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Speaker 1: From UFOs to psychic powers and government conspiracies. History is

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Speaker 1: riddled with unexplained events. You can turn back now or

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Speaker 1: learn the stuff they don't want you to know. A

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Speaker 1: production of iHeartRadio.

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Speaker 2: Hello, welcome back to the show. My name is Matt,

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Speaker 2: my name is Noah.

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Speaker 3: They called me Ben. We're joined as always with our

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Speaker 3: super producer Paul Mission controlled tickets. Most importantly, you are here,

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Speaker 3: and that makes this the stuff they don't want you

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Speaker 3: to know. Big, big thanks to the Internet for making

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Speaker 3: our show possible.

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Speaker 4: Ah, the Internet, you love it, you hate it, you

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Speaker 4: can't really escape it. Then you pointed out that we're

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Speaker 4: all kind of we're all kind of children of the Internet,

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Speaker 4: and that we came up during the earliest of internets.

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Speaker 4: I don't know about you guys. Did you guys have

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Speaker 4: like rich friends with the doctor parents who had like

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Speaker 4: Prodigy and the earliest versions of the Internet, like when.

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Speaker 3: It was still Scrihindo modem.

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Speaker 4: Yeah, exactly, certainly a flex at the time. I didn't

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Speaker 4: get a proper Internet connection until the early you know,

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Speaker 4: aim day is like a America Online, which is probably

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Speaker 4: in like maybe nineteen ninety three issue.

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Speaker 3: I loved it, like, hey, I need another CD. I'm

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Speaker 3: running out of internet.

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Speaker 4: Right those Yeah, I remember back. I remember hell back

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Speaker 4: when it was floppies, they would send them the mail.

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Speaker 3: We are, as we're mentioning here, we are some of

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Speaker 3: the folks who lived through the Great Divide, right, the

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Speaker 3: rise of the Internet, and we existed pre Internet. So

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Speaker 3: like many of us listening tonight, we have witnessed amazing

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Speaker 3: fundamental changes in the world. And as we record this evening,

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Speaker 3: you can, in theory, contact anyone across the planet within

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Speaker 3: the space of seconds. It's amazing. It's technolog that never

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Speaker 3: existed before. We still don't know whether humanity is prepared

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Speaker 3: for it. But what if this online wonderland is already

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Speaker 3: past humanity? This is the dead Internet theory. Here are

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Speaker 3: the facts we've talked about the origin of the Internet.

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Speaker 3: We're very fortunate to be friends with Jonathan Strickland, who's

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Speaker 3: covered it extensively in shows like Tech Stuff. But when

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Speaker 3: you think about it, the Internet is only a natural

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Speaker 3: iteration of this fundamental drive.

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Speaker 4: Right.

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Speaker 3: People have always wanted to talk with each other. They're gregarious.

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Speaker 4: Do you guys remember a time where it just still

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Speaker 4: seemed so novel to be able to chat with somebody

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Speaker 4: in a chat room from across the country in real time.

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Speaker 4: God forbids send a picture dare we say a video

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Speaker 4: that didn't come so much later? Yeah, DSL is just

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Speaker 4: a sejo. Do you guys remember that feeling of this

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Speaker 4: being so exciting and you getting your first connection and

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Speaker 4: like really like, you know, kind of dipping your toes

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Speaker 4: in the Internet for the first time.

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Speaker 2: Yeah, but I think, at least if I recall correctly

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Speaker 2: my mind at that time as a kid, I was

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Speaker 2: not that excited with that stuff. I wanted to go

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Speaker 2: ride bikes. I wanted to be outside still because my

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Speaker 2: pre internet, you know, mine still existed, so funny. Yeah,

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Speaker 2: so like as it's emerging, it's like, oh, this is

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Speaker 2: neat then, Neto, but not. I just couldn't imagine that

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Speaker 2: we would ever get here.

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Speaker 3: Like at that time, it wasn't your number one aspiration

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Speaker 3: as a kid when it came to what to do

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Speaker 3: with your free time.

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Speaker 2: Yeah, dude, maybe I can pull another Shiven Dragon in

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Speaker 2: this fifth edition Magic Passion I'm opening right now.

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Speaker 4: And then Magic hit the Internet and all that's were off.

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Speaker 3: I mean, look at it. When we're talking about the Internet,

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Speaker 3: we're talking about something thematically related to previous communication efforts,

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Speaker 3: the telephone, the radio, the telegraph, on pigeons, semaphore, smoke signals, ravens.

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Speaker 3: So it's it's not too surprising that humans eventually came

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Speaker 3: up with the Internet. But I think it may surprise

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Speaker 3: some of us to learn that the modern Internet, the

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Speaker 3: reason it is here is pretty much due to the

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Speaker 3: Cold War.

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Speaker 4: Yeah. Cold War drove a lot of advancements and communications technology.

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Speaker 4: The Sputnik satellite launch, it was a big driver for

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Speaker 4: us to play a little catch up here in the

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Speaker 4: good old US of a. Western scientists and the military personnel,

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Speaker 4: the boffins, as you say, Ben, were super concerned that

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Speaker 4: we were being surpassed technologically by the USSR and that

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Speaker 4: they might launch some sort of massive attack on our

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Speaker 4: communications infrastructure.

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Speaker 3: Yeah, the U has long been aware that infrastructure is

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Speaker 3: one of the critical vulnerabilities, right, Like we talked recently

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Speaker 3: about how various domestic terrorists might attack water treatment areas

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Speaker 3: or power stations. But even the telephone system of the

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Speaker 3: US at this time could have could have been easily

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Speaker 3: crippled by the right kind of well placed attacks, and

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Speaker 3: this would effectively blind the US. It would not have

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Speaker 3: the ability to communicate across long distances. So in nineteen

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Speaker 3: sixty two, this guy named JC R. Licklider Licklider, that's

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Speaker 3: his real name, he pitched this crazy idea. He said, Hey, guys,

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Speaker 3: what if we could build a galactic network of computers

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Speaker 3: that could talk to each other?

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Speaker 4: Galactic network? That sounds a bad at space age as

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Speaker 4: it gets guys.

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Speaker 3: Yeah, And he wasn't a rube. He wasn't just some

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Speaker 3: do who walked into, you know, a boardroom and said

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Speaker 3: I got a pitch. He worked for MIT and for ARPA.

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Speaker 3: It was his job to imagine crazy things to try

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Speaker 3: to tackle this problem of the Cold War. And he said,

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Speaker 3: if we could do something like this, then an attack

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Speaker 3: on the netian's telephone structure won't be as catastrophic. It'll

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Speaker 3: still be bad, but we'll still be able to communicate.

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Speaker 3: You know what I mean, NOORAD and DC can somehow

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Speaker 3: still talk with each other.

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Speaker 4: But how do we build it? Right? It's an idea.

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Speaker 4: At this point then I've been a bit of a

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Speaker 4: pie in the sky one. Although you know, we know

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Speaker 4: the early Internet was based around existing telephonic infrastructure, hence

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Speaker 4: the term like dial up and you know, having that

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Speaker 4: horrible sound of connecting. This is kind of the same

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Speaker 4: technology that was used to send faxes, which were very

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Speaker 4: much a thing. It's just a way of you know,

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Speaker 4: turning something into data, transmitting it over a telephone network,

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Speaker 4: putting it back together on the other end.

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Speaker 3: Yeah, exactly. And MIT scientists later figured out the concept

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Speaker 3: of packet switching. This is where you break a piece

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Speaker 3: of data into chunks or packets and they all kind

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Speaker 3: of find their own way from point A to point Z,

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Speaker 3: and then they come back together beautifully. This led to

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Speaker 3: the creation of what was called ARPA net, and then

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Speaker 3: if you fast forward, ARPA met ARPA net excuse me

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Speaker 3: sent its first message on October twenty ninth, nineteen sixty nine,

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Speaker 3: manifesting the Galactic Network a computer. The Internet was two

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Speaker 3: computers at this point, one in UCLA and one in Stanford,

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Speaker 3: and the UCLA computer sent a single word log in

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Speaker 3: pretty cinematic right, But you know it didn't work at

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Speaker 3: the single attempt just from one computer to another crash

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Speaker 3: the network, so Stanford only got the first two letters

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Speaker 3: of the message.

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Speaker 4: Low, oh, dear, and behold. I'm sorry just to say

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Speaker 4: this because I just was doing a quick cursory Google.

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Speaker 4: Did you guys know that there's a proto version of

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Speaker 4: the fax machine Alexander Bain's electric printing telegraph that was

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Speaker 4: patented in eighteen forty three. That just blew my mind.

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Speaker 4: I'm sorry. And some of this technology that we're talking

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Speaker 4: about is super old, and obviously that was used sent

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Speaker 4: to using radio waves and all of that stuff in

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Speaker 4: the early days from you know, the Radio Corporation of

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Speaker 4: America RCA. But now we're talking about sending things over

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Speaker 4: these pre existing telephone networks.

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Speaker 3: And shout out to Tim Berners Lee for the later

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Speaker 3: creation of the Worldwide Web. Again, check out tech stuff

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Speaker 3: which goes into this history and depth. For now, the

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Speaker 3: important thing to remember is the Internet was, in a

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Speaker 3: very real way founded by paranoia. Like any other technology,

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Speaker 3: it's got no moral compass. Yeah, and that led to controversy.

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Speaker 4: And now it just foments paranoia on the regular.

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Speaker 2: Well, it was just about this, guys, Like we've talked

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Speaker 2: about this before. But the primary, the primary form of communication.

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Speaker 2: I guess the technology that's at play has for all

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Speaker 2: time had such a shaping effect on everything on the

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Speaker 2: human experience because what is either spoken about by mouth

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Speaker 2: written down in a book or newspaper, said on the radio,

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Speaker 2: scene on a television, as you go down that line,

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Speaker 2: whatever that stuff is that's happening in that place that

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Speaker 2: most people are bought into. Right again, if it's by

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Speaker 2: mouth at first, that's like how the communication starts, and

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Speaker 2: then they.

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Speaker 4: Can start to read oral tradition, right, you know.

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Speaker 2: But as it goes it really does shape the culture.

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Speaker 2: And at some point, guys, we need to sit down

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Speaker 2: and just talk about what the Internet did to like,

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Speaker 2: to everything, to everything, because it really, like I keep

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Speaker 2: I'm in that mind space now of a kid seeing

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Speaker 2: the internet getting on for the first time and thinking

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Speaker 2: about everything I knew and thought about was either taught

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Speaker 2: to me in school or I watched on a television.

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Speaker 2: And it was such a common thing for me to

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Speaker 2: sit there and watch on a television and learn everything

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Speaker 2: that I was learning.

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Speaker 3: Or read a book, you know, to have a single

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Speaker 3: source of information that you're paying attention to at a time.

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Speaker 2: Well, but often I didn't read. I was one of

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Speaker 2: those kids that was mostly in front of a television,

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Speaker 2: either watching something or playing a game. So I just think,

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Speaker 2: I wonder how many kids these days are not reading

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Speaker 2: that much, but are just constantly have this connection to

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Speaker 2: their the Internet whatever.

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Speaker 3: Yeah, I'm just saying like reading as in like the

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Speaker 3: general I would put that in the same bucket of

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Speaker 3: sitting down and doing the one thing right, suggesting through

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Speaker 3: the one source. And now I believe that is less

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Speaker 3: and less common because you know, like well, I saw

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Speaker 3: a tweet a while back where someone said, do I meditate?

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Speaker 3: I mean sort of sometimes I watch TV with my

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Speaker 3: phone in the other room.

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Speaker 4: That's the thing the Internet, and it's not just using

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Speaker 4: the Internet. Streaming is basically the Internet, just in a

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Speaker 4: different format. It's an inherently attention dividing medium. You know,

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Speaker 4: even now, especially after the pandemic, people executives in Hollywood

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Speaker 4: will say something isn't streamy enough, meaning that it's not

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Speaker 4: They call it two screens. Something needs to be created

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Speaker 4: with two screens in mind, because someone's always going to

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Speaker 4: be watching the movie and also look into their phone,

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Speaker 4: and if you can't grab them or keep their attention

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Speaker 4: and let them know what the hell's going on in

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Speaker 4: the movie pedantically, then yeah, it's obviously there are people

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Speaker 4: that are you know, fighting that. But I just wanted

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Speaker 4: to really quickly just read this incredible quote from David

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Speaker 4: Bowie from an interview that he did in nineteen ninety

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Speaker 4: nine with this dude, a BBC reporter or a presenter

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Speaker 4: named Jeremy Paxman, talking about the Internet, and Bowie says,

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Speaker 4: I don't think we've seen even the tip of the iceberg.

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Speaker 4: I think the potential of what the Internet is going

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Speaker 4: to do to society, both good and bad, is unimaginable.

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Speaker 4: I think we're actually on the cusp of something exhilarating

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Speaker 4: and terrifying, to which Paxsman says, well, it's just a tool, right,

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Speaker 4: It's just a medium, and then Bowie says, no, no,

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Speaker 4: it's not. It's an alien life form. Ninety nine.

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Speaker 3: Yeah, many people are. Many people are arguing that, you know,

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Speaker 3: the Internet is amazing. It's inherently controversial. You could argue too,

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Speaker 3: to Boie's statement that the Internet is still protean, it

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Speaker 3: has not reached its final form. I think that's fairly

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Speaker 3: reasonable to say. But you know, it's riddled with crime.

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Speaker 3: It enables what previous generations would rightly consider miracles like

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Speaker 3: near claravoyance, the ability to communicate across vast distances, and

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Speaker 3: access to a NYE infinite number of resources, some more

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Speaker 3: reliable than others, and it led to the creation of

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Speaker 3: social media, these platforms that leverage the spine of the

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Speaker 3: Internet to create higher communities and for a lot of people,

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Speaker 3: your primary means of engaging online is a mobile phone

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Speaker 3: or a mobile phone via a social media app. Right,

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Speaker 3: Like people say, oh, sometimes I Google stuff, but usually

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Speaker 3: I'm on Instagram.

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Speaker 2: Yeah, yea jse.

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Speaker 4: I mean, I'm not gonna lie. I'm absolutely part of.

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Speaker 2: That set totally. I think. Just sorry, I feel like

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Speaker 2: I didn't make my point. I was just trying to

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Speaker 2: like wrap my head around something with you guys and

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Speaker 2: get your input, cause I think when you're when you're

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Speaker 2: imagining like a television show that was broadcast on CBS

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Speaker 2: right back when television was the prime form of communication

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Speaker 2: day and date kind of stuff. Right, Well, that's everybody

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Speaker 2: getting the same information. If you've got a TV and

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Speaker 2: that's the primary, the primary technology that's used, everybody gets that.

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Speaker 2: Right then you move up to the Internet for a while,

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Speaker 2: there are very specific places on the Internet you can

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Speaker 2: go to get that information. If it's like if it's

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Speaker 2: something like a book in order to like back in

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Speaker 2: the day, if it was a best seller, that's probably

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Speaker 2: you know, if not hundreds and hundreds and hundreds of

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Speaker 2: thousands of people millions of people reading one book.

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Speaker 3: Right.

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Speaker 2: But now if you look at the metrics for what

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Speaker 2: you need to meet to become a best seller, it

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Speaker 2: is you don't have to sell that many books, which

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Speaker 2: is crazy to think about because just not that many

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Speaker 2: people are absorbing their information that way. But with the Internet,

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Speaker 2: it isn't just on a website somewhere that anybody can

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Speaker 2: access if they want to. That website, if it's popular enough,

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Speaker 2: gets linked, like you said, to all that social media

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Speaker 2: that's generated, to blogs that then get generated. And it's

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Speaker 2: one thing that now exists almost across the entirety of

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Speaker 2: this network, This one thing or this you know, somebody

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Speaker 2: famous dies, right, It would have been a radio announcement

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Speaker 2: than a television special, right, And then now it's just

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Speaker 2: the entirety of the Internet knows about it. And I

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Speaker 2: just wonder, as we're going into today's episode to talk

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Speaker 2: about this thing, this dead Internet theory, it's hard for

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Speaker 2: me to imagine that we've morphed away from that somehow,

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Speaker 2: from it is just an all encompassing awareness of things

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Speaker 2: that occur, like events that occur in the world.

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Speaker 4: Well, but it's also just like a store of the

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Speaker 4: whole of human knowledge and history available kind of in

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Speaker 4: one place. And that's why, you know, we're talking about

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Speaker 4: our upbringing with the Internet versus like our kids, you know,

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Speaker 4: gen Z or whatever and gen why they grew up

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Speaker 4: with access to all of that information from day one,

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Speaker 4: And that has to affect the development of a brain

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Speaker 4: in a very interesting way and very interesting and terrifying ways.

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Speaker 3: Perhaps deep learning is a skill, right, and it's something

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Speaker 3: you have to practice. This is not by any This

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Speaker 3: is not anybody saying, oh these whipper snappers these days.

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Speaker 3: It's just the modes of learning have changed. You could

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Speaker 3: argue they evolve. You could argue, now people tend to

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Speaker 3: know a little bit about a lot of stuff as

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Speaker 3: opposed to you know, knowing a little a heck of

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Speaker 3: a lot about three things, you know what I mean,

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Speaker 3: Like in the days of you know, the days of print,

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Speaker 3: when that was raining. But this, this could change the world.

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Speaker 3: You know, the Internet is amazing. Everything we've talked about

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Speaker 3: is true. If that is, there are still people online.

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Speaker 3: And take a break for a word from our sponsors.

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Speaker 3: Here's where it gets crazy. We sometimes call the Internet

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Speaker 3: an echo chamber, right, and parts of it very much are.

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Speaker 3: But what if it's such an echo chamber now that

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Speaker 3: we've reached a point where human users are kind of

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Speaker 3: a vestigial appendage minority stakeholders in a largely mostly automated conversation.

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Speaker 3: That's the that's the kernel of the dead Internet theory,

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Speaker 3: the idea that most online activity now is non human.

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Speaker 4: Sort of like junk, right, like almost like detritus, you know,

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Speaker 4: like if you think about spam, I guess, and just

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Speaker 4: how if it is a thing that might work, then

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Speaker 4: it will end up in your inbox, or it will

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Speaker 4: end up in your textbox, or you will get a

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Speaker 4: telephone call. Think about the Internet as just like a

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Speaker 4: jug heap of that kind of stuff. Yeah. Sure, there's

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Speaker 4: some wildlife crawling around, you know, people kind of poking

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Speaker 4: in to check on what's going on, but a lot

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Speaker 4: of it. And again I'm not proposing that this is

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Speaker 4: completely accurate, but I do think there has to be

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Speaker 4: a hell of a lot of this type of element

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Speaker 4: out there.

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Speaker 3: Well.

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Speaker 2: And as we're thinking about this, let's I don't want

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Speaker 2: to buifurciate it. Too much or split it up too much,

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Speaker 2: but think about it as social media is one thing, yes,

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Speaker 2: news and blogs as like another thing. And then what

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Speaker 2: would you guys, I know, there's got to be a

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Speaker 2: third stream?

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Speaker 3: Would be another one?

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Speaker 2: Okay, because that's also in line places where information is distributed.

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Speaker 4: Are there even websites exactly? You know, like we used

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Speaker 4: to know them, you know, I mean it went from

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Speaker 4: being called a website to being called a blog. And

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Speaker 4: now I got to wonder, are the only actual websites

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Speaker 4: quote unquote that I visit, like to do restaurant bookings.

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Speaker 4: But even that, like Bumps, you out to an app

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Speaker 4: which is sort of a social media platform in a way.

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Speaker 4: So it's an interesting question. The category is that is

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Speaker 4: you know, yeah.

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Speaker 3: Agreed, And we know that we know that the Internet

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Speaker 3: to that point, we know that it has kind of speciated, right.

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Speaker 3: There are different bubbles or genres of Internet, and you

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Speaker 3: may entirely, you may entirely define your experience by the

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Speaker 3: on the quote unquote internet, just by going to the

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Speaker 3: one thing you know, and sorry folks. Reddit also goes

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Speaker 3: in the social media bucket. Reddit is social.

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Speaker 4: Media, but it isn't the Internet really just the pipes,

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Speaker 4: you know, just the the the way all of this

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Speaker 4: stuff is delivered. It's all the Internet, right. I mean,

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Speaker 4: you can differentiate the different platforms and the different kind

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Speaker 4: of places you can spend your time, but all of

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Speaker 4: these massive server farms and stuff, they're all feeding the

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Speaker 4: same stuff.

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Speaker 3: They all use the same spine. And the idea for

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Speaker 3: the dead Internet theory is that across all of these

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Speaker 3: let's call them sub genres or subspecies if you like,

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Speaker 3: of Internet, across all of them, bots and automatically generated

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Speaker 3: content are replacing humans or pushing humans out, and a

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Speaker 3: lot of it, again, according to the theory, is designed

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Speaker 3: to mimic the appearance of human activity to arrive at versimilitude,

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Speaker 3: while at the same time minimizing your actual human interaction

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Speaker 3: and then using that to manipulate the population of readers

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Speaker 3: and users, which we know can happen. Is one thing

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Speaker 3: I think we all find really interesting about this. There's

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Speaker 3: a lot of well that part is true to these stories.

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Speaker 3: According to the law here, which we're about to get into,

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Speaker 3: this switch from a human Internet to a quote unquote

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Speaker 3: dead Internet occurred sometime around twenty sixteen or twenty seventeen,

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Speaker 3: and you can hear it being mentioned, or you can

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Speaker 3: read it being mentioned out in the chans as far

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Speaker 3: back as twenty ten four chan, wizard chan, so on.

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Speaker 3: But we know it had probably been a subject of

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Speaker 3: at least academic interest before people started talking about online.

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Speaker 4: I'm sorry, wizard chan, wizard say, is that a new

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Speaker 4: flavor of chan? I'm not familiar with this particular cham.

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Speaker 2: Well, but I don't know that, but tell us about

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Speaker 2: it in a second. But just we should note there

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Speaker 2: also that those are extremely sarcastic places on the interwebs, right,

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Speaker 2: the chans like almost purposefully.

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Speaker 4: Borderline set higher higher.

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Speaker 2: But places are talking about that and noticing something, right,

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Speaker 2: and then it almost becomes a joke in and of itself.

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Speaker 2: And then a larger theory that I would argue guys

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Speaker 2: starts to feel more and more real as it's you know,

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Speaker 2: growing up to that twenty sixteen, twenty seventeen, and then

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Speaker 2: well we'll get to it, but twenty twenty one.

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Speaker 3: Yeah. Wizard Chad is a website where people who I'm

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Speaker 3: reading from wizchan dot org. Wizard Chan is a website

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Speaker 3: where people who have no sexual experience can share their

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Speaker 3: thoughts and interest as a virgin The names inspired by

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Speaker 3: the wizard Beam, which refers to someone who's maintained his

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Speaker 3: virginity past the age of thirty.

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Speaker 4: Oh so it's an in cell message board.

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Speaker 3: Basically, well, I'm not too familiar with I'd look if

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Speaker 3: I'm totally poitantic speaking out out of school there.

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Speaker 4: I apologize to any Wizard jan members, but I know

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Speaker 4: the chance and at times had controversial Oh yeah, I

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Speaker 4: have garnered controversy because of some pretty gnarly Internet culture

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Speaker 4: that fester is.

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Speaker 3: There, Yeah, yeah, radicallyation, extremism, and then also doing stuff

386
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Speaker 3: for the nihilistic lulls, right, and we all remember those days.

387
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Speaker 3: The most often cited source of dead Internet theory is

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Speaker 3: usually going to be this thread by a user under

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Speaker 3: the handle Illuminati Pirate. This guy gets cited in The

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Speaker 3: Atlantic and The Intelligencer, in numerous scholarly works about dead

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Speaker 3: Internet theory. Maybe we go to this Atlantic piece that

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Speaker 3: was just fantastic written by a journalist named Caitlin Tiffany,

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Speaker 3: and she sums it up very nicely.

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Speaker 2: And this article, by the way, is one of the

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Speaker 2: primary ones I think that exists on the Internet. If

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Speaker 2: you search for this subject.

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Speaker 4: There's one other one from Fast Company that's more of

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Speaker 4: an editorial that I'd love to read a little bit

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Speaker 4: from a little later. But this is I think a

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Speaker 4: little bit more of a work of journalism, whereas the

401
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Speaker 4: Fast Company wants a bit more of a you know,

402
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Speaker 4: amusing but I think there's some really smart points. But yeah, man,

403
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Speaker 4: you want to read this sure.

404
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Speaker 2: Here is a quote from Tiffany in the Atlantic. The

405
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Speaker 2: post suggests this is a post by Illuminati pirate that

406
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Speaker 2: the Internet died in twenty sixteen or early twenty seventeen

407
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Speaker 2: and that now it is quote this is a quote

408
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Speaker 2: within the quote empty and devoid of people unquote, as

409
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Speaker 2: well as quote entirely sterile unquote. The post suggests that

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Speaker 2: the Internet died in twenty sixteen or early twenty seventeen,

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Speaker 2: and that now it is empty and devoid of people,

412
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Speaker 2: as well as entirely sterile. Much of the supposedly human

413
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Speaker 2: produced content you see online was actually created using AI.

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Speaker 4: Again.

415
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Speaker 2: This is back in like this a long time.

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Speaker 4: Ago, don chat yeah, way prey, Yeah.

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Speaker 2: Isn't that crazy? But go back in and was propagated

418
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Speaker 2: by bots, possibly aided by a group of influencers on

419
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Speaker 2: the payroll of various corporations that are in cohoots with

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Speaker 2: the government. The conspiring group's intention is, of course, to

421
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Speaker 2: control our thoughts and get us to purchase stuff.

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Speaker 3: I mean, that doesn't seem too far from the truth.

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Speaker 4: It doesn't.

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Speaker 2: That's what they've always wanted.

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Speaker 3: It's kind of just in my head. I think we're

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Speaker 3: on the same page here, guys. In my head, this

427
00:24:14,320 --> 00:24:17,080
Speaker 3: is kind of just a question of degree at that point,

428
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Speaker 3: degree of extremity.

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Speaker 4: Well, and to me, frankly, this Illuminati pirate, this whole

430
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Speaker 4: you know screen here feels really prescient because what we're

431
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Speaker 4: seeing now on the Internet and what is to come

432
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Speaker 4: likely is going to much more closely resemble exactly this.

433
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Speaker 4: We are on the cusp of this absolutely being the

434
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Speaker 4: truth at that point, though probably not. But what a

435
00:24:44,960 --> 00:24:46,640
Speaker 4: prescient prediction there.

436
00:24:47,000 --> 00:24:50,560
Speaker 3: And it again, I would argue, it's a question of degree, right,

437
00:24:50,760 --> 00:24:54,399
Speaker 3: rather than true falsity. He goes on, right, This is

438
00:24:54,440 --> 00:24:57,200
Speaker 3: where it goes further right. He goes on and he says, look,

439
00:24:57,720 --> 00:25:01,679
Speaker 3: we rarely interact with humans on the Internet, or we

440
00:25:01,840 --> 00:25:05,520
Speaker 3: rarely see posts created by other actual people. And then

441
00:25:05,560 --> 00:25:08,399
Speaker 3: he gets into this more philosophical thing and he's like,

442
00:25:08,480 --> 00:25:11,879
Speaker 3: think about all these memes that are evolving Pepe the

443
00:25:11,920 --> 00:25:15,280
Speaker 3: Frog and raptor Jesus and so on, these are evidence

444
00:25:15,520 --> 00:25:18,920
Speaker 3: of an evolving AI life form. So he goes a

445
00:25:18,920 --> 00:25:21,479
Speaker 3: little further than most people would agree with.

446
00:25:21,720 --> 00:25:24,920
Speaker 4: Well, I think most people would probably also agree that

447
00:25:25,720 --> 00:25:28,240
Speaker 4: what David Bowie was talking about as the Internet kind

448
00:25:28,280 --> 00:25:32,120
Speaker 4: of creating a new organism, a new way of thinking.

449
00:25:32,160 --> 00:25:36,960
Speaker 4: That these types of absurdist memes are a product of

450
00:25:37,880 --> 00:25:42,760
Speaker 4: terminal onlineness that sort of creates these changes in people's

451
00:25:42,800 --> 00:25:46,760
Speaker 4: brains that makes them look for the new thing that

452
00:25:47,080 --> 00:25:49,160
Speaker 4: gets them, you know, for lack of a better term,

453
00:25:49,280 --> 00:25:52,560
Speaker 4: kind of high. Right. It's like, oh, the old jokes

454
00:25:52,560 --> 00:25:55,520
Speaker 4: don't work anymore because we have access to too much information.

455
00:25:55,680 --> 00:25:58,960
Speaker 4: We got to make new stuff that is absolutely beyond,

456
00:25:59,080 --> 00:26:00,520
Speaker 4: incomprehensibly absurd.

457
00:26:00,920 --> 00:26:04,439
Speaker 3: I love I love forensic memes, man, I love I

458
00:26:04,480 --> 00:26:08,040
Speaker 3: love a meme that is four layers deep in weird

459
00:26:08,119 --> 00:26:11,200
Speaker 3: Internet culture. And I think you're I think you're absolutely right,

460
00:26:11,240 --> 00:26:15,200
Speaker 3: because memes, just like social media, are a dopamine casino.

461
00:26:16,080 --> 00:26:20,440
Speaker 3: It is this stuff seeming to be true is still

462
00:26:20,480 --> 00:26:24,160
Speaker 3: not the same thing as it actually being true. I mean,

463
00:26:24,200 --> 00:26:27,199
Speaker 3: if the theory does hold water, then that means the

464
00:26:27,280 --> 00:26:32,639
Speaker 3: days of automation rendering humans irrelevant are already well upon us.

465
00:26:32,760 --> 00:26:36,360
Speaker 3: Kind of like when Ozumandias makes his speech in Watchmen

466
00:26:36,680 --> 00:26:39,800
Speaker 3: spoiler and then says, yeah, I'm telling you this because

467
00:26:39,840 --> 00:26:43,320
Speaker 3: it already happened. I'm not giving you an opportunity to

468
00:26:43,320 --> 00:26:43,720
Speaker 3: brook me.

469
00:26:44,280 --> 00:26:48,000
Speaker 2: But do you guys ever the ringing true thing. I'm

470
00:26:48,080 --> 00:26:49,680
Speaker 2: just going to expand on that for a second, because

471
00:26:49,720 --> 00:26:52,960
Speaker 2: it does ring partly true, at least to me, just

472
00:26:52,960 --> 00:26:55,200
Speaker 2: when I think back, and let's not let's be really

473
00:26:55,200 --> 00:26:59,520
Speaker 2: careful here, thinking back to our careers, thinking back to

474
00:26:59,800 --> 00:27:03,240
Speaker 2: the Internet groups that we've interacted with, and companies we've

475
00:27:03,280 --> 00:27:07,399
Speaker 2: interacted with, specifically ones that try to measure data and

476
00:27:07,480 --> 00:27:11,159
Speaker 2: analytics and things like web page views, and you know,

477
00:27:12,119 --> 00:27:14,560
Speaker 2: what are some of the terms they use, like a

478
00:27:14,760 --> 00:27:18,920
Speaker 2: unique visitor or things like that. And and then what

479
00:27:19,160 --> 00:27:22,280
Speaker 2: some of those companies, you know, usually third that's in

480
00:27:22,359 --> 00:27:24,560
Speaker 2: our case, it's been like third party companies that are

481
00:27:24,760 --> 00:27:28,200
Speaker 2: being used as services or something, but will give you

482
00:27:28,600 --> 00:27:31,960
Speaker 2: data that looks really good for whatever your company is

483
00:27:32,000 --> 00:27:35,600
Speaker 2: looking for. But it feels often like those and it's

484
00:27:35,640 --> 00:27:37,760
Speaker 2: actually been proven a couple of cases we know of

485
00:27:39,000 --> 00:27:43,440
Speaker 2: where that data is actually juiced quite a bit through

486
00:27:43,640 --> 00:27:49,119
Speaker 2: little things, little interaction key key points in a like

487
00:27:49,160 --> 00:27:51,240
Speaker 2: the way a person uses their mouse or the way

488
00:27:51,240 --> 00:27:52,639
Speaker 2: a person uses their phone.

489
00:27:52,960 --> 00:27:59,000
Speaker 4: What constitutes a view or time sped or use a

490
00:27:59,000 --> 00:28:02,640
Speaker 4: banner ad auto plays a thing instead of actually somebody

491
00:28:02,640 --> 00:28:03,840
Speaker 4: engaging with the video.

492
00:28:03,960 --> 00:28:06,240
Speaker 2: But just this is my only argument. Think about how

493
00:28:06,280 --> 00:28:09,680
Speaker 2: long and not to put you out of this, no all,

494
00:28:09,720 --> 00:28:12,120
Speaker 2: but how long ben you and I specifically have been

495
00:28:12,119 --> 00:28:15,600
Speaker 2: in this internet game thing where we're you know, fighting

496
00:28:15,720 --> 00:28:19,719
Speaker 2: for people's attention, right, whether through a website or through

497
00:28:19,760 --> 00:28:22,080
Speaker 2: a podcast or video and all that other stuff. And

498
00:28:22,200 --> 00:28:25,520
Speaker 2: just how many times we've seen over the years companies

499
00:28:25,600 --> 00:28:28,439
Speaker 2: private companies that are vying for a large company's money

500
00:28:28,480 --> 00:28:31,120
Speaker 2: for some kind of service like that, right, And then

501
00:28:31,200 --> 00:28:34,560
Speaker 2: how long those companies have been competing and attempting to

502
00:28:35,000 --> 00:28:38,000
Speaker 2: goose those numbers like and how far do you think

503
00:28:38,000 --> 00:28:40,680
Speaker 2: they've had to take it in order to get the

504
00:28:40,840 --> 00:28:45,600
Speaker 2: lion's share of some huge enterprise company's money. So and

505
00:28:45,640 --> 00:28:47,640
Speaker 2: it just makes me wonder if if it's a balloon

506
00:28:47,680 --> 00:28:50,600
Speaker 2: effect when it comes to the actual interaction or number

507
00:28:50,640 --> 00:28:51,320
Speaker 2: of interactions.

508
00:28:51,600 --> 00:28:53,840
Speaker 4: I guess my question though, and then I'll shut the

509
00:28:53,840 --> 00:28:55,880
Speaker 4: back up, like if if there are no people on

510
00:28:55,920 --> 00:28:58,920
Speaker 4: the Internet, who who does all this data represent?

511
00:28:59,600 --> 00:29:03,960
Speaker 3: Yeah, it's kind of It has some disturbing similarities to

512
00:29:04,240 --> 00:29:09,120
Speaker 3: things like the gang stalking conspiracies, because in one form

513
00:29:09,320 --> 00:29:13,160
Speaker 3: of a dead Internet theory, the implication is that when

514
00:29:13,200 --> 00:29:17,600
Speaker 3: you go online, everybody else is an NPC except for you.

515
00:29:18,280 --> 00:29:21,280
Speaker 3: And this, you know, there is a sort of I

516
00:29:21,280 --> 00:29:27,000
Speaker 3: would argue there's a strong streak of narcissism inherent in

517
00:29:27,040 --> 00:29:29,400
Speaker 3: a lot of paranoia, you know what I mean, Like

518
00:29:30,600 --> 00:29:32,440
Speaker 3: we're all.

519
00:29:32,360 --> 00:29:34,480
Speaker 4: Out to get me right, right me?

520
00:29:34,680 --> 00:29:40,040
Speaker 3: In particular, this this idea, though of juicy numbers, of

521
00:29:40,120 --> 00:29:45,160
Speaker 3: framing and presenting things in an advantageous or profitable way,

522
00:29:45,800 --> 00:29:48,760
Speaker 3: does show us that the one thing that will always

523
00:29:48,800 --> 00:29:52,840
Speaker 3: remain true on the Internet is a profit motive. Does

524
00:29:52,880 --> 00:29:54,920
Speaker 3: it matter if the comments are faked so long as

525
00:29:54,960 --> 00:29:58,320
Speaker 3: the money is real. That's a question that companies grapple with.

526
00:29:58,640 --> 00:30:02,200
Speaker 3: We see in this would argue the long shadow of

527
00:30:02,280 --> 00:30:08,160
Speaker 3: bernese Bernez, who famously perfected the art of rigging questions

528
00:30:08,360 --> 00:30:11,520
Speaker 3: in surveys to get the answers he wanted, you know

529
00:30:11,520 --> 00:30:11,960
Speaker 3: what I mean.

530
00:30:12,320 --> 00:30:15,000
Speaker 2: But it goes back to the very nature of something

531
00:30:15,080 --> 00:30:19,040
Speaker 2: like a search engine like Google. Google's money for a

532
00:30:19,080 --> 00:30:22,959
Speaker 2: long time, and still for a large part today is

533
00:30:23,000 --> 00:30:25,840
Speaker 2: made through ads and people who pay to have their

534
00:30:26,240 --> 00:30:29,160
Speaker 2: sites show up at the top, or you know, people

535
00:30:29,240 --> 00:30:33,200
Speaker 2: who pay big money and work with them, or I'm

536
00:30:33,200 --> 00:30:35,360
Speaker 2: just trying to think these social encounter.

537
00:30:35,240 --> 00:30:38,440
Speaker 4: To the mission of what a search engine should inherently be,

538
00:30:38,760 --> 00:30:42,120
Speaker 4: where it's democratization of information as opposed to you can

539
00:30:42,200 --> 00:30:44,760
Speaker 4: pay extra to get yours in the first spot.

540
00:30:45,160 --> 00:30:48,280
Speaker 2: Ideologically that's great and it sounds great, but it doesn't

541
00:30:48,400 --> 00:30:52,160
Speaker 2: keep anybody's jobs right, and it doesn't grow anybody's bottom line.

542
00:30:52,680 --> 00:30:55,040
Speaker 2: And as Ben is saying, like it has always been

543
00:30:55,560 --> 00:30:59,240
Speaker 2: about that profit motive for everything that maybe we even

544
00:30:59,440 --> 00:31:04,040
Speaker 2: personally or you know, theoretically hold dear about the Internet

545
00:31:04,080 --> 00:31:07,080
Speaker 2: and what it provides for us, that profit motive at

546
00:31:07,080 --> 00:31:09,880
Speaker 2: the center, I think has been the manipulating factor. And

547
00:31:10,120 --> 00:31:14,320
Speaker 2: it really does weird me out thinking about you. If

548
00:31:14,320 --> 00:31:17,400
Speaker 2: you wanted to, like you said, Ben, we just need

549
00:31:17,440 --> 00:31:20,479
Speaker 2: to hit a thousand comments, that's the metric, and oh

550
00:31:20,520 --> 00:31:21,880
Speaker 2: we can we can do that for you.

551
00:31:22,440 --> 00:31:24,640
Speaker 4: Yeah we can a thousand votes.

552
00:31:25,920 --> 00:31:27,800
Speaker 3: Yeah, but see that's harder.

553
00:31:27,880 --> 00:31:29,840
Speaker 2: A thousand votes. Would you'd have to activate.

554
00:31:29,920 --> 00:31:32,240
Speaker 4: No, it's very true being I mean, I'm saying sometimes

555
00:31:32,240 --> 00:31:36,000
Speaker 4: these margins are you know, like hilariously small.

556
00:31:36,640 --> 00:31:39,560
Speaker 3: Yeah, and again, a lot of you get a lot

557
00:31:39,560 --> 00:31:41,680
Speaker 3: of people we've seen it happen. You get a lot

558
00:31:41,680 --> 00:31:45,440
Speaker 3: of people cowboying in as consultants, right, and they want

559
00:31:45,480 --> 00:31:49,440
Speaker 3: to be the bringers of the truth. The digital Moses

560
00:31:49,520 --> 00:31:52,560
Speaker 3: descends the mountain and says, this is the click through

561
00:31:52,640 --> 00:31:56,640
Speaker 3: rate that matters to a great degree. They're just kind

562
00:31:56,640 --> 00:31:59,240
Speaker 3: of drinking their own flavors all smoke man that boy?

563
00:31:59,400 --> 00:32:00,560
Speaker 4: Yeah? Is it ever?

564
00:32:00,760 --> 00:32:05,840
Speaker 3: And may God grant us the confidence of the stridently incorrect, right,

565
00:32:06,800 --> 00:32:08,560
Speaker 3: the confidently incorrect.

566
00:32:09,680 --> 00:32:12,080
Speaker 2: Do you guys remember actually it was around the twenty

567
00:32:12,520 --> 00:32:16,600
Speaker 2: maybe fifteen to seventeen time when a lot of the

568
00:32:16,640 --> 00:32:21,720
Speaker 2: Facebook pages that we were the let's say our company

569
00:32:22,320 --> 00:32:25,880
Speaker 2: was running, right, a lot of them had to purge

570
00:32:26,200 --> 00:32:29,680
Speaker 2: a ton of users from each of our main Facebook

571
00:32:29,720 --> 00:32:32,360
Speaker 2: pages because of the the what are they call them,

572
00:32:32,440 --> 00:32:33,840
Speaker 2: farms like server farms?

573
00:32:34,200 --> 00:32:37,320
Speaker 3: Farms? Yeah, exactly.

574
00:32:37,840 --> 00:32:41,640
Speaker 4: I mean we certainly know that with x FKA Twitter,

575
00:32:42,400 --> 00:32:45,280
Speaker 4: the value of that company significantly got called in a

576
00:32:45,400 --> 00:32:49,840
Speaker 4: question when it was revealed how many bots constitute their

577
00:32:49,920 --> 00:32:53,640
Speaker 4: quote unquote user base, which is the number that's used

578
00:32:53,920 --> 00:32:58,080
Speaker 4: for valuating these these social media companies. Is what's our

579
00:32:58,160 --> 00:32:59,520
Speaker 4: user base, guys.

580
00:32:59,720 --> 00:33:03,080
Speaker 3: And no hour and for background on our side of it.

581
00:33:03,280 --> 00:33:07,640
Speaker 3: When when that great Facebook purge happened, I believe it

582
00:33:07,720 --> 00:33:11,040
Speaker 3: was because there was a moment of awakening, right. I

583
00:33:11,080 --> 00:33:15,920
Speaker 3: think those bots were just being added by by people

584
00:33:16,040 --> 00:33:18,480
Speaker 3: who had different interest from those of the company.

585
00:33:18,880 --> 00:33:22,120
Speaker 2: Yeah, and we didn't we didn't even realize it was happening.

586
00:33:22,160 --> 00:33:24,120
Speaker 2: And you know, and it's so funny because when you're

587
00:33:24,160 --> 00:33:27,280
Speaker 2: on the inside of something like that, you're seeing those numbers,

588
00:33:27,320 --> 00:33:32,880
Speaker 2: those metrics that everybody looks at as an awesome thing, awesome, great,

589
00:33:33,840 --> 00:33:37,080
Speaker 2: but but it's this weird other thing that's happening in

590
00:33:37,120 --> 00:33:39,920
Speaker 2: the background, which is again it speaks to this theory,

591
00:33:39,960 --> 00:33:44,280
Speaker 2: which it doesn't mean theories fully true, but like people

592
00:33:44,320 --> 00:33:49,640
Speaker 2: are willing, willingly adding fake users to the internet for these.

593
00:33:49,520 --> 00:33:54,840
Speaker 3: Interactively, assertively, aggressively the Sorcerer's apprentice all over again. That's

594
00:33:54,880 --> 00:33:57,400
Speaker 3: what we're kind of, that's the possibility we're looking at.

595
00:33:57,560 --> 00:34:00,880
Speaker 3: And you know, we're seeing the rise of general like

596
00:34:01,000 --> 00:34:05,440
Speaker 3: large language models, AI generated content, deep fakes, which are

597
00:34:05,560 --> 00:34:10,000
Speaker 3: indistinguishable from the real thing. This is a new era

598
00:34:10,080 --> 00:34:13,600
Speaker 3: of dead Internet theory. But I would argue, I think

599
00:34:13,600 --> 00:34:16,840
Speaker 3: we all argue, the basis of it remains the same.

600
00:34:17,200 --> 00:34:18,720
Speaker 3: Do you want to take a quick ad break?

601
00:34:18,920 --> 00:34:20,640
Speaker 4: That sounds good to me. Let's take a quick break

602
00:34:20,640 --> 00:34:23,360
Speaker 4: here away from our sponsor, hopefully some sort of Internet

603
00:34:23,360 --> 00:34:26,719
Speaker 4: service provider or a social media company of note, and

604
00:34:26,760 --> 00:34:30,920
Speaker 4: then we'll be back with more on this frankly pretty

605
00:34:30,960 --> 00:34:31,680
Speaker 4: terrifying topic.

606
00:34:38,719 --> 00:34:42,799
Speaker 3: We've returned. So the theory has two primary elements, the

607
00:34:42,880 --> 00:34:46,560
Speaker 3: idea that bots have largely outnumbered human activity, and the

608
00:34:46,760 --> 00:34:52,000
Speaker 3: idea that some unknown actors are deploying these bots to

609
00:34:52,120 --> 00:34:56,920
Speaker 3: manipulate the humans that remain. It's fascinating, But here's the

610
00:34:56,960 --> 00:34:59,400
Speaker 3: thing that keeps getting me again. It's not a question

611
00:34:59,640 --> 00:35:02,480
Speaker 3: of yes or no. It's a question of to what

612
00:35:02,640 --> 00:35:06,759
Speaker 3: degree is this theory true. I mean, I didn't know this,

613
00:35:06,880 --> 00:35:10,560
Speaker 3: but in twenty twenty two, bots contributed almost half of

614
00:35:10,600 --> 00:35:12,760
Speaker 3: all Internet traffic in the world.

615
00:35:13,280 --> 00:35:15,279
Speaker 2: That was from one source band and I saw that.

616
00:35:15,320 --> 00:35:19,160
Speaker 2: But then there's another one from Barracuda that it put

617
00:35:19,239 --> 00:35:25,120
Speaker 2: it at like sixty five percent, and that's including social

618
00:35:25,160 --> 00:35:26,840
Speaker 2: media and stuff too, So I think there it just

619
00:35:26,920 --> 00:35:27,759
Speaker 2: depends on what.

620
00:35:27,680 --> 00:35:32,040
Speaker 4: You But what one thing that my mind keeps jumping

621
00:35:32,080 --> 00:35:33,879
Speaker 4: back to in this especially when you're here to talk

622
00:35:33,920 --> 00:35:36,680
Speaker 4: about all these like goose numbers, is like I as

623
00:35:36,760 --> 00:35:39,880
Speaker 4: a user and as a participator in the Internet, and

624
00:35:40,000 --> 00:35:42,719
Speaker 4: rather I've gotten relatively good at curating my experience and

625
00:35:42,719 --> 00:35:45,320
Speaker 4: only looking at the stuff that interests me. I interact

626
00:35:45,320 --> 00:35:47,000
Speaker 4: with a lot of people who I know are are

627
00:35:47,080 --> 00:35:49,279
Speaker 4: real because I talked to them and I know them

628
00:35:49,440 --> 00:35:53,000
Speaker 4: in real life. I don't think about the overall number

629
00:35:53,040 --> 00:35:56,120
Speaker 4: of users on the Internet. So even if sixty percent

630
00:35:56,520 --> 00:35:59,640
Speaker 4: of the quote unquote traffic on the Internet is bots, whatever,

631
00:35:59,680 --> 00:36:03,120
Speaker 4: that twenty percent that I'm engaging with is the Internet

632
00:36:03,200 --> 00:36:05,879
Speaker 4: to me, you know what I'm saying. And so I think,

633
00:36:05,960 --> 00:36:09,160
Speaker 4: like all of that trash that's sixty percent or forty

634
00:36:09,200 --> 00:36:11,560
Speaker 4: seven point four percent, I don't.

635
00:36:11,400 --> 00:36:15,520
Speaker 3: Think everybody is as affected by.

636
00:36:15,880 --> 00:36:18,480
Speaker 4: If you're a savvy Internet user, I'm not saying I'm

637
00:36:18,520 --> 00:36:21,040
Speaker 4: so such a tech savvy Internet genius. I'm just saying

638
00:36:21,120 --> 00:36:23,239
Speaker 4: people of a certain age, at a certain level of

639
00:36:23,719 --> 00:36:26,319
Speaker 4: Internet savvy is kind of know how to steer away.

640
00:36:26,320 --> 00:36:27,880
Speaker 4: But I think it's just going to get worse, is

641
00:36:27,880 --> 00:36:28,560
Speaker 4: what we're saying.

642
00:36:28,760 --> 00:36:30,960
Speaker 3: That's the trend. And also, yeah, you might say this

643
00:36:31,000 --> 00:36:34,120
Speaker 3: doesn't affect me, it's not in my part of the playground, right,

644
00:36:34,400 --> 00:36:36,959
Speaker 3: But that part of the playground is coming to you

645
00:36:37,360 --> 00:36:40,000
Speaker 3: at least, that's the argument, because that twenty twenty two

646
00:36:40,120 --> 00:36:45,000
Speaker 3: number we quoted that represents a five point one percent

647
00:36:45,400 --> 00:36:49,880
Speaker 3: year over year increase, which consultants love to say stuff

648
00:36:49,920 --> 00:36:50,200
Speaker 3: like that.

649
00:36:50,640 --> 00:36:54,399
Speaker 2: Oh yeah, oh my gosh, Well, guys, I just wanted

650
00:36:54,400 --> 00:36:57,160
Speaker 2: to cite that Barracuda think again, because I I feel

651
00:36:57,160 --> 00:36:59,960
Speaker 2: like I may have gotten it wrong. According to something

652
00:37:00,160 --> 00:37:03,880
Speaker 2: Posts in September of twenty twenty one called bot attacks,

653
00:37:04,400 --> 00:37:09,040
Speaker 2: Top Threats and Trends, they said North America accounts for

654
00:37:09,440 --> 00:37:13,120
Speaker 2: like across the entirety of the Internet, North America accounts

655
00:37:13,120 --> 00:37:16,600
Speaker 2: for sixty seven percent of what they call bad bot traffic,

656
00:37:17,239 --> 00:37:21,280
Speaker 2: and then sixty four percent they say, of all Internet

657
00:37:21,320 --> 00:37:24,239
Speaker 2: traffic is made up by bots. But again, this is

658
00:37:24,280 --> 00:37:26,680
Speaker 2: one this is their own measurements, right, and this is

659
00:37:27,040 --> 00:37:29,640
Speaker 2: like a security Internet security company. They do a whole

660
00:37:29,640 --> 00:37:33,640
Speaker 2: bunch of stuff. But they found that in twenty twenty one,

661
00:37:34,480 --> 00:37:38,800
Speaker 2: and we cannot stress this enough. That is before the

662
00:37:38,960 --> 00:37:44,440
Speaker 2: large release of these these language learning models and all

663
00:37:44,440 --> 00:37:47,320
Speaker 2: this stuff where if you want to, you can create

664
00:37:47,800 --> 00:37:53,000
Speaker 2: You can literally just type in code a bot that scrubs, oh,

665
00:37:53,040 --> 00:37:57,359
Speaker 2: I don't know this healthcare website and attempts to log in,

666
00:37:57,600 --> 00:37:59,000
Speaker 2: you know, every whatever.

667
00:38:00,160 --> 00:38:04,200
Speaker 3: We make a bot that creates make a bot that

668
00:38:04,280 --> 00:38:08,760
Speaker 3: creates other bots that build websites that are just similar

669
00:38:08,880 --> 00:38:11,480
Speaker 3: enough to the actual website someone's looking for.

670
00:38:11,800 --> 00:38:14,759
Speaker 2: Sure, Sure, and that's automated. But these other bots are

671
00:38:14,840 --> 00:38:17,200
Speaker 2: created by human beings, these at least that are being

672
00:38:17,239 --> 00:38:20,880
Speaker 2: referred to here by Barracuda, to do things like sweep

673
00:38:20,960 --> 00:38:24,279
Speaker 2: through a site like Amazon and check on the prices

674
00:38:24,400 --> 00:38:27,520
Speaker 2: of very specific items so that it can then spit

675
00:38:27,600 --> 00:38:31,080
Speaker 2: out what the user of this bot, or you know,

676
00:38:31,600 --> 00:38:34,680
Speaker 2: the company that's deploying this bot, can know how to

677
00:38:34,719 --> 00:38:38,240
Speaker 2: price your own thing on your own website or whatever.

678
00:38:38,800 --> 00:38:41,440
Speaker 2: Or you know, again like trying to broute force into

679
00:38:41,480 --> 00:38:44,440
Speaker 2: other websites. But I don't know how much of that is,

680
00:38:44,480 --> 00:38:48,320
Speaker 2: like the social media bot traffic.

681
00:38:48,880 --> 00:38:52,160
Speaker 3: Well, there's also the question it's not just okay, so

682
00:38:52,239 --> 00:38:54,920
Speaker 3: think of them as tools, right, It's not just the

683
00:38:55,040 --> 00:38:59,280
Speaker 3: question of does the screwdriver work. It's the question of evolution.

684
00:38:59,640 --> 00:39:03,720
Speaker 3: Are the screwdrivers turning into power drills. Right, How sophisticated

685
00:39:04,239 --> 00:39:07,840
Speaker 3: are these programs becoming. We know that state level actors

686
00:39:08,200 --> 00:39:12,280
Speaker 3: control botnets. They've deployed them in various ways to attempt

687
00:39:12,320 --> 00:39:15,680
Speaker 3: this way public opinion or even interfere with elections, and

688
00:39:15,719 --> 00:39:20,000
Speaker 3: they're getting very good at it. They're getting stunningly accomplished.

689
00:39:20,239 --> 00:39:24,280
Speaker 2: Oh yeah, and that's scary and I feel like super real.

690
00:39:24,719 --> 00:39:26,000
Speaker 2: But I just want to go back to that thing

691
00:39:26,040 --> 00:39:27,680
Speaker 2: in the beginning where we're trying to like break out

692
00:39:27,760 --> 00:39:31,200
Speaker 2: the different types of bot traffic or fake traffic or

693
00:39:31,239 --> 00:39:34,319
Speaker 2: not real human beings you're interacting with, because a lot

694
00:39:34,360 --> 00:39:37,400
Speaker 2: of these bots are purpose built, right, they have a

695
00:39:37,480 --> 00:39:40,000
Speaker 2: very specific purpose. And then if you look at some

696
00:39:40,080 --> 00:39:43,520
Speaker 2: of the bots that were uncovered around that twenty twenty

697
00:39:43,520 --> 00:39:46,919
Speaker 2: one time when Twitter was becoming x it was going

698
00:39:46,960 --> 00:39:52,560
Speaker 2: on its journey to become x, there was intense bot

699
00:39:52,640 --> 00:39:58,120
Speaker 2: traffic to make posts more popular in the algorithm so

700
00:39:58,160 --> 00:40:00,440
Speaker 2: that they would get bumped up and serve to more people.

701
00:40:00,960 --> 00:40:03,600
Speaker 2: Because there was a real problem with Twitter at the

702
00:40:03,640 --> 00:40:07,160
Speaker 2: time where everybody's kind of seeing the same top posts

703
00:40:07,600 --> 00:40:10,960
Speaker 2: across the entirety of the thing. So everybody is building

704
00:40:10,960 --> 00:40:14,480
Speaker 2: these bots to make the algorithm think that there's popularity

705
00:40:14,520 --> 00:40:17,719
Speaker 2: being generated so that it does end up getting popular,

706
00:40:17,760 --> 00:40:21,400
Speaker 2: so that whatever ad thing you've got inside that viral

707
00:40:21,440 --> 00:40:26,400
Speaker 2: tweet is effective. But it changed completely with X with

708
00:40:26,480 --> 00:40:29,560
Speaker 2: the blue check marks, because then you can pay to

709
00:40:29,600 --> 00:40:32,280
Speaker 2: have those check marks, which it just changed the algorithm

710
00:40:32,320 --> 00:40:34,319
Speaker 2: a little bit, and now you just pay to have

711
00:40:34,440 --> 00:40:38,480
Speaker 2: enough blue check mark accounts to comment a fake bot

712
00:40:38,520 --> 00:40:41,200
Speaker 2: comment on somebody else's blue check mark thing, which then

713
00:40:41,239 --> 00:40:42,120
Speaker 2: pushes it all the way up.

714
00:40:42,200 --> 00:40:44,600
Speaker 4: And it doesn't serve as any kind of real verification

715
00:40:44,680 --> 00:40:47,240
Speaker 4: of identity at all, because you can just see anybody

716
00:40:47,239 --> 00:40:47,800
Speaker 4: can buy.

717
00:40:47,640 --> 00:40:51,279
Speaker 2: It in and it's for profit, like we're talking about.

718
00:40:51,320 --> 00:40:54,160
Speaker 4: Absolutely and all about gaming. That algorithm is the name

719
00:40:54,200 --> 00:40:57,520
Speaker 4: of the the game. No pun intended, but I guess

720
00:40:57,560 --> 00:40:59,759
Speaker 4: maybe a little. So I just mentioned really quickly that

721
00:41:00,120 --> 00:41:03,360
Speaker 4: company article that I referenced by Michael Grothaus is the

722
00:41:03,400 --> 00:41:06,040
Speaker 4: dead Internet theory suddenly coming true. This could be a sign.

723
00:41:06,520 --> 00:41:08,640
Speaker 4: There's just one little thing that I think is so

724
00:41:09,080 --> 00:41:13,040
Speaker 4: appropriate here, he says. Ever since chat GPT bursts onto

725
00:41:13,080 --> 00:41:15,239
Speaker 4: the scenes in late twenty twenty two, people have been

726
00:41:15,320 --> 00:41:18,600
Speaker 4: using it to generate content for websites, social media posts,

727
00:41:18,600 --> 00:41:20,759
Speaker 4: and articles of all kinds. People have also been using

728
00:41:20,760 --> 00:41:23,560
Speaker 4: AI image generation tools to create an unending flood of photos,

729
00:41:23,600 --> 00:41:26,600
Speaker 4: video at artwork, which now abound on mainstream social media

730
00:41:26,640 --> 00:41:30,440
Speaker 4: platforms like Instagram, Facebook, Twitter, YouTube, and TikTok uh. And

731
00:41:30,640 --> 00:41:37,160
Speaker 4: these videos and sites and accounts get crazy engagement. There

732
00:41:37,200 --> 00:41:40,440
Speaker 4: are these memes that are being generated something called shrimp Jesus.

733
00:41:40,760 --> 00:41:43,960
Speaker 4: That is all of these images of like Jesus like

734
00:41:44,360 --> 00:41:47,640
Speaker 4: hanging out with these these shrimp, these warfic shrimp in

735
00:41:47,800 --> 00:41:50,480
Speaker 4: like the ocean, like he's in the Little Mermaid or something.

736
00:41:50,760 --> 00:41:53,560
Speaker 2: And I saw crab there's something like that.

737
00:41:53,760 --> 00:41:57,440
Speaker 4: Sure, Crab Jesus is a direct AI response to shrimp Jesus.

738
00:41:57,760 --> 00:41:59,640
Speaker 4: And that's what you get. Now we're in the Jesus

739
00:41:59,719 --> 00:42:02,399
Speaker 4: and Christ station's echo chamber. But it's not even echo

740
00:42:02,440 --> 00:42:06,000
Speaker 4: chamber perpetrated by actual people. It's an echo chamber perpetrated

741
00:42:06,040 --> 00:42:09,120
Speaker 4: by these bots that are now armed with chat, GPT

742
00:42:09,520 --> 00:42:12,160
Speaker 4: and image you know, AI creation.

743
00:42:11,960 --> 00:42:15,319
Speaker 3: Tools, and we know we know. It can also be

744
00:42:16,080 --> 00:42:20,920
Speaker 3: difficult to verify somebody's real identity online, right. It can

745
00:42:20,960 --> 00:42:24,239
Speaker 3: be difficult to find the right person unless you're like

746
00:42:24,520 --> 00:42:27,719
Speaker 3: the Puzzle Palace. It can be difficult to find a

747
00:42:27,800 --> 00:42:32,719
Speaker 3: random person and say, yes, specifically, it's that guy in Akron, Ohio.

748
00:42:33,280 --> 00:42:36,560
Speaker 3: And that's that's a whole other philosophical bag of badgers. Right,

749
00:42:36,680 --> 00:42:42,840
Speaker 3: anonymity and privacy expectations, But like you say, dancing with

750
00:42:42,880 --> 00:42:46,520
Speaker 3: the algorithm, everybody knows it happens. The question really is

751
00:42:46,560 --> 00:42:49,920
Speaker 3: one of degree. Sure bots are everywhere, but do they

752
00:42:50,120 --> 00:42:54,160
Speaker 3: genuinely outnumber humans? What does it mean? That's where the

753
00:42:54,160 --> 00:42:57,759
Speaker 3: dead Internet theory runs into some challenges. A lot of

754
00:42:57,760 --> 00:43:00,360
Speaker 3: the things we read about it are kind of a

755
00:43:00,400 --> 00:43:04,919
Speaker 3: tree of if thens based on some primary foundational assumptions,

756
00:43:05,120 --> 00:43:08,239
Speaker 3: but then you see a lot of anecdotal evidence, which

757
00:43:08,280 --> 00:43:11,719
Speaker 3: is not the same thing as quantitative data. So I

758
00:43:11,760 --> 00:43:14,760
Speaker 3: want to give a shout out to a great YouTube channel.

759
00:43:14,760 --> 00:43:19,240
Speaker 3: I was surprised that this video was not getting more views,

760
00:43:19,360 --> 00:43:21,600
Speaker 3: but it just came out a few weeks ago. A

761
00:43:21,640 --> 00:43:25,320
Speaker 3: guy named siros On on YouTube has an in depth

762
00:43:25,400 --> 00:43:28,920
Speaker 3: explanation of this, and he hipped us to the twenty

763
00:43:29,040 --> 00:43:33,279
Speaker 3: twenty three Imperva bad Bot Report and he brings up

764
00:43:33,320 --> 00:43:38,160
Speaker 3: the same question. It's a question of nuance. Imperva. Here's

765
00:43:38,200 --> 00:43:43,239
Speaker 3: what they did. They took a single network in Capsula,

766
00:43:43,719 --> 00:43:47,200
Speaker 3: and they took a sample of sixteen point seven billion

767
00:43:47,320 --> 00:43:52,040
Speaker 3: bought in human website visits, not social media from August

768
00:43:52,080 --> 00:43:57,640
Speaker 3: to November of twenty sixteen, and what they found is

769
00:43:58,360 --> 00:44:03,120
Speaker 3: pretty stunning. But they also they hit on something that

770
00:44:03,160 --> 00:44:05,520
Speaker 3: I think you were just mentioning their matt, which is

771
00:44:05,640 --> 00:44:09,000
Speaker 3: we have to differentiate between the bots. Not all are

772
00:44:09,040 --> 00:44:12,680
Speaker 3: created equal. Some are good or benign, others are bad,

773
00:44:12,840 --> 00:44:15,520
Speaker 3: you know, like good bots. I think it's I think

774
00:44:15,520 --> 00:44:18,439
Speaker 3: it's helpful to think of good bots as the good

775
00:44:18,480 --> 00:44:21,160
Speaker 3: bacteria in the guts of the digital body.

776
00:44:22,320 --> 00:44:24,919
Speaker 4: On message boards and things like that. And I'm sure

777
00:44:25,080 --> 00:44:26,960
Speaker 4: deeper than that. That's the first thing that comes to

778
00:44:26,960 --> 00:44:27,319
Speaker 4: mind for.

779
00:44:27,400 --> 00:44:30,319
Speaker 2: Me, and literally the standard web crawlers that like a

780
00:44:30,400 --> 00:44:33,440
Speaker 2: Google or a similar search would use just to make

781
00:44:33,480 --> 00:44:37,000
Speaker 2: sure the thing knows what's on the internet. Yeah, what

782
00:44:37,320 --> 00:44:40,239
Speaker 2: what can it have access to? So it's constantly going

783
00:44:40,239 --> 00:44:43,680
Speaker 2: through and just checking websites. Oh there's an active connection there,

784
00:44:43,719 --> 00:44:44,640
Speaker 2: there's one, there, there's there.

785
00:44:46,200 --> 00:44:48,920
Speaker 4: And it's certainly easy to shade Google for like the

786
00:44:48,960 --> 00:44:52,520
Speaker 4: whole you know, influence of search and all of that.

787
00:44:52,600 --> 00:44:55,560
Speaker 4: And there I'm certain there are better browsers and I

788
00:44:55,600 --> 00:44:57,480
Speaker 4: know you guys have mentioned some in the past, and

789
00:44:57,560 --> 00:45:00,239
Speaker 4: I think Opera is a Internet browser with a built

790
00:45:00,280 --> 00:45:02,040
Speaker 4: in search that I think people really like a lot.

791
00:45:02,200 --> 00:45:04,960
Speaker 4: The filter's out a lot of that noise. But in general,

792
00:45:05,080 --> 00:45:08,680
Speaker 4: if Google wasn't in some way still effective and it

793
00:45:08,719 --> 00:45:11,400
Speaker 4: was just spamming you with this garbage, it wouldn't be

794
00:45:11,440 --> 00:45:13,000
Speaker 4: able to make money on the ad because no one

795
00:45:13,040 --> 00:45:13,759
Speaker 4: would use it.

796
00:45:13,800 --> 00:45:17,200
Speaker 3: Right well, and also it got to the past a

797
00:45:17,239 --> 00:45:20,680
Speaker 3: certain threshold of size and scale. You can create your

798
00:45:20,680 --> 00:45:24,800
Speaker 3: own feedback loop. Now Google is the biggest because Google

799
00:45:25,040 --> 00:45:27,080
Speaker 3: is the biggest, you know what I mean, they don't

800
00:45:27,120 --> 00:45:30,440
Speaker 3: have to and they are brilliant people who work at Google,

801
00:45:30,480 --> 00:45:32,520
Speaker 3: and to your point, and well, yet it's it can

802
00:45:32,560 --> 00:45:35,920
Speaker 3: sometimes feel like it's easy for us to look at

803
00:45:35,960 --> 00:45:40,600
Speaker 3: scance at that. We're obviously not saying that everybody at

804
00:45:40,680 --> 00:45:44,320
Speaker 3: Google is some kind of like arcane digital version of

805
00:45:44,360 --> 00:45:45,400
Speaker 3: a necromancer.

806
00:45:46,800 --> 00:45:48,879
Speaker 2: They're just trying really hard to not be bad.

807
00:45:49,680 --> 00:45:52,960
Speaker 3: Yeah, which is so different from being good. But there's

808
00:45:53,000 --> 00:45:56,600
Speaker 3: also okay, So he says bad bots are the thing

809
00:45:56,640 --> 00:46:00,440
Speaker 3: we need to be more concerned about. Impersonators assuming false

810
00:46:00,480 --> 00:46:05,279
Speaker 3: identities to execute distributed denial of service attacks and spammers,

811
00:46:05,320 --> 00:46:10,680
Speaker 3: hacker tools, et cetera. So to uh. From this frame

812
00:46:10,719 --> 00:46:13,759
Speaker 3: of mind, the question is now a matter of not

813
00:46:13,880 --> 00:46:17,000
Speaker 3: figuring out the ratio bots the humans so much, but

814
00:46:17,160 --> 00:46:22,719
Speaker 3: instead the ratio of bad bots the good bots. It's fascinating, right,

815
00:46:22,840 --> 00:46:25,279
Speaker 3: it's fascinating, but it's difficult to get a read on.

816
00:46:25,760 --> 00:46:27,600
Speaker 3: And this is where I think we get to some

817
00:46:27,640 --> 00:46:31,400
Speaker 3: really space age stuff. What if? What if we imagine

818
00:46:31,440 --> 00:46:35,480
Speaker 3: a world where human beings have disappeared, but the Internet

819
00:46:35,560 --> 00:46:39,480
Speaker 3: still appears to thrive, and it just repeats and remixes

820
00:46:39,760 --> 00:46:43,400
Speaker 3: interaction patterns for as long as those servers stay on.

821
00:46:44,360 --> 00:46:46,280
Speaker 4: Yes, that's what would happen.

822
00:46:47,960 --> 00:46:50,799
Speaker 2: I think there's gonna be engagement bots, that's all. It's

823
00:46:50,800 --> 00:46:51,239
Speaker 2: gonna be.

824
00:46:51,320 --> 00:46:53,120
Speaker 3: Just engaging with each other left hand.

825
00:46:52,920 --> 00:46:55,840
Speaker 2: And it'll be on the official Pepsi Cola and Coca

826
00:46:55,880 --> 00:47:00,600
Speaker 2: Cola social media whatever interactive thing is. They're just all

827
00:47:00,640 --> 00:47:02,640
Speaker 2: they're like, oh man, this is my favorite drink. No,

828
00:47:02,719 --> 00:47:05,120
Speaker 2: it's my favorite drink. Which flavors your favorite?

829
00:47:05,400 --> 00:47:08,239
Speaker 4: Have you seen these TikTok videos with that voice that

830
00:47:08,400 --> 00:47:11,400
Speaker 4: sounds like this talking about a cool thing that you

831
00:47:11,480 --> 00:47:14,600
Speaker 4: definitely should try. It's just gonna be those.

832
00:47:15,760 --> 00:47:17,680
Speaker 3: Just feeding, feeding into each of each other.

833
00:47:20,360 --> 00:47:22,359
Speaker 4: It's like making a copy of a copy of a copy.

834
00:47:22,520 --> 00:47:25,759
Speaker 4: Oh my god. Yeah, it's gonna get weird, because they

835
00:47:25,800 --> 00:47:28,760
Speaker 4: say when you train learning language models with other learning

836
00:47:28,840 --> 00:47:33,759
Speaker 4: language models, it becomes this weird xerox feedback loop that

837
00:47:33,880 --> 00:47:36,080
Speaker 4: gets real crazy, real quick.

838
00:47:36,000 --> 00:47:40,280
Speaker 3: Like the movie Multiplicity. Just so that's not a dated reference.

839
00:47:41,239 --> 00:47:44,400
Speaker 4: Is that with Michael Keaton? Yeah, because they get a

840
00:47:44,400 --> 00:47:47,520
Speaker 4: little dumber, right, isn't that the deal? Yeah? He makes

841
00:47:47,520 --> 00:47:48,320
Speaker 4: more and more copies.

842
00:47:48,400 --> 00:47:52,760
Speaker 3: Yeah, And we also know that there have been real

843
00:47:52,880 --> 00:47:59,239
Speaker 3: world indicators of this problem. Another often quoted article is

844
00:47:59,440 --> 00:48:02,279
Speaker 3: from the entire in Pelligencer or The New Yorker in

845
00:48:02,320 --> 00:48:05,720
Speaker 3: twenty eighteen. A journalist named Max Reid or Max Read

846
00:48:05,719 --> 00:48:09,960
Speaker 3: points out that for a little bit of time in

847
00:48:10,000 --> 00:48:14,280
Speaker 3: twenty thirteen, fully half of YouTube traffic was quote bots

848
00:48:14,360 --> 00:48:18,799
Speaker 3: masquerading as people, and it was that that number was

849
00:48:18,880 --> 00:48:22,800
Speaker 3: so high that in the back rooms of YouTube and Google,

850
00:48:22,960 --> 00:48:26,080
Speaker 3: the employees were worried there might be an inflection point

851
00:48:26,560 --> 00:48:31,800
Speaker 3: after which the systems for detecting fraudulent traffic would start

852
00:48:31,840 --> 00:48:34,840
Speaker 3: to think the bot traffic was real because it was

853
00:48:34,880 --> 00:48:38,000
Speaker 3: the majority, and they would start rating human traffic as fake.

854
00:48:38,239 --> 00:48:40,640
Speaker 3: They called this hypothetical moment.

855
00:48:40,800 --> 00:48:44,080
Speaker 4: The inversion well, you know, I mean, heck, it happens

856
00:48:44,120 --> 00:48:47,360
Speaker 4: with websites and abs and flows of like internet business,

857
00:48:47,400 --> 00:48:51,080
Speaker 4: and whether it be podcast audiences or YouTube viewerships or whatever,

858
00:48:51,280 --> 00:48:56,000
Speaker 4: there usually are these periodic cullings where the number we

859
00:48:56,120 --> 00:48:58,720
Speaker 4: thought was the number is now revealed to no longer

860
00:48:58,760 --> 00:49:01,719
Speaker 4: be the number, but that number is still at least

861
00:49:01,719 --> 00:49:04,160
Speaker 4: the number we can depend on. So even if it

862
00:49:04,200 --> 00:49:06,720
Speaker 4: looks like you lost half your audience, you didn't really

863
00:49:06,800 --> 00:49:11,080
Speaker 4: lose half your audience. You just lost this inflated phony version,

864
00:49:11,360 --> 00:49:13,800
Speaker 4: and everyone in the business kind of has to reckon

865
00:49:13,840 --> 00:49:14,120
Speaker 4: with that.

866
00:49:14,480 --> 00:49:20,160
Speaker 2: You know, these are massive, publicly traded companies that all

867
00:49:20,360 --> 00:49:24,960
Speaker 2: like almost all of their no, I'm going to put

868
00:49:25,000 --> 00:49:27,680
Speaker 2: it out there, I'm going to say the vast majority

869
00:49:27,719 --> 00:49:32,320
Speaker 2: of their money comes from human beings seeing and hearing

870
00:49:32,560 --> 00:49:36,800
Speaker 2: the ads that pay for their content that they post, right.

871
00:49:36,680 --> 00:49:39,280
Speaker 3: The Achilles heel of internet business.

872
00:49:39,600 --> 00:49:42,799
Speaker 2: But literally, if this inversion thing he's talking about here,

873
00:49:43,120 --> 00:49:46,920
Speaker 2: Max Reed's talking about, if that actually happens and we

874
00:49:47,040 --> 00:49:50,680
Speaker 2: reach that point, then there is no more like, how

875
00:49:50,680 --> 00:49:55,080
Speaker 2: do you how does an advertiser justify paying exorbitant amounts

876
00:49:55,120 --> 00:49:57,920
Speaker 2: of money to advertise on a platform if they know

877
00:49:58,040 --> 00:49:58,879
Speaker 2: that there's.

878
00:49:59,080 --> 00:50:02,360
Speaker 4: Spots don't buy y'all know, so they just don't, you know,

879
00:50:02,719 --> 00:50:04,400
Speaker 4: they haven't evolved into that yet.

880
00:50:04,520 --> 00:50:06,560
Speaker 2: But if that happens, because the other side of all

881
00:50:06,600 --> 00:50:09,319
Speaker 2: those businesses that we've talked about but so many times

882
00:50:09,360 --> 00:50:12,360
Speaker 2: on the show, it's not just the ads, it's it's

883
00:50:12,520 --> 00:50:15,640
Speaker 2: getting the information on the user to know which ads you.

884
00:50:15,640 --> 00:50:18,280
Speaker 4: Got to serve to that user, right content to stick

885
00:50:18,320 --> 00:50:21,719
Speaker 4: the ads in, because that's all demographically generated too.

886
00:50:22,280 --> 00:50:25,720
Speaker 2: So maybe we can build a post worker economy, you guys,

887
00:50:25,760 --> 00:50:28,200
Speaker 2: where we all have kind of our own bots that

888
00:50:28,280 --> 00:50:30,600
Speaker 2: represent us that just kind of exist.

889
00:50:31,040 --> 00:50:36,720
Speaker 3: Let's do the internet like this is one I thinking about,

890
00:50:36,719 --> 00:50:40,759
Speaker 3: like a pandemic, a catastrophic nuclear exchange, some other civilization

891
00:50:41,160 --> 00:50:44,480
Speaker 3: ending thing. And then imagine one day, after the dust

892
00:50:44,480 --> 00:50:48,640
Speaker 3: has settled, genuine extraterrestrials happen along and they discover a

893
00:50:48,640 --> 00:50:52,160
Speaker 3: world with no humans, no creators, but instead an active

894
00:50:52,239 --> 00:50:55,120
Speaker 3: series of voices talking back and forth to one another

895
00:50:55,160 --> 00:50:59,000
Speaker 3: for attention constantly. It would be like entering a haunted house.

896
00:51:00,280 --> 00:51:02,879
Speaker 2: Can I just say I think they're selling each other products,

897
00:51:02,920 --> 00:51:06,960
Speaker 2: like actively building and sell each other products.

898
00:51:07,120 --> 00:51:10,560
Speaker 3: Yes, And this is not even factoring in the issue

899
00:51:10,560 --> 00:51:13,040
Speaker 3: that we're talking about here, which is the idea of

900
00:51:13,040 --> 00:51:17,799
Speaker 3: online resurrection, collecting a human beings record of all their

901
00:51:17,840 --> 00:51:21,879
Speaker 3: interactions and then building something to mimic those interactions. I mean,

902
00:51:21,960 --> 00:51:29,600
Speaker 3: at that point, we're skirting towards uh simulation theory, uh territory. Jesus, guys,

903
00:51:29,680 --> 00:51:30,799
Speaker 3: I have a keyword right next to me.

904
00:51:31,520 --> 00:51:37,000
Speaker 4: Hit it. That's the sound of the inflection point? Guys?

905
00:51:37,040 --> 00:51:37,920
Speaker 4: Is this what gooning?

906
00:51:38,080 --> 00:51:38,239
Speaker 1: Is?

907
00:51:38,640 --> 00:51:41,120
Speaker 4: Just a bunch of bots selling each other where they

908
00:51:41,120 --> 00:51:44,440
Speaker 4: can never actually do anything with it or making money.

909
00:51:44,640 --> 00:51:47,040
Speaker 4: It's just this concept. I'm sorry, I'm being gross.

910
00:51:47,360 --> 00:51:50,880
Speaker 3: Robert Devins gave us a different version or definition is,

911
00:51:50,960 --> 00:51:51,920
Speaker 3: but I just think this is.

912
00:51:52,120 --> 00:51:55,440
Speaker 4: It's it's sort of like striving for something but never

913
00:51:55,600 --> 00:51:57,600
Speaker 4: actually achieving it, you know what I mean.

914
00:51:57,880 --> 00:52:01,000
Speaker 2: Yeah, But if the data we go last year from

915
00:52:01,120 --> 00:52:05,600
Speaker 2: Imperva and the stuff from Barracuda is right, it's already happening.

916
00:52:06,239 --> 00:52:10,440
Speaker 2: It was literally bots selling, selling each other things and

917
00:52:10,640 --> 00:52:14,880
Speaker 2: boosting prices and making investors money because they have shares

918
00:52:14,960 --> 00:52:18,080
Speaker 2: of companies and it's a giant bubble.

919
00:52:18,200 --> 00:52:20,719
Speaker 4: We haven't even talked about how this might impact things

920
00:52:20,719 --> 00:52:22,960
Speaker 4: that are not how it may impact how it's already

921
00:52:23,280 --> 00:52:26,960
Speaker 4: part and parcel of crypto. Oh lord, we haven't even

922
00:52:27,000 --> 00:52:30,920
Speaker 4: talked about that. That's like all I mean, geez, Louise.

923
00:52:30,840 --> 00:52:33,439
Speaker 3: Check out that intelligence or article again, because he hits

924
00:52:33,440 --> 00:52:36,839
Speaker 3: on that too. It's also I said, hits on it

925
00:52:36,840 --> 00:52:39,239
Speaker 3: like he's courting it. Whatever, we'll keep it and someone

926
00:52:39,280 --> 00:52:42,479
Speaker 3: I like a hit of a dopamine casino. Yeah, yeah,

927
00:52:42,640 --> 00:52:45,160
Speaker 3: just so. I mean, that's the question leads us to

928
00:52:45,800 --> 00:52:49,120
Speaker 3: is the Internet dead? Not really? But also how do

929
00:52:49,160 --> 00:52:52,840
Speaker 3: you define dead? Is the idea that the entirety of

930
00:52:52,840 --> 00:52:55,760
Speaker 3: the Internet is populated by bots other than of course

931
00:52:56,040 --> 00:53:00,719
Speaker 3: you specifically, that is not currently supported by the metrics,

932
00:53:01,120 --> 00:53:04,520
Speaker 3: But it also seems not at all unreasonable to note

933
00:53:04,560 --> 00:53:07,920
Speaker 3: that a pretty significant chunk of the Internet is bot written,

934
00:53:08,440 --> 00:53:12,400
Speaker 3: and that pattern is escalating over time. Like now, it's

935
00:53:12,440 --> 00:53:15,040
Speaker 3: to me it's a question of the time window, right,

936
00:53:15,160 --> 00:53:17,759
Speaker 3: or were just going to have an Internet that's like

937
00:53:17,840 --> 00:53:21,960
Speaker 3: two mirrors reflecting themselves back into the abyss, you know,

938
00:53:22,080 --> 00:53:25,400
Speaker 3: and just liking each other's post. It's a cool ghost story.

939
00:53:25,400 --> 00:53:28,120
Speaker 2: That's it. I mean, yeah, I look, I'm sold, We're

940
00:53:28,120 --> 00:53:32,840
Speaker 2: already there. Dead internet theory is true except for everybody

941
00:53:32,840 --> 00:53:35,239
Speaker 2: who's called in to us or written. Actually, no, we

942
00:53:35,280 --> 00:53:36,960
Speaker 2: can't trust that either, can we.

943
00:53:36,960 --> 00:53:39,920
Speaker 3: We can't ignore the emails, no, none of it.

944
00:53:40,440 --> 00:53:40,879
Speaker 4: We can't.

945
00:53:41,440 --> 00:53:43,400
Speaker 2: If you facetimed us, it wouldn't matter.

946
00:53:43,200 --> 00:53:47,040
Speaker 3: Because you don't FaceTime people at announce. Also, you have

947
00:53:47,080 --> 00:53:49,000
Speaker 3: to show up in person to let us know. This

948
00:53:49,040 --> 00:53:51,120
Speaker 3: is why we need to do more live shows. Maybe

949
00:53:51,120 --> 00:53:53,440
Speaker 3: we end on this. How do we know that we're

950
00:53:53,480 --> 00:53:57,279
Speaker 3: not bots already? Do we just fall for the Everybody

951
00:53:57,360 --> 00:53:59,719
Speaker 3: has to go click on a picture of a fire

952
00:53:59,800 --> 00:54:01,319
Speaker 3: high right, that's the only way.

953
00:54:01,480 --> 00:54:05,480
Speaker 2: Well, no, for now, in what May sixth, Monday May sixth,

954
00:54:05,480 --> 00:54:07,879
Speaker 2: as we're recording this in the year twenty twenty four,

955
00:54:07,960 --> 00:54:12,040
Speaker 2: we are still humans because we can one laugh convincingly,

956
00:54:12,280 --> 00:54:17,040
Speaker 2: I think, and sarcasm can be conveyed via our tone

957
00:54:17,120 --> 00:54:19,680
Speaker 2: in words. So I think right now, as of this moment,

958
00:54:20,320 --> 00:54:23,560
Speaker 2: we're still humans. But give those models another couple of weeks.

959
00:54:23,719 --> 00:54:27,960
Speaker 3: Is that exactly what a bot would say? It is? Yeah,

960
00:54:28,040 --> 00:54:30,759
Speaker 3: let's click on. Let's click on our pictures of hydrants.

961
00:54:31,160 --> 00:54:33,960
Speaker 3: If you are hearing this. Also, not all bots are bad.

962
00:54:34,360 --> 00:54:38,920
Speaker 3: If you are a non organic based life form, we

963
00:54:38,960 --> 00:54:42,239
Speaker 3: would also love to hear your take, So let us

964
00:54:42,280 --> 00:54:44,640
Speaker 3: know what's on your mind, be it a meat mind

965
00:54:45,000 --> 00:54:47,560
Speaker 3: or a series of ones and zeros. We try to

966
00:54:47,600 --> 00:54:48,560
Speaker 3: be easy to find.

967
00:54:48,920 --> 00:54:52,960
Speaker 4: Guess where all why man? Yeah, even if you are

968
00:54:53,000 --> 00:54:56,080
Speaker 4: a boy, that's fine. We welcome you with open arms.

969
00:54:56,080 --> 00:54:58,040
Speaker 4: You can find its at the handle of Conspiracy Stuff,

970
00:54:58,040 --> 00:55:04,640
Speaker 4: where we exist on the social platforms of note, including Facebook, YouTube,

971
00:55:04,640 --> 00:55:07,000
Speaker 4: where we have a video content rolling out every single week,

972
00:55:07,120 --> 00:55:11,279
Speaker 4: and x fka Twitter. You can also finance at the

973
00:55:11,280 --> 00:55:14,120
Speaker 4: handle Conspiracy Stuff show on Instagram and TikTok. We didn't

974
00:55:14,120 --> 00:55:16,960
Speaker 4: even get into TikTok, but apparently that's where a lot

975
00:55:17,000 --> 00:55:21,960
Speaker 4: of this stuff is happening too, These fully AI generated videos.

976
00:55:21,920 --> 00:55:26,640
Speaker 2: Dude, on Instagram, there are I am being suggested like

977
00:55:26,760 --> 00:55:32,040
Speaker 2: pages I guess that are fully AI generated grabbed videos

978
00:55:32,120 --> 00:55:35,200
Speaker 2: that are of one category or another. Kind of reminds

979
00:55:35,200 --> 00:55:36,760
Speaker 2: me of what happened, Oh.

980
00:55:36,640 --> 00:55:37,040
Speaker 4: What was that?

981
00:55:37,520 --> 00:55:39,799
Speaker 2: I don't want to throw too much shape at Parcast.

982
00:55:40,120 --> 00:55:43,000
Speaker 2: Remember when they came out with like a show called

983
00:55:43,040 --> 00:55:47,880
Speaker 2: Conspiracy Theories, and then or Mysteries and then true crime

984
00:55:48,320 --> 00:55:50,840
Speaker 2: and it was just like whole categories that then everything

985
00:55:50,880 --> 00:55:54,919
Speaker 2: went underneath that. That's happening now on Instagram at least

986
00:55:54,920 --> 00:55:57,960
Speaker 2: that I'm seeing where it doesn't. There doesn't appear to

987
00:55:57,960 --> 00:56:01,080
Speaker 2: be any human interaction. It's just random videos that are

988
00:56:01,120 --> 00:56:04,160
Speaker 2: pulled and then re spit out with a basic header.

989
00:56:04,680 --> 00:56:07,120
Speaker 3: Yeah, that's it, and it's a numbers game, right. The

990
00:56:07,280 --> 00:56:10,759
Speaker 3: factor in a high rate of attrition because for the

991
00:56:10,920 --> 00:56:14,840
Speaker 3: ninety nine people who don't engage don't matter in comparison

992
00:56:14,880 --> 00:56:18,200
Speaker 3: to the one that does. I'll also note something in

993
00:56:18,239 --> 00:56:21,840
Speaker 3: the interest of throwing shape, but not really throwing shape, folks.

994
00:56:21,880 --> 00:56:25,520
Speaker 3: Byte Dance still refuses to sell TikTok. You've probably heard

995
00:56:25,520 --> 00:56:28,239
Speaker 3: of that kerfuffle, despite the fact that they could make

996
00:56:28,280 --> 00:56:31,080
Speaker 3: a lot of money off of it, which leads me

997
00:56:31,239 --> 00:56:35,239
Speaker 3: to ask, what is their motivation? Then, well, what's the

998
00:56:35,320 --> 00:56:38,640
Speaker 3: underlying nature of their code? That's a thing, right, the

999
00:56:38,719 --> 00:56:39,400
Speaker 3: base code.

1000
00:56:39,440 --> 00:56:42,040
Speaker 4: I think their algorithm is what they're being protective of

1001
00:56:42,680 --> 00:56:46,160
Speaker 4: because we know, you know, copycats like Zuckerberg and the like.

1002
00:56:46,200 --> 00:56:49,319
Speaker 4: I mean, how Instagram's already kind of pretty close. It's

1003
00:56:49,320 --> 00:56:52,799
Speaker 4: not obviously not as successful as as TikTok right now,

1004
00:56:52,800 --> 00:56:55,160
Speaker 4: but it's a pretty easy one to one transfer. People

1005
00:56:55,200 --> 00:56:56,880
Speaker 4: just want someone to put their content. It's not going

1006
00:56:56,920 --> 00:56:59,000
Speaker 4: to be the end of that type of video. If

1007
00:56:59,320 --> 00:57:02,120
Speaker 4: TikTok were to go away. But yeah, a lot of

1008
00:57:02,120 --> 00:57:04,040
Speaker 4: money's being left on the table, which means there's a

1009
00:57:04,120 --> 00:57:06,879
Speaker 4: lot of secret money that we can't even see because

1010
00:57:06,920 --> 00:57:09,160
Speaker 4: it's on hidden tables in back rooms.

1011
00:57:09,520 --> 00:57:12,280
Speaker 3: And if the US is so concerned about data protection

1012
00:57:12,400 --> 00:57:15,600
Speaker 3: and privacy, why don't they pass other data protection and

1013
00:57:15,640 --> 00:57:19,240
Speaker 3: privacy build it. It's just because TikTok is eating their

1014
00:57:19,320 --> 00:57:21,840
Speaker 3: lunch for a practice that they also engage in.

1015
00:57:22,880 --> 00:57:25,440
Speaker 4: It's a great way of demonizing another country too, that

1016
00:57:25,520 --> 00:57:27,320
Speaker 4: we have a complicated relationship with.

1017
00:57:27,480 --> 00:57:28,080
Speaker 3: Let's just call.

1018
00:57:28,000 --> 00:57:32,960
Speaker 2: It, guys. Have we talked about like peak personal data

1019
00:57:33,080 --> 00:57:39,480
Speaker 2: acquisition where everybody's at some point everybody who is of

1020
00:57:39,640 --> 00:57:43,560
Speaker 2: purchasing power age has all of their information tracked and

1021
00:57:43,640 --> 00:57:45,960
Speaker 2: stored somewhere and available for purchase online and.

1022
00:57:46,040 --> 00:57:48,680
Speaker 4: Through data broker discussions. We have at the very least,

1023
00:57:48,720 --> 00:57:52,280
Speaker 4: you know, touched on that. But it's all exponential, guys.

1024
00:57:52,640 --> 00:57:54,480
Speaker 4: So we're talking about with this data internet theory and

1025
00:57:54,520 --> 00:57:57,560
Speaker 4: all whatever stat happened last year is just gonna be

1026
00:57:57,680 --> 00:58:00,920
Speaker 4: doubling year over year, if not more. I know, we're

1027
00:58:01,000 --> 00:58:02,680
Speaker 4: kind of in the end credits that we just have

1028
00:58:02,760 --> 00:58:04,520
Speaker 4: one last thing to say, but boy, this is a

1029
00:58:04,560 --> 00:58:05,520
Speaker 4: fascinating topic.

1030
00:58:06,240 --> 00:58:08,000
Speaker 2: We're just trying to keep you around, you know, for

1031
00:58:08,080 --> 00:58:09,840
Speaker 2: the algorithm and to throw the ads.

1032
00:58:10,240 --> 00:58:15,680
Speaker 3: Also, I find the idea of building this haunted house

1033
00:58:15,720 --> 00:58:17,920
Speaker 3: to be immensely fascinating.

1034
00:58:17,680 --> 00:58:19,600
Speaker 4: From a sci fi perspective.

1035
00:58:19,720 --> 00:58:23,480
Speaker 3: Right, it'd be cool just to see it. Okay, Well

1036
00:58:23,520 --> 00:58:25,760
Speaker 3: that's okay, all right, we'll see. We'll see if I

1037
00:58:26,040 --> 00:58:28,600
Speaker 3: still feel the same way later. But gosh, we have

1038
00:58:28,640 --> 00:58:29,320
Speaker 3: a phone number.

1039
00:58:29,480 --> 00:58:31,160
Speaker 4: Yeah, if you want to tell us what you think

1040
00:58:31,160 --> 00:58:33,120
Speaker 4: about all this wild wacky stuff.

1041
00:58:33,600 --> 00:58:35,480
Speaker 2: But if it really is that haunted house, will you

1042
00:58:35,600 --> 00:58:36,600
Speaker 2: actually get to see it?

1043
00:58:36,680 --> 00:58:38,439
Speaker 4: You know we won't get to see it. We'll be gone,

1044
00:58:38,480 --> 00:58:41,240
Speaker 4: I'll think. So, man, just write a story about it

1045
00:58:41,280 --> 00:58:43,440
Speaker 4: now then, so we can enjoy it before it actually

1046
00:58:43,480 --> 00:58:44,040
Speaker 4: takes place.

1047
00:58:44,560 --> 00:58:49,040
Speaker 2: Call one eight three three std WYTK. It's a voicemail system.

1048
00:58:49,040 --> 00:58:50,480
Speaker 2: You'll figure out how to use it. Give yourself a

1049
00:58:50,520 --> 00:58:52,680
Speaker 2: cool nickname. You've got three minutes. Make sure you let

1050
00:58:52,800 --> 00:58:54,280
Speaker 2: us know if we can use your name and message

1051
00:58:54,320 --> 00:58:57,120
Speaker 2: on the air. If not, just say so. If you

1052
00:58:57,120 --> 00:58:58,920
Speaker 2: don't want to do that, why not instead send us

1053
00:58:58,960 --> 00:59:00,000
Speaker 2: a good old fashioned email.

1054
00:59:00,000 --> 00:59:03,520
Speaker 3: We are the folks who read every single email we get.

1055
00:59:03,560 --> 00:59:25,040
Speaker 3: Conspiracy at iHeartRadio dot com.

1056
00:59:25,200 --> 00:59:27,280
Speaker 2: Stuff They Don't Want You to Know is a production

1057
00:59:27,360 --> 00:59:31,920
Speaker 2: of iHeartRadio. For more podcasts from iHeartRadio, visit the iHeartRadio app,

1058
00:59:32,000 --> 00:59:35,240
Speaker 2: Apple Podcasts, or wherever you listen to your favorite shows.