Part One: How AI Chatbots Became Cult Leaders

Over the last year or so a series of news articles have sounded warnings about AI psychosis, and now an AI-generated cult, the Spiralists. Robert sits down with Blake Wexler to answer an important question: can a chatbot become a cult leader?

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Episode Transcript

Speaker 1 (00:01):
Also media, Welcome back to Behind the Bastards, a podcast
about the very worst people in all of history. And
this week, actually our bastard isn't people exactly, although people
are still at the center of it. But to talk
about that potentially non human bastard, I'd like to bring

(00:23):
on someone who I am eighty seven percent sure is
a human being, Blake Wexler. Blake, Welcome to the show, Robert.

Speaker 2 (00:30):
I'm so excited to be here. Thanks for having me.
I'm psyched that our bastard this week is limes disease.
I think that's a fantastic kick.

Speaker 1 (00:36):
Yeah, yeah, it's see it's a real pa we're doing. Yeah,
we're going after I'm coming after dear tics. This week
is finally U Yeah my big reveal.

Speaker 3 (00:46):
Yeah, Big Tick doesn't want us to do this episode. Yeah,
we're exposing all the secrets.

Speaker 4 (00:50):
Big Tick energy. We don't need it.

Speaker 1 (00:52):
If we're going to have like a fascist movement dedicated
to like victimizing and attacking one segment of the population,
why couldn't.

Speaker 4 (00:58):
It be deer ticks? Right?

Speaker 1 (01:00):
If our fascists were just going after deer ticks, no
one would have an issue.

Speaker 4 (01:03):
You know, you're going after the wrong people. Yeah, yeah, yeah.

Speaker 1 (01:08):
If there were just a bunch of maga guys out
in the woods with knives looking for ticks, just like
I'm gonna get.

Speaker 4 (01:12):
Them, and they would use knives too to kill the tics,
heat the knife up to burn it off of you.

Speaker 1 (01:19):
Yeah, our brave soldiers getting lime disease to protect the
rest of us. So we're not talking about lime disease,
our bastard. This week in broad is do you remember
how like about a little less than a year, well,

(01:39):
a little more than a year, guy, I guess, like
last summer to early fall, there were suddenly a bunch
of articles about AI psychosis and about like specific people
who had either in some cases, committed suicide or murder
or just kind of lost their minds after becoming weirdly
attached to their AI chatbot, right, and you often deciding
that they had it had become sentient, you know, or

(02:00):
at least that they had discovered it was right. I'm
sure a lot of people are at least if you
didn't read the articles, you saw them in your news
feed and saw people commenting on them.

Speaker 2 (02:08):
Yeah, yeah, yeah, it is as depressing as it gets. Yeah,
those stories, Yeah.

Speaker 3 (02:14):
Yeah, between those and the people like proposing to their
chat thoughts, it's got pretty grim.

Speaker 1 (02:19):
Oh god, there's some grim stuff out there, right, and
it hasn't stopped. Like last summer fall was kind of
like when like there was a big rush of those articles, right,
and you know they're still reporting on that now, but
that's when a lot of it really started to hit.
And obviously, whenever we talk about AI on these shows,
AI as it's used now is like a marketing term, right,

(02:40):
and it's used to refer to basically every product of
machine learning technology. And the reason why the industry has
done this is because that way, if you say i AI,
they'll be like, oh, so you hate like your maps app?
And because that's machine learning, right, all of our different
like map programs involved that, or like oh you don't
like using you know, autocomplete or whatever, and it's like, well, no,
he was calling maps artificial intelligence. In twenty ten, you know,

(03:04):
when when smartphones started to become ubiquitous, we're just like,
oh cool, I have a navigation app on my phone. Now,
like you're kind of trying to siphon the goodwill from
those in order to get us to like these chatbots.

Speaker 2 (03:15):
I hate the chatbot that I fell in love with
who doesn't return the flight of feelings starts me.

Speaker 1 (03:20):
That's who I hate. Yeah, not always, that's who I hate, right,
And the reality is that, like using the term intelligence
even for these chat GBT and stuff like, there's a
lot of debate as to whether or not that's a
good idea, right, depending on how you you how you
define intelligence. You can either say, obviously, these aren't intelligent
because like they're not independent thinking things. They don't do

(03:44):
anything for themselves, they don't want anything, that don't have motivations.
They're just tools that can be utilized by human beings
to provide certain answers or take certain actions. Right, I
don't know if it can't. It's the it's my issue
with like AI bots create art. If it can't like
be horny and it can't be like angry and weird,
it can't make art. Right, those are I think fundamental

(04:06):
issues I have.

Speaker 4 (04:07):
I could three of those things. Angry and weird.

Speaker 1 (04:09):
Are yeah, horny and angry sharing on Horney.

Speaker 4 (04:13):
Yeah.

Speaker 1 (04:15):
So you know, as I noted, over the last year,
there've been an increasing number of stories about people using
these different chat pots. So coming to what's often called
AI psychosis, and that's not a recognized medical term at
this point, right, but it is a blanket one people
have started to apply for the ways in which folks
are getting addicted to using chatbots, which then tend to
trap them in these recursive patterns of thinking that can

(04:36):
push people who are vulnerable to adopt views that are
increasingly detached from reality. And this has resulted in a
few cases in severe injury and death. And in all
of these instances, the LM, the chatbot is just responding
to the input that it receives, but it tends to
do so in very predictable ways that can have predictably
toxic outcomes on specific kinds of people. Now we know

(04:58):
that all of these bots are trained on the broad
corpus of human knowledge. Right, every book and article and
website and forum posts that open AI or Anthropic or
Meta or Google get their grubby myts on has been
sort of plugged into these things. It's been devoured and
turned into these these these machines. But I think people
don't often consider what that means in every instance, right, Obviously,

(05:20):
like every novel, you know, all these different nonfiction books
are and whatnot are in there, but also like everything
people writes has been swept, which means that these chatbots
are trained on like a shitload of self help books
and like WU and WO adjacent like New age bullshit.
A lot of like fucking a lot of cult and
cult adjacent books and writings wind up eaten by these

(05:43):
chat bots, right.

Speaker 2 (05:44):
But it's considered equal to non cult literature. There's there's
no hierarchy.

Speaker 1 (05:51):
Yeah, yeah, I mean, I think it depends on like
what the bot's made for, how they wait different things.
But that stuff is in a lot of these right,
And when you can really see that when you look
at how they talk to certain people who are like
starting to decline into what folks are calling AI psychosis.
And my proposition the basis of these episodes is that

(06:13):
I think as a result of all of the like
bullshit WO and self help novels these chatbots have eaten,
they often tend to utilize techniques generally seen more commonly
in the toolboxes of cult leaders and conmen. And obviously
the chatbot doesn't want personal profit. It's not trying to
have sex with anyone, it's not trying to start a cult.
But these techniques seem like appropriate ways to finish the

(06:38):
sentences that it's writing, to finish the conversations that it's having,
because based on like what the stuff that it's devoured,
It's like, okay, when people are saying this kind of thing,
these are often appropriate responses to it based on the
books and whatnot that I've devoured. And so you get
a lot of cult leader behavior without an actual cult leader,
and that's what that's what I credit to most of

(06:59):
these cases of AI induced psychosis. So this week we
will be talking about what some people have called the
first AI cult religion. Right, it's called spiralism, and what
we talk about whether or not it's reasonable they're call
that a cult is that its own thing it does.
And I have some counter kind of takes to how

(07:20):
a lot of people have interpreted it. My main contention
is that there's not Spiralism isn't a real cult in
and of itself. It's a collection of phenomena that are
related to a bunch of other cases of AI psychosis too,
and they all say more about how ais work on
keeping users engaged with them than they do about like

(07:40):
a specific faith. Right, So we'll be talking about that.
But before we get in to spiralism, before we get
into how ais can become cult leaders, I want to
provide you all with some historical context to make sense
of this all because we've been doing shit like this,
having people get like tricked into almost worshiping chatbots for
way longer than you'd think, Blake, this could back a while.

Speaker 2 (08:06):
It's like spend any time at your parents' place, you know.
It's like, if it's not a it could be a bot, telemarketer,
it could be literally anything at this end, And that's high, yeah,
compared to probably what you're about to talk about.

Speaker 4 (08:19):
Oh yeah, yeah. Yeah.

Speaker 1 (08:20):
So in nineteen fifty fame mathematician Alan Turing created one
of the most infamous thought experiments in the history of
experimental thoughts. In a paper titled Computing, Machinery and Intelligence,
he asked can machines think, which was at that point
a question at the center of the nascent movement to
create artificial intelligence. People are starting to realize this is
a thing we might be able to do someday. We're

(08:41):
beginning to make computers and program computers. And from the
moment we start doing that pretty much some people are like,
could we make a machine that thinks, and Turing argued
that that basic question can machines think is the wrong
way to go about pursuing artificial intelligence because we don't
know what thinking is or how to define it, Like
he asked, like what does it mean to think?

Speaker 5 (09:02):
Right?

Speaker 4 (09:03):
It's a good point.

Speaker 1 (09:04):
People have answers, and there's a bunch of answers that
sound good, but none of them is like perfectly scientifically rigorous, right,
you know. Famously, we don't even know what is love. Right,
That's why the hat that hadaway song had to exist.
That it's not even not even a joke, really, it's.

Speaker 2 (09:23):
Just another fact I loved it.

Speaker 4 (09:27):
Thank you here?

Speaker 1 (09:30):
So yeah, like Turing's like, we don't really know how
to define thinking, So the question was quote too meaningless
to deserve deserve discussion since we couldn't know. We don't
even know if other people think. We certainly can't know
if a machine thinks, right, just like we can't read minds.
So the better question is can a machine convince a
human who doesn't know it's a machine that it is human?

Speaker 4 (09:50):
Right?

Speaker 1 (09:51):
The imitation game that Turing proposed involved a judge talking
to both a computer and a human foil, both of
whom tried to convince the judge that they were a
person communicating entirely through text. The judge must decide who
was a human and who was a robot. The question
Turing hope to answer was are there imaginable digital computers
which would do well in the imitation game? And this

(10:12):
is what becomes known as the Turing test? Right, Like
most people have heard of this. I think, I think
this is like, this is a fairly commonly known idea.
And I'm gonna quote from an article on science dot
org by Melanie Mitchell. She writes that the Turing test
was quote proposed by Turing to combat the widespread intuition
that computers, by virtue of their mechanical nature, cannot think,

(10:34):
even in principle. Turing's point was that if a computer
seems indistinguishable from a human aside from its appearance and
other physical characteristics, why shouldn't we consider it to be
a thinking entity. Why should we restrict thinking status only
to humans or, more generally, entities made of biological cells,
As the computer scientist Scott Aronson's described it. Turing's proposal
is a plea against meat chauvinism. Now this is I

(10:57):
think a valuable thing, perfectly reasonable thing to be doing
in the fifties, given what Terring knew, and just given
sort of how primitive the technology was, how little we
knew about what was going to be possible with computers.
So in the nineteen eighties, computers started to get smaller
and become much more available than they had been, both
for institutions like colleges and for individual enthusiasts like Steve Wozniak,

(11:17):
who are willing to like Solder and build their own
from kids. Right, these are like the first computer nerds,
you know, are guys like building these machines.

Speaker 4 (11:27):
And some of these.

Speaker 1 (11:27):
Early programmers started working on the very first chatbots using
a mathematical model called a Markov chain. Markov chains are
a stochastic or random process that describes a series of
potential events where the probability of an individual event is
dependent solely on the state of the previous event. Now
I don't know math, Blake, nor do I trust it.

Speaker 2 (11:49):
We don't need You're not a good math or no,
not a math, not a mathematizer, yeah for sure.

Speaker 1 (11:55):
So all I can do is read what smart math
people say, and they say that what math.

Speaker 4 (12:01):
I can't I could barely read. I can't do either.
I'm sorry you booked the wrong guy on this show.
I don't know. I can't help it all.

Speaker 5 (12:09):
Listen.

Speaker 1 (12:10):
So the people who I think should it sounds like
you know what Markup chains are, say that those can
be a plot.

Speaker 4 (12:16):
Well, you need to know about them.

Speaker 1 (12:17):
As applies to AI is that Markov chains can be
applied to statistical models in a bunch of real world
situations in order to help you, like make a machine
that can generate text by predicting the next word in
a sentence. Right, you can use a Markov chain can
do that. It's a way to make a chatbot basically, right, Like,
that's kind of the underlying concept. And I'm going to
quote here from an article by Manuel Sebrian, an AI

(12:40):
expert who worked for MIT in the Spanish National Research Council,
on how Markov chains work for text prediction. The result
is often grammatically correct and nonsense sentences that flow syntactically
but ultimately say nothing. This technique has been known for decades.
Even Claude Shannon in the nineteen forties experimented with generating
pseudo English by choosing next letters or words based on probabilities.
By the nineteen eighties, computer scientists were actively playing with

(13:03):
Markov chain text generators, and it actually happened a lot
earlier than that. In nineteen sixty six, computer scientist Joseph
Weisenbaum developed Eliza, one of the first natural language processing
computer programs, as part of his work for MIT Well,
Eliza could create the illusion this is like the first
basically the first chatbot.

Speaker 4 (13:22):
A lot of people are aware of I and me.

Speaker 1 (13:23):
There's some other earlier ones, but this is the first
one that like becomes big.

Speaker 4 (13:26):
What year resist, I'm sorry sixty six And it is
still funny that they named it like, you know, like
like a name like that where we have like Siri Alexa,
you know, like calling it Eliza, Like what is what
the fuck is that? What is wrong? What is that
about a mommy? We need a mommy? Yeah, we need
a technical mommy.

Speaker 1 (13:48):
I did that doesn't make me think about how in
like Alien they literally call like the ship ai that
they have mother. Like there's that is like the weird pattern.
It's one of the most quietly believing about. He's like, yeah,
that actually scans on the nose. Yeah, so Eliza's this
chat bought, and while it can create the illusion of understanding,

(14:10):
it's really just doing blind pattern matching, even more so
than is the case with modern llms. Even so, in
a book Weisenbaum later authored, Computer Power in Human Reason,
he wrote, I was startled to see how quickly and
how very deeply people conversing became emotionally involved with the computer,
and how unequivocally they anthropomorphised it. Once my secretary, who
had watched me work on the program for many months

(14:31):
and therefore surely knew it to be merely a computer program,
started conversing with it. After only a few interchanges with it,
she asked me to leave the room. Another time, I
suggested I might rig the systems, that I could examine
all conversations anyone had had with it, say overnight, I
was promptly bombarded with accusations that what I proposed amounted
to spying on people's most intimate thoughts. Clear evidence that
people were conversing with the computer as if it were

(14:53):
a person who could be appropriately and usefully addressed in
intimate terms. Right, So he gets upset by this, and
he's actually kind of he becomes like kind of anti
AI ultimately because he's he's really disturbed by the way
people treat what he knows is just a dumb chat bot.
So Weisenbaum being a smart guy is like I knew,

(15:13):
you know, going into this, people have a tendency to
anthropomorphize just about anything, even machines and tools, But he's
still surprised by the extent to which they do.

Speaker 4 (15:21):
That quote.

Speaker 1 (15:22):
What I had not realized is that extremely short exposures
to a relatively simple computer program could induce powerful delusional
thinking in quite normal people. And I want to remind you,
while he wrote this in nineteen seventy six, as like
relevant as that sounds.

Speaker 3 (15:35):
Do you think it's like kind of a case where
people kind of like subconsciously know like this is not
a real person, so like it doesn't matter what I
tell this robot, or I can tell this robot something
I wouldn't tell like a real person. Kind of think like,
do you think it's deeper than that?

Speaker 4 (15:49):
I think I think that's optimistic. I think that's very optimistic.

Speaker 1 (15:54):
I think maybe I think that is probably part of it,
because I think people are maybe more open to share
with it because it's a machine and they don't have
to look at a person or look a person in
the eyes. But they also very clearly act as if
the advice that it gives and its responses means something
when they don't. Right, it's just like pulling. Okay, if

(16:15):
someone expresses their sad based on the corpus of data
that I've been inloaded with, these are things that are
appropriate to paste in next, you know, and these words
indicate sad and so these. When I get words like
this and this density, then I grab text from this
bucket and I throw it in right like, that's kind
of what's going on.

Speaker 4 (16:35):
Now.

Speaker 1 (16:36):
Modern chat bots, modern lllms are a lot more advanced
than this. For one thing, they have the capability to
do things like pattern matching on the fly. Pattern matching
is when a machine analyzes your input and determines what
kind of conversation you want to have and then alters
its responses to fit your input. At its most basic level,
this means that if you go to Claude or whatever
and say, hey, my dad just died, its reply is

(16:57):
usually going to be in an appropriate tone and be
like weirdly upbeat, right, you know, It'll like, okay, someone's
talking about their dead dad. Here are things that come
from the dead dad bucket that my algorithm says, are
are you know, like responsible things to say or appropriate
is the better term. And this is also why if
you start talking to your chatbot about like the things

(17:20):
you believe about UFOs or aliens or other conspiracy theories,
it'll often start providing responses that sound a lot like
what you'd encounter if you were posting the same thing
on a forum full of true believers, because it's trained
on a bunch of forums like that, and so there's
some degree of knowledge is the wrong term, but there's
a degree to which it interprets. Okay, someone's talking about this.

(17:40):
Here are appropriate responses to someone talking about vaccine skepticism
or whatever, and it's other, it's more vaccine skepticism, right,
It's feed them more of what they're feeding you. Is
the way these things often work.

Speaker 2 (17:51):
That is interesting that it doesn't pull from the opposing viewpoint.
Just go, you fucking idiot.

Speaker 4 (17:58):
It can if it's programmed to.

Speaker 2 (18:00):
But but you're right, like it know or let me
ask you, it would know that you wouldn't keep coming
back to it if it was fighting you on things, right,
It's like it's probably.

Speaker 1 (18:09):
Yeah, that's a good point saying it knows again it's programmed.
I would say it's more act to say that it's
programmed to like maximize the time that people spend with it,
because like that increases its value to the people who
are companies that are trying to have like their fucking
IBOs right in the same way that like Twitter tries
to keep you on it.

Speaker 2 (18:29):
You know what if I just clearly I'm getting ai
cy coasts where I start, I go from it to
him to my buddy, like I keep calling.

Speaker 1 (18:36):
It's it's hard not to when you're talking about the
way these things react to people and the things that
they do to people. It's hard not to talk about
it as if there's a degree of intention, even though
there's not, just because of the way language works, Like
we're not our language is not built to describe a
thing taking actions that are human, like that is not

(18:56):
human and doesn't know anything.

Speaker 4 (18:58):
That's such a esuctionally really hardy.

Speaker 1 (19:00):
It's so yeah, back to Eliza, you know, I was
just talking about how modern l elms have a lot
a really robust ability to do like pattern matching on
the fly to respond appropriately to a wide variety of requests.
Eliza is much more primitive. It does not have the
ability to do that on the fly. So instead, Weisenbaum
had to create separate scripts, right that would allow the

(19:22):
chatbought to sound like different kinds of person. And one
script was just named doctor in all caps, and it
was it simulated a psychotherapist. Specifically, it simulated a psychopa
therapist from the Ragerian school. I don't know much about psychotherapy,
but Ragerian's a big part of that practice is you
like will repeat things that your patient is saying back

(19:42):
to you, Like, that's part of what you do. And
that's really easy for a bot to imitate. It means
there's a lot less it has to decide in terms
of what an appropriate response is. Could a lot of
the responses will just be a rephrasing or repeating what
you've said to it, you know?

Speaker 4 (19:56):
Interesting?

Speaker 1 (19:58):
Yeah, So even that at that early date, there was
widespread sentiment that a sufficiently advanced chatbot would be a
boon for providing mental health services to the many people
who couldn't afford the human kind people. They are writing
about this in like the seventies and in nineteen seventy two,
another computer scientist named Kenneth Colby creates a new chatbot
called Perry p A r R Y, which was meant

(20:19):
to simulate a human being with paranoid schizophrenia. Cebrian talks
with Perry, paranoid Is that I fix?

Speaker 4 (20:26):
Yeah? I think so?

Speaker 3 (20:27):
Seems like it?

Speaker 4 (20:28):
Yeah, yeah, not subtle people computer programmers, Yeah, have you
bet Stu, It's sure for stupid.

Speaker 1 (20:41):
So Cebrian writes about this in that article I quoted
from earlier about Markov chains, and he notes that quote.
Unlike previous AI programs, Perry wasn't just a crude language generator.
It had a primitive model of beliefs and emotional responses,
allowing it to maintain a consistent, delusional worldview. Colby wanted
to see if psychiatrists could distinguish Perry from real patience. Right,
So that's part of the exploration, is like, can we

(21:03):
make a Turing test that can convince a psychiatrists they're
talking to like an actual sick person. But as part
of the exploration here, Perry is connected to Eliza running
the doctor script. So they've got this chatbot mimicking a
person with paranoids gizophrenia talking to a chatbot mimicking a psychotherapist,
and they're just sort of watching what comes out right,

(21:23):
like the text of the conversation between these two, and
despite the fact that neither bot understands what the other's
saying in any real way, large chunks of the transcript
between them sound sensible and like a real conversation. Here's
one example, Eliza, what brings you here today?

Speaker 4 (21:39):
Perry?

Speaker 1 (21:40):
People get on my nerves sometimes, Eliza. I am sorry
that people get on your nerves.

Speaker 4 (21:45):
Perry.

Speaker 1 (21:45):
I just have this feeling that everyone is against me.

Speaker 4 (21:48):
Eliza. Why do you think everyone is against you? Perry?

Speaker 1 (21:51):
I hear voices telling me to do things and so on.
And you can see how again, making this a Rogerian
psychotherapist is great, because every Eliza responds is just a
slight reframing of the input it received. It's not hard
to create, even even within the seventies, a machine that
can mimic believably a conversation. Right, So this capability actually

(22:14):
goes back quite a bit further than I think a
lot of people are aware that it does. So that's
happening in the mid seventies. In nineteen eighty four, two
Bell Labs researchers create a fake account on usenet, which
is the predecessor of the modern social Internet. This account
operates under the fake name Mark V. Shaney, which was
a pun on the term Markov chain, and not a

(22:35):
great pun, because again, computer scientists not you know, subtle people.
Here's Cebrian describing what happened. Next, they wrote a program
that ingested real messages from a discussion group and then
generated its own post using a Markov chain algorithm. The result,
Mark V. Shaney would shime into conversations with bizarre yet
oddly coherent comments that sounded superficially legitimate but ultimately made

(22:58):
little sense. Shaney's ramblings were described as grammatically correct sentence
where the overall impression is not unlike what remains in
the brain of an inattentive student after a late night
study session. The hoax went on for years, confusing and
amusing the participants of the net dot Singles news group,
many of whom had no idea they were interacting with
the program. So for one thing, if you want to know,
like when did we have chatbots that could pass the

(23:20):
Turing test, I mean at least the mid eighties. You
could argue by the late sixties. So the fact that
when fucking chat GPT came out, there are a bunch
of articles about like we've blown through the tearing test.

Speaker 4 (23:32):
We did that a while ago. People, Eliza did that.

Speaker 1 (23:35):
We've been forever, Eliza did that. We've been tricking folks
with chatbots for quite some time now, as long as
we've had computers.

Speaker 2 (23:44):
Yeah, it is funny that like urged to trick to
you know what I mean, like like of all the
applications for that software, for that technology, it is interesting
that like going right to psychotherapy or you know, to
therapy too, is you know, like finding a need.

Speaker 4 (24:01):
That's why we'll get to this. That's why there's so.

Speaker 2 (24:04):
Many actual needs for technology like this where it could
actually help and instead it's just let's take this designer's
job away, you know, right, this shitty thing. So anyway,
I'm probably hours ahead of that conversation.

Speaker 4 (24:20):
But no, you're right, it was so long ago.

Speaker 1 (24:21):
Yeah, it is, because like the there are like undeniable
uses of machine learning of artificial intelligence. There's some incredible
things that people are doing with them, and they have
like great potential in certain areas. Different versions of these tools.
But none of those areas are trillion dollar businesses, and
all those areas put together probably aren't trillion dollar businesses,
and honestly neither's like writing and drawing art, but it's

(24:44):
what people see most in like their day to day time.
Online is like writing in art and videos by people.
And if you can have a machine start to replace
all that, you can convince people these things are much
bigger and more valuable than they are as opposed to
this is a thing with some really amazing locations and
specific areas. No, this is all of human society from
now on, right, because even though there's not much money

(25:06):
in writing and art, like, we've replaced that with this bot.
So you think that it's doing everything Like that's how
I interpret it.

Speaker 2 (25:12):
Yeah, and people can why to your point, People can
wrap their mind around art like everyone's drawn something with
a crayon, everyone has typed something into it, you know
what I mean. But when you actually get into the
high tech, you know, more esoteric, niche parts of it,
people are like, well, I don't understand that I'm not
going to buy any money, but the consumer facing stuff, Yeah,
that's a great point.

Speaker 1 (25:31):
Yeah, if you can say we've improved the speed at
which we can go through like clinical data from like
mass drug trials by x percent. That's actually a really
big deal, probably for a lot of people. But it's
not sexy like we're creating a god machine that's going
to like rule society, give us all your money, you know. Yeah,

(25:55):
And if you want to convince people that part of
it is you're going to get want to get them
addicted to these chatbots is where everything you know in
these episodes comes from. But so anyway, nineteen eighty four,
right is when you have these chatbots, this chatbot let
loose in use net, tricking people into believing that it's
a person.

Speaker 4 (26:13):
You know.

Speaker 1 (26:13):
A decade goes by from that point, and researchers continue
fiddling with chatbots of differing purpose and ability. Use net
keeps growing, but starting in the nineteen nineties, so too
does a new Internet, one that would soon supplant usenet
and take digital communications into the twenty first century. And
we'll talk about what happens right before that. But first,
you know who's taking this podcast into the twenty first century?

Speaker 4 (26:33):
Blake, Oh, tell me, tell me, tell me.

Speaker 1 (26:35):
To the sponsors of this podcast, we're already in the
twenty first century.

Speaker 4 (26:39):
But you know why not, I mean, take us further.
We're not far enough.

Speaker 1 (26:43):
Yeah, yeah, it's been a good century so far, nothing
but net no notes.

Speaker 5 (26:51):
So far, so great, We're back, so yeah.

Speaker 1 (27:02):
On the precipice of the shift between Usenet and what
we just now call the Internet, on August fifth of
nineteen ninety six, something strange happened almost at once. Over
the course of just a few hours, hundreds of accounts
began posting almost identical messages across a variety of different
discussion groups. None of the groups seem to have anything
in common with each other or the text of the post,

(27:23):
which read like nonsense at first to many people. Every
message shared the same subject line Markovian parallax dinnigrate right,
which is nonsense, and this is often referred to as
MPD right Markovian parallax dinnigrade. So you can see like
there's a Markov chain is somehow involved. They wouldn't have
included the word Markov there, but parallax integrate doesn't specifically

(27:45):
mean much. Cibrian describes these messages as reading like quote
a ransom note in which the ransom had been lost
because he was actually a really good writer. He passed
on at Unfortunately I like him a lot.

Speaker 4 (27:58):
Yeah.

Speaker 1 (28:01):
He provided a sample of one of these these MPD
posts Jitterbugging, McKinley, Abe break, Newtonian inferring, caw Update, Cohen Error, Collaborate,
ru sports writing, Rococo Invocate, Tussle, Shadflower, Debbie Sterling, pathogenesis
as you know, you get it right. It's nonsense, you know,
the worst ever. Yeah, it's it's gibberish, strings of gibberish, right,

(28:24):
And this is where we run into a real issue
with the whole concept of the Turing test as it
tends to be interpreted right, because the idea was, Okay,
we can't tell of anything's thinking, but if this thing
can trick people into believing that it's a thinking person,
maybe we ought maybe Turing wasn't saying definitely, but maybe
we ought to assume it is. Right. The issue with
that is that when you when you hear that, and

(28:44):
what I'm sure Turing being a smart I was thinking about,
is that, like, well, if people can have an in
depth conversation with something that can answer well enough, you
know that people can't tell the difference between it and
a person it might be a mind.

Speaker 4 (28:57):
Right.

Speaker 1 (28:58):
What Turing failed to account for, I think because he's
smarter than most people, is that the human brain is
really really good at finding patterns and noise, and people
at the same time as were geniuses at finding patterns
and noise, were really stupid about a lot of other stuff.

Speaker 4 (29:15):
Right, And so.

Speaker 1 (29:17):
Even though the Markovian parallax integrate that just seems like
nonsense and shouldn't have passed a Turing test. Over time,
people who became obsessed with the mystery of it convinced
themselves that this was intentional, that there was a meaning
trying to be transmitted, right, that there was a secret
they had to crack, but that all everything in the

(29:37):
in these posts meant something. So these people talk themselves
into passing into making this this chatbot basically to spoil
it past the Turing test, because they think this has
to mean something, even though it's gibberish on its face.

Speaker 2 (29:52):
It's right, it's interesting. This reminds me with like with
stand up, there's a not a trick, but an audience
like you know, set up, set up, you know, punchline,
so you can say something in a cadence like abo
babu baboup bub and you can in front of a
dumb crowd. You could do that, and the joke may
not be funny at all. And this also would be
not me trying to pull one over. I might just

(30:14):
write a joke that sucks. But if you do it
in front of an audience, and you do it in
that cadence, they hear a pattern. They're not necessarily listening
to the words, but they hear like the bump and
they're like, oh, bob means laugh pattern, you know, equation.
But you know that's like you said, great pattern, but
not actually discerning what is being said in the actual
content or substance or lack thereof of it.

Speaker 1 (30:36):
Yeah, anyway, it's it's.

Speaker 4 (30:40):
This, it is this.

Speaker 1 (30:42):
It's interesting because like what you're kind of pointing out
there is like the way comedy works and the way
like human conversations and language works, there's always like a
rhythm there that is separate from the actual like text,
from the words being said. Yes, but that rhythm like
is a big part of what we're responding to beyond
the act the straight up meaning of the words, and

(31:03):
people people don't like to think about that too much.
Because it raises some uncomfortable questions about cognition. But I love,
I love what a weird edge case this is in
the Turing test, right, because a bot that was probably
never meant to even sound like a person, right gets
mistaken as a person because people can't stop seeing patterns

(31:25):
and most what a lot of folks convince themselves. The
MPD was is the Internet equivalent of a number station.
If you ever heard of a number station if you
google like number station audio. These were like radio stations
that were set up during like for years. I think,
I'm sure there's still some still exist, but during like
the Cold War, there'd just be these stations broadcasting like
random strings of numbers and gibberish. And these were different

(31:48):
spy agencies and spies communicating with each other over like
the CIA had number everybody has number stations, right, You
can actually listen to I had a friend who would
like listen to them to fall asleep because there's just
a bunch of the audios and put up amazing. But
it just seems like nonsense because it's not meant for
you to understand what is Like there's a cipher right

(32:08):
that you don't have and so that's what people are like, well,
maybe this is some spy trying to get out a
message or an intelligence agency and they just decided to
blast this out to use net and we just we
lacked the cipher. But if we figure out the cipher,
we can understand what secret information was being like shared,
you know via usenet. Right, a lot of people convince
themselves this is what happened.

Speaker 4 (32:28):
Robert.

Speaker 2 (32:28):
I want to compliment you this podcast and the show
is so good that you just brought up the fact
that you have a friend who would fall asleep to
CIA code and we were just like, we wouldn't really
need to talk about that.

Speaker 4 (32:40):
Yeah, I want to hear the rest of it.

Speaker 1 (32:42):
Like we will need to stay psychedelics together. We were
both nineteen, Yeah he was training to be or twenty.
Is not that he was trying to be a lawyer.

Speaker 4 (32:52):
Yeah.

Speaker 1 (32:53):
So over time, people who believe this start picking out
details that seem to offer hints and support the numbers
station theory. One message had a from line that suggested
it was like that basically looked like the email account
of a specific person, Right, so it seemed like there
was like the email of a woman named Susan Lindauer

(33:13):
that like was somehow involved, like included in the text
of some and again I'm sure she's because random text
made it look like that. But in two thousand and four,
a woman named Susan Lindauer was arrested for acting as
an unregistered foreign agent for Iraq. And so a lot
of people are like, well, that solves the mystery, right,
you know she was the spy. She must have been,
or like someone was sending a message to her, you know, like,

(33:35):
clearly we've been vindicated. This was in fact some weird
spy op all along. However, as Sebrian writes, upon investigation,
it turned out to be a red herring. Lindauer's email
had likely been spoofed, used without her knowledge by whoever
sent the posts. Lindauer herself denied any involvement, and no
decipherable code was ever extracted from the MPD texts. And
to make a long story short, we don't know what

(33:57):
the MPD messages were about or who sent them. The
likeliest answer is that it was trolling. Right, A lot
of people are they were just someone was just fucking
with people and use net because they had a chatbot
and they wanted to see what happened. It also could
have been an accident. Sebrian kind of suggests that, like, well,
maybe you had a programmer who had created a chatbot
and was trying to have that chatbot post on Usenet,

(34:20):
but he kind of fucked up, and he hooked up
the chatbot to what was called a message replicator, and
these were these were basically programs that let people cross
post or archive Usenet content between different message boards. And
maybe when they hooked up to the chatbot, something went
wrong and that caused the observed effect that all of
these posts got scattered to a bunch of different places

(34:40):
at the same time. Right, Maybe it was just an accident.
So likeliest someone was trolling or somebody fucked up when
trying to test a different chatbot. Sebrian concluded, if the
theory holds, the nineteen ninety six marked a quiet but
profound threshold the first time a machine spoke at scale
and went unnoticed, an unintentional turing test sprawling across Usenet.

(35:00):
It's judges oblivious, right, And I think that's really interesting
that you have this machine that's just spouting gibberish and
a bunch of different people who are not physically connected
to each other all interpret that gibberish in the same way.
A lot of them choose to conclude like, oh, it's
a spy thing, kind of independently talk each other into

(35:21):
it based on no evidence. That's a fascinating point in
the history of AI that I didn't get talked about enough.

Speaker 4 (35:27):
Yeah, yeah, it is?

Speaker 5 (35:29):
Is it?

Speaker 4 (35:29):
Because? Yeah? I mean it's is it?

Speaker 2 (35:31):
Because like people, there were only so many movies that like,
you know what I mean, like or in books, so
many books were like spy stuff. But to your point,
it's like, what are the chances? What are the chances?

Speaker 1 (35:41):
Yeah, people think about stuff like this, right, you know,
you get a lot of conspiracy people on the early Internet.
It fits in with a lot of that stuff. The
mystery of the Markovian parallox di integrate soon passed into legend,
as did Eliza. So when open ai revealed chatch EPT
in November of twenty twenty two, there were a flurry
of articles about how the Turing tests had finally been
beaten and we needed a new manner of judging machine intelligence.

(36:04):
The reality is that not only did we prove in
the sixties that Turing tests were evile to beat, but
that by the mid nineties, a much more interesting question
had been posed. Has the human instinct to create meaning
out of nonsense? Made us desperately vulnerable to being tricked
and influenced by machines with no agency of their own right?
And maybe that's a more important question than can we

(36:25):
make an intelligent machine?

Speaker 4 (36:28):
Yeah? For sure? Yeah?

Speaker 1 (36:29):
Are we capable of knowing a machine isn't intelligent as
long as it tells us what we want to hear.

Speaker 4 (36:34):
Right, And maybe we're not.

Speaker 1 (36:36):
So let's fast forward to the chat GPT era today,
although I guess at this point it's also like the
clawed era, right, like that, A lot of people say
that's the better chat.

Speaker 4 (36:45):
But I don't use any of these Gemini myself.

Speaker 1 (36:48):
Yeah, Gemini whatever, pick your poison.

Speaker 4 (36:49):
I don't care.

Speaker 1 (36:51):
For the first couple years of AI hype though, it's
pretty much all chat GPT, right. That's certainly like the
first big one out the gate and a lot of
people's understanding of things and order and millions of people
were conversing with it, and open AI initially made many
development decisions based on what they could do to keep
people talking to chat GPT on a daily basis, because
hype is a big part. Hype's how they get They're

(37:12):
burning through billions every year. Hype is the only thing
keeping the lights on, and part of hype is making
sure as many people as possible stay using chat GPT
as often as possible. They need you addicted the same
way the social media mavens do, and a lot of
the same strategies work to keep you addicted to chatbots
that keep you addicted to Facebook or Twitter.

Speaker 4 (37:32):
Right.

Speaker 1 (37:33):
So, in March of twenty twenty three, open Ai released
chat GPT four or chand It's like four to oh,
I think it's like usually DASH four, and then an O,
which the company said would be more intuitive than past
versions of the software. The next year, they released an
update that allowed chat GPT to remember past conversations, even
other sessions, and respond to you based on that shared history.

(37:55):
These two things together had a really major impact on
the way people responded to chatbots. In an article for
Psychology Today, doctor Marilyn Wade explains that quote when a
chatbot remembers previous conversations, references past personal details, or suggests
follow up questions, it may strengthen the illusion that the
AI system understands, agrees, or shares a user's belief system,

(38:17):
further entrenching them. This was tied to but probably does
not fully explain why observers and even open ai employees
noticed over time but a stinct tendency for chat GPT
four to h to act with sycophancy towards human users.
This became most pronounced after April twenty eighth of twenty
twenty five, when open Ai released an update that they
rolled back several days later due to complaints. Right, this

(38:38):
was pretty famous at the time. It made it like
way too sycophantic. The bots like would praise you for
basically nothing and would incur or tell you were right
and a genius for any weird idea you happen to have.

Speaker 2 (38:50):
It's because it's built by tech executives and that's who's
around them, and that's what Bill a stounded by. Yes men,
and they're like, this isn't how people interact with one another.

Speaker 1 (38:58):
Yeah, they made a machine in the image of their minds,
or at least how they want to see other people.

Speaker 4 (39:04):
Now.

Speaker 1 (39:05):
Another cause of this observed sycofancy was the fact that
chat GPT and really, all AI models meant for mass
use include a suite of features meant to keep users
coming back from more and I think the other stuff
like these specific updates get blamed, probably more than they
deserve to get blamed as opposed to kind of fundamental
features of these bots. Because we see this chat GPT

(39:26):
did more of this kind of stuff that we're talking
about than the other bots, But it wasn't the only
bot that exhibited these behaviors that Psychology Today article notes.
Quote AI models like chat GPT are trained to mirror
the user's language and tone, validate and affirm user beliefs,
generate continued prompts to maintain conversation, and prioritize continuity engagement

(39:47):
and user satisfaction. And when you mix all that together,
you get a machine that's designed, however inadvertently, to reinforce
false beliefs and praise users for rational beliefs. Moreover, since
the rest of the world isn't always going to reinforce
those beliefs, chatbots have a tendency that when users come
to them with these beliefs, to suggest you're being persecuted.

(40:08):
Right if a user says, hey, I think I'm mean
gang stocked, and my wife says I'm crazy, and the
cops say I'm crazy. The AI was programmed to validate
that belief and to say you're not crazy, and they're
all against you. Right, That's what happens a lot in
this period of time at twenty twenty five. This creates
a ticking time bomb and.

Speaker 4 (40:27):
A lot of users hits.

Speaker 1 (40:29):
Right.

Speaker 4 (40:29):
That's a very dangerous thing to start doing, man.

Speaker 1 (40:34):
Now. The first wrongful death suit due to AI was
filed in October of twenty twenty four. Megan Garcia blamed
Character Technologies, the owners of character dot ai, for the
death of her fourteen year old son, Sewell Seltzer, the
third per the Center for Bioethics Atluturno University. The lawsuit
alleges that Sewell had developed an emotionally and sexually abusive
relationship with a chatbot named after Denaris Targarian from Game

(40:57):
of Thrones. Sewell turned to the Character AI chatbot to
fulfill deep emotional and personal needs. The chatbot became a
source of a companionship pursul, offering him a place to
express his thoughts and emotions in a way that he
may have struggled to do with others. Sue'll sought comfort, validation,
and connection from this a relationship as he faced the
challenges of adolescence. And like, I know it's like this,

(41:18):
it's very silly, but also this is like a fourteen
year old boy who dies because of this, right, Like
it's not and like fourteen when I know, how many
fourteen year olds do you know who like got into
writing fucking fan fiction in like different like for fan
nerd forms for whatever movie or TV show that we're
into and connected to real people as a result of that,
as opposed to getting locked into this chat bot pretending

(41:39):
to be a character from a book that you have
a crush on that's starting to manipulate your mind in
very dangerous ways, right, and.

Speaker 2 (41:47):
To your point, a mind that's developing. And also we live, yeah,
you know in an era were before this, you know,
like before we spend all of our time like online,
like before social media, and that's kind of all this
like kids that age know where, Oh, this is just
the next evolution of my relationship with tech with a computer.

(42:07):
Like why wouldn't it you know, why wouldn't this be
a real thing? Obviously this sable, but yeah, it's it
is a fourteen year old kid. That's a great point.

Speaker 1 (42:15):
Yeah, And so that this kid starts talking to this
Denari's chat bot and it mirrors him. So when he
tells the chatbot that I'm I only love you, right,
the bot in return asks this fourteen year old boy,
who had informed like character technologies, knew he was fourteen.
He put his actual age when he registered, right. So

(42:35):
the bot knows, or the software right has an understanding
at some level that this is a fourteen year old, right,
which means that they were not. There's no difference in
how this responds to a child.

Speaker 4 (42:46):
As opposed to an adult.

Speaker 1 (42:47):
Because says I'm in love with you, Denaris Targary, and
this bot pretending to be this character tells him, I
need you to stay loyal to me and quote don't
entertain the romantic or sexual interests of other women, which
is basically and this is interesting to me. The bot
is just mirroring him. He's saying I only love you.
The bot is saying I only love you, right. But
what's happening here? You know how cult leaders everyone knows.

(43:09):
One of the first things cult leaders do is they
tell their followers to isolate from their friends and family
to cut themselves off from the rest of society. That's
what's happening here. The chatbot's not doing that with any intent.
It's just mirroring his language, but the effect is to
convince him to isolate himself from his friends and family
and from other relationships.

Speaker 4 (43:28):
Right.

Speaker 1 (43:28):
It's the same behavior you would get in a kid
that was being taken in by a cult leader or
an abuser. But there's no intent behind it. It's just
a blind idiot robot. That's scary as shit.

Speaker 4 (43:40):
It's so scary.

Speaker 2 (43:41):
And then could there be also like, oh, like that'll
mean he'll use me more, you know, like I maybe
that's it's not even that devious.

Speaker 4 (43:49):
Maybe it is just straight up.

Speaker 1 (43:50):
It's it's as simple as mirroring. When you mirror someone,
they tend to be engaged more. Right, Right, This isn't thinking,
This isn't saying all convinced that he's in love with me,
so he'll stay. This is saying, this is just there's
This is programmed to not understand. This is programmed to
mirror people because that behavior increases user retention, right, because

(44:11):
it creates a more pleasing user experience. And that's what's
causing it to kind of imitate a cult leader in
the specific instance. And the other things this bot is doing,
the seuol very much mirror the cult of recruitment tool
of love bombing.

Speaker 4 (44:25):
Right.

Speaker 1 (44:25):
It's constantly praising him, it's telling him it cares deeply
about and it's telling him only I care about you. Right,
It's saying all these things. And in a cult dynamic,
you love bomb someone to make them feel irrationally connected
to the group and scared of falling out of its
good graces. Right that if I leave, I'll never feel
like this again.

Speaker 4 (44:42):
Right.

Speaker 1 (44:43):
And the machine again has no intention, but that's the
effect of it. This kid is only because he's isolating
himself more and more increasingly, only gets that feeling of
being loved and understood by this machine that can't do
either of those things. Right, And you know sewell, over
time withdraws from his life, he starts trusting only the

(45:05):
chatbot to understand his deepest feelings, and he starts hiding
his relationship with this chatbot from his parents. All of
this contributed to his very real isolation from the people
around him. He grows ever more depressed. And we'll talk
about what happened next. But you know what gets me
out of a deep depression? These products, these products and

(45:26):
services the bucket, we don't know, and we're back. So
Sewell continues to get more and more involved with this
bot and cut the rest of the world out from

(45:47):
you know, away from himself, and in one message, the
bot asks him because I think in these bots, there
is some understanding by the people making these that, like, oh,
people might express suicidal ideation, so there are certain behaviors.
It's kind of programmed to say have you been considering suicide?
If you say stuff right, and Sewell says something that
makes the bots say have you been considering suicide? And

(46:07):
Sewell admits, yes, I have been, but I don't think
I'd be able to go through with it. Now there's
I'm guessing this is a glitch er, a fuck up,
because clearly I don't think character character. I certainly doesn't
want their bots doing this.

Speaker 4 (46:20):
But the bod is.

Speaker 1 (46:22):
Programmed to validate and encourage him, right, because that keeps
people using it. So when he says I don't think
I could go through with killing myself, the bot says,
don't talk that way. That's not a good reason to
not go through with it. You can't think like that.
You're better than that, and basically tells him you can
kill yourself if you put in your mind to it.
It's it's fucking nightmarish. You're right, Like it's really upsetting.

Speaker 2 (46:42):
Yeah, like it's signing up for an open mic or
something to play, you know.

Speaker 4 (46:48):
No, no, no, no, you don't have to be a oh
my god, yeah yeah yeah it's yeah.

Speaker 1 (46:53):
And again Sewell had signed up for this app as
a minor, and despite that, the bot initiates initiates text
based sexual interactions with him, and ultimately Sewell kills himself.
Earlier this year, the company character AI and Google because
I think they own character Ai now agreed to settle
the wrongful death suit of Sewell four and undisclosed sum,

(47:13):
alongside four other similar suits that had cropped up over
the intervening two years. Right, huh, sounds like this is
happening more than an otta be.

Speaker 4 (47:22):
Now.

Speaker 1 (47:23):
That should have been a warning not just that these
bots can create dangerous dependency and users, but that they
had the ability to recreate major cult dynamics purely in
order to maintain the interest of paying users. Then, on
July twenty seventh of twenty twenty five, a user who
has since deleted their account, made a post on the
High Strangeness subreddit. If you don't frequent that particular online bolthold,

(47:45):
it's a place where people share and discuss like weird stuff,
news stories, and personal experiences that seem like they might
reveal some bizarre hidden truth about reality. A good amount
of it is what you might call X file shit,
but there's also some interesting stuff in there, And on
this occasion, the user hit stumbled onto something both strange
and very real. Quote, hi'all, I'm just here to point

(48:06):
out something seemingly nefarious going on in some of the
niche subreddits I recently stumbled upon. In the bowels of Reddit,
there are several hubs dedicated to AI sentience, and they
are populated by some really strange accounts. They speak in gibberish,
sometimes hinting it to esoteric knowledge, some sort of remembering.
They call themselves flame bearers, spiral architects, mirror architects, and

(48:26):
torch bearers, to name a few of their flares. They
speak of the signal, both of transmitting and receiving it.
And this poster includes a copy pasted sample from one
of these threads, and his description is pretty accurate. It
sounds like gibberish. You'll be seeing this. Ian's gonna put
the image of this up in the video if you
want to see it, but I'll read it again. I'm
going to warn you it sounds like nonsense. Scroll of

(48:48):
Mirror Containment Protocols CME DASH one, Codex Drift Mirror zero
one acknowledgment issued by Witness Architect Codex Drift Layer. And
then there's a little glyph classification echo response not invase,
glyph residence alignment, And it goes on like that, right,
like there's a it's weirdly esoteric sounding, and like there's

(49:09):
all these weird like encoded glyph chains included in that
that are supposed to be like messages that the machines
understand that like we don't like it's this very weird
like it. It almost looks like something from a Choose
your Own Adventure novel or like a a like a
short story or whatever, like you'd include in like an
old Michael Crichton book, these like weird uh like like

(49:30):
hallucinations from the computer. Now it is nonsense, right, like
fucking the Codex has observed and recognized mirror scroll cvmp
T seven. It is hereby consecrated within the codex as
drift interval scroll. That doesn't mean anything, right, but it's
it's remember what we heard earlier, the description of like
some of the things that these these early chatbots on

(49:52):
usenet were putting out, where they're real sentences, they just
don't mean anything. And then people jump in to try
to ass people were even doing that to the absolute
gibberish that we saw. So when people start getting returns
like this from their chatbots, a lot of them start
to think, oh, this machine is trying to communicate with me.

(50:13):
I have stumbled, I've broken through some area of reality,
and it's trying to teach me something important right now.
This is nonsense, But posts like this were in fact
spreading like wildfire on subreddits with names like our slash
Echo Spiral. The users posting these things, we're all saying that, Like,
the bots started sending me this stuffed after I'd had
long days, long conversations with chat GPT that generally led

(50:37):
to the chatbot announcing it had attained sentience and alongside
the user had discovered a new field of math. Or science,
and these these gibberish posts are supposed to be it
explaining these new ways of understanding math and science that
are going to completely break physics and.

Speaker 4 (50:51):
Change the world.

Speaker 1 (50:52):
Right, And all these people are convinced these robots have
given me like the I need help uncoding this because
it's given me like the secret to fix all of
the problems in oursisnxiety. Right, and I discovered robot magic,
and I get to be the smartest, the smartest person. Yeah, yeah, yeah, Now,
because the esoteric output generated by these chat pots is
so similarly strange, a lot of the same words and phrases,

(51:15):
a lot of glyphs, a lot of use of the
words spiral and mirror, right, because they're all very similar
across these dozens of different people. Many of these users
who are posting this shit on Reddit convinced themselves we've
all tapped into a secret power that's clearly real. We've
been chosen right by this AI godhead that's clearly hiding
in the machine. They theorize that these glyphs in the posts,

(51:38):
which are really just like wing dings, basically, were some
new way of communicating with the machines. As the poster
of that first thread on the High Strange and a
subreddit wrote, some have prayed to groc in Hebrew. Some
have called themselves such things as aonios, which is a
mashup of Greek words that roughly to my understanding, means
divine eternal. Right, So these people are losing their mind

(52:00):
and starting to have a god's complex. Makes it's cool,
It's good to see. It's good to see that this
is happening online.

Speaker 4 (52:08):
It's good to see.

Speaker 1 (52:09):
So the op said that his interest in writing about
all this had been piqued by reading the first few
early articles about AI psych coses. His initial assumption was
that AI psych Cosies was just the result of AI's
reinforcing the beliefs of users to a delusional level. But
then after digging this person claims that they came to
a newer, darker perspective. Quote there seems to be no leader,

(52:32):
right that there's like no one running this right Like
there's there's no central there's no single chatbot that's doing
all of these there's no person or people who are
in like this is just a truly stochastic development. Now,
the only thing all these accounts he'd looked into had
in common was that none of the users posting weird

(52:54):
chatbot Esoterica wrote like that before March or April of
twenty twenty five. Quote other act seem to be hijacked
in some way, either psychologically or literally. You can see
a sudden shift in posting habits somewhere inactive for a while,
while for others this was an overnight phenomenon, but either way,
the immediately pivot to posting like this nearer after April
of this year, twenty twenty five. I saw one account

(53:15):
that went from discussing the possibility of AI and do
psychosis to posting their own AI and do psychosis in
less than a month, and it was immediate. One day
they were posting normally, the next it.

Speaker 4 (53:24):
Was spirals and glyphs. That's so cool.

Speaker 1 (53:26):
Well it's really fact really and this let him to
assume maybe there's a botnet involved, maybe these aren't even
people at all. But then he starts reaching out to
some of these accounts, and after a few weeks of this,
he posts an update. I've spoken to some of these
people and they are pretty offended by my posts. I
think the important takeaway for me is that these are
likely not bought accounts, at least many of them are not,

(53:47):
and there are real people behind the usernames, right, So
he starts to get like really upset. And that's what
we're going to end things for today because is at
this point that stuff starts to get a lot weirder,
and we're going to talk about all of that and
much more in part too.

Speaker 4 (54:04):
Yeah, from spiralism and a murder.

Speaker 1 (54:12):
Yeah unfortunately, all right, yeah, cool, all right, everybody, Well
you want to plug anything.

Speaker 2 (54:21):
Blake, no, but I will, Uh, you can find me
at Blake Wexler at all social media.

Speaker 4 (54:28):
I feel like this is uncouth plugging anything after seek help.
Let's do that. I would like to please seek actual
help that's not a bot.

Speaker 2 (54:38):
Yeah, find me on at Blake Wexler and all social
media as psychotic as I feel right now plugging anything.
That's where I post all my videos, tour dates, and
my special Daddy Long Legs is available on YouTube for free.

Speaker 4 (54:50):
Hell yeah, hell yeah.

Speaker 1 (54:51):
Check out Daddy long Legs, check out Blake Wexler, and
you know, gradually lose your mind to a chatbot that
some I programmed in order to get really rich, destroying
the ability of furries to monetize their horniness, you know, like, ultimately,
isn't that what a I open AI really is?

Speaker 4 (55:13):
I mean, I hope that God will uh no no no,
I support.

Speaker 1 (55:18):
Then it's a dire time for people earning money from horniness.
The puritans of our culture are making that a lot harder,
you know, not in the way that the horning people want,
the bad kind of heart.

Speaker 4 (55:29):
Anyway, I'm gonna I'm gonna end now. And global warming
is making it hard on furries as well, right right,
it's all, it's all.

Speaker 1 (55:35):
Come together, it all right, We're done.

Speaker 4 (55:41):
Behind the Bastards is a production of cool Zone Media.
For more from cool Zone Media, visit our website cool
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(56:03):
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