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A bookseller independently decided to put a tracking device in one of their books. The final ping from their tracking device was in a giant paper mill in Mexico where they receive recycling materials and then they turn it into like toilet paper, paper towels and stuff like that.

Wow. The circle of life is a beautiful thing.

You might be wiping your ass with like a copy of whatever.

Which just means scammed by Amazon. Yeah. Hello, and welcome to the four zero four Media Podcast where we bring you unparalleled access to hidden worlds both online and IRL. Four zero four Media is a journalist founded company and needs your support. To subscribe, go to 404media.co.

As well as bonus content every single week, subscribers also get access to additional episodes where we respond to their best comments. Gain access to that content at 404media.co. Also, do remember to subscribe to our YouTube channel where you can watch all of our episodes, including this one. Subscribe at youtube.com/404mediaco.o. I'm your host, Joseph, and with me are two of the other four zero four Media co founders.

The first being Sam Cole.

Hey.

And Emmanuel Mayberg. Hello. Sam, first of all, this Thursday and Friday, those are the days of our three year anniversary events, the live podcast recording on Thursday, the party on Friday. What's the ticket situation looking like for people if they still wanna get a ticket?

Yeah. Tickets are very limited at this point. I would say they're, like, edging, selling out. So if you haven't, get your tickets. Thursday, we're doing, like you said, the the live panel at the green space.

It's a WMIC, event space that's down I guess it's considered like Hudson. It's like Chelsea Soho Intersection in Manhattan. So we're gonna have Matthew Gault joining us. Becky Ferreira is coming out to talk about, cool science stuff. So definitely get your tickets for that if you haven't.

That, at this point, is very much almost sold out. And then on Friday, there is an open bar party at Three's Brewing in Gowanus, and that is free for paid subscribers. So if you're a subscriber at the supporter level, get your ticket. You still need a ticket. You just need to sign up, but definitely get in there if you're already a supporter.

It's free for you to come out. We're gonna have snacks. We're gonna have good snacks, like, you know, fries and veggies and stuff like that. I don't know, bar snacks, I guess.

But I'm good there, more

of And good beer, wine, cocktails, all that goods. We'll have the photo booth again. We'll all be there most importantly to party with you. And if you're not a supporter, you can actually get 50% off of that event if you are coming to the Green Space live panel. So lots of ways you can get into this, and we'll put the link in the show notes for all the details.

Here is a little secret in case it wasn't obvious in us promoting this event over and over again. You can buy a ticket to the open bar for about $30 or you become a subscriber at $10, and then you get access to an open bar part. So you're just paying $10 Yeah. For, like, somewhat unlimited beer. I mean

It's a good deal.

So how how many beers do I need to drink to make up the cost of $10?

Doing it three

quarters of one. Yeah. Okay.

And how many beers do I need to drink to cover the cost of an annual subscription?

An annual?

Well, I wouldn't do that.

Yeah. Like 10.

I mean, buy an annual subscription. I just I don't think you should probably drink all of those beers in one go

at If the you come to the bar and you show me that you're a super fan, which is a thousand dollar subscription, I will drink the cost of a super fan subscription with you.

Good lord.

Don't do that because Emmanuel will die and then we will be I

will die. That is true.

I mean, that's the author.

That's the author. Yeah.

The sacrificial lamb. If you would like to kill me. Yeah. It

will be easier. So

Yes. As Sam said, check the link in the show notes.

We have merch at a discount. So if you're coming in person, we'll have merch that's cheaper and easier to get, obviously, because we'll just hand it to you than it is online right now. And then we'll also have exclusive posters, which just came in the mail today. They're like holographic, really cool event posters that we're gonna have.

So good.

Yeah. They look very sick. And then we'll have special, stickers that I just slapped together and basically in paint and put in to the printer and go. So, yeah, lots of things to lots of things to not miss this week. Yeah.

Hell, yeah. I like the paint stickers. It it is kind of like a story we did where those businesses are going viral for doing anti AI whiteboards, like pen on paper adverts, we're doing that as well. Alright. As for this week's stories, let's start with a really interesting update to one of Emmanuel's about the Amazon AI training warehouse that will be recapped on in a second.

The headline of this one is Inside the Warehouse Where Amazon Scans and Destroys Books for AI Training. This is obviously a huge story that we did a couple of weeks ago at this point, Emmanuel. Just recap our listeners super briefly. What is this warehouse, and how did we find it?

Yeah. So the warehouse is in Las Vegas. It is called VGT3, and it is at least one location that we know of where Amazon, they purchase huge bulks of books, they're shipped there. People who work at the warehouse cut off the spine and scan the loose pages in order to create AI training data, and we know this because we had suspicion that many AI companies were doing this. We weren't able to say that for sure because the buyers on these marketplaces are anonymous, but we put a tracking device in one of the shipments and saw that the shipment ended up at this warehouse where we were able to confirm that this is in fact what was happening.

So that reporting, obviously, as you say, was based mostly on the Apple AirTag and then conversations with the bookseller source, and you also did find discussion online from people who worked at this warehouse saying, oh yeah, you know, we take the spines off the books, blah blah, all of that. But you managed to get in touch with somebody who actually worked inside this facility. We'll get to what they said in a minute, and the article is sort of formatted as a Q and A, and frankly, I'm going to basically recreate that Q and A by asking you the same questions and you repeat their answers. But before we get to what they actually said, why did you want to speak to somebody inside? Like, what were you hoping to learn or get by speaking to somebody who'd actually been inside this facility?

Well, initially, when I was reporting the previous article, I wanted additional confirmation that they're destroying the books. But what I thought was useful about this conversation is a few things. One, there is a better idea of the scale of the operation just in terms of how many people are there and what does the space look like? What does the equipment look like? How much equipment there is, how many books are coming in, and then also what type of books are coming in.

And then as always, you know, as a publication, we're always interested in the perspective of workers, right? It's like this is a big operation. Presumably this is happening in many warehouses across the world, and there are hundreds, maybe thousands of people involved in this and just like, what are their working conditions? What do they feel about the objective of what they're doing? And we're interested in that always.

If we're reporting on Uber, we want to know how drivers are doing. If we're reporting about Amazon warehouse, we want to know how the warehouse workers are doing, and they often provide like the best insight, which I mean, there's definitely great insight in this conversation, I think.

Yeah. It totally makes sense. We always want to speak to essentially as many people as possible. And I think for us especially, we do focus on people who are actually doing the work, like we're never going to get interviews with Mark Zuckerberg or Jeff Bezos or we're never going to get interviews with the executive class, basically, right? And frankly, I think when you have conversations with those sorts of people, you actually really don't get that much out of it.

They are trying to push a certain message, but speaking to an actual worker, you're going to get more specifics on what is actually going on. So first of all, what did this person say about the sort of books Amazon is scanning? Because the article focused on rare books because that is what was being ordered, but like what else did this person say about the sort of books that Amazon is buying to then despine and scan and destroy ultimately?

So first of all, there's confirmation that it's any and all books, right? It's like you can see some logic in terms of there being a lot of textbooks stuff like that, but there's a huge variety of books. The worker did, however, see a few things that I thought were interesting. One is they would get big shipments of specific languages, right? So it's like they come into work one day and there's a palette of Japanese books.

They'll come into work one day and there'll be a palette of Russian books. And that doesn't mean that this isn't happening at other AI companies around the world. In fact, there was some reporting in Europe that was able to identify a Chinese AI company that was buying books, but we've seen reports of booksellers reporting the same thing I heard, but in The Netherlands, in Spain, in Germany, and I was wondering like, okay, are those local companies or are all these books being shipped to The US? And at least in this case, could say at least some of those books are in fact being shipped to The US. Another thing that was interesting is some bulk orders clearly included library books.

They had all the tags and the markings of books that you would lend from the library.

Like the tags still on them or like

Yeah, like, you know, on the spine you have like the code and all that. So it's like they would get big shipments like that, and that could be from a library liquidation sale. It could also be from a bookseller who bought it from a library liquidation sale. It's hard to say for sure, but we do know that library books are ending up in there. The last thing I thought was interesting in terms of like what books they were seeing is there was another shipment that clearly came from The UK and seemed like it came from a university, and there were a lot of textbooks and stuff like that, but there were also books that didn't actually have spines, they were stapled together, and they looked like government reports.

I think as the worker speculated, and I agree, they're most likely public reports. It's not like it's super secret information or anything, but it's just interesting to note that it doesn't have to be like a bound book. They would get other, you know, reports and, you know, guides and stuff like that, that weren't necessarily published books.

Yeah, because obviously with a lot of US reports, you can just get those online and AI companies would have grabbed those in their mass scraping of the web. But in some cases, and I'll say this is definitely the case for The UK where like information just isn't as available on the internet in a lot of UK stuff. So like I can see that, oh, maybe somebody had to print it out or something to scan over. We haven't any evidence for this, but it just kind of made me think because I wonder if the AI companies are scraping like PACER, The US court record system as well, like ingesting that.

I can't say for certain, but I guarantee it. Like, I'm willing to bet money on it.

I'm just trying to think of the value because there's like a lot of there definitely is value in that who will be like, well, here's the understanding of the law or something, and this is how lawyers use

Or just formatting stuff in the style of complaints or motions and stuff like that. I mean, obviously, know from other reporting we do that lawyers use agents all the time or chatbots all the time.

Yeah. It's just interesting because there's also a lot of wrong information in court records as well, where it's all allegations hasn't been proved and that's anyway, maybe we'll put a pin on that because that is interesting and maybe we should look into that. But back to this Q and A, what did this Amazon worker say about the scanners? Like, many are there in this warehouse as they know of? Like, how big are they?

That sort of thing.

Yeah, so a little bit about the operation. It's pretty much what I imagined and what I gathered from discussion online, but basically trucks come in, they take everything off the truck in an area they call staging, then this person, you know, saw that there's a team that's in charge of, like, taking stuff from, like, this staging area and then putting stuff into bins that then another team will take over to an area called receiving, which is where the books are scanned in, as in they're not scanning the content of the book, they're scanning the barcode to see like what are they getting. From there, they're taken to a bunch of stations where they cut the spines off the book. This is a big machine with like a blade. You put the book into like this secure area, you remove your hands from the area, you press a button, a big blade comes down and cuts the spine off the book.

Then the loose pages are put onto these carts and they're separated by little pieces of cardboard and are taking over to the scanners where the worker said there's about 20 to 25 scanners there. And I haven't been able to nail down exactly what the machine is. There are a bunch of machines, a bunch of scanners that are designed for this process. The worker described these as, you know, those cash counting machines you always see in crime movies, you feed it a big wad of cash and it makes that satisfying flipping noise. So it's like,

it's a And very neatly churns out. Yeah. Yeah. Yeah.

Yeah. So it's like, it's one of those, but for scanning, and there's like a monitor next to the scanner that, you know, shows you what you captured, like there's an image of the page. From there, everything, all the loose pages are tossed into these giant cardboard open boxes. People in the business of book selling call these gaylords. Amazon calls them shuttles.

The workers speculated I didn't put this in the article, but the workers speculated it's because people were like being juvenile about the

Obviously, term the term has taken on a slang meaning and a pejorative meaning in modern context, so having a corporation like Amazon officially refer to something as Gaylord not go with the company's HR policies, I guess is what it

gave Right. Yeah. So they call them shuttles, and then everything is kind of like loosely tossed in there, and we'll get to like what happens to the books after, but the Worker observed, and I think it's inarguable that there is no way to salvage what goes into that giant box. Like it just piles of loose paper. And they also noted that not all the books that they get end up getting scanned.

They don't know why. Maybe it's a duplicate. Maybe it's not a book that they're interested in, maybe it's something that they didn't actually order but ended up in the shipment. And those books end up in that pile as well. So these are books that are functioning salvageable books, right?

They're not destroyed, but almost certainly they're ending up in like a pile of books that will get recycled.

Damn. So yeah, they are, I mean, on one side, they're obviously destroying the books and then scanning them for those AI purposes, but in some cases they are just destroying some books that don't even get scanned at all. Yeah. Just a couple more brief questions. What did they say about sort of the job itself?

Because in your original article, on what people were saying online, it seems like quite a desirable job, at least inside Amazon itself. Like, what did they say about that?

Yeah. So I didn't get the feeling that this worker found this job particularly desirable. Like I said in the previous story, the same structure, the same building where VGT three is also has a separate operation for print on demand. It sounds like maybe that is a harder job by comparison, and maybe that's what makes people say that VGT three is desirable, but it sounds like a normal Amazon job. You're at one of these stations, so you're either cutting the books, you're lifting a bunch of books, or you're tossing them.

Everything else they have to say is kind of like normal complaints that people have about their workplace and typical of Amazon, which is it's a big operation. There's a

lot of

turnover. And this worker got the feeling that they would come in and like Amazon was still figuring out how this works. Amazon was still figuring out the ins and outs of the operation and how to make it efficient. So they would feel like the order of things would change daily or like who was doing out who was doing what would change would change daily. But I think it's hard to say whether that says anything in particular about this operation or that's just what it's like working on Amazon or that's just what it's like working at a big warehouse.

Yeah. And just to round it off, I mean, since you published this piece, you've done a ton of media interviews and appearances on TV and for other outlets and that sort of thing, and we've also had, you know, more mainstream outlets like the Wall Street Journal follow-up on our reporting and publish like their own stories. Have we learned anything else either about the Amazon story specifically or the broader trend of AI companies scanning and destroying books like since we published?

There has been a lot of pick up on it. I think what other reporters were able to get is interviews with booksellers and bookstores that are confirming the same activity, which is to say giant purchases of books. There was one interesting thing about that Wall Street Journal story, which I have some corroborating evidence for, but basically, a bookseller independently decided to put a tracking device in one of their books just because they were curious about what was happening to the to to the book. And they they saw it kind of make a similar route across the country as as what we saw, but they ended up, like the final ping from their tracking device was in a giant paper mill in Mexico, in Mexicali. And I looked up this location, I was able to find it.

And yeah, I mean, it's like, without a doubt, that is what is happening. Like the tracker that was in this book eventually ended up at this giant paper mill where they receive recycling materials and then they turn it into like toilet paper, paper towels and stuff like that. So we can say that at least in some cases that that's the ultimate location for the books.

Wow. The circle of life is a beautiful thing.

Dude, really I was thinking about it. It's like, you might be wiping your ass with like a copy of whatever, you know what mean?

Which just means scammed by Amazon.

Yeah.

All right, with that, we'll leave that there. When we come back, we're gonna talk about AI ghosts. No, we're not personifying them. Don't worry, it's another sort of ghost. We'll be right back after this.

All right, and we are back. This is one Emmanuel wrote, but I definitely have some questions for Sam as well because it strongly relates to an article she recently wrote. But the headline for this one is the AI ghosts contaminating academic publishing. So I'll just read the lead and then I'll ask you about Emmanuel because I think it sums up really, really well, or rather, I think it's a quote from the study. Elena Vasquez and Marcus Chen have appeared as volcano experts, astronauts, thriller protagonists, podcast hosts, and academic co authors across hundreds of independently produced AI generated documents never having lived.

That's a pretty compelling sentence. As people can probably get from the headline, these names, and just for the sake of this conversation, these people, these personas, these characters, whatever, they are AI generated and a new paper is looking at that. So what's the deal? These names keep appearing in AI generated text, like what did this paper find?

So there is this phenomenon with LLMs where they keep producing the same names in certain contexts. Obviously, you know, it's a lot more complicated than this. I do not mean to, like, minimize the technology of large language models, but it is like a statistical model, right? So statistically, the same data will often produce the same concepts and also the same names. And this is known, there's been other reporting on this, we'll talk about Sam's story in a bit, but it just so happens that they could appear in other contexts, but mostly when you're looking for, if you tell Claude like, hey, like, tell me a story about an expert in chemistry, it will often come up with the same names.

And essentially, the researchers here were trying to use this as a way to find AI generated content on the internet, and it proved to be, I would say, rather successful. You can't rely on it solely as a way to determine whether something is AI generated or not, but because Elena Vazquez and Marcus Jen are so closely associated with a specific Claude version, if you see those names together, that is a pretty strong signal that you're looking at something that was AI generated.

Yeah. So there's this phenomenon, as you say, just to sum it up, where LLMs keep spitting out the same names for some reason, right? You know, the articles mentions that if you ask something to do with, you know, software development or something like that, Marcus Chen will come up sometimes that way. So this phenomenon has noticed where these LLMs keep using these same names for whatever reason. These researchers then took those names, searched for them across academia and found, woah, there is a ton of academic publishing which is using those names, which would, I think, indicate that they were AI generated papers or AI assisted papers in some way.

Obviously, apologies to somebody who's actually called Marcus Chen and you work in academia. Sucks to be you, sorry. But like, what were they finding that these names were appearing in what exactly? Like all sorts of academia, like what's the sort of scale we're talking about?

So there is a repository that allows you to create DOIs. DOIs are the ID numbers for academic publishing, and there's a website, for example, called Zenodo, where anyone can go in and submit a paper and automatically, like without any human verification, generate a DOI, and this is in order for you to then submit the paper to an actual journal. But they searched this database and found sixteen fifty five ghost authored records, as they call them. So it's like papers that include one of these names or combinations of these name indicating that they were AI generated. I should clarify something.

The paper determines that it is much easier to identify AI generated names if they come in specific groups. Like it is statistically more likely that the paper is AI generated if it includes Elena Vazquez and Marcus Chen together as opposed to one of them alone. So they use this to kind of see that there's, you know, almost 2,000 AI generated papers on this database, which is like that that is maybe not as catastrophic as it sounds because like I said, it's an open access thing. Like anyone can I can go there and like make up a bullshit paper? You think you can get

it potentially. Yeah.

Yeah. But but the thing is that there are other services that scan Zenodo and kind of pull out all the DOIs and pull them into other databases like Google Scholar, if you've ever used one of those. Like Google Scholar is, if you search for an academic paper, you're probably going to end up there. You can click on the name of the author to see other papers they've written. Research Gate is another similar service like this.

So they're going to this free service, but that is feeding other databases. So it's kind of like infecting the Internet from there on.

Yeah. And that's where the contamination, like analogy

Yeah. I should also say like, the researcher joke that it's like they made the extremely scientific experiment of like Googling the names, which then turned up a bunch of AI generated books on Amazon and Google and so on.

Yeah, yeah. So it is spreading. And I guess in academic study, it's like, in this case, well, we just focus on this database because those are the parameters of the study, obviously, right? And it's like, yeah, you could also do the same thing with Google Scholar and you could search that, but this is like a really, really interesting baseline of like where these names are appearing and how frequently. Sam, this is obviously very similar to a story of yours, I think from a few months ago.

Could you just remind us what was that and like what was this character persona AI generated thing that kept coming up there?

Yeah. So people started noticing that if you asked an LLM like ChatGPT to tell you a story without giving any kind of, like, details about what kind of story, a lot of the time it would tell a story about a clockmaker, a lighthouse keeper, or a librarian. And a lot of the time, it was a lighthouse keeper. So it would be kind of like a it was like a mystery or like a cozy story about, these these specific tropes from literature. And a lot of the time, they were naming the LMs were naming the character in these stories Elias Thorne specifically, which was weird.

It was like Elias Thorne is all of these different characters, but doesn't actually exist, in, like, really strongly in mainstream media, I guess. So people were noticing this. I got tipped off to this by a software engineer named Daniel May. And then researchers were writing about this already and and found that it was all coming down to model collapse, basically. So all the the models are trained off of, these open models, specifically OpenAI's first ChatGP model, which was GBT 3.5, is kind of the root of this family tree, and it was used to make wild chat, which is a training set that then was used to make other training sets.

And, I mean, it was they were all using kind of these same tropes, but also these specific stories were very safe for work. And when the models and people making LMs were trying to create kind of like safety guardrails and weights that would make safe stories when, you know, anybody asks for a story. A lot of the times, it would just default to these specific types of stories about clockmakers and lighthouse keepers. So, I mean, it's not even that, like, there's a ton of stories about Elias Thorne in literature. It's that the models landed on this as a very safe and sanitized output that they could repeat over and over.

And and then they did. And then people started making, like like, AI generated, a lice thorn lighthouse keeper mystery books for Amazon and selling them. And so it kinda like it perpetuated it more and more as, like, it would kind of, like, deepen that connection to, oh, this is a story that people are interested in, so I'm gonna repeat it again and then. Yeah. It was it was a it's kinda like a weird there's a ton of them on YouTube, which is kinda odd.

You know, if you search Elias Thorne on YouTube, you find a lot of, like, AI generated dramas about it's always an old man, but, yeah, weird stuff.

So, Emmanuel Sam there mentioned model collapse and sort of the origins of that there when it came to producing this character. These researchers that you looked at with this academic stuff and these sort of new characters like Chen and the grouping of those together, do they think it's the same reason, like it's model collapse? Or have we learned anything else about why the LLMs are doing this from the study you looked at?

Yeah, I mean, it's to begin with, it is, again, statistical, right? So it's going to end up landing on the same names because it's all coming out of the same model. And then they did note that there is like a reinforcing cycle where it's more likely to produce these names, those names then end up on the internet, and then presumably the LLMs are fed additional training data from the internet. So it will kind of repeat and only become stronger. I think he also said that that ultimately might complicate the goal of using this as a way to detect LLMs because the models will correct themselves.

Right? It's like, presumably, OpenAI will go in there and be like, okay, well, don't don't keep coming up with Marcus Chen as a name, but I think we need to live with these models a little bit more in the wild before before we see if that's the case.

Yeah. It might be like right now there is a window of time where the LLMs are doing that and it acts as a convenient and useful indicator of a potentially AI generated article, but in the not so far future that avenue may not exist

anymore because

either potentially in the training data itself as it maybe gets more varied, but also just as you say, from direct intervention by the AI companies who are making this, which seems more likely. I feel like it doesn't look good for them if it's constantly churning out the same names, you know? Yeah. Mhmm. Alright.

We will leave that there. If you're listening to the free version of the podcast, I'll now play us out. But if you are a paying four zero four Media subscriber, we're going to talk about a bunch of recent immigration and customs enforcement purchases, including those Boston Dynamic robot dogs. Remember the cute ones to do the cool dances and stuff? Yeah, work for ICE now.

You can subscribe and gain access to that content at 404media.co. We'll be right back after this. Alright, We are back. Sam, do you wanna ask the questions about these couple of short, ice stories? I mean, remember the Boston Dynamic robots.

Right? Yeah. Yeah.

I've been blogging about the Boston Dynamic robots for a very long time. I think I wrote a story for motherboard, maybe my one my last stories from motherboard that was like, I'm gonna kick this thing in the head. Like, it was that was the headline. Something like that. I'm sure we can pull it up.

But

I'm literally googling it.

Please do. Yeah. I'm sure it was, like, the dumbest thing. It was, right when they came out, and I was just, like, threatening to kill these things. Because everyone was, they're so cute, and I was, like, I hate this.

Kill it with fire.

I I found the article. Remember? The headline the headline is, I could kick that Boston Dynamics robot's ass no problem.

And now they've or now they're working for ICE. So I don't know. I'm kinda scared of them now. I don't know if I can

keep harassing. Often have, like, machine guns

They have guns on them now. Yeah. They got guns. I don't know if I can compete with that.

Officially, I'll say, because I I don't know if I wrote this question down. No, I didn't. I I was supposed to. But, yeah, random people attach guns to them, right? Yeah.

On the Chinese knockoff of the robots. Yeah.

Yeah. Yeah. Jesus Christ.

It's not their it's not it's not Boston Dynamics policy to allow weapons. Like, I think they said that in their statement to me, which we'll get to, but I just wanna say that since you brought it up.

They've been saying that for so long and it's like, okay, for sure. I don't know. Like, I'm glad that's not your policy. That's a 100% what people are doing with these things, that you're selling them to. So yeah.

So, anyway, ICE is spending millions on boson or plans to spend millions on Boston Dynamics robot dogs. Why why is my first question. Why is ICE buying buying these? And what I guess, what specifically are they buying?

Yeah. What specifically? I'm just trying to find the line in the article, but it's millions of dollars. Here we go. ICE plans to spend between 1 and $2,000,000 on this purchase.

I'll say this is like another ICE procurement database, which isn't the same as sam.gov, which is where you go to see confirmed purchases. This is another one when you'll sometimes see stuff there a day before or a couple of days before, and it's announcing the intention to buy. And it could change in that window, but usually it doesn't. So there it says spend between 1 and 2,000,000, and a Boston Dynamics robot starts around 7,500. That's probably if you're buying like the crap one, you know, like the car with like no features or anything.

So realistically, maybe a little bit more. But millions of dollars, ICE is planning to buy at least several of these robots, right, to answer that question. As for why, sort of the usual stuff like, oh, we need to be in hazardous environments, all of that sort of thing. And I think the key term this came out to me was quote, officer safety, end quote. Because officer safety is a very loaded term in the age of ICE in the second Trump administration in that, well, we need to shoot people in the back of the head or in the face in the name of officer safety, even when those people don't pose any sort of threat to them whatsoever, obviously in the case of Alex Preti, when they're good.

So the idea that they're purposely buying robots for the explicit purpose of officer safety, I mean, that could mean anything in the in the age of, you know, Trump two point o ICE, and that's why I pulled out.

Okay. Gotcha. I mean, yeah, it's people in the comments are obviously comparing us like Black Mirror. I feel like this is this is the most Black Mirror thing I've seen in a minute, but not to be I've seen that. Outdone.

I know. I I know it I know it keeps coming up where we keep putting up that mirror, like, the subscriber section. But, like, there is one where they have the the little

They're running from the specific dog. Yeah. It's like this specific robot is, like, the the thing that they're running from in the in the episode. And I think when it came out, they were still like, you know, isn't this fun and cute and would be used for like wildfires or, you know, like hostage situations or something and delivering, you know, DoorDash or whatever. And now obviously, we're just like fully in that in that world where you could see in the future having to like escape from one of these robots being piloted by an ice agent.

And they're making humanoid robots now as in Boston Dynamics, which I don't feel has got as much attention, but it was worth mentioning. Yeah.

Those I feel like I could take. Dude, you could you could

get is is the classic, like, and death. Yeah. Yeah. It's like

Sam and the Boston Dynamics. You think you got

a Yeah.

On an on an on an advantage against the four legs, I don't know if I could get I don't know. We there was also someone had published, like, a how to take one of these down guide that I think we blogged at some point, but, you know, it was that was a different era, obviously. Well, you take

the badge you take the battery out. I know you're trying to move to the story for NA.

No, please. We'll talk about this for an hour if you want.

But but the guide, at least I saw, or maybe it's the same one you're referring to, but somebody

It's the battery. Yeah.

Yeah. Alleged that the battery is stored like on the cute little belly of the Boston Dynamics dog. So if you, like, pull it, the battery falls out or some shit. No idea if that's true.

Yeah. I mean, yeah. Maybe we'll find out someday. So Ice is on a little cute little, shopping spree, the next story that you wrote about was ICE wants the country's voter data. So in this case, what is ICE buying?

Yeah. And it's weird because you may think, wait, why are they buying voter data that is like free to access and public record essentially? And that is true. Like, you can go to a website like voteref.com, which I think is run by right wing whack jobs, right? Where they're basically using the data as an intimidation tactic or as lobbying tool to try to get changes to election voting laws or whatever.

I don't know. I haven't checked what they're doing in a minute. But you can go to that website and you can, like, type type in somebody. And, basically, if they voted, you've now doxed them, and you have their name and address. And we covered this, I think, the day after the most recent election, because, you know, I I I still think that's fucking crazy that you vote and that's like a security trade off, and I don't think people are aware of that.

Anyway, this data is out there. You can go to a state website, you can download it, you can, you know, maybe do a public records request or something, but often you don't need to. What ICE is doing here is it's trying to find a federal contractor, you know, a big government contractor that will give ICE access to this voter data and handle it at the same time. So rather than ICE having to do all the work of figuring out where the data is and download and store it, they want a contractor to do all of that. And that would be voter registration data, which I think includes name, address, like that sort of thing, but then also voter history data as well.

So again, maybe people don't know this is technically a public record and that's news to them, I think probably not. But ICE wants all of that data in a much more easy to access and easy to manage and easy to handle format. And obviously, with essentially the blank check that ICE has at this point is prepared to, you know, pay a contractor just to do it.

Yeah. Gotcha. What was the reason that they gave in this that that they're giving, I guess, to want this data?

So they said it was to investigate voter fraud, and it was and and I won't go too in-depth for that because I'll leave it for the last question. But the the the reason they gave is voter fraud and it was specifically with Homeland Security Investigations, HSI, the part of ICE, that does investigate voter fraud. There was a case recently the agency highlighted where there was a Chinese national, I think, who voted twice or did something bad around voting and didn't fully look into the details, but it was voter fraud and they did a big press release about that and all of that sort of thing. So that is within HSI's remit in the same way that financial fraud is or money laundering or all sorts of other sorts of fraud. That's the the stated reason that I saw HSIs given for wanting to obtain the CC to maxes photo data.

Okay. I see. Yeah. Voter fraud has been like the excuse slash reason for a lot of shenanigans in the Trump administration. How else have you seen voter fraud coming up in ICE contracts specifically?

Yeah. Because well, fraud has been used as a pretense for, like, a lot of, like, these immigration enforcement operations, like the stuff that happened in Minnesota and Minneapolis that was sort of, like, from a half real, half conspiratorial allegations of fraud that came out of the states and the city rights and that got really, really big on right wing media and then the Trump administration did a crackdown there. Like allegations of fraud are a big thing when it comes to actually sort of directing where ICE is going to look at at any particular point in time. But voter fraud has come up in a few different contracts now. There's this one and then the other one I'm thinking of is there's this Thomson contract for $125,000,000 where ICE will get access to, I think, CLEAR or the other personal data that Thomson Reuters holds, and specifically that contract references voter fraud as well.

I need to go back and like look at more contracts to see like, is this a new phenomenon that they're buying data for voter fraud? But I will say that somebody who closely monitors Thomson Reuters specifically in those contracts, when I showed it to them, they said, This is the first time I've ever seen voter fraud come up in any of these contracts. And they're an activist shareholder in this company, so they probably cover it more closely than me. It does feel like reading the tea leaves a little bit and reading between the lines, but there's a potentially increasing number of contracts from ICE explicitly mentoring voter fraud, and that comes as we're approaching the midterm elections. I don't think I can speculate any more than that beyond just saying like those two facts, but there's something there coming at some point, and I don't know what that is, but that that's kind of where we are at the moment, I think.

Okay. Gotcha. Something to keep an eye on, I guess.

Yeah. I guess I will go back and try to figure out how many contracts actually do mention voter fraud. That might take me a minute, though. Alright. With that, I will play us out.

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