that doesn't mean people are always going to do it. What do we think about where this might go? We now have two companies who either have text watermarking or are introducing text watermarking. Obviously, there is some laws now that say companies have to do this. Do we expect the other AI producers to follow suit? It's very difficult to know. The onus on compliance is going to be on those big companies. So that's probably who the EU would go after first. But it could create this kind of standard, I suppose, where everybody is expected to do it.

8:16Nature Podcast Team: It is quite onerous to do also, like to add that layer. If you think about it, every time it generates some text, it not only has to do the job of like, okay, what's it going to say? It then has to add in this quite complex algorithmic element about precise word choice. Compute more. Absolutely. And for some people, that is not going to be worth their while. Open models, also, people can make their own versions of. You can distill a model and in your version, add no watermark. They're always going to be available, I'm sure, for people to use. Maybe they're not going to be absolutely at the frontier, but they will be available.

8:50Nature Podcast Team: But, you know, even in a world where just the most used models have a watermark, even if that watermark can be gotten rid of, I think it feels like a broadly positive measure towards transparency. One thing we have covered on the podcast is the future of education, which obviously is a huge topic, but how students are engaging with this brave new world of AI and content creation and essay writing, this sort of thing. I guess educators might be interested in this. Absolutely. So I spoke to a few people for the story and the The broad feeling was that given the limitations of the watermark, exactly as we talked about, you don't really know how that person engaged with AI in what ways they used it.

9:35Nature Podcast Team: There's a big worry that the very fact that there is a watermark out there might end up being used as some kind of automated measure or binary measure of like, this is good, this is bad by universities. And that's probably not a good idea, not least because the ones who are probably most motivated to cheat might also be the ones most likely to get rid of the watermark, right? if they're going to do that in the first place, they might go the extra way and raise the signs of it. And so the feedback that I had was like a kind of real like begging of universities really like to not use the fact that this tool exists as their gauge by which to judge cheating in university or inappropriate use of AI, because it really just does not tell you that.

10:10It's all about nuance.

10:11Nature Podcast Team: It's hugely about nuance. One thing that I guess I wonder, a few times we've talked about how AI is doing research, or he's moving towards doing original research. It may not be there yet. In that instance, knowing that an AI has done something maybe is one of these situations where having a watermark kind of doesn't matter, right? Totally. So Paul Ginsberg, who was one of the founders of the archive, the big famous preprint repository, he said to me like, watermarking is kind of fighting last year's battle. So last year's battle was we had all this AI slop that was being generated. No one knew what to do with it.

10:46Nature Podcast Team: And okay, maybe that still exists. But increasingly, AI is being used in cutting edge research, you know, as you say, not necessarily on its own, but as part of the process, especially in some fields like mathematics, where you are able to verify results. We had a step towards solving the Ryman hypothesis last week. And so it may become just de rigueur that papers involve AI, almost expected in some fields that you're going to have used AI. So the idea that you have a watermark that says so just is very kind of meaningless. so the value of the watermark will also be shaped by this idea of just how accepted it is even expected it is that you will have used ai to some extent in your research well i have a feeling this isn't the last we're going to hear about this topic and you and i are going to talk about this topic but we'll link to your story in the show notes of course let's move on to our second story this week lizzie are you ticklish there's no need to call hr but this is a legit question I most certainly am Me too Do you know what's my feet for me to think it's so ticklish Anyway There is a reason for this And this is a story In Nature That I read about And it's based on a paper In Nature Human Behaviour And it's all about How certain types Of ticklishness I suppose Seem to be a consistent thing Around the world Okay amazing And what are we talking about In terms of types Like places That you're tickled Or methods of tickling Or I have learnt From reading this article There are different types Wow Of tickling Okay now Now, this article is talking about gargalesis.

12:13Now, this is the type of tickling that's associated with play, like being tickled. If someone comes and tickles you, that's gargalesis, right? So that elicits laughter and sometimes squirming, all the rest of it. This is not knismesis. Now, that's like if someone brushes a feather against you, that kind of you feel like a ticklish in your skin, but it doesn't make you laugh. Now, the latter has attracted a lot of research attention because it's similar to itching. and you can think of a lot of diseases and skin conditions that result in itching and so researchers have looked at that gargalesis then the fun one the fun one is not well understood and folk have written about it since antiquity what is it what is it for and we know that humans aren't the only ticklish animal other great apes tickle each other rats and meerkats apparently respond to human tickling which suggests that this sensation has been preserved across evolution and There's a link in the article to a video of a gorilla being tickled.

13:08This gorilla is having the timeless life, I'll tell you what. But what is going on is a question that researchers have had, and that's what they're trying to move towards solving with this research.

13:17Nature Podcast Team: Well, I mean, it does feel like something quite instinctive. I mean, the fact that we're talking about, you know, kids and play, like, my children are incredibly ticklish, love being tickled, love tickling. Like, it feels like something that humans just do. Yeah, and there have been a few ideas as to why it exists, which we'll get to in a bit. But to test what might be going on, some researchers recruited 448 participants from three distinct cultural backgrounds. We've got Dutch, Greek and Chinese. Now, each person then completed a survey about their experiences and perceptions of tickling. And then they went onto a computer and they coloured in areas of a body model to create maps of where they were ticklish, repeating this exercise for other body sensations like pain or pleasurable touch.

14:01so what they've made in this research these two researchers is a high resolution tickle map

14:06Nature Podcast Team: okay so we're talking feet yep um like tummy yeah belly under your arms yep and neck is the other one yeah okay yeah yeah and almost all the participants so 98.4 percent of them in fact reported having experienced tickling and 95.8 percent reported having tickled somebody else Wait, so two-ish percent have never tickled or felt being tickled. Right. Now, this might not sound too surprising that most people have done one or the other. But studies suggest that how people interpret touch that is sort of processed emotionally, such as hugging, for example, that can differ by cultural background. But tickling maybe seems kind of across the board.

14:53And as we say, these ticklish areas were highly consistent between cultures and individuals. So, yeah, neck, armpit, belly, soles of feet. And this is different to the comparisons and maps of the other sensations like pain or pleasure, suggesting that the sensation of tickling is distinct and unique. And nobody really knows why it exists. And in this research, the researchers kind of tested five theories. Some of these were ancient. Some of these were new. Aristotle attributed ticklishness to different areas of the skin being more delicate, thinking that maybe you'd be more ticklish where the skin is thinner.

15:30Charles Darwin, though, his idea was that areas that are touched the least are most ticklish. And it turns out that the factor that showed significant association with ticklishness was this idea by Darwin. so it doesn't explain all of it but the evidence is that that seems to be at least a part of it and the authors say that perhaps there's kind of a surprise based mechanism going on here because areas that are rarely touched maybe without your feet you're more surprised if someone does and so

16:00Nature Podcast Team: it feels ticklish and that tallies with the fact that you can't tickle yourself because it's never a surprise and that's right because you're two parts of your brain are working at once you know the feeling of touch and also the act of you going to do it but they also say that maybe there's kind of a self-reinforcing mechanism here. Some areas are ticklish because they're rarely touched and they're rarely touched because they're ticklish. Yes, that also makes sense. I mean, it does make sense, but I have to say this is not a cut and dried thing. I mean, they've only tested three cultural groups here.

16:27They didn't test situational context. But as you say there, people often enjoy tickling kind of innately. And it does seem like it is this conserved thing. So whether it plays a role in social bonding or protection like your armpits you know there's a lot of blood vessels there that could be damaged for example hard to know but it's an interesting story because it does shine a light on this phenomenon this activity that is so potentially so universal but

16:56Nature Podcast Team: quite poorly understood i love the idea that you might you know go to amazonia and find a tribe that's never met anybody else from outside and you know one thing you could share is that you're all ticklish. This is something that would have to be uncovered, I suppose. Well, if that story has tickled your fancy, sorry, we'll put a link to that one in the show notes as well, as well as a link on where you can sign up to The Nature Briefing to get even more stories like this delivered directly to your inbox. But for this week, all that's left to be said is I've been Benjamin Thompson, Lizzie Gibney.

17:26Thank you so much for being here.

17:27Nature Podcast Team: Thank you so much for having me. You've got social dialed in. Search is doing its thing. So why do your marketing results look the same as six months ago. That's because you're fishing in the same pond as everyone else. Podcast listeners are a different audience entirely, more engaged, harder to reach through traditional channels, and ready to act when someone they trust makes a recommendation. We're Acast, and we put them right in front of you. Browse thousands of the world's leading podcasts, book host reads or run your own ads, and track every conversion in real time. Same skills you already have, brand new results.

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