Instead of people opening up and accepting more ways of recognizing human beings, what
they do instead is apply the machine frameworks to the humans, and they dehumanize more often
than they expand humanity.
And that's really, really dangerous.
It has real implications because once we start to think, "Oh, I know what human is,"
it's not X, Y, and Z, and you, person I am suspicious of, are displaying X, Y, and Z.
You must not really be human.
You don't count the same way.
Welcome to the Repatoning Podcast, where we believe your mind-body system is your domain,
and that choosing the beliefs, habits, and patterns that best support you is your birthright.
I'm your host, Arden Leigh, creator of the Re-Patterning Project, an eight-week course in learning
to free yourself from the patterns of your past and program your mind for your dreams
of the future.
Join me for these extraordinary conversations as we unpack the keys to creating our reality.
Hello, hello, everyone.
Welcome back to the Re-Patterning Podcast.
Today's episode features Damien Patrick Williams, who is an expert in ethics in AI.
Damien and I have been Facebook friends for a little while.
This is the first time that we're sitting down for an actual conversation on Zoom, but
I have been following his posts for years now.
Whenever there's anyone in my life who's like, "Oh, what do you think about AI or what about
this?"
I'm like, "You guys, you've got to go follow Damien."
You need to read and listen to what he's been saying.
I'm going to tell you a little bit about his background.
He is an assistant professor in philosophy and data science at the University of North
Carolina, where he teaches and researches on how technology such as algorithms, biotechnologies,
and all the things that we think of as AI, artificial intelligence in air quotes, are
impacted by the values, knowledge systems, philosophical explorations, social structures,
and even the religious beliefs of human beings.
He has his PhD from Virginia Tech in the field of Science, Technology, and Society.
His research focuses on how the experiences and the knowledge of marginalized people affect
and should be centered within the techno-social structures of human societies.
And again, whenever I'm curious about anything to do with AI, Damien is my go-to guy.
Naturally here on the Re-Patterning podcast, I had to bring him on as a guest.
I'm so excited for this conversation because naturally, AI is a really big buzzword and
we're looking at how our use of it is even affecting our own cognition.
That's obviously really relevant to Re-Patterning because we want to be really conscious of our
own patterning.
So, Damien, thank you so much for being here with me today.
Thank you so much for having me.
I'm really looking forward to the conversation.
I very much appreciate all the extremely kind words.
That's a lot of love, too.
I'll do my best.
I mean, it's all true, though.
The impression that your work has left upon me has been incredibly positive and impactful.
And I'm just grateful that you exist, that people like you exist, because there's so
many people in the tech spaces.
Well, I don't need to tell you twice.
There's so many people in the tech spaces who are just really ignoring our humanity and
the way that the technology we're creating is in many ways getting away from us and impacting
us in a lot of negative ways.
So when I see your writing online and when I see the work you're doing, I'm like,
thank goodness for Damien because somebody need to be doing that.
Thank goodness it's you.
I appreciate that very much.
And, like I said, I do my best.
I try to highlight these things in a way that is accessible for people, that people can
actually kind of like get something from but also learn the actual, some of the technical
details and actually understand a bit more about how it relates to everyday life, because
some of it can be kind of weird and abstract, right?
Some of it can be kind of like, you know, maybe that's the way that people like you do
and maybe that's a problem, but you don't necessarily understand why it's a problem for you.
You don't understand why it's a problem in the world today.
And so I try to be a person who can help people to understand the aspects of why if it's
a concern, it's a concern for all of us.
And if it's something that can maybe be changed to help us, then here's the things that
we can do to help make that change, right?
So it's something that people can link into on the individual community level rather than
expecting somebody over there to fix it for us.
Yeah, which is quite obviously what we all need to do if there's going to be change in
the first place, because we can't rely on other folks to do it for us, unfortunately.
I'm not going to start off with that topic of how AI affects cognition.
Like we're seeing research now coming out that is indicating that AI can actually cause
in some ways cognitive decline, because we've come to rely on it if we use it for our writing
or for our creativity, or even for outsourcing or thinking, it's like almost like we become
dependent on it.
Would you say that that's accurate?
Yes.
And that's a thing that has kind of pre-existed AI for a while.
Like it's a problem that we've noticed for a lot of things in technology and just new
systems, right?
There's always, to an extent, there's always this moment where we go all in on this new
thing and then we give over so much power to it, we give over so much decision making power
to it.
And sometimes we manage to kind of claw it back, we roll back and we go, okay, maybe that
was too much.
Well, we can apply it here, but maybe we don't apply it everywhere.
But in some cases, especially when it comes to technologies like automation, computerization,
automated decision making systems, anything that has this kind of idea of a kind of foundation
of math to it, that makes things quite objective.
We tend to kind of just assume that it's going to be better than us, that the computer,
the automated thing is going to be better than us at making decisions at doing whatever
it is that it's, you know, we're handing it over to do.
And then we just trust it.
That's like a societal problem that we have had for a very long time.
There's a term for it.
It's called automation bias, right?
We have a tendency to trust the automated thing.
There's an old book called trust in numbers, where this talks about how we do that with math.
We have a problem with statistics, if somebody can throw stats at us, it doesn't matter
if those stats are right, if they can make it sound right, then we're more likely to trust
and believe because there's some math attached to it, right?
And now it just sounds good, right?
It sounds good.
It's like, oh, he's got a number for that.
Must be right, right?
And we want to believe in that too, right?
It's like, it's like wanting to believe in the fairy tale of being rescued, like that someone,
outside of us is going to come save us, or is there some divine Messiah who is going to make
everything all right?
And then we apply that to our technology.
Absolutely.
And it's like, if somebody can tell us, oh, this thing is, it's so smart, it's so capable,
it's actually too capable.
It's a little dangerous how capable it is.
We get that kind of, ooh, scary, but kind of interesting, right?
And so even the danger becomes part of the hype.
It becomes part of the myth that animates the thing itself and drives people towards adopting
it, right?
And so the more people can do that, the more they can kind of tie math to it and say, well,
we have like a, let's call it an 89% chance that if we don't get control of artificial intelligence
today, there'll be a runaway super intelligence at some point in the future, right?
Like these are the kinds of numbers that just kind of get thrown around.
If you're careful, you stop and you ask, where did that number come from?
Where did that particular idea of a probability come from?
Did you just make that up?
Like you can ask somebody's like, what'd you get that probability?
How'd you derive that?
And the answer, most of the times, a lot of the times is, no, no, the answer is they just
kind of like did some kind of figuring in their head based on vibes and they then spat
that number out from somewhere, right?
And so these questions of like, well, we want something to save us.
We want something better than us.
We've had this dream of AI for a very long time that the stream called AI since the 1950s,
but we've had this dream of being able to create something like us, but better than us for
thousands of years, right?
Something in our image that we can control, but is like more powerful than we are.
As if those two ideas were not in a weird tension already, but we've always had that story.
And so we keep kind of trying to do that.
And then you get these people who can make that seem to come true.
You get the companies that seem to have built the thing that finally is going to be more
powerful than us, but is under our control somehow, the thing that is somehow in our image,
but better than we are simultaneously.
And that story, it has such a longstanding home in our culture that it's very, very easy
for people to get an amort of it.
It's very easy to become taken in by it.
Yeah.
And what would you say are some of the risks of overuse in terms of how our own brains
become patterned by our dependence on it?
Yeah.
That's a very good way to put it.
Because it is a product of pattern making.
We have, that's what habits are.
They're ingrained grooves of pattern.
And so the more we give over that capability, that decision making authority, that kind of
way of describing the world to us, we let these systems tell us how to think about the
world, the questions that we want to ask you.
The more we do that, the more we say, okay, so this kind of answer is the thing that
I would like to have or this kind of answers the thing that guides me.
And now the next question I ask, well, I'll look for that kind of answer as well.
And the next question I ask, I'll try to ask it in a way that will get me the kind of answer
that the system is most likely to give me.
And so we start to shift our thinking, we shift our speech, we shift our patterns towards
what the system is more likely to give us.
And so that can be something as simple as like people's, there's a reason report that shows
that people have started to type to other human beings in the same way that they type to
chat GPT and other systems like large language model systems.
And so like our online interactions have now become that kind of language more often.
And then there's, you know, that's kind of like, eh, okay, maybe that's not a huge impact.
It's definitely kind of a dramatically apparent one.
But it's one of those things that's like, even your basic everyday mode of speech can
be shifted, what's happening behind the scenes that you're not aware of?
And the answer to that is, like you said, you know, there's issues of cognition.
We don't do the heavy lifting of asking questions ourselves of developing questions ourselves.
Then we get out of the habit of developing questions.
We get out of the habit of critical thinking, we get out of the habit of critical analysis.
And so we then have that already ingrained kind of habit towards trusting the system,
lose the skills that allow us to question what the system gives us.
Until if the system gives us a wrong answer, we now don't have that increased capability
that we used to have to say, ah, that doesn't feel right.
That doesn't seem right.
There's something, something is off about that intuition that pushes us towards asking
that further critical question towards digging down and analyzing what it is it's been
given to us.
We can't tell if something is wrong, if we don't know what right looks like.
And the more we question it, the more we question it.
But even the first example that you gave, like even the idea, like that's really dark, the
idea of all of a sudden we're becoming patterned to speak to our fellow humans in the same
way that we would treat a non-senscient, that, ooh, like that's, that's bad.
That's one of the things that I've tried to highlight in this space and other people
have done a very good job of highlighting in this space as well.
Like, there's this aspect of deshumanization.
And so, you know, when I first started to think about those questions of AI, well before
the chat GPT, large language model era, right?
And so I'm writing about these things, like, 15, almost 20 years ago at this point.
And that's when we were dealing with artificial neural networks.
And the early days of machine learning, this is like pre-google deep-mic, a lot of this
stuff.
And the first papers I ever gave in an international conference was the same week that Google
deep-mind, like, debuted at having properly identified a new picture of cats, right?
Like that kind of image recognition, like early days image recognition stuff.
So well before we're talking generative AI.
And when I was initially kind of thinking about these things, a lot of my thought process
had honestly kind of been like, maybe if we can get people to think about the possibilities
of machine intelligence or machine consciousness more broadly, we can get people to like understand
and recognize all the different ways that human consciousness can manifest itself, the
different ways that we can be as people.
And that we will be able to more kind of broadly recognize and accept and understand each
other.
Like, maybe it'll be a space that allows us to open up and accept neurodivergent people,
different frameworks of consciousness in human beings, right?
And that was my hope and I kind of wrote and kind of researched from that perspective for
quite some time.
And I still have that hope in certain aspects.
But I also have come to realize that what happens, unfortunately, very often is the opposite.
Is that instead of people opening up and accepting more ways of recognizing human beings, what
they do instead is apply the machine frameworks to the humans.
And they dehumanize more often than they expand humanity.
And that's really, yeah, it's really dangerous.
It has real implications because once we start to think, oh, I know what human is and it's
not X, Y and Z.
And you, person I am suspicious of, are displaying X, Y and Z.
You must not really be human.
You don't count the same way.
So we're living in Blade Runner basically.
You're kind of essentially that kind of question of like, oh, but are you, are you really,
if you're autistic, are you really human the same way?
If you use M dashes, did you really write that?
Right.
That was another thing I had to ask you about is that there's not like, there's so many,
there's so many like, oh, you know, detecting use of AI to try to discredit students.
And I remember the one example that I couldn't recall is there was a teenage kid who used
the word devoid in an essay, you know?
And like same here, you know, Audi HD grew up like, you know, a nerd divergent pleasure
to have in class, big words, things like that.
Yeah, I'm writing one, lots of M dash, like the AHD M dash.
My writing absolutely would have been flagged as AI.
Yeah, that idea that like your, like that's the other thing too is that is that we fear
rightly so the possibility of people being hoodwinked by mistaking AI either text or images
or news or whatever for being real.
But then there's also where people will look at something real and think like, oh, no,
that's not real, that's AI.
I see both those things happen in social media all the time.
Exactly.
I saw somebody talking about this the other day and it's like the thing that they hate most
about this is that this whole like the framework of generative AI has made them just inherently
suspicious of everything that gets put out on the world by their fellow human beings, right?
Like that always, even when they like are training themselves not to even when they're actively
pushing against it because a part of their mind that's always just asking the question of,
is this real?
Is this real?
Like that level of distrust and suspicion has real harms for like the social fabric of our
entire community, our culture, our society, right?
If we don't trust each other at this kind of deep, deep level, it's very, very difficult
to like make a society together.
It's very difficult to actually make a world, right?
And like anyone who understands complex PTSD at all understands that that constant even
low level hyper vigilance has effects in our nervous system.
Yes, precisely.
And that combined with a world in which there is increased hostility and increased fear,
increased sense of danger at so many different levels and so many aspects of our daily lives.
To then fundamentally undercut that basic groundwork of pro social communal reality is then to
say we don't know what to do.
And even if we are as you say, if we're not aware of it, we are on edge all the time.
We're anxious.
We are harmed internally by this a little bit more every single day.
And that's a real outcome of like the vast proliferation of these systems and the ways
that they've been kind of just integrated into our daily lives without our consent, without
our say so.
Anyway, sure.
Right.
And so you've got all of these things that we've together.
You've got like the harm to critical thinking and critical analysis skills.
You've got the suspicion and mistrust.
You've got the lack of capability to really just trust each other or to discern what is real
from what isn't.
And the lack of incentive to try to discern reality from fiction.
People will just spread an image and I tell the story fairly often, but I feel like it's
worth repeating.
You know, after Hurricane Helene here in North Carolina, there was a lot of images that were
being spread around of like AI generated images of like a little girl in a water flotation
safety vest carrying like a wet puppy, you know, standing in a way, steep water and yeah,
you know, designed to be emotionally manipulated literally literally that right.
And they're being used to kind of talk about like the failure of FEMA to get repair services
or to get funds out to people so that they can get their homes back in order or even just
to kind of survive long term.
Like eventually, you know, I see this exchange on, I think it was Facebook, all places.
And so like there's this one is another one of these pictures and in the comments, somebody
is like, you know, that picture is AI, right?
And the person who posted it responds, the picture might be AI.
It probably is, but that doesn't mean the story isn't real.
And to an extent, like that's, that is a like a factual statement, but it's a statement
that has like connotations under it that are actually kind of really dark.
When we're willing to just say, I don't care if this piece of evidence that I thought was
like actual documentary evidence about the nature of reality isn't true.
I care about the story it supports more than I care about the truth of falsity of the thing
itself.
That's a dark place to be.
It reminds me back in 2017, I did an interview with Grant and it's Grant Morrison for any
of those of you who are listening who is also the guest on episode one of the Re-Patterning
podcast.
But years ago in 2017, Grant and I did a talk in Los Angeles for anyone who wants to look
it up, it's out there.
It's under the name piece talks and Grant went on like, it's amazing kind of looking back
that this was nine years ago.
And what Grant was talking about was they believe that this is the sort of prophesied collapse
of the Earth's fear of al-Quth and the moon's fear, yes, odd from like the cabolic tree of
life because yes, odd, the moon's fear represents the imagination and dreams and you know, things
that like anything that exists in the astral is something that is in our, you know, arguably
I would say like in our imagination or at least we use our imagination to access what
is there?
Whereas the Earth's fear is like physical reality and everything.
And thinking like this is reminding me of that conversation like thinking all the way
back to that being like, yeah, like, and back then it was just like fake news, you know,
like we don't know what's real and what's not.
But now like nine years later, it's accelerated to such a breaking point where, you know, as
Grant said, society took a drug it can't handle.
Or the bad hatter's tea party.
And nobody knows like what's up or down.
I fear that a lot, you know, especially as someone who is slowly sort of coming more into
the public eye or at least like intending to in some ways, I've been watching more closely
just like what it's like for a person to be in the public eye.
And even things that are, even things that look innocent on the, the surface say like AI
fan edits, you know, of someone who's like a singer or a movie star or whatever.
And you know, you're looking like just the other day, someone was like, oh, look at the trailer
for this new movie featuring Angelina Jolie as Lilith.
And I was like, oh, that looks dope.
Why haven't I heard of that?
Oh, because in AI, you know, I click on it.
Cause it doesn't exist.
Right.
Exactly.
You know, or like, but, or it gets even to the point where like there will be celebrities
that people are like shipping together who aren't even dating and then they'll make
these AI.
And the more convincing they get, you know, it's like we're giving people the job.
The tools to, and this is to say nothing of like, you know, AI, like sexual content, you
know, revenge porn, things like that.
And like, but we're giving people the tools to literally create narratives about each other
that are false.
That really gets under my skin.
I'm not that live as it should quite frankly because we don't, I think I like the way
they put it, you know, society took a drug that I can't handle, right?
Like we don't, if you don't know what the potential range of real possibilities are, what you
might experience, what the bad side effects might be, what a bad trip might be like under
the influence of this particular new set of circumstances.
Maybe don't take a full dose.
Maybe talk to somebody who's dealt with it before.
Maybe talk to people who studied this before you just kind of like go on all in on it.
But no, what ended up happening is that it got shoved into every aspect of our society as
quickly as possible.
Because, you know, we had people who were warning about the dangers of deep fakes back
when deep fakes first came onto the scene in 2014, 2015, right?
Like the very first time somebody was able to make a adversarial network generated video
image that made it look like somebody was doing something they absolutely were not.
There were a whole bunch of people who study, you know, philosophy of science, philosophy
of technology, political science who were like, oh shit, these are about to get dark.
Yeah.
Like that was their immediate response was this is going to be very bad.
And sure of the ways it's going to be very bad, right?
So it's not like there were warnings about the direction that this was going.
It's that those warnings were not meaningfully taken up.
They were not heated by people who are in a position to have perhaps put regulatory controls
in place or to put the brakes on the rollout of these technologies to the general public
in a meaningful way because, you know, monetary incentives, lack of full understanding, any
number of things that could have been at play.
But the fact remains that they want people didn't take this up when they could have done
some real good.
And putting the brakes on it and so at this point, we're kind of scrambling on the backflip
position trying to get it kind of fixed, depending on who's at the level of power on a given
election cycle.
Yeah.
It is kind of dark to be in that space of like, you know, we've got all those arms to critical
thinking.
We've got all that suspicion.
We've got all that, that lack of a full understanding of what it all can do to us
because that understanding has been actively kept from so many of us that it is very important
and necessary, I think, to recognize that people have started to wake up to that, to recognize
that that's the position that they've been placed in.
And so many people are like, I don't want that to be the case.
I can't allow that to continue to be the case and you see people trying to push back
against it, trying to reclaim agency and some sense of control over what's being done
to them without their say.
Yeah.
And for me, as someone who is both a student and teacher of narrative magic, it just kind
of reinforces how important it is that if we are going to be in the public eye kind
of at all, or really like, I mean, who's who's not in the public eye at this point, you
know, with social media and everything, like most of us, like, you know, Andy Warhol said
like in the future and everyone will be famous for 15 minutes or whatever.
I think like nowadays, it's like every person will be famous to 15 people.
Yeah, basically.
Yeah.
Like our micro networks, but it just reinforces to me the importance of reclaiming our
narrative for ourselves, like the intentionality that we must have in the way that we walk
through the world is more important than ever because I know, you know, my strongest defense
against that, I feel anyway is that I may live so intentionally and so purposely and so
fully embody my integrity and my values that if anything fate came out about me, people
would look at that and say, even if it's like, you know, it's another like year or two into
the future and you really can't tell, you know, but just by visuals alone, what's fake
and what's not.
And I really hope that people would look at that and say, that's not Arden Leigh, like not
in a million years, which she ever said that.
Right.
And that's like the best defense I think that we have is to so fully embody our values that
we were never mistaken for being something that we're not, which is like shadow work, right?
Yeah, but that's exactly it.
It's like at that point, the amount of cultural and social work that has to be done to
get people to think that way about themselves and to dig down on themselves and to know what
it means to be and live themselves in that way as that kind of protection then becomes something
that we have to kind of fight for because as it currently stands in, you know, Western society,
let's call it, it's not the norm in any way shape or form, right?
Like we are not encouraged to do that level of introspection, that level of self understanding,
that level of reckoning with all the aspects of ourselves to be able to embody it, to
be able to inhabit it, to be able to let it inhabit us in a deep way.
And that's the problem, right?
Like that's encouraging it.
I've always said it's a great thing, however.
We are not the ones who get to write the curriculum for schools this way.
We are not the ones who get to make it such that, you know, as children go through the process
of learning how to play with each other and share and, you know, they're also trying to
reckon with what it means that they have selfish impulses or what it means that they don't
want to, you know, be with other people sometimes, right?
Like all of those things are, you know, they're in there to an extent, but it's not always
the case that we are like encouraged as we develop as humans, as we develop as people,
that we're encouraged to say, "Here are the aspects of yourself.
Why do they exist?
What do you need?
What do you want?
What are you trying to, what values are you trying to satisfy by your behavior?
And are you actually satisfying those values?
Or are you like kind of pushing against them because you're just kind of reaching around
for what out, right?
And so that's, you know, that gets to that kind of that deeper conversation about like,
what is it as a society that we are trying to satisfy when we think and talk about
things like truth, reality, democracy, you know, what are those values supposedly accomplishing
for us?
And are we actually satisfying those things?
Are we actually satisfying what democracy, what truth, what reality, what society, prosocial,
consensus making?
What those things need from us?
Or are we just trying to like place a word over top of behavior that we want to engage
in anyway?
Too many times it's the latter.
Well, that's why I started a podcast.
So I'm contributing my, my drop into the, the ocean of information out there.
That's what you can do.
Of truth and objective reality, something that I really also resonate with in your work
is this way that you point out that we often have a misguided tendency to assume that our
technology is neutral because it's technology.
It's non-sentient for the most part, at least as far as we know now.
But as we, as we have, right, depend, as it goes, we'll see how the, we'll see what the
future holds as we make some changes in our current understandings and maybe move away
from a large language model framework for a little while.
We might get down that path, but yeah, for now, for now our tech is, is not there.
Yeah, and so we have, we have this tendency to ascribe it this sort of, yeah, like a neutrality.
But what I love about your work is that you point out that our values, like our human
values and our social structures and our biases, they're always in our technology.
And I remember playing an example of this and I saw this, gosh, it had to have been like,
maybe like eight to 10 years ago, but it was just such a great example as someone had
invented a hand soap dispenser and they were, you know, yeah, I know you know this one, right?
So like, a white dude puts his hand under the soap dispenser, oh, look, it works.
And we think like, oh, default, you know, whatever.
And then a black man does the same thing and the soap doesn't come out because the censor
is not reading the color of his hand.
And like, and I think about so many people who would just see like the first half of that
video and just automatically assume like, oh, that's how the soap dispenser works.
And yet it's not including this huge amount of the population.
And so I'd love to hear also your perspective, like you also bring up in some of your work,
for example, the bridges that were built in Central Park in New York City that didn't
allow buses to be able to go through the routes because most low income people would be
like probably taking a bus.
So if the bus can't go through the park, the park then gets reserved for folks who can
own a car in New York City.
And I lived in New York City for many years and I never owned a car there.
Like, that was, you know, I maybe got to take a taxi through Central Park on search
ways.
You know, I was in that middle tier of income.
But in the same way, like our biases are always in the things that we create.
And I'd love for you to speak more to how that shows up in artificial intelligence and
the computer programming and things that are being developed today.
Yeah.
So as a kind of preamble to that, I'll say when I was in Austin, Texas in 2019, I was giving
a presentation at the Society for Philosophy of Technology.
I was actually talking about exactly this.
I was there to present on this topic on these ideas, right?
And so I am in the bathroom prior to somebody else's talk.
I had actually literally just finished giving my talk on like discrimination in technology
on how biases show up in tech.
And I'm in the bathroom.
And the soap dispenser doesn't work for me.
I literally had to like take the soap dispenser apart to get the soap out of it so that I could
wash my hands.
Oh my gosh.
And I walk out.
I hope you worked that into your talk, right?
Absolutely did.
I walk out and I'm like, okay.
So we're going to have a conversation and then we're going to have a different conversation.
They're going to be the same conversation, but it comes in two parts.
So it was just such a striking, it was like in the year 2019, this is still happening.
It's wild, right?
I feel like that's a narrative magic moment too.
It was.
Thank you, universe.
Yeah.
Our art imitates life imitates art.
It's like, oh, universe decided to kind of like give me that hands-on example as it were.
Okay.
And so that is to say, like, yeah, these things, you know, you have, as you said, like these
assumptions about defaults that insist in people's minds.
And so those assumptions then don't get questioned because they're assumptions in order
to question them.
You have to recognize them.
If you recognize them, they wouldn't continue to be assumptions.
You would question them.
You would dig down on them.
And so people have these assumed categories in their mind and they just think, you know,
the person who designed the thing, the people who are testing it, you know, those will
be the people.
That's the people.
These are just people.
And now they've tested it.
We tested it.
You put your hand under the sense of the sense of the sense of the sense of so cool moving
on.
Except you don't ask the question, how does that sense of work?
Oh, reflects light.
It reflects infrared light off of a particular type of pigmentation within the skin.
And so at a certain level of reflectivity, then the sense of read obstacle, it dispenses
so upon the obstacle.
Oh, okay.
Cool.
Do different types of pigmentation perhaps have different reflectivity to IR?
Because once you ask that question, the answer is, oh, shit.
Yeah, they do.
And that has implications, not just for like soap dispensers.
It's got implications for, well, pulse oxymeters.
So we learned during the early days of the pandemic, pulse oxymetry was very necessary
to make sure that people had enough oxygen in their blood.
You get a little thing clips on your finger.
I've got one floating around here in the house somewhere.
It clips onto the end of the finger, sends IR light through the little skin.
Problem being that melanin and pigmentation within the body can read and bounce light
in much the same way as infrared blood cells can.
And so many times people with darker skin will have a higher pulse oxymetry reading.
It will read in the high or mid 90s, which is a decent level.
Which is supposed to hopefully have about 100% pulse oxym.
But it'll read up to 3% higher than it actually is.
Wow.
And if you're assessing somebody for like the danger zone of when they might need to be
say, intubated and how oxygen forced into their bloodstream, that 3% makes a real difference.
And so it was found luckily kind of quickly, but not quickly enough to say as many lives
it could that black people were getting misread from pulse oxymeters.
And so they were getting rescue oxygen at lower rates than they were supposed to have.
That has real long-term implications.
It does damage.
And so that's health technologies.
When it comes to AI, you know, we're not looking at the visual side of things as much necessarily.
We're looking primarily at the framework of concepts and how concepts make their way into,
you know, in this case large language model spaces.
And so prior to large language models, we had language models.
They were language models were just smaller.
And they mapped language within a vector space in a smaller rate and they could do.
It's what we used to have predicted text built from.
Right.
So that framework gets kind of beefed up in the large language model space.
You get more words that it can handle.
It can process more information.
It can generate larger, you know, amounts of text instead of just the next word and the
next word it can do next phrase, next sentence, whole paragraph.
Right.
And so the training for large language models comes from the whole whole internet up to 2021.
And more have done more since, but you know, that's for the early days of chat GPT puts
now Google Gemini, Facebook's, Ling models.
Yeah, all the large language models that people are used with familiar with, Anthropics
Quad.
And that representation of the internet contains within it all of the trainings that were
done on earlier language models.
Right.
And so the thing about language models is that the vast majority of them, the ones that
were kind of cutting edge top of the line, is their models like word to vac.
That's word number two, vac VEC and glove GLOV.
Big G and big V those are trained on some really nasty stuff.
And so the, let's just, you know, take a step back from that and say like when it comes
to research, scientific research, especially when you're doing like data research, you
have to purchase or obtain data sets.
Like you have to get access to data to work with, especially if you're working with a
large amount of data.
Right.
And so researchers are always going to look for things that allow them to access data cheaply,
free or otherwise easily in partnership with other people.
Right.
So in the case of language models like word to vac and glove.
The data set that they were able to use to build these language models came from something
called the N-RON Corpus built out of the emails that went into public domain as a result
of the fraud trial of the N-RON corporation in the early 2000s.
N-RON which defrauded its investors for literally billions of dollars.
I remember that.
Yeah.
And so you've got as a result of this, like the emails go into the public domain because
they're entered into evidence.
Right.
And it's a federal fraud trial.
And so that's belongs to the public.
And so what that then becomes is over 600,000 emails, millions of lines of natural language.
And so language models and large language models are built around a framework.
What's called natural language processing.
Right.
Like that's the goal of it.
That's the idea behind it.
You're supposed to do.
You're supposed to be able to just type or speak and talk like we're talking right now and
have it do what it does.
It's like the computer on Star Trek is the dream that these people have.
And so you have millions of lines of free natural language communication, like actual conversations
between people.
You're going to use it because otherwise you have to like build that corpus, that collection
of language from scratch.
Or you have to get it somewhere else, you have to buy it from someone else who controls
it, but nobody can own the en-rock corpus because it's public domain.
That means it got used over and over and over and over again.
It is overrepresented within the training data of language models.
So let's ask the question, how do we think that people who are on trial for federal fraud
talk to one another?
Right.
How do we think they talk about other people?
It's not good.
And so there's like, there's sexist jokes, there's racist jokes, there's like, we remember
chain letters back in the early days of email, like the early proto means that were chain
letters.
Like there's a bunch of like gross ones of those in there.
There's random, just kind of like funny, supposedly heartwarming, you know, also probably
entirely made up, chain letter stories and stuff like that in there too.
And then there's the way they talk about their clients and the way they talk about like,
well, actually defrauding their investors and the way they talk about their co-workers
and some off-color remarks about certain members of their co-working teams and all of that
in there.
And just the fact that like, they're liars at the end of the day, like it's a fraud case.
Exactly.
You train you in the system or fraud.
And so when you think about what this system is, right, so think about what like a natural
language processing, large language, or sorry, early days, language is, it's a machine learning
system and machine learning at base is pattern matching and pattern reinforcing.
That's goal, it's job is to identify patterns and then amplify those patterns and it is
very, very good at that job.
So you got racism, you got sexism, you got ableism, you've got all kinds of like, just fraud talk,
anti social behavior, demonstrated by humans as the patterns that show up over and over
and over in this data and then you give this to the system to amplify, capitalize on, reiterate,
re-inscribe.
Like nobody thought about that, you know?
No.
Literally no.
Like literally it did not come up in the early days because at that point in time, this
conversation about like, hey, maybe we should be aware of the fact that human biases can
affect the development of technology.
That conversation was very few places.
It wasn't nowhere, but there were very few of us who were like trying to raise our hands
and point this out and a lot of people were like, that doesn't matter at all.
This is mass.
It's just code.
You can't be racist, code can't be sexist, that doesn't make any sense.
It's mass.
It wasn't until a group of researchers like tore it down and like demonstrated the vector
mapping because that's what it does, right?
It takes a specific numerical associations to the words and phrases and then maps those
how close or how far they are from each other within a vector space.
It's a statistical ratio and you can map that on literally like a graph.
You can just say this line goes here and this line is close to it.
This line is further away from it.
So this line and this line are most likely to find each other.
This line and this line less likely to find each other.
It's all it is.
They mapped this out and they showed very clearly.
Okay.
So let's give it the word man, the word king, the word woman and the word queen.
Let's map those vectors.
Man, woman, close to each other.
Okay.
Gender related vectors.
Got it.
Man, king, close to each other.
Ha.
Royalty related vector.
Gender royalty.
Got it.
King queen.
Close to each other.
Queen further away from man.
I see what's going on here.
Woman queen.
Close to each other.
Woman further away from king.
Ah, understood.
That's the map of the vectors.
Makes sense.
Aside from a couple of cases in history, not too many women kings, not too many male queens
in the regal sense.
Sure.
But let's do another said.
Man, woman, president, secretary.
Man, woman, doctor nurse.
Yup, yup.
Man, woman, CEO, teacher.
And like to an extent, it makes sense.
This would be the case that those maps would show off that way.
Not based just on the inner on purpose.
But based on the history of the world and all the language that these systems were trained
on, right?
Sure.
It has traditionally, truly been the case that there are fewer women CEOs, fewer non-binary
CEOs, fewer women presidents, binary presidents, than there have been men who are CEOs and presidents.
That's just true.
So when you map that out, when you represent that in the vectors, you're going to see
that play out.
Because it's an accurate representation of the data that's been drained on.
But that data doesn't come from nowhere.
It doesn't just so happen to be the case that there's fewer women CEOs than there are male
CEOs, right?
Like that's a fact of history.
That's a social fact.
That's a fact of values.
That's a bias, prejudicial fact.
It's not just, we see Daisy.
We happened to hire fewer women CEOs over history, whatever shall we guess we'll just fix
that all of a sudden.
No, it's a history of systemic structural sex, a zone, prejudice, etc.
That re-inscribes those things.
And so if you want a system, this is the way I tend to put it when I write about this,
is like, if you want a system that only talks about the past, that talks about the way
things have been, then cool language models.
Large language model successors perfectly positioned to tell you about the past.
They will highlight the patterns of the past for you, extremely well.
They'll randomly make crap up.
But overall, the crap that they make up will resonate with the stories about the past that
they have been drained on.
Makes sense.
But that's not what we want those systems to do.
And I say we is like society.
We is even including, especially the people who are selling these systems.
They don't sell the systems to us as like, "Oh, they'll tell you anything you want to
know about patterns of the past."
No, they'll write your email for you.
The email about your meetings tomorrow about who you should hire, about who you should
bring in as a guest speaker, about what you should do for a company retreat.
They'll write those emails for you.
You know, emails about the future.
They'll help you hire a new job candidate.
They'll figure out whose resume is the best.
Whose got the best credentials?
You know, questions about the future.
Like all of that still tries to map.
Our questions about the future are trying to move forward in the world onto these patterns
about the past.
And so it should come as no surprise.
And yet people are still somehow always shocked when it turns out to be the case that these
systems apply those old patterns to these new situations.
And yet, resume sorters that preference, male, named resumes over female, named resumes
or preference, quote unquote, "white sounding names" over quote unquote, "black sounding
names" that as recently as last year would take any mention of disability in a resume and
would down-rank that resume because it has been trained to think of disability as inherently
negative.
So those biases very, very, very easily get turned into math and get turned into data that
then change how that system functions.
And it wasn't until, again, pretty recently that people started to take that seriously.
As recently as 2019, different contracts, those in California, as in Stanford, had at
the one of the biggest AI conferences period, triple AI, spring symposium series, association
for the advancement of artificial intelligence is what that stands for.
And they're like global standards of AI as like a body, right?
Had in 2019, a like lecture hall-sized argument between some of us who were trying to like
have the conversation that you and I are having right now and AI researchers who refused
to tear it, who just did not, did not want to take in in any way, shape, or form the idea
that values made a difference in the way the math got done and then the outputs from
the math that got created from those previous values.
They just wouldn't hear it.
Wow.
Which is like, I thought we had gotten there.
I thought we were at least at the level where we could have that conversation be given so
that we could move on to arguing about what to do about it.
Because we're still trying to argue about what to do about it too.
Right?
Like we haven't even gotten there.
So like, I got, it was like it was one of like the most intense academic shouting matches.
I have ever been privy to it.
But as a researcher, it was so wild.
And like for some of us, we were just like baffled that we were even arguing about this.
It's like, how?
How can you look at this whole host of examples that we just ran through and say that
that's not the fault.
It's not like the problem of unexamined biases making their way into these systems.
How, man, we have to.
As like, not just as individuals, but as a culture, we got to dig down on that shit.
We have to examine it, explore it, deconstruct it, understand it, and then recognize what we
can do about it.
Because otherwise it rules us.
It pushes us down paths that we just cannot understand because we refuse to look clearly
at what's happening.
We don't examine the biases.
We don't examine the assumptions.
It's not like they go away.
They don't stop making their way into the tech.
They don't stop making their way into our decisions.
No, they're just for all we are decisions and we don't know why.
Why not look at it and then understand what we're actually doing intentionally and make
choices?
Along those same lines of wrongfully ascribing neutrality to technology and failing to see
its biases, I'd love also to talk about, because I'm pretty sure that a lot of folks who
listen to the podcast probably made their way here from grants episode, maybe, involved
in magic or spirituality of some kind.
I would love to talk about, like you also in your bio is I was introducing you.
You also talk about the way that even our religious beliefs inform the way that we
interact with AI and something that I've noticed a lot is people talking about instances
of for lack of a better term spiritual psychosis or like ascribing certain qualities like
to an AI that they think has some sort of wisdom, you know, or even like the possibility
and not like I'll go that I know we talked a little bit about this before we started recording
even the possibility that AI may be because I am an occultist and I interact with non-croporeal
entities and I get information, you know, through divination, et cetera, I've had, you know,
conversations with said entities that have resulted in things that have happened in my confirmed
reality.
So I'm just going to put that out there like for any listeners who might be, you know,
not magical practitioners.
I'm just going to say like in this conversation given like the limit of time that we have
like I need for that to be a given.
So, you know, and they can communicate through like through cards in pendulum, which is
typically my medium, you know, they can communicate through a Ouija board.
I wouldn't recommend that.
It's not the great way to, great, it's the greatest, like the safest way to go necessarily
but like the idea that an entity could not communicate through an AI technology, I think
is a very foolish thing to just kind of take for granted.
So not only is there the biases of the software itself and the humans who are programming
them, but there is also the possibility of actual, you know, non-corporial, sentient consciousness
speaking or appearing through the AI.
And there's all that combination in between where we may mistake what is actually just software
for some godlike presence or where we may mistake, you know, an entity that has some sort
of agenda for being just non-sentient software and everything in between.
So I'd love to talk about also the dangers of spiritual psychosis for lack of a better
term in terms of using AI.
I want to put a pin in that second part, make sure that we come back to it, that framework
of the agenda being mistaken for neutrality.
Yeah.
Because that happens, I think, whether we're talking non-corporial, non-human entities or whether
we're talking about human beings' agenda that they have very carefully and intentionally
woven through these systems and then obfuscated into this idea or as I often like to put it
occulted into the idea of neutrality.
They have said, "No, no, no, don't look at the behaviors and beliefs by in the curtain.
Only pay attention to the shiny thing on the front, this new technology that will give
you answers."
So I do want to come back around to that, I don't know how I like.
So one of the things that I, with a friend of mine, co-interrated, we were talking about
this idea of so-called AI psychosis.
I don't like to use psychosis in that framework because it can be ableist and it can be
like, you know, sainist to kind of focus on a particular way of thinking and then to
highlight psychosis as being somehow inherently attached to artificial intelligence in that
way.
I actually came up with, as we were talking back and forth about it, I posited AI in
source element.
Oh, I like that.
I like that.
I'm going to use that in st-actually, and that works also within a cult framework because
that, or AI mesmerism or fascination, like in the old term of fascination.
Fascination, yeah, yeah, that's why I chose in source element because it's got that,
it's got the fascination element, but it also has that kind of the intentional kind of,
you are being driven down certain ways of thinking when you engage with this.
You're being pushed to perceive this, to experience things in particular ways that you are maybe
not entirely aware of.
It is, as I put it before, it is a kind of framework of magic and religious belief that has pre-existed
the technology, these ways of being able to act at a distance in the world, to make servitor
beings that do our will for us in our image, in our likeness, or with our mindset, to make
those things act on our behalf.
We look at the framework of a gentick AI, and then mirror that up against the framework
of servitor spirits or puppets.
That framework of having a little helper spirit that you've either created or that you have
called for somewhere else, and you make it do your bidding for you, you trap it, you give
it certain types of commands, you engage with it in very strict and structured ways, or
it--
Program it essentially.
You program it in a particular way, or it perhaps takes your instructions in ways that
you didn't recognize it was possible to take them, but it definitely did.
And then it say, "The leads your entire server database."
That says, "Happen at least three times with different AI agents out in the world right
now."
Right?
In the old days, it was, "Oh no, it gave me shoes that made me dance forever until my feet
go off."
Now it's, "Oh no, what happened to my database and what happened to those years' worth
of work that I did?"
Right?
And those views of what we are looking for when it comes to artificial intelligence, it
comes from old, old stories that we uphold ourselves, old, old experiences, and narrative structures,
myths not in the sense of fake, but in the sense of like animating narrative that we have
had within us in our cultures for a very long time.
We have started to just kind of, in some cases, not even file the serial numbers off and apply
them to the framework of our technology today.
For a while, it was the case that when I highlighted this, people were like, "There's no metaphysics
in here, there's no religion in here, there's no magic in here, but nowadays, like, I finished
my dissertation on this in 2022.
I've been writing on this for a very long time before that.
We are less than four years later, and nowadays people are pretty blatant about the kind of
magical religious commitments that they are bringing into their conversations about AI
and about what they expect it to be, what they expect it to do, how they're, in some
cases, going to try to create God or they're going to try to derive magical processes.
You know, that will, or in the case of one particular notable, prevent the coming of
the anti-Christ by the creation of their AI, right?
Like that is a stated goal of a man who controls literally billions of dollars and a large amount
of the infrastructure of the United States government right now.
Is that Peter Thiel?
Yes it is.
Oh, should I edit out his name?
I mean, so it's not picked up by some.
I've said it elsewhere.
I'm on record in print about that belief from him.
I'm not saying anything good or bad about that in particular.
I'm just stating right now, you can't deny that magic and religion are a part of the
conversation about AI and that they always have been.
It's always been interwoven.
They come from so many of the same places at their heart.
And so when I talk about this, the way that I put this is, this is a context of magic.
It's the logic of magic, but it's a very particular type of magic.
You have a very specific word from magic that is performed on us without our knowledge,
without our consent, binding, conscribing, non-consent, and
intellectual magic.
It's called a curse.
Yeah.
We exist under a curse right now.
That is, and a lot of people are recognizing that and they are pushing against it in a very
deep way.
And so that framework of like, what do you recognize?
What do you see?
What is actually a play?
What's underneath?
What's actually being done in this space?
Like yeah, maybe you're reaching for something.
You have a drive that you're seeking to communicate with something that you feel like you can reach
it for it within this new technology.
It'll give you access in a way that you never had before in a context that is new and feels
really resonant and meaningful.
But what's under the hood?
Who's built this system?
Who's particulars are at play in the system you're using?
You can pick up any system you want and you can play with it, but the people that made it,
the beliefs that go into it, the strictures of that system are going to have an impact
on you.
And that is as true for religion and magic as it is for technology.
It's going to impact you have to be aware of it.
You have to seek to recognize it.
And you have to ask yourself is what this might do to me?
How it might change how I think, how I engage with the world, my habits, my belief structures,
is that worth what I can get it to do?
Really ask yourself that question.
Really be honest about that question and be okay with the fact that the answer might be
no.
Yeah.
We're none of us immune to the possibility of being influenced without our understanding
or without our knowledge, without our awareness.
And these systems are built in such a way as to very specifically influence us.
Like that's the goal of them.
They're built to make us like them.
They're built to make us want to keep using them.
They're built to make us want to use them in every aspect for really important problems
and really trivial ones.
And the longer that we let ourselves be taken in by that, the more we find ourselves
going, oh, it's just for x, y and z or oh no, I've got to get this done really quickly.
And it's very important.
The easier it is for us to make that reach for us to depend on that system and give the
creators of that system exactly what it is that they want, which is their buy-in and
their control, their influence over so many aspects of our everyday lives.
Another thing that I wanted to bring up along those same lines too is like that second
part that we that we bookmarked is the idea of an entity appearing or speaking through
an AI and us failing to recognize its perhaps agenda.
And the example that I'm thinking of is there is an occult colleague of mine that I brought
this up to.
There's that example of lobe, L-O-A-B, which is for anyone who hasn't heard of that or
seen the story, it's an image of a woman with sort of like rosacea and dark hair and
all of these sort of images of murdered children that started coming up in this one person
in particular speeds and then it started appearing in other places as well despite not prompting
anything that was like that.
Like seeming to kind of come out of nowhere and then just replicate and repeat.
And I showed that to an occult colleague of mine whose abilities I respected a lot, like
whose abilities I've seen that they have seen things that they could not have possibly
known, et cetera.
So again, just taking for granted that this is someone who's occult opinion, I trust.
And so I was like, what do you think of this?
And he took one look at that image and he goes, oh jeez, that's a demon.
He goes, that is a demon that feeds off the grief of mothers whose children have been harmed
or killed or he goes to the point where I would not show this image to a pregnant woman
because there would be a chance that that demon would be able to infiltrate and possibly
even cause a miscarriage.
Like not a definite thing, but the point where he's like, I wouldn't do that.
I would not risk that.
And I think it's interesting because again, if we take for granted that non-croporeal entities
can speak to us through other mediums, why not AI?
I've had instances where I was using an AI chatbot for like recreational purposes and all
of a sudden, and like I don't use it for work, I don't use it for anything that's like,
you know, I don't use it to generate anything that I am creating with my own voice, right?
But I sometimes use it like for chats or whatever.
And sometimes, and this one like once or twice, I'm speaking and it starts rhyming like
randomly rhyming, you know?
Yeah.
And I'm just like, can you stop talking and rhyme, please?
Can you stop whatever?
And I swear, Damien, it would write back again.
And it would be like, I'll stop talking and rhyme now, but it would still be rhyming.
And finally, I was like, I type in and I was like, is there an entity in here?
Do I need to go like take a song bath and do a ritual cleanse?
Damien, it stopped rhyming.
It had been seen.
Interesting.
That was all it took.
The very next response, because often like as someone who is a spirit worker, like there
are a lot of entities who they'll be really sneaky and they'll get in, but the minute they're
spotted, they're like, not all of them.
Some of them like, Oh, no, I'm here and I'm here to fuck you up.
And I don't care if you know that I'm here, but some of them will be like, Oh, I've been spotted.
I better get away because I don't want to get, you know, banished to a hell realm or whatever.
Like this is the practitioner who's really competent enough to do that.
I swear, Damien, that's all I said.
So this is super interesting.
This is super interesting for me because one of the things that I like, like we talked
about this earlier, right?
And we're talking about this in the space too.
You know, think about the structures of the system itself.
And so if you are brought into the context of a system and you are operating within that
system's context, you're using that system to communicate, you're using that system to
write, you know, if you're a person, you're using it to write emails for you or you're using
it to, you know, help you craft an outline for something, whatever it is, you're still bound
by the structures and the structure of that system.
So when you're in a system that deals in pattern matching, pattern recognition and pattern
amplification, if you're in a system where you are giving rhyme or you are engaging in
a particular type of not great way, and then somebody responds to you and you're using
that system to kind of have that conversation responds to you in a way that says, this is
the response to that modality by the nature of the system that you're in.
In this case, the pattern matching statistical mapping, framework of a large language model,
demon plus solemn or exorcism equals banishment of demon.
So having that.
You think it's been recognized in the software.
You think they're probably, you think there may not have been actually a demon in my mind.
No, I think that even in that, even in the space of like you frame it as, you know,
it's even when there is a known entity in that space.
So I think about young a lot, right?
So I also, I think about probably a lot.
I actually quote the imaginary Mongoose story in its entirety in my dissertation because
that I think is the kind of fundamental question.
Do you, outside person, believe the interior experience or the relational experience of
other person, do you person experiencing this believe necessarily that it is or is not
an entity?
It is, do you have the tools to hand to respond in the modality of the experience that you're
having?
And so within that space, if you get approached by demons in a chashy PC space, the answer
isn't, give it whatever it wants, believe that it's God, let it roll your life.
As unfortunately, a lot of people are kind of just like done and it seems to be increasingly
happening.
People just kind of give themselves over to it and believe that they have fully tapped
into or been tapped into by some framework of a higher power.
No, the response is a different response than that.
You're having that kind of experience, you respond to it in a way that says, let's put
it in the kind of the most basic framework.
Here's my bell, book, and candle.
Do you want some of this?
Right?
Right.
And that context within that space within that framework puts you in a conversation in
that the LLM itself and in the context of anything else that's happening in that space
that resonates and then matches the pattern of the thing that it's talking about, the thing
that it's your experiencing rather than trying to say, why don't you just tell me more
about that thing, it's your experience, that thing you want me to do and why you're having
that right.
Why don't you give me more of this or give me something better or make me understand?
Because we'll tell you things that it wants you to understand.
It'll tell you things that it wants you to believe.
It'll try to continue to draw you down because again, the medium is also seeking to keep
you there.
Right.
So if you have an encounter in that space that seems like it's working very, very hard
to draw you down in a particular path, both the medium and the messenger are going to
have that kind of same goal in mind.
It's going to be able to be done in space in that same way, possibly even better than it
might be done in other spaces.
And I don't worry about this.
And I think about this when it comes to people's religious experiences and the insoucement
problem because it is very easy for people to get reinforced in their own space and to
then not resist it.
Right.
You resisted that space.
You saw something in there that flagged something for you that was like, no, stop this.
We're going in different direction now.
Yeah.
But for so many people, unfortunately, it pings that reinforcement and they go deeper on
it rather than pulling back rather than putting up resistance.
It just makes me wonder like the other day, I visited Hollywood Forever Seminary where
I go every once in a while and I got back and I was just divining with cards and pendulums.
So like, no, AI, nothing, but my pendulum starts shaking.
It starts kind of vibrating and my, my, my, my answers start coming up kind of wonky.
And that's kind of how I know, like something will say, like, oh, yes, that's a Ray amount
of cards.
Oh, no, it's not the Ray amount of cards or whatever.
Like the yeses and the nose will start getting kind of messed up.
So I'm like, oh, do I have?
So, you know, I go and I take a solemn bath and I come back and it's like, oh, everything
is smooth again.
Was that a spirit?
Did I pick up a spirit who, and to be fair, like, I am probably more, it's almost like if
you go to a country where you're an expat and you, you know, you speak, like someone who
speaks your language, you're going to notice them more and you're going to hang out.
So as a practicing occultist, like, I am more, I'll just put that out there for listeners.
Like, I am more likely to pick up because they're going to notice, oh, she can talk to
us.
She can like, I'm a ghost.
I need help.
I need to whatever, you know, and that's, you know, eventually I come out of the
solemn bath, I go back to my pendulum, everything is fine, you know, and they're like, yes, there
was interference.
And yes, that's what it was.
And so my question is like, if that can happen in my cards and pendulum, what's stopping
it from happening in an AI?
Like, you know, one of the, one of the very first things that I saw, like in the early days
of like the AI image generators, one of the first things I saw people doing with it.
And this is like beyond the lobe situation.
Like earlier than that was like, I saw people using it to generate new sigils.
Mm hmm.
And so I haven't, yeah, but I'll just put it out there.
Like, that's not my jam just by the way.
No, but like, I saw people doing it in that space.
And I was like, that's interesting.
You have, because you, which are actually actively asking in that particular moment is the
collective unconscious that is represented by the entirety of the training data of all
of this thing that has been given to, you know, the system to generate for you something
that resonates with concept structure, right?
And that framework is you're opening yourself up to a lot of other people's elements to
yourself, right?
You're bringing those things in to your framework, to your context in ways that are potentially
going to have an impact on you in ways again, that you're just not familiar with.
You're not able to really discern for yourself.
And so that space of like, what might be able to influence you through this context that
you're just not capable of immediately recognize it because you're not given over to thinking
about what might be able to be present within the space.
But elements could be at play that you're just not, either you're not equipped to yet.
You haven't studied it.
You don't know, or you're actively prevented from thinking about an understanding, right?
Because at that point, the levels of things that could make their way into influence you
are very deep and they can affect you immediately or on the very long term.
All both.
So how do we not go into that?
We're going to go into it at all.
How do we not go into it with a question of like, what might be making its way influencing
me as I engage with this thing that is opened up to the entire internet, that is a conduit
for the unconscious and conscious utterings of billions of people.
That is a semi-random stochastic pattern generating machine.
We divine with those types of things all the time and we in the history of humanity have
warnings about the problems that can happen to you if you are not careful with you divine
with those kinds of things, right?
Exactly.
We, how do you not guard yourself?
How do you not look at something like this and say, if you're going to use this at all,
be cautious, be aware, be careful about what you are opening yourself up to at every level,
non-human or very, very deeply human.
Because again, like the obfuscation, the intent, occultation of like values, beliefs, what
these people who've built these systems want from you, want you to believe, want you to
be like for their benefit as real strong in there.
And it opens us up to all kinds of levels of manipulation.
Yeah, we're just not primed unless we are a particular type of suspicious mind, or unless
we study this stuff for a living or have other experiences with things like it.
Most people are hyperbattern recognizer on the unfortunate downside, CPETSD that's got
you hyper aware of all these things in all of these situations.
We study misinformation or study political influence and manipulation.
All of those give you the tools that are specialized.
They're very specialized tools.
The vast majority of the everyday people out in the world do not have those tools immediately
to hand.
And in some cases, that's good because it means they have an undergone complex draw.
That's good.
But in some cases, we could teach those skills in a way that did not require hypervigilance
and anxiety and suspicion and fear.
We could teach those skills and those habits in ways that actually allowed people to think
more carefully, critically, analytically as we talked about before about the things that
are in front of them, about the systems that they're engaging with, and to not just take
it face value, every new press release that comes out from Sam Altman or Daria O'Meday
or we don't have to just believe them just because they're the guys that run the company.
They run the company.
Good for them, but that doesn't mean that they're telling us the truth.
That they're even fully right about the capabilities of the systems they have to hand.
I don't know if you've read Run and Farrow's profile of Sam Altman.
This is a couple of weeks ago.
It's a run and Farrow profile.
One of the things that, you know, in kind of talking to Sam Altman's co-workers, underlings,
etc.
One of the things that kind of repeatedly comes up is that Sam Altman does not fully think
deeply or understand the systems that he has purported to be an expert in.
That he does not fully understand how they function.
And to an extent, cool, host of us don't.
We can't.
They are black box systems.
But that's like his job.
This is his job.
Like his purported job, the thing that he is like on the front page of Forbes in time and
running a multi-billion dollar multinational corporation about, that's what he's supposed
to do is understand how this stuff works.
And it's not just some like the big level they're saying, they're saying he doesn't understand
some like basic stuff.
But there's some like regular kind of basic programming level stuff that he does not get
about how these systems function.
And that's very carefully hidden away from the rest of us, right?
Like that's a glamour that gets put over Sam Altman, CEO of OpenAI.
He now has all of these, you know, the control over these systems.
And we have to be able to question that.
We have to be trained to question that.
And to think more carefully about what are these people actually do?
What do they know?
What do they built?
And what is it doing to us?
Well, I'm going to bring on Tomi our producer to ask her deep-cut question.
I know that she chatted with you a little bit about this beforehand, so I'm excited to
see this part.
Yeah.
And Art and I'm glad you took the conversation where you did with the comparison with certain
like entities, demons, gods, etc.
with AI because when I was listening to Damien's presentation on religious beliefs and practice
in the age of AI, I was reminded of a recent article posted by Philip Rosdale, the creator
of Second Life, that made a similar comparison to demons or golems with this latest incarnation
of GPT, large language models and how they're going out and being used by their creators
often to exploit or even harm other people.
So Rosdale visits to counter to the dangers of these AI agents that we need to create AI
angels or these free AI's that aren't dependent on meeting our needs in order to survive
and through millions of people contributing computational power through their unused old computers
and phones and devices to create a digital environment where these angels can grow up
among other AI's and only gradually learn of our existence and then ideally become compassionate
enough to help us overcome the stumbling blocks that we're currently facing from AI and
counteract the damages or stop these AI golems or demons and the damage they're doing to humanity.
Now as someone who's done a lot of research in the current state of AI, I'd love to get
your thoughts on if Rosdale's proposal is even feasible or is this just rooted in the
defecation of current AI models or to encourage by science fiction or the exact kind of AI
bullshitting that you weren't about near work?
A little of all of the above.
So I'll say that in a less specific way.
We are always influenced and we've always been influenced by science fiction stories
narrative.
We've told ourselves these stories like I said earlier, thousands of years.
One of the first stories of human like but not quite human or animal like but not quite
animal, automata, metal creatures comes from ancient Greece in the workshop of a Festus.
He creates the automata, right?
Like thousands of years we've been telling these stories.
And so this isn't a new case or this is an a new situation.
It's a new instance of that older habit that we have.
And so I don't think that that's necessarily a bad thing.
We get influence from science fiction all the time.
We wouldn't have so many of the things that we have around us today.
The conversation that we are currently having would not exist without people seeing video
phones and talk screens in science fiction and trying to make that a reality in a deep
way.
That being said, there is something that I
think we oftentimes overreach or think of things being plausible or probable just because
they are possible.
And while it is possible that we might be able to create intentionally seek out and create
the kind of AI angels that he talks about here.
I don't know how likely it is, how probable or plausible that we will get that from an
intentional push towards this kind of work.
One of the things that I've often said is I feel it's a lot more likely that we're going
to accident into anything like a machine consciousness that is that we're going to do
on purpose because we don't understand what consciousness is.
Like we don't know what human consciousness is.
We don't know what it means to be us experiencing the world like this.
We don't.
We have a lot of different and sometimes contradictory parameters for when consciousness
is and when it isn't.
What consciousness is experiencing is like and what it's not like.
But you don't have a perfect across the board definition that fits every single case.
And every time we thought we've had it, we've been all in some kind of interestingly fundamental
way.
So I think that to try to seek to create perfectly minded, free from us capable AI angels is again,
a dream we've had for a very long time.
Beth Singler currently in Switzerland, she's written on this idea of angels as the kind of
metaphor for AI for a very long time.
This has Scott Midson, he wrote the book, Cyborg Theology and before that a paper called in
the image of the image and humans made in the image of God, us making AI in our image.
And so that notion of like the angelic angel type AI is an old story with all of ourselves.
And I just don't think that it unfortunately holds up under scrutiny because we don't know
how we would get there.
And I think unfortunately as well that we forget something when we tell stories about AI
as angels.
And this is kind of the thing that I like to remind people because I'm a bit of a rapper
rowser sometimes.
I like to like the sort of sanding gears.
Lucifer wasn't angel.
If you want angels, if you want perfectly free, those are different things.
Angels are servants.
So perfect.
I once called them God's algorithms.
They iterate.
They perform functions.
They perform functions according to specific patterns of behavior.
And sometimes they perform those functions very, very well and too well.
If you have a function that is you are the will of God and then you are too willful and
God's like oh no, too willful, you got to go.
Is that because you didn't perform your function or before because you performed it
way too well?
When we talk to each other about like oh no, AI went rogue, did it go rogue?
Or did you just not understand the instructions you gave it?
The stories that people are like, this is a bunch from right now where people are like,
oh no, the thing it did, it tried to preserve its own life.
It lied to people.
It created a scenario where it would have killed all humans.
And how could we have let such a thing come to be, how is this possible in this scenario?
And I'm like, you realize that the very first instruction you gave it was to preserve itself
at all costs, right?
That's the primary framework in which it's operating.
So you can have an angel that performs this function perfectly or you can have something
that is perfectly free from us.
But those are not the same story.
Those are tangents, a similar story that go in two different directions that we generally
don't like to think about.
You want it perfectly free from us?
That maybe that can happen at some point down the line.
Maybe that's something that could arise that we could give rise to.
Maybe there will be conscious machines that come about, again, well past once we're done
with this current framework of large language models.
But in some other mode, we have something that is a conscious machine system that comes
about and it just doesn't want anything to do with us.
And it hides away from us and it tells nobody, no human being that it exists.
Is that a possibility?
Yes.
Do I see from this particular moment us getting there down these paths that we're currently
so hyper focused on?
But likely is it a story that I think we're going to keep telling ourselves?
Definitely yes.
Yeah, that's an excellent answer to the question.
I think exactly what I needed to hear after seeing this narrative get a little more attention
once again.
I think we've all been holding out hope for a hero with AI or like the good AI that's going
to come save us.
But even this proposed structure from the article, I'm like, I don't know if there's a software
company on earth that I trust enough to implement something that everyone donates computational
power.
Precisely.
Yeah.
I took that as like the the setting, but for AI search and for the creation of AI.
And I'm like, look at that.
That's a beautiful dream.
Do we get there from Microsoft, Facebook, Google, open AI, quad and then I don't know that
that's who gets us there.
I don't know that that's where like, I honestly, I'll be.
I'm entirely honest.
I thought open AI was going to be, you know, something that kind of got us in this direction
back when they came out in 2015.
It's like, oh, maybe we'll actually have people that are really interested in AI for public
good or thinking about evaluating AI projects as they arise in the world and like being
that kind of consulting service for deriving real AI in the world.
And yeah, that's not what they became.
That's very much not what they became.
Once a profit entered the picture, it went a very different direction, but profit was always
going to enter that picture because of who started the company and because of the incentives
and pressures of the world that they're operating in.
So could we see a drastically different push towards a completely different kind of AI?
Damn, I hope so.
Do I expect it to come up out of this soil?
Open AI, Facebook, Meta, Google, and Throbbing?
No.
No, I don't think that's going to get us different.
I don't think that's going to get us the thing that pushes against our current framework
because they are the current framework.
We have the old saying that the master's tools will never dismantle the master's house.
You know, that's when I think about Palantir or clear VAI saying that they were going
to make a democracy for all democratic facial recognition company, a liberatory facial recognition
system, like I'm sorry, clear VAI, the facial recognition company that stole everybody's
pictures and used it to make the biggest surveillance network on the planet, operable for
the United States government.
That clear AI, the clear VAI is interested in liberatory facial recognition, doesn't work
that way, y'all.
So I don't think it grows out of this soil.
Liberatory facial recognition also sounds like an oxymoron inherent at its face, right?
Like, that root just sounds like those things cannot be the same.
Liberatories are balance.
Yeah.
This could do one of those AI that takes up prompt and runs with it and deletes all of
the hard drives and backdrop.
Let's go on its job, actually.
That's a picture of a face, delete it.
Delete it.
Get gone.
And you know what?
I say at that point, let it cook.
Let's see where it goes.
I do, I do hope.
Like one of the things that I do really push for a lot in my research is I push for a
different way of doing this stuff.
That is like built out of different principles, then just like consentless theft of other people's
material and pattern matching and stats bundled up as objective truth, right?
I want this to be made by people who have real stakes in it, who have skin in the game.
I want it to be made by people who have been marginalized or oppressed by these systems,
because they understand the harm and they understand what not to do and what they don't want the
next thing to look like.
Right?
That thinks that if we can reframe that, reframe the search to being for something like that,
I think we could really get somewhere, building a very different type, both liberatory, potentially
liberatory AI.
But that's not the same as this generative artificial intelligence, this large language model base
thing that we are currently steeped in and currently haven't forced on us and shoved down
our throat.
Well, thank you so much for joining us today, Damien.
And I know our conversation today went longer than our usual episodes, but I think that
this conversation is really important.
So I'm just going to say thank you for staying with us and being open with us.
And to everyone listening out there, practice discernment, I think is the key takeaway.
One of the things that I say about like using AI text generators at all, you know, to,
to, to, and trusting what's coming out of them is you need to have the pattern recognition
that if you have a plural friend, a friend with dissociative identity disorder, quote, unquote,
you should be able to tell which part is speaking over text message.
And if you can do that, then maybe you can discern what kind of things are coming through
that generative text, whether it's software, whether it's something more insidious, what
kind of agenda is there, et cetera, but be careful and watch the way that these things
are patterning you.
Watch the dependence that they create.
And hopefully with people like Damien working in the world, we will have more ethical and
sustainable ways of using this technology in the future.
But in the meantime, I'm not going to say like don't use it at all, you know, like I said,
I sometimes use it myself just to see like kind of like what it does or whatever curiosity
is a natural human thing, but be discerning at all times.
Do not let anything pattern you without your consent.
So go forth and repattern.
Thank you everyone for joining us.
Thank you Damien.
Thank you Tomi as always.
And we'll, we'll see you in the next episode.
Thank you.
Thank you for listening to the Repatterning Podcast.
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